Professor Philip Evans

A Monte-Carlo model was developed to simulate the response of a pixelated hyperspectral CZT X-ray detector. The first part of the simulation was carried out using Geant4, to obtain a list of energy depositions inside the CZT crystal. The second part of the simulation used charge transport equations to calculate the size of the electron charge cloud, as it drifts under the electric field to be read out. Experimentally acquired data from an Am-241 source with the HEXITEC detector were compared to simulated data, and good agreement was found. The model was used to investigate the energy dependence of fluorescence and charge sharing effects. Firstly, the probability of producing an escaped fluorescence photon was quantified as a function of primary photon energy. As expected, at primary photon energies just above the K-edge of Cd, there is a greater chance of producing an escaped fluorescence photon, and this probability decreases as the primary photon energy increases. Secondly, the probability of an event being shared across multiple pixels as a function of primary photon energy was quantified. It was found that as the primary photon energy is increased, there is a greater chance of producing an event shared across multiple pixels. The detector response to a Bremsstrahlung spectrum was simulated. Using previous results, fluorescence and charge sharing effects were corrected for, giving a corrected spectrum in good agreement with the input spectrum.

Radiomics involves the extraction of information from medical images that are not visible to the human eye. There is evidence that these features can be used for treatment stratification and outcome prediction. However, there is much discussion about the reproducibility of results between different studies. This paper studies the reproducibility of CT texture features used in radiomics, comparing two feature extraction implementations, namely the MATLAB toolkit and Pyradiomics, when applied to independent datasets of CT scans of patients: (i) the open access RIDER dataset containing a set of repeat CT scans taken 15 min apart for 31 patients (RIDER Scan 1 and Scan 2, respectively) treated for lung cancer; and (ii) the open access HN1 dataset containing 137 patients treated for head and neck cancer. Gross tumor volume (GTV), manually outlined by an experienced observer available on both datasets, was used. The 43 common radiomics features available in MATLAB and Pyradiomics were calculated using two intensity-level quantization methods with and without an intensity threshold. Cases were ranked for each feature for all combinations of quantization parameters, and the Spearman’s rank coefficient, rs, calculated. Reproducibility was defined when a highly correlated feature in the RIDER dataset also correlated highly in the HN1 dataset, and vice versa. A total of 29 out of the 43 reported stable features were found to be highly reproducible between MATLAB and Pyradiomics implementations, having a consistently high correlation in rank ordering for RIDER Scan 1 and RIDER Scan 2 (rs > 0.8). 18/43 reported features were common in the RIDER and HN1 datasets, suggesting they may be agnostic to disease site. Useful radiomics features should be selected based on reproducibility. This study identified a set of features that meet this requirement and validated the methodology for evaluating reproducibility between datasets.

Radiomics involves the extraction of information from medical images that are not visible to the human eye. There is evidence that these features can be used for treatment stratification and outcome prediction. However, there is much discussion about the reproducibility of results between different studies. This paper studies the reproducibility of CT texture features used in radiomics, comparing two feature extraction implementations, namely the MATLAB toolkit and Pyradiomics, when applied to independent datasets of CT scans of patients: (i) the open access RIDER dataset containing a set of repeat CT scans taken 15 min apart for 31 patients (RIDER Scan 1 and Scan 2, respectively) treated for lung cancer; and (ii) the open access HN1 dataset containing 137 patients treated for head and neck cancer. Gross tumor volume (GTV), manually outlined by an experienced observer available on both datasets, was used. The 43 common radiomics features available in MATLAB and Pyradiomics were calculated using two intensity-level quantization methods with and without an intensity threshold. Cases were ranked for each feature for all combinations of quantization parameters, and the Spearman’s rank coefficient, rs, calculated. Reproducibility was defined when a highly correlated feature in the RIDER dataset also correlated highly in the HN1 dataset, and vice versa. A total of 29 out of the 43 reported stable features were found to be highly reproducible between MATLAB and Pyradiomics implementations, having a consistently high correlation in rank ordering for RIDER Scan 1 and RIDER Scan 2 (rs > 0.8). 18/43 reported features were common in the RIDER and HN1 datasets, suggesting they may be agnostic to disease site. Useful radiomics features should be selected based on reproducibility. This study identified a set of features that meet this requirement and validated the methodology for evaluating reproducibility between datasets.

Objectives The Dietetic Assessment and Intervention in Lung Cancer (DAIL) study was an observational cohort study. It triaged the need for dietetic input in patients with lung cancer, using questionnaires with 137 responses. This substudy tested if machine learning could predict need to see a dietitian (NTSD) using 5 or 10 measures. Methods 76 cases from DAIL were included (Royal Surrey NHS Foundation Trust; RSH: 56, Frimley Park Hospital; FPH 20). Univariate analysis was used to find the strongest correlates with NTSD and 'critical need to see a dietitian' CNTSD. Those with a Spearman correlation above +/- 0.4 were selected to train a support vector machine (SVM) to predict NTSD and CNTSD. The 10 and 5 best correlates were evaluated. Results 18 and 13 measures had a correlation above +/- 0.4 for NTSD and CNTSD, respectively, producing SVMs with 3% and 7% misclassification error. 10 measures yielded errors of 7% (NTSD) and 9% (CNTSD). 5 measures yielded between 7% and 11% errors. SVM trained on the RSH data and tested on the FPH data resulted in errors of 20%. Conclusions Machine learning can predict NTSD producing misclassification errors

The effectiveness of Intensity Modulated Radiation Therapy (IMRT) is compromised by involuntary motion (e.g. respiration, cardiac activity). Feasibility of processing ultrasound echo data to automatically estimate 3D liver motion for real-time IMRT guidance was previously demonstrated with an acquisition speed limit of 2 volumes per second, due to hardware restrictions of a mechanical linear array probe. Utilizing a 2D matrix array probe with parallel receive beamforming offered increased acquisition speeds, and the contributions of higher volume rates were investigated. In vivo livers of three volunteers were scanned with and without respiratory motion, at volume rates of 24 and 48 Hz, respectively. Correlation-based, phase-sensitive 3D speckle tracking was applied to consecutively-acquired volumes. Volumes were omitted at fixed intervals and 3D speckle tracking was reapplied to study the effect of lower scan rates. Results revealed periodic motion that corresponded with the heart rate or breathing cycle, in the absence or presence of respiration, respectively. For cardiac-induced motion, volume rate limits ranged from 8-12 Hz and were limited by the frequency of the beating heart. In respiratory-dominated motion, volume rate limits ranged from 4-12 Hz and were limited by the accuracy of tracking estimates.

Accurate segmentation of tissues is a prerequisite for a number of quantitative investigations of breast such as biomechanical modeling. A characteristic of breast that might affect the segmentation accuracy is the distribution of tissues. An appropriate method to classify breast with sparse distribution of fibroglandular tissue has so far not been studied. Our aim is to identify a texture feature that can be used to classify the distribution of tissue. This work studied and evaluated texture features to classify fibroglandular tissue distribution in the breast. Radiotherapy planning computed tomography (CT) data of 24 patients in the supine position were analyzed. These breast datasets were visually assessed and ranked by an expert for the sparseness of the fibroglandular tissue distribution. In this study texture features were derived using properties of the radial glandular fraction (RGF) such as the mean, and standard deviation. RGF, presented by Huang et al., describes the distribution of fibroglandular tissue within the breast. Patients were grouped into non-sparse and sparse tissue distribution based on expert rank and texture features of these two groups were compared. A Wilcoxon rank test was used to test significance of differences between the two groups and the Bonferroni correction was used to adjust the significance threshold for multiple comparisons. The radial glandular fraction of the two groups, non-sparse and sparse was substantially different for the three breast regions studied. There were significant differences between these two groups for a number of features. This study indicates that texture features derived from the RGF can provide a good indicator for the classification of the distribution of fibroglandular tissue in the breast. Performance of these texture features to classify the fibroglandular tissue distribution is presently being investigated.

A new technique is presented for obtaining breathing traces from any sequential planar X-ray image-set, such as that acquired during a cone-beam CT scan (CBCT). The technique is based on extracting a signal from the fast variations in summations of pixels values. The method has been tested against existing methods using patient data and verified using a breathing phantom. The advantage of this technique over existing methods is that it can be completed for any field of view.

This study enables a comparison between two proposed algorithms in the literature for proton computed tomography (pCT) reconstruction; these are the analytical filtered back-projection (FBP) and the iterative algorithm of diagonally relaxed orthogonal projections (DROP) with total variation superiorization (TVS). The analytical model of the cubic spline path (CSP) has been implemented into DROP-TVS algorithm to account for scattering, using measurements of individual proton positions/trajectories and energy before and after traversing a selected phantom. Spatial resolution and relative stopping power (RSP) accuracy of the reconstructed images were used as comparison criteria. Parametric changes of projection angular ranges from 0 0 to 180 0 and 0 0 to 360 0 , as well as angular steps of 0.5 0 and 1 0 have been investigated. Experimental data of the CT0404 "Sensitom" and the CTP528 "Line Pair" modules of the Catphan® 600 phantom were used. DROP-TVS appeared to provide better noise reduction compared to FBP while the resolution worsened with reduced projections. On the other hand, FBP resulted in degraded image quality with more noise and worse spatial resolution compared to that of the DROP-TVS scheme. Interplane artifacts were present with both algorithms which became more acute in FBP reconstructions and with a limited number of projections. Reduced number of projections had an adverse effect on both reconstruction methods. The study outcomes highlight the optimal acquisition for pCT reconstruction for superior image quality but there must always be a trade-off between noise and spatial resolution for optimal data acquisition.

Validation of breast tissue segmentation algorithms is a vital step required to assess their suitability for the intended task such as biomechanical modeling of breast. A problem with such validation is that the true segmentation, a reference standard, is generally unavailable. Therefore, comparison of algorithmic segmentation with expert outlining of the breast tissues is preferably carried out for such validation. Often outlines from two or more experts are used to overcome the differences between different expert’s outlines of the same region i.e. inter-expert variability. However, the most appropriate approach with which to compare multiple expert outlines with algorithmic segmentation is so far unclear and several approaches are used in practice. We present a validation index (VI), a model based measure of the spatial overlap between algorithmic segmentation and multiple expert outlines. The levels of agreement i.e., the overlaps of experts’ outlines were used to define validation index (VI). The VI was evaluated using three idealized cases and data from a clinical study. The performance of VI with respect to three common formulations of the Dice similarity coefficient (DSC) was also studied. It was found that VI was more sensitive than the three DSCs to the change in agreement between experts and in all cases VI was smaller than the corresponding three DSCs. Also, VI was found to be unaffected by the number of experts used for the validation. VI may be used for a range of validation studies such as an evaluation of algorithmic segmentation methods.

Proton computed tomography (pCT) offers unique image formation attributes, with a potential for increasing accuracy of treatment planning in proton beam therapy. To maximize the potential of pCT it is necessary to develop advanced reconstruction algorithms that can accurately recover relative proton stopping power maps. This study aims to integrate pCT into STIR (Software for Tomographic Image Reconstruction), a popular Multi-Platform Object-Oriented framework for reconstruction in tomographic imaging to benefit from its software infrastructure. Open source STIR library is currently suitable for reconstructing and manipulating data from Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT), which are based on cylindrical scanner geometries. Although pCT has a noncylindrical geometry, STIR provides the framework for single event detection and modelling of the proton interactions. This initial implementation includes classes and functions with new features such as general proton scanner geometry, binning of list mode proton data into sinograms and uses analytical reconstruction algorithms already available in STIR. The structure of the new implemented features is discussed. Future work will include additional components to establish STIR as a potential toolkit for pCT image reconstruction.

Background Whole-breast radiotherapy (WBRT) is the standard treatment for breast cancer following breast-conserving surgery. Evidence shows that tumour recurrences occur near the original cancer: the tumour bed. New treatment developments include increasing dose to the tumour bed during WBRT (synchronous integrated boost) and irradiating only the region around the tumour bed, for patients at high and low risk of tumour recurrence, respectively. Currently, standard imaging uses bony anatomy to ensure accurate delivery of WBRT. It is debatable whether or not more targeted treatments such as synchronous integrated boost and partial-breast radiotherapy require image-guided radiotherapy (IGRT) focusing on implanted tumour bed clips (clip-based IGRT). Objectives Primary – to compare accuracy of patient set-up using standard imaging compared with clip-based IGRT. Secondary – comparison of imaging techniques using (1) tumour bed radiotherapy safety margins, (2) volume of breast tissue irradiated around tumour bed, (3) estimated breast toxicity following development of a normal tissue control probability model and (4) time taken. Design Multicentre observational study embedded within a national randomised trial: IMPORT-HIGH (Intensity Modulated and Partial Organ Radiotherapy – HIGHer-risk patient group) testing synchronous integrated boost and using clip-based IGRT. Setting Five radiotherapy departments, participating in IMPORT-HIGH. Participants Two-hundred and eighteen patients receiving breast radiotherapy within IMPORT-HIGH. Interventions There was no direct intervention in patients’ treatment. Experimental and control intervention were clip-based IGRT and standard imaging, respectively. IMPORT-HIGH patients received clip-based IGRT as routine; standard imaging data were obtained from clip-based IGRT images. Main outcome measures Difference in (1) set-up errors, (2) safety margins, (3) volume of breast tissue irradiated, (4) breast toxicity and (5) time, between clip-based IGRT and standard imaging. Results The primary outcome of overall mean difference in clip-based IGRT and standard imaging using daily set-up errors was 2–2.6 mm (p 

Purpose: Radiography and tomography using proton beams promises benefit to image-guidance and treatment planning for proton therapy. A novel proton tracking detector is described and experimental demonstrations at a therapy facility reported. A new type of proton CT reconstructing relative ‘scattering-power’ rather than ‘stopping-power’ is also demonstrated. Notably, this new type of imaging does not require the 55 measurement of the residual energies of the protons.Methods: A large area, silicon micro-strip tracker with high spatial and temporal resolution has been developed by the PRaVDA consortium and commissioned using beams of protons at iThemba LABS, Medical Radiation Department, South Africa. The tracker comprises twelve planes of silicon developed using technology from high energy physics with each plane having an active area of ∼10 × 10 cm segmented into 2048 micro-strips. The tracker is organised into four separate units each containing three detectors at 60◦ 60 to one another creating an x-u-v co-ordinate system. Pairs of tracking units are used to reconstruct vertices for protons entering and exiting a phantom containing tissue equivalent inserts. By measuring the position and direction of each proton before and after the phantom, the non-linear path for each proton through an object can be reconstructed. Results: Experimental results are reported for tracking the path of protons with initial energies of 125 MeV and 191 MeV. A spherical phantom of 75 mm diameter was imaged by positioning it between the entrance and exit detectors of the tracker. Positions and directions of individual protons were used to create angular distributions and 2D fluence maps of the beam. These results were acquired for 36 equally spaced projections spanning 180◦ , allowing, for the the first time, an experimental CT image based upon the relative scattering 70 power of protons to be reconstructed. Conclusions: Successful tracking of protons through a thick target (phantom) has demonstrated that the tracker discussed in this paper can provide the precise directional information needed to perform proton radiography and tomography. When synchronized with a range telescope, this could enable the reconstruction of proton CT images of stopping power. Furthermore, by measuring the deflection of many protons through 75 a phantom it was demonstrated that it is possible to reconstruct a new kind of CT image (scattering power) based upon this tracking information alone.

Objectives This study tested the hypothesis that shows advanced image analysis can differentiate fit and unfit patients for radical radiotherapy from standard radiotherapy planning imaging, when compared to formal lung function tests (FEV1, Forced Expiratory Volume in 1 second) and TLCO (Transfer Factor of Carbon Monoxide). Methods An apical region of interest (ROI) of lung parenchyma was extracted from a standard radiotherapy planning CT scan. Software using a grey level co-occurrence matrix (GLCM) assigned an entropy score to each voxel, based on its similarity to the voxels around it. Density and entropy scores were compared between a cohort of fit patients (defined as FEV1 and TLCO above 50% predicted value) and unfit patients (FEV1 or TLCO below 50% predicted). Results 29 fit and 32 unfit patients were included. Mean and median density and mean and median entropy were significantly different between fit and unfit patients (p= 0.0021, 0.0019, 0.0357 and 0.0363 respectively, 2 sided t-test). Conclusions Density and entropy assessment can differentiate between fit and unfit patients for radical radiotherapy, using standard CT imaging. Advances in knowledge This study shows that a novel intervention can generate further data from standard CT imaging. This data could be combined with existing studies to form a multi-organ patient fitness assessment from a single CT scan.

Advanced radiotherapy techniques such as volumetric modulated arc therapy (VMAT) require verification of the complex beam delivery including tracking of multileaf collimators (MLC) and monitoring the dose rate. This work explores the feasibility of a prototype Complementary metal-oxide semiconductor Image Sensor (CIS) for tracking these complex treatments by utilising fast, region of interest (ROI) read out functionality. An automatic edge tracking algorithm was used to locate the MLC leaves edges moving at various speeds (from a moving triangle field shape) and imaged with various sensor frame rates. The CIS demonstrates successful edge detection of the dynamic MLC motion within accuracy of 1.0 mm. This demonstrates the feasibility of the sensor to verify treatment delivery involving dynamic MLC up to ∼400 frames per second (equivalent to the linac pulse rate), which is superior to any current techniques such as using electronic portal imaging devices (EPID). CIS provides the basis to an essential real-time verification tool, useful in accessing accurate delivery of complex high energy radiation to the tumour and ultimately to achieve better cure rates for cancer patients. © Published under licence by IOP Publishing Ltd.

Aims: To measure cardiac tissue doses in left-sided breast cancer patients receiving supine tangential field radiotherapy with multileaf collimation (MLC) cardiac shielding of the heart and to assess the effect on target volume coverage. Materials and methods: Sixty-seven consecutive patients who underwent adjuvant radiotherapy to the left breast (n=48) or chest wall (n=19) in 2009/2010 were analysed. The heart, left anterior descending coronary artery (LAD), whole breast and partial breast clinical target volumes (WBCTV and PBCTV) were outlined retrospectively (the latter only in patients who had undergone breast-conserving surgery [BCS]). The mean heart and LAD NTD and maximum LAD doses (LAD) were calculated for all patients (NTD is a biologically weighted mean dose normalised to 2Gy fractions using a standard linear quadratic model). Coverage of WBCTV and PBCTV by the 95% isodose was assessed (BCS patients only). Results: The mean heart NTD (standard deviation) was 0.8 (0.3) Gy, the mean LAD NTD 6.7 (4.3) Gy and the mean LAD 40.3 (10.1) Gy. Coverage of the WBCTV by 95% isodose was

Aims: To determine the effect of image-guided radiotherapy on the dose distributions in breast boost treatments. Materials and methods: Computed tomography images from a cohort of 60 patients treated within the IMPORT HIGH trial (CRUK/06/003) were used to create sequential and concomitant boost treatment plans (30 cases each). Two treatment plans were created for each case using tumour bed planning target volume (PTV) margins of 5 mm (achieved with image-guided radiotherapy) and 8 mm (required for bony anatomy verification). Dose data were collected for breast, lung and heart; differences with margin size were tested for statistical significance. Results: A median decrease of 29 cm (range 11-193 cm) of breast tissue receiving 95% of the prescribed dose was observed where image-guided radiotherapy margins were used. Decreases in doses to lungs, contralateral breast and heart were modest, but statistically significant (P < 0.01). Plan quality was compromised with the 8 mm PTV margin in one in eight sequential boost plans and one third of concomitant boost plans. Tumour bed PTV coverage was 91%) of the prescribed dose in 12 cases; in addition, the required partial breast median dose was exceeded in nine concomitant boost cases by 0.5-3.7 Gy. Conclusions: The use of image guidance and, hence, a reduced tumour bed PTV margin, in breast boost radiotherapy resulted in a modest reduction in radiation dose to breast, lung and heart tissues. Reduced margins enabled by image guidance were necessary to discriminate between dose levels to multiple PTVs in the concomitant breast boost plans investigated.

This work evaluates a three-dimensional (3D) freehand ultrasound-based localisation system with new probe pressure correction for use in partial breast irradiation. Accuracy and precision of absolute position measurement was measured as a function of imaging depth (ID), object depth, scanning direction and time using a water phantom containing crossed wires. To quantify the improvement in accuracy due to pressure correction, 3D scans of a breast phantom containing ball bearings were obtained with and without pressure. Ball bearing displacements were then measured with and without pressure correction. Using a single scan direction (for all imaging depths), the mean error was

In many biomedical imaging applications Flat Panel Imagers (FPIs) are currently the most common option. However, FPIs possess several key drawbacks such as large pixels, high noise, low frame rates, and excessive image artefacts. Recently Active Pixel Sensors (APS) have gained popularity overcoming such issues and are now scalable up to wafer size by appropriate reticule stitching. Detectors for biomedical imaging applications require high spatial resolution, low noise and high dynamic range. These figures of merit are related to pixel size and as the pixel size is fixed at the time of the design, spatial resolution, noise and dynamic range cannot be further optimized. The authors report on a new rad-hard monolithic APS, named DynAMITe (Dynamic range Adjustable for Medical Imaging Technology), developed by the UK MI-3 Plus consortium. This large area detector (12.8 cm × 12.8 cm) is based on the use of two different diode geometries within the same pixel array with different size pixels (50 μm and 100 μm). Hence the resulting device can possess two inherently different resolutions each with different noise and saturation performance. The small and the large pixel cameras can be reset at different voltages, resulting in different depletion widths. The larger depletion width for the small pixels allows the initial generated photo-charge to be promptly collected, which ensures an intrinsically lower noise and higher spatial resolution. After these pixels reach near saturation, the larger pixels start collecting so offering a higher dynamic range whereas the higher noise floor is not important as at higher signal levels performance is governed by the Poisson noise of the incident radiation beam. The overall architecture and detailed characterization of DynAMITe will be presented in this paper.

Scatter in a detector and its housing can result in image degradation. Typically, such scatter leads to a low-spatial frequency 'glare' superimposed on the primary signal. We infer the glare-spread function (GSF) of an amorphous-silicon flat-panel detector via an edge-spread technique. We demonstrate that this spread (referred to as 'scatter-glare' herein) causes a low-spatial frequency drop in the associated modulation-transfer function. This results in a compression of the range of reconstructed CT (computed tomography) numbers and is an impediment to accurate CT-number calibration. We show that it can also lead to visual artefacts. This explains previously unresolved CT-number discrepancies in an earlier work (Poludniowski et al 2009 Phys. Med. Biol. 54 3847). We demonstrate that after deconvolving the GSF from the projection images, in conjunction with a correction for phantom-scatter, the CT-number discrepancies disappear. We show results for an in-house-built phantom with inserts of tissue-equivalent materials and for a patient scan. We conclude that where scatter-glare has not been accounted for, the calibration of cone-beam CT numbers to material density will be compromised. The scatter-glare measurement method we propose is simple and requires no special equipment. The deconvolution process is also straightforward and relatively quick (60 ms per projection on a desktop PC).

An algorithm for dynamic multileaf-collimator (dMLC) tracking of a target performing a known a priori, rigid-body motion during volumetric modulated arc therapy (VMAT), has been experimentally validated and applied to investigate the potential of the Agility (Elekta AB, Stockholm, Sweden) multileaf-collimator (MLC) for use in motion-compensated VMAT delivery. For five VMAT patients, dosimetric measurements were performed using the Delta(4) radiation detector (ScandiDos, Uppsala, Sweden) and the accuracy of dMLC tracking was evaluated using a gamma-analysis, with threshold levels of 3% for dose and 3 mm for distance-to-agreement. For a motion trajectory with components in two orthogonal directions, the mean gamma-analysis pass rate without tracking was found to be 58.0%, 59.0% and 60.9% and was increased to 89.1%, 88.3% and 93.1% with MLC tracking, for time periods of motion of 4 s, 6 s and 10 s respectively. Simulations were performed to compare the efficiency of the Agility MLC with the MLCi MLC when used for motion-compensated VMAT delivery for the same treatment plans and motion trajectories. Delivery time increases from a static-tumour to dMLC-tracking VMAT delivery were observed in the range 0%–20% for the Agility, and 0%–57% with the MLCi, indicating that the increased leaf speed of the Agility MLC is beneficial for MLC tracking during lung radiotherapy.

Purpose To determine whether voluntary deep-inspiratory breath-hold (v-DIBH) and deep-inspiratory breath-hold with the active breathing coordinator™ (ABC-DIBH) in patients undergoing left breast radiotherapy are comparable in terms of normal-tissue sparing, positional reproducibility and feasibility of delivery. Methods Following surgery for early breast cancer, patients underwent planning-CT scans in v-DIBH and ABC-DIBH. Patients were randomised to receive one technique for fractions 1-7 and the second technique for fractions 8-15 (40 Gy/15 fractions total). Daily electronic portal imaging (EPI) was performed and matched to digitally-reconstructed radiographs. Cone-beam CT (CBCT) images were acquired for 6/15 fractions and matched to planning-CT data. Population systematic (Σ) and random errors (σ) were estimated. Heart, left-anterior-descending coronary artery, and lung doses were calculated. Patient comfort, radiographer satisfaction and scanning/treatment times were recorded. Within-patient comparisons between the two techniques used the paired t-test or Wilcoxon signed-rank test. Results Twenty-three patients were recruited. All completed treatment with both techniques. EPI-derived Σ were ≤1.8 mm (v-DIBH) and ≤2.0 mm (ABC-DIBH) and σ ≤2.5 mm (v-DIBH) and ≤2.2 mm (ABC-DIBH) (all p non-significant). CBCT-derived Σ were ≤3.9 mm (v-DIBH) and ≤4.9 mm (ABC-DIBH) and σ ≤ 4.1 mm (v-DIBH) and ≤ 3.8 mm (ABC-DIBH). There was no significant difference between techniques in terms of normal-tissue doses (all p non-significant). Patients and radiographers preferred v-DIBH (p = 0.007, p = 0.03, respectively). Scanning/treatment setup times were shorter for v-DIBH (p = 0.02, p = 0.04, respectively). Conclusions v-DIBH and ABC-DIBH are comparable in terms of positional reproducibility and normal tissue sparing. v-DIBH is preferred by patients and radiographers, takes less time to deliver, and is cheaper than ABC-DIBH. © 2013 Elsevier Ireland Ltd. All rights reserved.

The purpose of this work was to investigate the use of an experimental complementary metal-oxide-semiconductor (CMOS) active pixel sensor (APS) for tracking of moving fiducial markers during radiotherapy.

Several studies have recently reported on the value of CT texture analysis in predicting survival, although the topic remains controversial, with further validation needed in order to consolidate the evidence base. The aim of this study was to investigate the effect of varying the input parameters in the Kaplan–Meier analysis, to determine whether the resulting P-value can be considered to be a robust indicator of the parameter's prognostic potential. A retrospective analysis of the CT-based normalised entropy of 51 patients with lung cancer was performed and overall survival data for these patients were collected. A normalised entropy cut-off was chosen to split the patient cohort into two groups and log-rank testing was performed to assess the survival difference of the two groups. This was repeated for varying normalised entropy cut-offs and varying follow-up periods. Our findings were also compared with previously published results to assess robustness of this parameter in a multi-centre patient cohort. The P-value was found to be highly sensitive to the choice of cut-off value, with small changes in cut-off producing substantial changes in P. The P-value was also sensitive to follow-up period, with particularly noisy results at short follow-up periods. Using matched conditions to previously published results, a P-value of 0.162 was obtained. Survival analysis results can be highly sensitive to the choice in texture cut-off value in dichotomising patients, which should be taken into account when performing such studies to avoid reporting false positive results. Short follow-up periods also produce unstable results and should therefore be avoided to ensure the results produced are reproducible. Previously published findings that indicated the prognostic value of normalised entropy were not replicated here, but further studies with larger patient numbers would be required to determine the cause of the different outcomes.

Volumetric-modulated arc therapy (VMAT), a form of intensity-modulated arc therapy (IMAT), has become a topic of research and clinical activity in recent years. As a form of arc therapy, portal images acquired during the treatment fraction form a (partial) Radon transform of the patient. We show that these portal images, when used in a modified global cone-beam filtered backprojection (FBP) algorithm, allow a surprisingly recognizable CT-volume to be reconstructed. The possibility of distinguishing anatomy in such VMAT-CT reconstructions suggests that this could prove to be a valuable treatment position-verification tool. Further, some potential for local-tomography techniques to improve image quality is shown.

Introduction The dose-volume effect of radiation therapy on breast tissue is poorly understood. We estimate NTCP parameters for breast fibrosis after external beam radiotherapy. Materials and methods We pooled individual patient data of 5856 patients from 2 trials including whole breast irradiation followed with or without a boost. A two-compartment dose volume histogram model was used with boost volume as the first compartment and the remaining breast volume as second compartment. Results from START-pilot trial (n = 1410) were used to test the predicted models. Results 26.8% patients in the Cambridge trial (5 years) and 20.7% patients in the EORTC trial (10 years) developed moderate-severe breast fibrosis. The best fit NTCP parameters were BEUD(50) = 136.4 Gy, γ50 = 0.9 and n = 0.011 for the Niemierko model and BEUD (50) = 132 Gy, m = 0.35 and n = 0.012 for the Lyman Kutcher Burman model. The observed rates of fibrosis in the START-pilot trial agreed well with the predicted rates. Conclusions This large multi-centre pooled study suggests that the effect of volume parameter is small and the maximum RT dose is the most important parameter to influence breast fibrosis. A small value of volume parameter 'n' does not fit with the hypothesis that breast tissue is a parallel organ. However, this may reflect limitations in our current scoring system of fibrosis. © 2013 Elsevier Ireland Ltd. All rights reserved.

Medical physics has been central to the scientific and technical development of radiotherapy since its inception as a treatment modality for cancer patients. Radiotherapy centres, as well as delivering a safe and effective cancer treatment, are routinely implementing innovations into the clinic (Jacobs et al 2016) and physicists are central to innovation generation and innovation adoption. Bortfeld and Jeraj (2011) highlighted the historic achievements of physics research in radiation therapy (radiotherapy) and argued for the continuing role, and need to develop academic medical physics and radiotherapy physics research. Following up on this, Bortfeld et al (2015) identified the potential risk of the radiotherapy physics profession having only a clinical physicist role and argued strongly for the need for academic positions. This was supported more recently by Klein et al (2017) who highlighted the need for physicists who can adapt to changes caused by the rapid evolution and expansion of radiotherapy technology and imaging options within the clinic. The recent review of global radiation therapy research by Aggarwal et al (2018) highlighted physics research as an important metric and area of research within radiation therapy.

Proton radiography and tomography have long promised benefit for proton therapy. Their first suggestion was in the early 1960s and the first published proton radiographs and CT images appeared in the late 1960s and 1970s, respectively. More than just providing anatomical images, proton transmission imaging provides the potential for the more accurate estimation of stopping-power ratio inside a patient and hence improved treatment planning and verification. With the recent explosion in growth of clinical proton therapy facilities, the time is perhaps ripe for the imaging modality to come to the fore. Yet many technical challenges remain to be solved before proton CT scanners become commonplace in the clinic. Research and development in this field is currently more active than at any time with several prototype designs emerging. This review introduces the principles of proton radiography and tomography, their historical developments, the raft of modern prototype systems and the primary design issues.

To measure cardiac tissue doses in left-sided breast cancer patients receiving supine tangential field radiotherapy with multileaf collimation (MLC) cardiac shielding of the heart and to assess the effect on target volume coverage.

The use of proton beam therapy (PBT) offers the opportunity to improve greater conformality of radiotherapy treatment delivery in some patients. However, it is associated with a high capital cost and the need to build new dedicated facilities. We discuss how the global radiotherapy community can respond to the challenge of producing high-quality evidence of clinical benefit from PBT in adult patients. In the UK, the National Cancer Research Institute-funded Clinical and Radiotherapy Translational group has established the PBT Clinical Trial Strategy Group. An eight-point framework is described that can assist the development and delivery of high-quality clinical trials.

The effectiveness of intensity-modulated radiation therapy (IMRT) is compromised by involuntary motion (e.g. respiration, cardiac activity). The feasibility of processing ultrasound echo data to automatically estimate 3D liver motion for real-time IMRT guidance was previously demonstrated, but performance was limited by an acquisition speed of 2 volumes per second due to hardware restrictions of a mechanical linear array probe. Utilizing a 2D matrix array probe with parallel receive beamforming offered increased acquisition speeds and an opportunity to investigate the benefits of higher volume rates. In vivo livers of three volunteers were scanned with and without respiratory motion at volume rates of 24 and 48 Hz, respectively. Respiration was suspended via voluntary breath hold. Correlation-based, phase-sensitive 3D speckle tracking was applied to consecutively acquired volumes of echo data. Volumes were omitted at fixed intervals and 3D speckle tracking was re-applied to study the effect of lower scan rates. Results revealed periodic motion that corresponded with the heart rate or breathing cycle in the absence or presence of respiration, respectively. For cardiac-induced motion, volume rates for adequate tracking ranged from 8 to 12 Hz and was limited by frequency discrepancies between tracking estimates from higher and lower frequency scan rates. Thus, the scan rate of volume data acquired without respiration was limited by the need to sample the frequency induced by the beating heart. In respiratory-dominated motion, volume rate limits ranged from 4 to 12 Hz, interpretable from the root-mean-squared deviation (RMSD) from tracking estimates at 24 Hz. While higher volume rates yielded RMSD values less than 1 mm in most cases, lower volume rates yielded RMSD values of 2-6 mm.

This paper studies the sensitivity of a range of image texture parameters used in radiomics to: i) the number of intensity levels, ii) the method of quantisation to select the intensity levels and iii) the use of an intensity threshold. 43 commonly used texture features were studied for the gross target volume outlined on the CT component of PET/CT scans of 50 patients with non-small cell lung carcinoma (NSCLC). All cases were quantised for all values between 4 and 128 intensity levels using four commonly used quantisation methods. All results were analysed with and without a threshold range of -200 HU to 300 HU. Cases were ranked for each texture feature and for all quantisation methods with the Spearman's rank correlation coefficient determined to evaluate stability. Results showed large fluctuations in ranking, particularly for low numbers of levels, differences between quantisation methods and with the use of a threshold, with values Spearman's Rank Correlation for many parameters below 0.2. Our results demonstrated the sensitivity of radiomics features to the parameters used during analysis and highlight the risk of low reproducibility comparing studies with slightly different parameters. In terms of the lung cancer CT datasets, this study supports the use of 128 intensity levels, the same uniform quantiser applied to all scans and thresholding of the data. It also supports several of the features recommended in the literature for such studies such as skewness and kurtosis. A recommended framework is presented for curation of the data analysis process to ensure stability of results.

Purpose: International consensus has not been reached regarding the optimal number of implanted tumour bed (TB) markers for partial breast/breast boost radiotherapy target volume delineation. Four common methods are: insertion of 6 clips (4 radial, 1 deep and 1 superficial), 5 clips (4 radial and 1 deep), 1 clip at the chest wall, and no clips. We compared TB volumes delineated using 6, 5, 1 and 0 clips in women who have undergone wide-local excision (WLE) of breast cancer (BC) with full-thickness closure of the excision cavity, in order to determine the additional margin required for breast boost or partial breast irradiation (PBI) when fewer than 6 clips are used. Methods: Ten patients with invasive ductal BC who had undergone WLE followed by implantation of six fiducial markers (titanium clips) each underwent CT imaging for radiotherapy planning purposes. Retrospective processing of the DICOM image datasets was performed to remove markers and associated imaging artefacts, using an in-house software algorithm. Four observers outlined TB volumes on four different datasets for each case: (1) all markers present (CT); (2) the superficial marker removed (CT); (3) all but the chest wall marker removed (CT); (4) all markers removed (CT). For each observer, the additional margin required around each of TB, TB, and TB in order to encompass TB was calculated. The conformity level index (CLI) and differences in centre-of-mass (COM) between observers were quantified for CT, CT, CT, CT. Results: The overall median additional margins required to encompass TB were 8 mm (range 0-28 mm) for TB, 5 mm (range 1-13 mm) for TB, and 2 mm (range 0-7 mm) for TB. CLI were higher for TB volumes delineated using CT (0.31) CT (0.32) than for CT (0.19) and CT (0.15). Conclusions: In women who have undergone WLE of breast cancer with full-thickness closure of the excision cavity and who are proceeding to PBI or breast boost RT, target volume delineation based on 0 or 1 implanted markers is not recommended as large additional margins are required to account for uncertainty over true TB location. Five implanted markers (one deep and four radial) are likely to be adequate assuming the addition of a standard 10-15 mm TB-CTV margin. Low CLI values for all TB volumes reflect the sensitivity of low volumes to small differences in delineation and are unlikely to be clinically significant for TB and TB in the context of adequate TB-CTV margins. © 2013 Elsevier Ireland Ltd. All rights reserved.

The data from eight patients who had undergone stereotactic body radiotherapy were selected due to their 4D-CT planning scans showing that their tumours had respiratory induced motion trajectories of large amplitude (greater than 9 mm in cranio-caudal direction). Radiotherapy plans with personalized motion-assessed margins were generated for these eight patients. The margins were generated by inverse 4D planning on an eight-bin phase-sorted 4D-CT scan. The planning was done on an in-house software system with a non-rigid registration stage being completed using freely available software. The resultant plans were then recalculated on a 4D-CT scan taken later during the course of treatment. Simulated image-guided patient set-up was used to align the geometric centres of the tumour region and minimize any misalignment between the two reconstructions. In general, the variation in the patient breathing patterns was found to be very small. Consequently, the degradation of the mean dose to the tumour region was found to be around a few percent (

Purpose: In Part 1 of this two-part work, predictions for light transport in powdered-phosphor screens are made, based on three distinct approaches. Predictions of geometrical optics-based ray tracing through an explicit microscopic model (EMM) for screen structure are compared to a Monte Carlo program based on the Boltzmann transport equation (BTE) and Swank's diffusion equation solution. The purpose is to: (I) highlight the additional assumptions of the BTE Monte Carlo method and Swank's model (both previously used in the literature) with respect to the EMM approach; (II) demonstrate the equivalences of the approaches under well-defined conditions and; (III) identify the onset and severity of any discrepancies between the models. A package of computer code (called phsphr) is supplied which can be used to reproduce the BTE Monte Carlo results presented in this work.Methods: The EMM geometrical optics ray-tracing model is implemented for hypothesized microstructures of phosphor grains in a binder. The BTE model is implemented as a Monte Carlo program with transport parameters, derived from geometrical optics, as inputs. The analytical solution of Swank to the diffusion equation is compared to the EMM and BTE predictions. Absorbed fractions and MTFs are calculated for a range of binder-to-phosphor relative refractive indices (n = 1.1-5.0), screen thicknesses (t = 50-200 μm), and packing fill factors (pf = 0.04-0.54).Results: Disagreement between the BTE and EMM approaches increased with n and pf. For the largest relative refractive index (n = 5) and highest packing fill (pf = 0.5), the BTE model underestimated the absorbed fraction and MTF50, by up to 40% and 20%, respectively. However, for relative refractive indices typical of real phosphor screens (n ≤ 2), such as Gd2O2S:Tb, the BTE and EMM predictions agreed well at all simulated packing densities. In addition, Swank's model agreed closely with the BTE predictions when the screen was thick enough to be considered turbid.Conclusions: Although some assumptions of the BTE are violated in realistic powdered-phosphor screens, these appear to lead to negligible effects in the modeling of optical transport for typical phosphor and binder refractive indices. Therefore it is reasonable to use Monte Carlo codes based on the BTE to treat this problem. Furthermore, Swank's diffusion equation solution is an adequate approximation if a turbidity condition, presented here, is satisfied.

This work investigates the feasibility of using a prototype complementary metal oxide semiconductor active pixel sensor (CMOS APS) for real-time verification of volumetric modulated arc therapy (VMAT) treatment. The prototype CMOS APS used region of interest read out on the chip to allow fast imaging of up to 403.6 frames per second (f/s). The sensor was made larger (5.4 cm × 5.4 cm) using recent advances in photolithographic technique but retains fast imaging speed with the sensor's regional read out. There is a paradigm shift in radiotherapy treatment verification with the advent of advanced treatment techniques such as VMAT. This work has demonstrated that the APS can track multi leaf collimator (MLC) leaves moving at 18 mm s(-1) with an automatic edge tracking algorithm at accuracy better than 1.0 mm even at the fastest imaging speed. Evaluation of the measured fluence distribution for an example VMAT delivery sampled at 50.4 f/s was shown to agree well with the planned fluence distribution, with an average gamma pass rate of 96% at 3%/3 mm. The MLC leaves motion and linac pulse rate variation delivered throughout the VMAT treatment can also be measured. The results demonstrate the potential of CMOS APS technology as a real-time radiotherapy dosimeter for delivery of complex treatments such as VMAT.

Background and purpose: To evaluate non-coplanar volumetric modulated arc radiotherapy (VMAT) trajectories for organ at risk (OAR) sparing in primary brain tumour radiotherapy. Materials and methods: Fifteen patients were planned using coplanar VMAT and compared against non-coplanar VMAT plans for three trajectory optimization techniques. A geometric heuristic technique (GH) combined beam scoring and Dijkstra's algorithm to minimize the importance-weighted sum of OAR volumes irradiated. Fluence optimization was used to perform a local search around coplanar and GH trajectories, producing fluence-based local search (FBLS) and FBLS+GH trajectories respectively. Results: GH, FBLS, and FBLS+GH trajectories reduced doses to the contralateral globe, optic nerve, hippocampus, temporal lobe, and cochlea. However, FBLS increased dose to the ipsilateral lens, optic nerve and globe. Compared to GH, FBLS+GH increased dose to the ipsilateral temporal lobe and hippocampus, contralateral optics, and the brainstem and body. GH and FBLS+GH trajectories reduced bilateral hippocampi normal tissue complication probability (p = 0.028 and p = 0.043, respectively). All techniques reduced PTV conformity; GH and FBLS+GH trajectories reduced homogeneity but less so for FBLS+GH. Conclusions: The geometric heuristic technique best spared OARs and reduced normal tissue complication probability, however incorporating fluence information into non-coplanar trajectory optimization maintained PTV homogeneity.

Purpose: Monte Carlo methods based on the Boltzmann transport equation (BTE) have previously been used to model light transport in powdered-phosphor scintillator screens. Physically motivated guesses or, alternatively, the complexities of Mie theory have been used by some authors to provide the necessary inputs of transport parameters. The purpose of Part II of this work is to: (i) validate predictions of modulation transform function (MTF) using the BTE and calculated values of transport parameters, against experimental data published for two Gd2O2S:Tb screens; (ii) investigate the impact of size-distribution and emission spectrum on Mie predictions of transport parameters; (iii) suggest simpler and novel geometrical optics-based models for these parameters and compare to the predictions of Mie theory. A computer code package called phsphr is made available that allows the MTF predictions for the screens modeled to be reproduced and novel screens to be simulated.Methods: The transport parameters of interest are the scattering efficiency (Qsct), absorption efficiency (Qabs), and the scatter anisotropy (g). Calculations of these parameters are made using the analytic method of Mie theory, for spherical grains of radii 0.1-5.0 μm. The sensitivity of the transport parameters to emission wavelength is investigated using an emission spectrum representative of that of Gd2O2S:Tb. The impact of a grain-size distribution in the screen on the parameters is investigated using a Gaussian size-distribution (σ = 1%, 5%, or 10% of mean radius). Two simple and novel alternative models to Mie theory are suggested: a geometrical optics and diffraction model (GODM) and an extension of this (GODM+). Comparisons to measured MTF are made for two commercial screens: Lanex Fast Back and Lanex Fast Front (Eastman Kodak Company, Inc.).Results: The Mie theory predictions of transport parameters were shown to be highly sensitive to both grain size and emission wavelength. For a phosphor screen structure with a distribution in grain sizes and a spectrum of emission, only the average trend of Mie theory is likely to be important. This average behavior is well predicted by the more sophisticated of the geometrical optics models (GODM+) and in approximate agreement for the simplest (GODM). The root-mean-square differences obtained between predicted MTF and experimental measurements, using all three models (GODM, GODM+, Mie), were within 0.03 for both Lanex screens in all cases. This is excellent agreement in view of the uncertainties in screen composition and optical properties.Conclusions: If Mie theory is used for calculating transport parameters for light scattering and absorption in powdered-phosphor screens, care should be taken to average out the fine-structure in the parameter predictions. However, for visible emission wavelengths (λ < 1.0 μm) and grain radii (a > 0.5 μm), geometrical optics models for transport parameters are an alternative to Mie theory. These geometrical optics models are simpler and lead to no substantial loss in accuracy.

A novel approach to proton CT reconstruction using backprojection-then-filtering (BPF) is proposed. A list-mode algorithm is formulated accommodating non-linear proton paths. The analytical form is derived for the deblurring kernel necessary for the filtering step. Further, a finite matrix correction is derived to correct for the limited size of the backprojection matrix. High quantitative accuracy in relative stopping power is demonstrated (⩽0.1%) using Monte Carlo simulations. This accuracy makes the algorithm a promising candidate for future proton CT systems in proton therapy applications. For the purposes of reconstruction, each proton path in the object-of-interest was estimated based on a cubic spline fit to the proton entry and exit vectors. The superior spatial-resolution of the BPF method over the standard filtering-then-backprojection approach is demonstrated. As the BPF algorithm requires only one backprojection and filtering operation on a scan data set, it also offers computational advantages over an iterative reconstruction approach.

Monte Carlo simulation is the gold standard method for modelling scattering processes in medical x-ray imaging. General-purpose Monte Carlo codes, however, typically use the independent atom approximation (IAA). This is known to be inaccurate for Rayleigh scattering, for many materials, in the forward direction. This work addresses whether the IAA is sufficient for the typical modelling tasks in medical kilovoltage x-ray imaging. As a means of comparison, we incorporate a more realistic 'interference function' model into a custom-written Monte Carlo code. First, we conduct simulations of scatter from isolated voxels of soft tissue, adipose, cortical bone and spongiosa. Then, we simulate scatter profiles from a cylinder of water and from phantoms of a patient's head, thorax and pelvis, constructed from diagnostic-quality CT data sets. Lastly, we reconstruct CT numbers from simulated sets of projection images and investigate the quantitative effects of the approximation. We show that the IAA can produce errors of several per cent of the total scatter, across a projection image, for typical x-ray beams and patients. The errors in reconstructed CT number, however, for the phantoms simulated, were small (typically < 10 HU). The IAA can therefore be considered sufficient for the modelling of scatter correction in CT imaging. Where accurate quantitative estimates of scatter in individual projection images are required, however, the appropriate interference functions should be included.

Purpose Proton CT is widely recognised as a beneficial alternative to conventional X-ray CT for treatment planning in proton beam radiotherapy. A novel proton CT imaging system, based entirely on solid-state detector technology, is presented. Compared to conventional scintillator-based calorimeters, positional sensitive detectors allow for multiple protons to be tracked per read out cycle, leading to a potential reduction in proton CT scan time. Design and characterisation of its components are discussed. An early proton CT image obtained with a fully solid-state imaging system is shown and accuracy (as defined in Section IV) in Relative Stopping Power to water (RSP) quantified. Method A solid-state imaging system for proton CT, based on silicon strip detectors, has been developed by the PRaVDA collaboration. The system comprises a tracking system that infers individual proton trajectories through an imaging phantom, and a Range Telescope (RT) which records the corresponding residual energy (range) for each proton. A back-projection-then-filtering algorithm is used for CT reconstruction of an experimentally acquired proton CT scan. Results An initial experimental result for proton CT imaging with a fully solid-state system is shown for an imaging phantom, namely a 75 mm diameter PMMA sphere containing tissue substitute inserts, imaged with a passively-scattered 125 MeV beam. Accuracy in RSP is measured to be 1.6% for all the inserts shown. Conclusions A fully solid-state imaging system for proton CT has been shown capable of imaging a phantom with protons and successfully improving RSP accuracy. These promising results, together with system the capability to cope with high proton fluences (2x108 protons/s), suggests that this research platform could improve current standards in treatment planning for proton beam radiotherapy.

The characteristics of an Elekta Precise treatment machine with a gating interface were investigated. Three detectors were used: a Farmer ionization chamber, a MatriXX ionization chamber array and an in-house, single pulse-measurement ionization chamber (IVC). Measurements were made of dosimetric accuracy, flatness and symmetry characteristics and duty cycle for a range of beam-on times and gating periods. Results were compared with a standard ungated delivery as a reference. For all beam-on times, down to 0.5 s, dosimetric differences were below +/-1% and flatness and symmetry parameter variations were below +/-1.5%. For the shorter beam-on times the in-house detector deviated from the other two detectors, suggesting that this device should be used in conjunction with other detectors for absolute dosimetry purposes. However, it was found to be useful for studying gated beam characteristics pulse by pulse.

The penetration characteristics of electron beams into x-ray targets are investigated for incident electron kinetic energies in the range 50-150 keV. The frequency densities of electrons penetrating to a depth x in a target, with a fraction of initial kinetic energy, u, are calculated using Monte Carlo methods for beam energies of 50, 80, 100, 120 and 150 keV in a tungsten target. The frequency densities for 100 keV electrons in Al, Mo and Re targets are also calculated. A mixture of simple modeling with equations and interpolation from data is used to generalize the calculations in tungsten. Where possible, parameters derived from the Monte Carlo data are compared to experimental measurements. Previous electron transport approximations in the semiempirical models of other authors are discussed and related to this work. In particular, the crudity of the use of the Thomson-Whiddington law to describe electron penetration and energy loss is highlighted. The results presented here may be used towards calculating the target self-attenuation correction for bremsstrahlung photons emitted within a tungsten target.

PURPOSE: To investigate a fluence-based trajectory optimization technique for non-coplanar VMAT for brain cancer. METHODS: Single-arc non-coplanar VMAT trajectories were determined using a heuristic technique for five patients. Organ at risk (OAR) volume intersected during raytracing was minimized for two cases: absolute volume and the sum of relative volumes weighted by OAR importance. These trajectories and coplanar VMAT formed starting points for the fluence-based optimization method. Iterative least squares optimization was performed on control points 24° apart in gantry rotation. Optimization minimized the root-mean-square (RMS) deviation of PTV dose from the prescription (relative importance 100), maximum dose to the brainstem (10), optic chiasm (5), globes (5) and optic nerves (5), plus mean dose to the lenses (5), hippocampi (3), temporal lobes (2), cochleae (1) and brain excluding other regions of interest (1). Control point couch rotations were varied in steps of up to 10° and accepted if the cost function improved. Final treatment plans were optimized with the same objectives in an in-house planning system and evaluated using a composite metric - the sum of optimization metrics weighted by importance. RESULTS: The composite metric decreased with fluence-based optimization in 14 of the 15 plans. In the remaining case its overall value, and the PTV and OAR components, were unchanged but the balance of OAR sparing differed. PTV RMS deviation was improved in 13 cases and unchanged in two. The OAR component was reduced in 13 plans. In one case the OAR component increased but the composite metric decreased - a 4 Gy increase in OAR metrics was balanced by a reduction in PTV RMS deviation from 2.8% to 2.6%. CONCLUSION: Fluence-based trajectory optimization improved plan quality as defined by the composite metric. While dose differences were case specific, fluence-based optimization improved both PTV and OAR dosimetry in 80% of cases.

Computed tomography images have been acquired using an experimental (low atomic number (Z) insert) megavoltage cone-beam imaging system. These images have been compared with standard megavoltage and kilovoltage imaging systems. The experimental system requires a simple modification to the 4 MeV electron beam from an Elekta Precise linac. Low-energy photons are produced in the standard medium-Z electron window and a low-Z carbon electron absorber located after the window. The carbon electron absorber produces photons as well as ensuring that all remaining electrons from the source are removed. A detector sensitive to diagnostic x-ray energies is also employed. Quantitative assessment of cone-beam computed tomography (CBCT) contrast shows that the low-Z imaging system is an order of magnitude or more superior to a standard 6 MV imaging system. CBCT data with the same contrast-to-noise ratio as a kilovoltage imaging system (0.15 cGy) can be obtained in doses of 11 and 244 cGy for the experimental and standard 6 MV systems, respectively. Whilst these doses are high for everyday imaging, qualitative images indicate that kilovoltage like images suitable for patient positioning can be acquired in radiation doses of 1-8 cGy with the experimental low-Z system.

A new method is proposed for scatter-correction of cone-beam CT images. A coarse reconstruction is used in initial iteration steps. Modelling of the x-ray tube spectra and detector response are included in the algorithm. Photon diffusion inside the imaging subject is calculated using the Monte Carlo method. Photon scoring at the detector is calculated using forced detection to a fixed set of node points. The scatter profiles are then obtained by linear interpolation. The algorithm is referred to as the coarse reconstruction and fixed detection (CRFD) technique. Scatter predictions are quantitatively validated against a widely used general-purpose Monte Carlo code: BEAMnrc/EGSnrc (NRCC, Canada). Agreement is excellent. The CRFD algorithm was applied to projection data acquired with a Synergy XVI CBCT unit (Elekta Limited, Crawley, UK), using RANDO and Catphan phantoms (The Phantom Laboratory, Salem NY, USA). The algorithm was shown to be effective in removing scatter-induced artefacts from CBCT images, and took as little as 2 min on a desktop PC. Image uniformity was greatly improved as was CT-number accuracy in reconstructions. This latter improvement was less marked where the expected CT-number of a material was very different to the background material in which it was embedded.

Three-dimensional (3D) soft tissue tracking using 3D ultrasound is of interest for monitoring organ motion during therapy. Previously we demonstrated feature tracking of respiration-induced liver motion in vivo using a 3D swept-volume ultrasound probe. The aim of this study was to investigate how object speed affects the accuracy of tracking ultrasonic speckle in the absence of any structural information, which mimics the situation in homogenous tissue for motion in the azimuthal and elevational directions. For object motion prograde and retrograde to the sweep direction of the transducer, the spatial sampling frequency increases or decreases with object speed, respectively. We examined the effect object motion direction of the transducer on tracking accuracy. We imaged a homogenous ultrasound speckle phantom whilst moving the probe with linear motion at a speed of 0-35 mm s⁻¹. Tracking accuracy and precision were investigated as a function of speed, depth and direction of motion for fixed displacements of 2 and 4 mm. For the azimuthal direction, accuracy was better than 0.1 and 0.15 mm for displacements of 2 and 4 mm, respectively. For a 2 mm displacement in the elevational direction, accuracy was better than 0.5 mm for most speeds. For 4 mm elevational displacement with retrograde motion, accuracy and precision reduced with speed and tracking failure was observed at speeds of greater than 14 mm s⁻¹. Tracking failure was attributed to speckle de-correlation as a result of decreasing spatial sampling frequency with increasing speed of retrograde motion. For prograde motion, tracking failure was not observed. For inter-volume displacements greater than 2 mm, only prograde motion should be tracked which will decrease temporal resolution by a factor of 2. Tracking errors of the order of 0.5 mm for prograde motion in the elevational direction indicates that using the swept probe technology speckle tracking accuracy is currently too poor to track homogenous tissue over a series of volume images as these errors will accumulate. Improvements could be made through increased spatial sampling in the elevational direction.

The problem of using information from the analysis of megavoltage images to adjust patient set-up has been addressed. In the case of rotational corrections it has been assumed that the treatment head is to be adjusted, although for gantry angles of 0 degree and 180 degrees couch rotation may be used. In the case of translational shifts adjustment of the collimator jaws or of the couch have both been considered for arbitrary combinations of couch and gantry angle. For couch movement the case has been considered where it is desirable to minimize both the number of parameters to be adjusted and also the magnitude of the change in the patient's position. Values obtained for frequently used set-up parameters have been presented. Adjustment of the treatment couch positioning is the most desirable option, as this should bring the patient closer to the correct position for subsequent treatment fields. However, rotational errors are not correctable for all gantry angles and furthermore the collimator settings may be set more accurately than those of the treatment couch. Hence, in some cases, adjustment of the collimation system may be desirable or necessary. The formulae given in Equations (13) to (18) are currently being used in an intervention study to correct patient set-up during the course of a treatment fraction.

BACKGROUND: Large breast size is associated with increased risk of late adverse effects after surgery and radiotherapy for early breast cancer. It is hypothesised that effects of radiotherapy on adipose tissue are responsible for some of the effects seen. In this study, the association of breast composition with late effects was investigated along with other breast features such as fibroglandular tissue distribution, seroma and scar. METHODS: The patient dataset comprised of 18 cases with changes in breast appearance at 2 years follow-up post-radiotherapy and 36 controls with no changes, from patients entered into the FAST-Pilot and UK FAST trials at The Royal Marsden. Breast composition, fibroglandular tissue distribution, seroma and scar were assessed on planning CT scan images and compared using univariate analysis. The association of all features with late-adverse effect was tested using logistic regression (adjusting for confounding factors) and matched analysis was performed using conditional logistic regression. RESULTS: In univariate analyses, no statistically significant differences were found between cases and controls in terms of breast features studied. A statistically significant association (p < 0.05) between amount of seroma and change in photographic breast appearance was found in unmatched and matched logistic regression analyses with odds ratio (95% CI) of 3.44 (1.28-9.21) and 2.57 (1.05-6.25), respectively. CONCLUSIONS: A significant association was found between seroma and late-adverse effects after radiotherapy although no significant associations were noted with breast composition in this study. Therefore, the cause for large breast size as a risk factor for late effects after surgery and optimally planned radiotherapy remains unresolved.

Proton radiotherapy has demonstrated benefits in the treatment of certain cancers. Accurate measurements of the proton stopping powers in body tissues are required in order to fully optimise the delivery of such treaments. The PRaVDA Consortium is developing a novel, fully solid state device to measure these stopping powers. The PRaVDA Range Telescope (RT), uses a stack of 24 CMOS Active Pixel Sensors (APS) to measure the residual proton energy after the patient. We present here the ability of the CMOS sensors to detect changes in the signal sizes as the proton traverses the RT, compare the results with theory, and discuss the implications of these results on the reconstruction of proton tracks.

Artifacts in treatment-room cone-beam reconstructions have been observed at the authors' center when cone-beam acquisition is simultaneous with radio frequency (RF) transponder tracking using the Calypso 4D system (Calypso Medical, Seattle, WA). These artifacts manifest as CT-number modulations and increased CT-noise. The authors present a method for the suppression of the artifacts.

A software program, SpekCalc, is presented for the calculation of x-ray spectra from tungsten anode x-ray tubes. SpekCalc was designed primarily for use in a medical physics context, for both research and education purposes, but may also be of interest to those working with x-ray tubes in industry. Noteworthy is the particularly wide range of tube potentials (40-300 kVp) and anode angles (recommended: 6-30 degrees) that can be modelled: the program is therefore potentially of use to those working in superficial/orthovoltage radiotherapy, as well as diagnostic radiology. The utility is free to download and is based on a deterministic model of x-ray spectrum generation (Poludniowski 2007 Med. Phys. 34 2175). Filtration can be applied for seven materials (air, water, Be, Al, Cu, Sn and W). In this note SpekCalc is described and illustrative examples are shown. Predictions are compared to those of a state-of-the-art Monte Carlo code (BEAMnrc) and, where possible, to an alternative, widely-used, spectrum calculation program (IPEM78).

Purpose To compare mean heart and left anterior descending coronary artery (LAD) doses (NTDmean) and positional reproducibility in larger-breasted women receiving left breast radiotherapy using supine voluntary deep-inspiratory breath-hold (VBH) and free-breathing prone techniques. Materials and methods Following surgery for early breast cancer, patients with estimated breast volumes >750 cm3 underwent planning-CT scans in supine VBH and free-breathing prone positions. Radiotherapy treatment plans were prepared, and mean heart and LAD doses were calculated. Patients were randomised to receive one technique for fractions 1–7, before switching techniques for fractions 8–15 (40 Gy/15 fractions total). Daily electronic portal imaging and alternate-day cone-beam CT (CBCT) imaging were performed. The primary endpoint was the difference in mean LAD NTDmean between techniques. Population systematic (Σ) and random errors (σ) were estimated. Within-patient comparisons between techniques used Wilcoxon signed-rank tests. Results 34 patients were recruited, with complete dosimetric data available for 28. Mean heart and LAD NTDmean doses for VBH and prone treatments respectively were 0.4 and 0.7 (p < 0.001) and 2.9 and 7.8 (p < 0.001). Clip-based CBCT errors for VBH and prone respectively were ⩽3.0 mm and ⩽6.5 mm (Σ) and ⩽3.5 mm and ⩽5.4 mm (σ). Conclusions In larger-breasted women, supine VBH provided superior cardiac sparing and reproducibility than a free-breathing prone position.

This paper gives an overview of recent developments in non-coplanar intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT). Modern linear accelerators are capable of automating motion around multiple axes, allowing efficient delivery of highly non-coplanar radiotherapy techniques. Novel techniques developed for C-arm and non-standard linac geometries, methods of optimization, and clinical applications are reviewed. The additional degrees of freedom are shown to increase the therapeutic ratio, either through dose escalation to the target or dose reduction to functionally important organs at risk, by multiple research groups. Although significant work is still needed to translate these new non-coplanar radiotherapy techniques into the clinic, clinical implementation should be prioritized. Recent developments in non-coplanar radiotherapy demonstrate that it continues to have a place in modern cancer treatment.

Breath-holding techniques reduce the amount of radiation received by cardiac structures during tangential-field left breast radiotherapy. With these techniques, patients hold their breath while radiotherapy is delivered, pushing the heart down and away from the radiotherapy field. Despite clear dosimetric benefits, these techniques are not yet in widespread use. One reason for this is that commercially available solutions require specialist equipment, necessitating not only significant capital investment, but often also incurring ongoing costs such as a need for daily disposable mouthpieces. The voluntary breath-hold technique described here does not require any additional specialist equipment. All breath-holding techniques require a surrogate to monitor breath-hold consistency and whether breath-hold is maintained. Voluntary breath-hold uses the distance moved by the anterior and lateral reference marks (tattoos) away from the treatment room lasers in breath-hold to monitor consistency at CT-planning and treatment setup. Light fields are then used to monitor breath-hold consistency prior to and during radiotherapy delivery. © JoVE 2006-2014. All Rights Reserved.

OBJECTIVE: To determine if subsets of patients may benefit from smaller or larger margins when using laser setup and bony anatomy verification of breast tumour bed (TB) boost radiotherapy (RT). METHODS: Verification imaging data acquired using cone-beam CT, megavoltage CT or two-dimensional kilovoltage imaging on 218 patients were used (1574 images). TB setup errors for laser-only setup (dlaser) and for bony anatomy verification (dbone) were determined using clips implanted into the TB as a gold standard for the TB position. Cases were grouped by centre-, patient- and treatment-related factors, including breast volume, TB position, seroma visibility and surgical technique. Systematic (Σ) and random (σ) TB setup errors were compared between groups, and TB planning target volume margins (MTB) were calculated. RESULTS: For the study population, Σlaser was between 2.8 and 3.4 mm, and Σbone was between 2.2 and 2.6 mm, respectively. Females with larger breasts (p = 0.03), easily visible seroma (p ≤ 0.02) and open surgical technique (p ≤ 0.04) had larger Σlaser. Σbone was larger for females with larger breasts (p = 0.02) and lateral tumours (p = 0.04). Females with medial tumours (p 

Proton imaging is a promising technology for proton radiotherapy as it can be used for: (1) direct sampling of the tissue stopping power, (2) input information for multi-modality RSP reconstruction, (3) gold-standard calibration against concurrent techniques, (4) tracking motion and (5) pre-treatment positioning. However, no end-to-end characterization of the image quality (signal-to-noise ratio and spatial resolution, blurring uncertainty) against the dose has been done. This work aims to establish a model relating these characteristics and to describe their relationship with proton energy and object size. The imaging noise originates from two processes: the Coulomb scattering with the nucleus, producing a path deviation, and the energy loss straggling with electrons. The noise is found to increases with thickness crossed and, independently, decreases with decreasing energy. The scattering noise is dominant around high-gradient edge whereas the straggling noise is maximal in homogeneous regions. Image quality metrics are found to behave oppositely against energy: lower energy minimizes both the noise and the spatial resolution, with the optimal energy choice depending on the application and location in the imaged object. In conclusion, the model presented will help define an optimal usage of proton imaging to reach the promised application of this technology and establish a fair comparison with other imaging techniques.

A maximum likelihood approach to the problem of calculating the proton paths inside the scanned object in proton computed tomography is presented. Molière theory is used for first time to derive a physical model that describes proton multiple Coulomb scattering, avoiding the need for the Gaussian approximation currently used. To enable this, the proposed method approximates proton paths with cubic Bézier curves and subsequently maximizes the path likelihood through parametric optimization, based on the Molière model. Results from the Highland formula-based Gaussian approximation are also presented for comparison. The simplex method is utilized for optimisation. The scattering properties of the material(s) of the scanned object are taken into account by appropriately calculating the scattering parameters from the stopping power map that is calculated/updated at every iteration of the algebraic reconstruction process. Proton track length constraint imposed by the proton energy loss is also accounted for. The method is also applied in the case that no exit angle data are measured. Geant4 Monte Carlo simulations were performed for model validation. Our results show that use of Molière probability density function for modelling the multiple Coulomb scattering presents a modest 2% accuracy improvement over the Gaussian approximation and most-likely-path method. Simulations of voxelized phantom showed no essential benefit from the inclusion of the material information into the optimization, while path optimization with energy constraint slightly increased path resolution in a bone/water interface phantom. Method error was found to depend on energy, proton track-length within the medium, and proportion of data filtering.

Lung cancer is the leading cause of cancer mortality worldwide. Treatment pathways include regular cross-sectional imaging, generating large data sets which present intriguing possibilities for exploitation beyond standard visual interpretation. This additional data mining has been termed ‘radiomics’ and includes semantic and agnostic approaches. Texture Analysis (TA) is an example of the latter, and uses a range of mathematically derived features to describe an image or region of an image. Often TA is used to describe a suspected or known tumour. TA is an attractive tool as large existing image sets can be submitted to diverse techniques for data processing, presentation, interpretation and hypothesis testing with annotated clinical outcomes. There is a growing anthology of published data using different TA techniques to differentiate between benign and malignant lung nodules, differentiate tissue sub-types of lung cancer, prognosticate and predict outcome and treatment response, as well as predict treatment side effects and potentially aid radiotherapy planning. The aim of this systematic review is to summarise the current published data and understand the potential future role of TA in managing lung cancer.

BACKGROUND: Accurate segmentation of breast tissues is required for a number of applications such as model based deformable registration in breast radiotherapy. The accuracy of breast tissue segmentation is affected by the spatial distribution (or pattern) of fibroglandular tissue (FT). The goal of this study was to develop and evaluate texture features, determined from planning computed tomography (CT) data, to classify the spatial distribution of FT in the breast. METHODS: Planning CT data of 23 patients were evaluated in this study. Texture features were derived from the radial glandular fraction (RGF), which described the distribution of FT within three breast regions (posterior, middle, and anterior). Using visual assessment, experts grouped patients according to FT spatial distribution: sparse or non-sparse. Differences in the features between the two groups were investigated using the Wilcoxon rank test. Classification performance of the features was evaluated for a range of support vector machine (SVM) classifiers. RESULTS: Experts found eight patients and 15 patients had sparse and non-sparse spatial distribution of FT, respectively. A large proportion of features (>9 of 13) from the individual breast regions had significant differences (p

Aims To evaluate the feasibility and heart-sparing ability of the voluntary breath-hold (VBH) technique in a multicentre setting. Materials and methods Patients were recruited from 10 UK centres. Following surgery for early left breast cancer, patients with any heart inside the 50% isodose from a standard free-breathing tangential field treatment plan underwent a second planning computed tomography (CT) scan using the VBH technique. A separate treatment plan was prepared on the VBH CT scan and used for treatment. The mean heart, left anterior descending coronary artery (LAD) and lung doses were calculated. Daily electronic portal imaging (EPI) was carried out and scanning/treatment times were recorded. The primary end point was the percentage of patients achieving a reduction in mean heart dose with VBH. Population systematic (Σ) and random errors (σ) were estimated. Within-patient comparisons between techniques used Wilcoxon signed-rank tests. Results In total, 101 patients were recruited during 2014. Primary end point data were available for 93 patients, 88 (95%) of whom achieved a reduction in mean heart dose with VBH. Mean cardiac doses (Gy) for free-breathing and VBH techniques, respectively, were: heart 1.8 and 1.1, LAD 12.1 and 5.4, maximum LAD 35.4 and 24.1 (all P

Radiotherapy treatment plans using dynamic couch rotation during volumetric modulated arc therapy (DCR-VMAT) reduce the dose to organs at risk (OARs) compared to coplanar VMAT, while maintaining the dose to the planning target volume (PTV). This paper seeks to validate this finding with measurements. DCR-VMAT treatment plans were produced for five patients with primary brain tumours and delivered using a commercial linear accelerator (linac). Dosimetric accuracy was assessed using point dose and radiochromic film measurements. Linac-recorded mechanical errors were assessed by extracting deviations from log files for multi-leaf collimator (MLC), couch, and gantry positions every 20 ms. Dose distributions, reconstructed from every fifth log file sample, were calculated and used to determine deviations from the treatment plans. Median (range) treatment delivery times were 125 s (123–133 s) for DCR-VMAT, compared to 78 s (64–130 s) for coplanar VMAT. Absolute point doses were 0.8% (0.6%–1.7%) higher than prediction. For coronal and sagittal films, respectively, 99.2% (96.7%–100%) and 98.1% (92.9%–99.0%) of pixels above a 20% low dose threshold reported gamma  

Purpose: In breast radiotherapy, the target volume may change during treatment and need adaptation of the treatment plan. This is possible for both tumour bed (TB) and whole breast (WB) target volumes. Delineation of the target (to detect changes) is also subject to uncertainty due to intra- and inter-observer variability. This work measured the uncertainty, due to intraobserver variability, in the quantification of tissue deformation. Methods: Datasets consisting of paired prone and supine CT scans of three patients were used. Significant deformation in target volumes is expected between prone and supine patient positions. The selected cases had 1) no seroma, 2) some seroma, and 3) large seroma. The TB and WB were outlined on each dataset three times by one clinician. Delineation variability was defined as the standard deviations of the distances between observer outlines. For each target volume and each case, tissue deformation between prone and supine delineations was quantified using the Dice similarity coefficient (DSC) and the average surface distance (ASD). The uncertainty in the tissue deformation (due to delineation variability) was quantified by measuring the ranges of DSC and ASD using all combinations of pairs of outlines (9 pairs). Results: For the TB, the range of delineation variability was 0.44-1.16 mm. The deformation, DSC and ASD, (and uncertainty in measurement) of the TB between prone and supine position of the cases were: 1) 0.21 (0.17-0.28) and 12.4 mm (11.8-13 mm); 2) 0.54 (0.51-0.57) and 3.3 mm (3.1-3.5 mm); 3) 0.62 (0.61-0.64) and 4.9 mm (4.6-5.2 mm). WB deformation measurements were subject to less uncertainty due to delineation variability than TB deformation measurements. Conclusion: For the first time, the uncertainty, due to observer variability, in the measurement of the deformation of breast target volumes was investigated. Deformations in these ranges would be difficult to detect. This work was supported in part by Cancer Research-UK under Programme Grant C46/A10588 and in part by the National Institute for Health Research (NIHR) through funding of the biomedical research imaging centre. P. Juneja is supported by the EPSRC Platform Grant EP/H046526/1.

Purpose: To validate and compare methods for breast tissue segmentation using a new approach based on supine and prone computed tomography data. Method and Materials: The breast was segmented into fibroglandular and fatty tissue for 24 patients, who had CT scans in both supine and prone position on the same day. The segmentation methods explored were: physical density thresholding; two compartment model; interactive thresholding; fuzzy c‐means clustering (FCM) with different thresholds; and k‐means clustering. Firstly, validation was based on the assumption that the breast composition is the same for supine and prone CT. Volumetric breast density (VBD, proportion of breast composed of fibroglandular tissue) of supine and prone scans and its relative difference (RDVBD) were calculated. Expert outlining was used for further validation using the Dice similarity coefficient (DSC). Analysis of variance (ANOVA) followed by post‐hoc comparisons (Bonferroni, p

Purpose: To design and evaluate an optimised radiotherapy imaging beam, based on a prototype Elekta waveguide, with a novel coupling device (rotovane) allowing for a wide, continuously variable energy range. Methods: A waveguide test piece consisting of a buncher, rotovane and short relativistic section was used to investigate the performance of the novel continuously variable coupling device, and in particular investigate imaging at low megavoltage energies. An optimised imaging system utilising the lowest electron energy of the waveguide (1.4 MeV) was designed using BEAMnrc and implemented experimentally. Characterisation of the imaging beam was conducted experimentally and via Monte Carlo simulations. Cone beam computed tomography images (CBCT) were acquired using a Caesium Iodide imaging panel of humanoid anthropomorphic phantoms and a Catphan phantom. The contrast to noise ratio was assessed for CBCT and compared to kilo‐voltage and megavoltage imaging systems. Results: The optimised imaging beam target assembly consisted of an electron window, 5 mm carbon electron absorber and 2.5 mm of Aluminium filtration. The x‐ray beam had an average photon energy of 220 keV and a half value layer of 5.9 mm of Copper. Images with the same contrast to noise ratio as a 100 kVp CBCT system (XVI, Elekta) were obtained in doses less than 2 cGy; this is 11x higher than XVI but 150x lower than a megavoltage imaging system. Qualitatively, kilo‐voltage equivalent images of head and pelvis phantoms were obtained in doses between 1 and 8 cGy. Conclusions: The prototype waveguide section was capable of producing electron energies from 1.4 to 9 MeV, suitable for imaging and therapy. The waveguide technology has the potential for producing near kilo‐voltage equivalent images in acceptable dose from the therapy beam portal without the need for add‐on x‐ray systems. Additionally such a system could provide for enhanced target tracking during radiotherapy treatment. This work is supported by Elekta Ltd and The Institute of Cancer Research. Work of the ICR radiotherapy physics group is partially supported by Cancer Research UK under programme grant C46/A3970

Purpose: This study investigated how object speed affects 3D speckle tracking accuracy and precision in the azimuthal and elevational directions when using a mechanically swept 3D ultrasound probe. Methods: A 3D probe was used to acquire B‐mode volumetric ultrasound images of a homogenous tissue‐mimicking ultrasound phantom. Object motion was simulated by moving the probe in the azimuthal and elevational directions using a translational stage with 3‐axis of motion whilst volumetric images were continuously acquired. To form volumetric images the transducer was mechanically swept back and forth and therefore object motion was prograde or retrograde to the transducer's sweep motion. Displacement between volumes was estimated using 3D correlation‐based speckle tracking of a region of interest (ROI) located at various positions within the phantom. We investigated tracking accuracy and precision for speed of 0 to 35 mm s‐1 for fixed displacements of 2mm and 4mm, for prograde and retrograde motion and as a function of depth. Results: For the azimuthal direction, both accuracy and precision were better than 0.1mm and 0.15mm for 2mm and 4mm displacements respectively and no significant correlation was found between accuracy and speed and between accuracy and depth. For the elevational direction and 2mm displacement, accuracy was 0.25mm and 0.3mm for prograde and retrograde motion respectively. Accuracy and precision were greatest at the elevational focus (60mm). For a 4mm elevational displacement with retrograde motion, accuracy and precision reduced with speed and tracking failure was observed at speeds > 14mms‐1, this was not observed for prograde motion. Conclusion: For mechanically swept 3D probes tracking in the elevational direction is poor for retrograde motion at speeds of greater than 14mms‐1. Thus for inter‐volume displacements greater than 2mm only prograde motion should be tracked which will decrease temporal resolution by a factor of 2.

Purpose: To develop a fast Monte‐Carlo‐based scatter‐correction algorithm for clinical keV cone‐beam CT (CBCT) images. Method and Materials: Estimates of the scatter in the projection‐views of a CBCT scan were obtained by an iterative process, each step consisting of: (1) a coarse CBCT reconstruction; (2) simulation of photon histories for projections using a purpose‐written Monte Carlo code; (3) scoring scatter contributions to fixed points on the detector (a “forced detection” technique); and (4) subtraction of scatter‐estimates from the measured pixel‐values. The scatter signal at each pixel was estimated using linear interpolation spatially between the values calculated at the fixed points and angularly between projection angles. Following convergence to a set of scatter‐corrected profiles, a final full‐resolution scatter‐corrected reconstruction was performed. All CBCT reconstructions were performed using software developed in‐house. The x‐ray tube spectrum and the energy‐response of the detector were both modeled. To validate the technique, projection measurements (120 kV and 0.4 mAs per projection) of a Catphan quality‐assurance phantom (The Phantom Laboratory) were obtained using a Synergy XVI CBCT unit (Elekta Limited). Results: Typically the algorithm took less than 2 min to complete 4 iterations on a desktop PC, after which convergence was obtained. Qualitatively, the algorithm resulted in an improved image with the characteristic ‘cupping’ artifacts, due to scatter, disappearing. Quantitatively, non‐uniformity was decreased after correction from about 15% to 1% or less at a cost of an increase in image noise from 3.7% to 5.1%. CT number accuracy was also markedly improved. Conclusion: It was shown Monte‐Carlo‐based scatter‐correction of clinical keV CBCT images does not have to be prohibitively slow. Such a scatter‐correction can be successfully performed in a few CPU minutes.

Purpose: This study investigates the use of a mechanically swept 3D ultrasound (US) probe to estimate intra-fraction motion of the prostate during radiation therapy using an US phantom and simulated transperineal imaging. Methods: A 3D motion platform was used to translate an US speckle phantom while simulating transperineal US imaging. Motion patterns for five representative types of prostate motion, generated from patient data previously acquired with a Calypso system, were using to move the phantom in 3D. The phantom was also implanted with fiducial markers and subsequently tracked using the CyberKnife kV x-ray system for comparison. A normalised cross correlation block matching algorithm was used to track speckle patterns in 3D and 2D US data. Motion estimation results were compared with known phantom translations. Results: Transperineal 3D US could track superior-inferior (axial) and anterior-posterior (lateral) motion to better than 0.8 mm root-mean-square error (RMSE) at a volume rate of 1.7 Hz (comparable with kV x-ray tracking RMSE). Motion estimation accuracy was poorest along the US probe's swept axis (right-left; RL; RMSE < 4.2 mm) but simple regularisation methods could be used to improve RMSE (< 2 mm). 2D US was found to be feasible for slowly varying motion (RMSE < 0.5 mm). 3D US could also allow accurate radiation beam gating with displacement thresholds of 2 mm and 5 mm exhibiting a RMSE of less than 0.5 mm. Conclusion: 2D and 3D US speckle tracking is feasible for prostate motion estimation during radiation delivery. Since RL prostate motion is small in magnitude and frequency, 2D or a hybrid (2D/3D) US imaging approach which also accounts for potential prostate rotations could be used. Regularisation methods could be used to ensure the accuracy of tracking data, making US a feasible approach for gating or tracking in standard or hypo-fractionated prostate treatments.

Purpose: To find appropriate parameter values for the Lyman‐Kutcher‐Burman (LKB), Normal Tissue Complication Probability (NTCP) model for modern, clinically relevant late rectal side effects experienced after prostate radiotherapy. Method and Materials: Rectal dose‐volume histograms and detailed long‐term follow‐up data from 178 patients from the MRC RT01 multicentre randomized controlled trial of conformal prostate radiotherapy were analysed. Endpoints chosen to represent late toxicities reported in modern practice were rectal bleeding and proctitis recorded by the clinician and loose stools and urgency recorded by the patient. The various grading schemes used in the trial were standardized in terms of moderate/severe toxicity. Patients with pre‐treatment symptoms were excluded from the analysis. Optimal LKB parameter values for TD50(1), m and n were found using the maximum likelihood estimation of log‐likelihood. 95% confidence intervals were calculated using the profile‐likelihood method. Results: The maximum‐likelihood estimation yielded values of TD50(1)=67.50 (CI 65.49–69.96), m=0.15 (CI 0.11–0.21), n=0.10 (CI 0.07–0.14) for proctitis; TD50(1)=67.75 (CI 63.64–72.89), m=0.25 (CI 0.20–0.34), n=0.28 (CI 0.18–0.45) for rectal bleeding; TD50(1)=73.50 (CI 64.29–86.73), m=0.38 (CI 0.30–0.49), n=1.00 (CI 0.37 — outside range calculated) for loose stools and TD50(1)=67.00 (CI 61.89–73.60), m=0.30 (CI 0.22–0.44), n=0.30 (CI 0.17–0.56) for rectal urgency. Conclusion: The NTCP parameters obtained for four clinically relevant rectal side effects were significantly different from each other. The results for proctitis provide the best comparison with the original Emami data, the values for m and n were in good agreement whilst TD50(1) was significantly lower, perhaps reflecting the reduction in severity of complication. Values of n implying both serial and parallel volume effect were observed. These variations highlight the complexity of the dose‐volume response of the rectum and indicate that the NTCP model should be used with caution as a clinical tool.

Purpose: To develop a free and easy‐to‐use software program to model the x‐ray spectra emitted from x‐ray tubes. Such a program is useful for the education of physicists, technicians and technologists working in radiation physics but also as a research tool. Method and Materials: A Graphical User Interface (GUI) was created using REALbasic (REAL software, Inc.). This GUI, designated the name SpekCalc, allows the user to calculate and display the x‐ray spectra emitted from tungsten‐anode x‐ray tubes. The underlying theoretical description for the bremsstrahlung and characteristic x‐ray production is taken from a recent published model. Results: The user selects the tube potential in kVp, the take‐off angle and the amount of filtration. At a click of a button the resulting spectrum is calculated, displayed and can be saved for later use. Beam quality parameters such as the half‐value‐layer, in mm of aluminum and copper, and the mean beam energy, in keV, are also presented to the user. The range of potentials that can be modeled is wide (40–300 kVp) making Spekcalc useful to both the diagnostic imaging and keV photon radiotherapy fields. Filtration can be selected in mm, for 7 materials: aluminium, copper, tungsten, tin, beryllium, water and air. This allows an in‐depth exploration of the filtration effects of materials of differing atomic number. Over 300 individuals have downloaded this program thus‐far, for reasons as diverse as teaching in universities, to learn interactively about x‐ray tubes, for research in radiology and radiotherapy. Conclusion: A useful educational tool for physicists, technicians and technologists has been created, in the form of freely‐available software utility to calculate x‐ray tube spectra.

Objective: The purpose of the work was to estimate the dose received by the heart throughout a course of breath-holding breast radiotherapy. Methods: 113 cone-beam CT (CBCT) scans were acquired for 20 patients treated within the HeartSpare 1A study, in which both an active breathing control (ABC) device and a voluntary breath-hold (VBH) method were used. Predicted mean heart doses were obtained from treatment plans. CBCT scans were imported into a treatment planning system, heart outlines defined, images registered to the CT planning scan and mean heart dose recorded. Two observers outlined two cases three times each to assess interobserver and intraobserver variation. Results: There were no statistically significant differences between ABC and VBH heart dose data from CT planning scans, or in the CBCT-based estimates of heart dose, and no effect from the order of the breath-hold method. Variation in mean heart dose per fraction over the three imaged fractions was,6 cGy without setup correction, decreasing to 3.3 cGy with setup correction. If scaled to 15 fractions, all differences between predicted and estimated mean heart doses were

We describe a feasibility study testing the use of gold seeds for the identification of post-operative tumour bed after breast conservation surgery (BCS). Fifty-three patients undergoing BCS for invasive cancer were recruited. Successful use was defined as all six seeds correctly positioned around the tumour bed during BCS, unique identification of all implanted seeds on CT planning scan and ⩾3 seeds uniquely identified at verification to give couch displacement co-ordinates in 10/15 fractions. Planning target volume (PTV) margin size for four correction strategies were calculated from these data. Variability in tumour bed contouring was investigated with five radiation oncologists outlining five CT datasets. Success in inserting gold seeds, identifying them at CT planning and using them for on-treatment verification was recorded in 45/51 (88%), 37/38 (97%) and 42/43 (98%) of patients, respectively. The clinicians unfamiliar with CT breast planning consistently contoured larger volumes than those already trained. Margin size ranged from 10.1 to 1.4mm depending on correction strategy. It is feasible to implant tumour bed gold seeds during BCS. Whilst taking longer to insert than surgical clips, they have the advantage of visibility for outlining and verification regardless of the ionising radiation beam quality. Appropriate correction strategies enable margins of the order of 5mm as required by the IMPORT trials however, tackling clinician variability in contouring is important.

Local cancer relapse risk after breast conservation surgery followed by radiotherapy has fallen sharply in many countries, and is influenced by patient age and clinicopathological factors. We hypothesise that partial-breast radiotherapy restricted to the vicinity of the original tumour in women at lower than average risk of local relapse will improve the balance of beneficial versus adverse effects compared with whole-breast radiotherapy. IMPORT LOW is a multicentre, randomised, controlled, phase 3, non-inferiority trial done in 30 radiotherapy centres in the UK. Women aged 50 years or older who had undergone breast-conserving surgery for unifocal invasive ductal adenocarcinoma of grade 1-3, with a tumour size of 3 cm or less (pT1-2), none to three positive axillary nodes (pN0-1), and minimum microscopic margins of non-cancerous tissue of 2 mm or more, were recruited. Patients were randomly assigned (1:1:1) to receive 40 Gy whole-breast radiotherapy (control), 36 Gy whole-breast radiotherapy and 40 Gy to the partial breast (reduced-dose group), or 40 Gy to the partial breast only (partial-breast group) in 15 daily treatment fractions. Computer-generated random permuted blocks (mixed sizes of six and nine) were used to assign patients to groups, stratifying patients by radiotherapy treatment centre. Patients and clinicians were not masked to treatment allocation. Field-in-field intensity-modulated radiotherapy was delivered using standard tangential beams that were simply reduced in length for the partial-breast group. The primary endpoint was ipsilateral local relapse (80% power to exclude a 2·5% increase [non-inferiority margin] at 5 years for each experimental group; non-inferiority was shown if the upper limit of the two-sided 95% CI for the local relapse hazard ratio [HR] was less than 2·03), analysed by intention to treat. Safety analyses were done in all patients for whom data was available (ie, a modified intention-to-treat population). This study is registered in the ISRCTN registry, number ISRCTN12852634. Between May 3, 2007, and Oct 5, 2010, 2018 women were recruited. Two women withdrew consent for use of their data in the analysis. 674 patients were analysed in the whole-breast radiotherapy (control) group, 673 in the reduced-dose group, and 669 in the partial-breast group. Median follow-up was 72·2 months (IQR 61·7-83·2), and 5-year estimates of local relapse cumulative incidence were 1·1% (95% CI 0·5-2·3) of patients in the control group, 0·2% (0·02-1·2) in the reduced-dose group, and 0·5% (0·2-1·4) in the partial-breast group. Estimated 5-year absolute differences in local relapse compared with the control group were -0·73% (-0·99 to 0·22) for the reduced-dose and -0·38% (-0·84 to 0·90) for the partial-breast groups. Non-inferiority can be claimed for both reduced-dose and partial-breast radiotherapy, and was confirmed by the test against the critical HR being more than 2·03 (p=0·003 for the reduced-dose group and p=0·016 for the partial-breast group, compared with the whole-breast radiotherapy group). Photographic, patient, and clinical assessments recorded similar adverse effects after reduced-dose or partial-breast radiotherapy, including two patient domains achieving statistically significantly lower adverse effects (change in breast appearance [p=0·007 for partial-breast] and breast harder or firmer [p=0·002 for reduced-dose and p

In this study, we investigated the capacity of various ion beams available for radiotherapy to produce high quality relative stopping power map acquired from energy-loss measurements. The image quality metrics chosen to compare the different ions were signal-to-noise ratio (SNR) as a function of dose and spatial resolution. Geant4 Monte Carlo simulations were performed for: hydrogen, helium, lithium, boron and carbon ion beams crossing a 20 cm diameter water phantom to determine SNR and spatial resolution. It has been found that protons possess a significantly larger SNR when compared with other ions at a fixed range (up to 36$\%$ higher than helium) due to the proton nuclear stability and low dose per primary. However, it also yields the lowest spatial resolution against all other ions, with a resolution lowered by a factor 4 compared to that of Carbon imaging, for a beam with the same initial range. When comparing for a fixed spatial resolution of 10~lp/cm, carbon ions produce the highest image quality metrics with proton ions producing the lowest. In conclusion, it has been found that no ion can maximize all image quality metrics simultaneously and that a choice must be made between spatial resolution, SNR, and dose.

19 Background: Particle imaging can increase precision in proton and ion therapy. Interactions

To develop and demonstrate an end-to-end assessment procedure for adaptive radiotherapy (ART) within an MR-guided system. A 3D printed pelvic phantom was designed and constructed for use in this study. The phantom was put through the complete radiotherapy treatment chain, with planned internal changes made to model prostate translations and shape changes, allowing an investigation into three ART techniques commonly used. Absolute dosimetry measurements were made within the phantom using both gafchromic film and alanine. Comparisons between treatment planning system (TPS) calculations and measured dose values were made using the gamma evaluation with criteria of 3 mm/3% and 2 mm/2%. Gamma analysis evaluations for each type of treatment plan adaptation investigated showed a very high agreement with pass rates for each experiment ranging from 98.10% to 99.70% and 92.60% to 97.55%, for criteria of 3%/3 mm and 2%/2 mm respectively. These pass rates were consistent for both shape and position changes. Alanine measurements further supported the results, showing an average difference of 1.98% from the TPS. The end-to-end assessment procedure provided demanding challenges for treatment plan adaptations to demonstrate the capabilities and achieved high consistency in all findings.

A Machine Learning approach to the problem of calculating the proton paths inside a scanned object in proton Computed Tomography is presented. The method is developed in order to mitigate the loss in both spatial resolution and quantitative integrity of the reconstructed images caused by multiple Coulomb scattering of protons traversing the matter. Two Machine Learning models were used: a forward neural network and the XGBoost method. A heuristic approach, based on track averaging was also implemented in order to evaluate the accuracy limits on track calculation, imposed by the statistical nature of the scattering. Synthetic data from anthropomorphic voxelized phantoms, generated by the Monte Carlo Geant4 code, were utilised to train the models and evaluate their accuracy, in comparison to a widely used analytical method that is based on likelihood maximization and Fermi-Eyges scattering model. Both neural network and XGBoost model were found to perform very close or at the accuracy limit, further improving the accuracy of the analytical method (by 12% in the typical case of 200MeV protons on 20 cm of water object), especially for protons scattered at large angles. Inclusion of the material information along the path in terms of radiation length did not show improvement in accuracy, for the phantoms simulated in the study. A neural network was also constructed to predict the error in path calculation, thus enabling a criterion to filter out proton events that may have a negative effect on the quality of the reconstructed image. By parametrizing a large set of synthetic data, the Machine Learning models were proved capable to bring - in an indirect and time efficient way - the accuracy of the Monte Carlo method into the problem of proton tracking.

Introduction: A standard method of tumour bed (TB) delineation for partial-breast irradiation (PBI) involves outlining titanium clips and architectural abnormalities on CT images. Uncertainties remain regarding delineation of TB/normal tissue interface between clips. MRI offers greater soft-tissue contrast.We investigated whether MRI adds information leading to changes in CT/clip-defined target volumes, and evaluated the clinical significance of differences. Methods: 30 women with breast invasive ductal carcinoma/DCIS underwent lumpectomy during which 6e12 titanium clips were secured in the four radial, anterior and deep excision margins of the TB. Patients underwent CT imaging and MRI in the same prone position. 3D-MRI datasets (T1-weighted [standard and fat-suppressed] and T2-weighted) were co-registered with CT data (matched using clips). TB was delineated separately on CT, MR, and fused MR-CT datasets. Clinical (CTV) (TB + 15 mm) and planning target volumes (PTV) (CTV + 10 mm) were generated. The primary endpoint was conformity index (CI) between CT and fused-MRCT TB (volume of agreement divided by total delineated volume [volumetotal]). DiscordanceCT was defined as percentage of volumetotal missed by CT, and discordanceMRCT as percentage of volumetotal missed by MRCT. Partial-breast dose distributions were generated for CT/clip-CTV, and percentage of MRCT-CTV receiving O95% of isocentre dose. Results: Median CT/clip and MRCT-TB volumes were 5.7 cm3 and 9.7 cm3, respectively (mean percentage volume increase ¼ 55.1%). Mean CIs for CT vs MRCT were 0.54 (TB), 0.84 (CTV) and 0.89 (PTV). For CT vs MRCT TB, discordanceCT (i.e. geographical miss of seroma/haemorrhage seen on MR) was 37.1%. DiscordanceMRCT (i.e. inappropriate inclusion of normal breast tissue on CT) was 9.2%. Median coverage of CT/clip-CTV by 95% isodose was 97.1% (30/30 CTV covered). Median coverage of MRCT-CTV was 96.5%. 4/ 30 MRCT-CTV were inadequately covered (worst coverage ¼ 89.0%). Conclusions: Addition of MR to CT/clip data increases TB volume by identifying additional seroma/haemorrhage. TB discordance rarely translates into clinically significant differences in CTV/PTV. CT/ clip-based PBI plans adequately cover MRCT-defined target volumes in most cases. CT/clip-based TB delineation should remain the current standard for PBI.

Breast radiotherapy increases risks of late cardiovascular mortality/morbidity. LAD irradiation is implicated in pathogenesis, but the effects of prone positioning on its dosimetry are unknown. We compared LAD and heart doses from whole (WBI) and partial (PBI) breast radiotherapy planned prone and supine. Methods: Thirty-nine (14 left-breast-affected) patients had titanium clips placed in excision cavity walls at breast-conservation surgery. Each underwent standard supine CT scanning before repositioning and re-imaging prone on an in-house platform with an aperture through which index breast falls. Partial-breast (PB) CTV was defined as tumour bed (clips/architectural distortion) plus 15 mm margin. WBclinical target volume (CTV) was defined using radio-opaque wire marking clinically palpable breast tissue. Heart and LAD were outlined. Conventional tangential-field PBI and WBI plans and dosevolume histograms were produced for each position (total: 156 plans). Mean heart/LAD, and maximum LAD doses were compared. Results: In left-breast-affected patients, mean (SD) LADmean doses were 11.5 (8.4) Gy (supineWB), 12.1 (7.4) Gy (proneWB), 1.7 (1.6) Gy (supinePB), and 3.2 (3.0) Gy (pronePB). Mean (SD) LADmax doses were 47.5 (5.7) Gy (supineWB), 47.4 (3.7) Gy (proneWB), 22.8 (19.3) Gy (supinePB) and 32.1 (17.1) Gy (pronePB). Prone positioning improved heart and LAD doses in 6/ 14 WBI (mean improvement in LADmean ¼ 12.0 Gy) and 3/14 PBI cases (mean improvement in LADmax ¼ 25.3 Gy), but worsened doses in 7/14 WBI (mean increase in LADmean¼ 9.8 Gy) and 8/14 PBI (mean increase in LADmax¼ 24.7 Gy) cases. Breast volume O1000 cm3 correlated with a benefit of prone treatment (P ¼ 0.02). Heart and LAD parameters agreed on the best plan in 24/28 instances. PBI reduced heart and LAD doses in 100% of patients compared to WBI. Conclusions: LAD doses from WBI are significant. Prone positioning is likely to improve heart and LAD dosimetry in women with breast volumes O1000 cm3 (RE cup), but to increase heart/LAD doses in women with breast volumes !1000 cm3. PBI universally improves cardiac dosimetry compared to WBI and all eligible women should be offered participation in PBI trials where available.

Purpose/Objective(s): In order to minimize the dose delivered to healthy tissue near amoving tumor during radiotherapy it is first necessary to accurately measure tumor position as a function of time. For example, a portal imager can be used to detect surrogate markers implanted around the tumor in order to track its motion with a moving collimator. Lung tumors can move at up to 30 mm/s, requiring a sampling rate of 30 frame/s to achieve mm accuracy. However the passive a-Si Flat Panel Imagers (FPIs) available with current linear accelerators operate at 2 - 10 frames/s, significantly slower than the required rate. Furthermore a-Si FPIs provide low image quality at their fastest frame rates and are susceptible to damage by the treatment beam, requiring replacement every 1 - 2 years. Emerging CMOS active pixel sensors use an addressable and partial read-out architecture to achieve significantly improved frame-rates relative to their passive counterparts. They are also capable of higher resolution, image quality and radiation-hardness. This study investigates the feasibility of using a CMOS APS to quickly and accurately track radio-opaque markers during radiotherapy. Materials/Methods: A custom CMOS imaging system was designed and constructed in collaboration with the MI3 consortium. The performance of this system was characterized and compared with an a-Si FPI. Four cylindrical gold markers of diameter 0.8 to 2 mm and length 8 mm were positioned on a motion-platform and moved according to the Lujan approximation to respiratory motion. Images were acquired using the megavoltage treatment beam at a range of frame and dose rates. The success rate of an automatic detection routine, absolute mean-error from the expected position and contrast-to-noise ratio of the marker images were then evaluated as a function of marker size, marker speed, frame rate and dose rate. Results: TheCMOSimager was found to offer improved resolution and signal-to-noise than the standard a-Si FPI at a comparable dose. The long integration time of the FPI resulted in marker images being too blurred to detect. The CMOS was able to detect the three largest markers 100% of the time and estimate their position to within 0.3 mm at 150 - 300 MU/min and 20 - 50 frame/s. However success rate declined with decreasing dose or frame rate. Conclusions: A CMOS megavoltage imaging system was found to offer superior signal-noise and resolution than the standard a-Si FPI. Furthermore the high speed of CMOS provided sub mm tracking of moving markers at a clinically acceptable dose rate and marker size.

Proton imaging is a promising technology for proton radiotherapy as it can be used for: 1) direct sampling of the tissue stopping power, 2) input information for multi-modality RSP reconstruction, 3) gold-standard calibration against concurrent techniques, 4) tracking motion and 5) pre-treatment positioning. However, no end-to-end characterization of the image quality (signal-to-noise ratio and spatial resolution, blurring uncertainty) against the dose has been done. This work aims to establish a model relating these characteristics and to describe their relationship with proton energy and object size. The imaging noise originates from two processes: the Coulomb scattering with the nucleus, producing a path deviation, and the energy loss straggling with electrons. The noise is found to increases with thickness crossed and, independently, decreases with decreasing energy. The scattering noise is dominant around high-gradient edge whereas the straggling noise is maximal in homogeneous regions. Image quality metrics are found to behave oppositely against energy: lower energy minimizes both the noise and the spatial resolution, with the optimal energy choice depending on the application and location in the imaged object. In conclusion, the model presented will help define an optimal usage of proton imaging to reach the promised application of this technology and establish a fair comparison with other imaging

Introduction: This study assessed complex, target-tracking, intensity- modulated delivery by the Elekta MLCi system. For treatment sites where intrafraction tissue motion is a significant problem, target-tracking deliveries have the potential of reducing motion margins used in radiotherapy planning. Method: A toroidally shaped target surrounding an organ at risk (OAR), necessitating multiple field segments to irradiate the target and spare the OAR, was defined in a solid water phantom. The phantom was programmed to move in a reproducible 2D elliptical trajectory. A static and target-tracking delivery were planned for delivery on a standard Elekta Precise series linac with integrated MLCi system. Dose was delivered in 3 ways: (i) static delivery to the static phantom, (ii) static delivery to the moving phantom and (iii) tracking delivery to a moving phantom, and was assessed by film measurement. The dose delivery was quantified by measurement of the mean and standard deviation of the dose on the central plane through the target. Results: The mean target doses measured were: 100% 2.8%, 95.8% 7.2% and 98.5% 2.6%, respectively, for the three cases listed above, whereas the mean doses to the OAR from the three delivery scenarios were: 38.2% 24.4%, 54.0% 18.1% and 38.2% 19.7%. All dose measurements are quoted relative to the static target dose from a static delivery. Conclusion: Target-tracking deliveries have been shown to be realisable on the current generation of Elekta linacs. The tracking techniques have been shown to remove the negative effects of tissue motion. In this case, reducing the mean dose to the OAR by 15.8% whilst restoring the target dose homogeneity to the static case. However, many obstacles remain before the technique can be safely used in the clinic and these are the subject of further research in the field.

About 1.7 million new cases of breast cancer were estimated by the World Health Organization (WHO) in 2012, accounting for 23 percent of all female cancers. In the UK 33 percent of women aged 50 and above were diagnosed in the same year, thus positioning the UK as the 6th highest in breast cancer amongst the European countries. The national Screening programme in the UK has been focused on the procedure of early detection and to improve prognosis by timely intervention to extend the life span of patients. To this end, the National Health Service Breast Screening Programme (NHSBSP) employs 2-D planar mammography because it is considered to be the gold standard technique for early breast cancer detection worldwide. Breast tomosynthesis has shown great promise as an alternative method for removing the intrinsic overlying clutter seen in conventional 2D imaging. However, preliminary work in breast CT has provided a number of compelling aspects that motivates the work featured in this thesis. These advantages include removal of the need to mechanically compress the breast which is a source of screening non-attendances, and that it provides unique cross sectional images that removes almost all the overlying clutter seen in 2D. This renders lesions more visible and hence aids in early detection of malignancy. However work in Breast CT to date has been focused on using scaled down versions of standard clinical CT systems. By contrast, this thesis proposes using a photon counting approach. The work of this thesis focuses on investigating photoncounting detector technology and comparing it to conventional CT in terms of contrast visualization. Results presented from simulation work developed in this thesis has demonstrated the ability of photoncounting detector technology to utilize data in polychromatic beam where contrast are seen to decrease with increasing photon energy and compared to the conventional CT approach which is the standard clinical CT system.

The DAIL (Dietetic Assessment and Intervention in Lung Cancer) study investigated the need for dietetic input in patients with Non-Small Cell Lung Cancer (NSCLC). It based need to see a dietician on the PG-SGA (Patient Generated Subjective Global Assessment), as the gold standard test. This abstract reports on a sub-study aimed at identifying if machine learning could be used to predict the need to see a dietitian using alternative data points collected during the study, when compared to the PG-SGA.Methods96 patients with stage 3b and 4 lung cancer were recruited between April 2017 and June 2019. Of these 20 had incomplete data, leaving 76 patients; 56 from Royal Surrey County Hospital (RSH) and 20 from Frimley Park Hospital (FPH). The PG-SGA was completed in all cases. This was compared to data points collected from the study, which included: the G8 frailty assessment, EORTC QLQ C30 and LC13 quality of life assessments, hand grip strength, psoas muscle surface area, spirometry, routine blood tests, Body Mass Index (BMI) and weight change, leading to 137 data points for each patient. Univariate analysis was used to find the strongest single correlates with “need to see a dietitian” (NTSD) and “critical need to see a dietitian” (CNTSD). The correlates with a Spearman correlation above +/-0.4 were selected to train a Support Vector Machine (SVM) to predict NTSD and CNTSD (SVM1) and the misclassification error calculated.ResultsThe number of measures with Spearman correlation coefficients above +/-0.4 was 18 and 13 out of a total of 137 for NTSD and CNTSD respectively. SVMs trained with these measures produced 3% and 7% misclassification error. For the SVM trained on the RSH data and tested on the FPH data the results were weaker with errors of 20% or more. This is likely to be due to the fact that only 20 patients were included in the FPH data set.ConclusionThis work suggests that machine learning can be used to predict the need to see a dietician for lung cancer patients. The results are promising, producing low misclassification rates. It could potentially automate screening for need to see a dietitian. However the results for FPH data using a model trained on RSH data suggest more work is needed to transfer the model between datasets from different hospitals.

None of the patient-and/or tumor-related variables were significantly correlated with non-response. Without harmonization, none of the CE-CT radiomic features identified in the training/validation set had predictive power in the testing set. After ComBat harmonization, Zone Size Percentage GLZSM was significantly correlated with non-response to chemotherapy in the training set (AUC= 0.67, Se= 70%, Sp= 64%, p= 0.04) and obtained a satisfactory performance in the validation set (Se= 80%, Sp= 67%, p= 0.03).

A scanning megavoltage imaging detector, with associated image storage and analysis facilities has been developed. This produces images of the treatment portals in under 10 seconds, in a digital format, facilitating rapid, quantitative image analysis. Image quality is comparable to, and at some sites improves upon, that available from film. Clinical problems in the use of megavoltage imaging include limited field of view, loss of information at the field edge due to penumbra effects, degradation of the image by bowel gas, and difficulties in the detection of soft tissue-air interfaces. Possible solutions to these problems are discussed. The imaging system has been used to assess the random errors occurring during routine para-aortic nodal irradiation. The errors detected are small, with over 95% of set-ups lying within +/- 4.5 mm of the mean daily position. No differences were detected in the magnitude of random errors between anterior and posterior treatment fields.

In many biomedical imaging applications there is a strong demand for large area sensors. Nowadays the most common detectors in this field are Flat Panel imagers which offer a reasonably large area, typically greater than 20 cm×20 cm. Even so such detectors present severe drawbacks such as large pixels, high noise, low frame rate and excessive image artefacts. In the last two decades Active Pixel Sensors (APSs) have gained popularity because of a potential for overcoming such issues. Furthermore, in recent years, improvements in design and fabrication techniques have made available fabricative processes for wafer scale imagers, which can be now seamlessly scaled from a few centimetres square up to the whole wafer size. A suitable detector for biomedical imaging application needs to fulfil specific requirements: it should have a high spatial resolution, a low noise and a high dynamic range. These figures of merit are connected with the pixel size. Since the pixel size is normally fixed at the time of the design, spatial resolution, noise and dynamic range cannot be further optimized. The authors propose a novel edge-buttable wafer scale APS (12.8 cm×12.8 cm), named the Dynamic range Adjustable for Medical Imaging Technology or DynAMITe, developed by the Multidimensional Integrated Intelligent Imaging Plus (MI-3 Plus) consortium. This APS is based on the use of two different diode geometries in the same pixel array and with different size active pixels. As the effective pixel size is no longer fixed, but two different pixel sizes are used for the whole detector matrix, this detector can deliver two inherently different resolutions each with different noise and saturation performance in the same pixel array. The DynAMITe design has great potential for use in a variety of biomedical imaging applications. In its initial deployment the authors will be developing demonstrators in radiotherapy portal imaging, breast mammography and diffraction imaging and also in sequencing methods for the life sciences.

Introduction: Treatment plan evaluation requires knowledge of the effect of the plan, not only on the intended target, but also the surrounding normal tissues that are unavoidably irradiated. Recent literature has provided estimations of tolerance doses and proposed dose-volume constraints for many of the organs at risk. However, very few of these recommendations have been independently validated. This study details how constraints proposed for the rectum were tested using data from the RT01 randomised prostate radiotherapy trial. Method: An independent validation of the rectal dose-volume constraints used in the CHHiP trial and proposed recently by Fiorino et al. was performed. The constraints were applied retrospectively to the treatment plans collected from the RT01 trial. Odds ratios (OR) were calculated to compare the reported incidence of specific late rectal toxicity end points in the group of patients whose treatment plan met a specified dose-volume constraint compared to the group of patients who failed that constraint. Results: Statistically significant ORs were observed for every constraint tested (except 75 Gy) for at least one clinical end point. For the CHHiP constraints between 60 and 70 Gy, the ORs calculated for rectal bleeding (RMH score defined in protocol) exceeded 2.5 (P!0.02). Similarly the ORs for CHHiP constraints between 30 and 65 Gy exceeded 2.4 (P!0.021) for urgency (UCLA PCI). The Fiorino constraints between 40 and 60 Gy resulted in ORs O2 (P!0.02) for loose stools (UCLA PCI) Conclusion: Implementing rectal dose-volume constraints from 30 Gy up to the prescription dose will result in a decrease in the incidence of late rectal toxicity. Constraints for doses as low as 30 Gy were statistically significant, further challenging the concept that the rectum is a serial structure where the maximum dose to the organ is the only consideration.

Since the first proof of concept in the early 70s, a number of technologies has been proposed to perform proton CT (pCT), as means of mapping tissue stopping power for accurate treatment planning in proton therapy. Previous prototypes of energy-range detectors for pCT have been mainly based on the use of scintillator-based calorimeters, to measure proton residual energy. However, such an approach is limited by the need for only a single proton passing through the energy-range detector per read-out cycle. A novel approach to this problem could be the use of pixelated detectors, where the independent read-out of each pixel allows to measure simultaneously the residual energy of a number of protons in the same read-out cycle, facilitating a faster and more efficient pCT scan. This paper investigates the suitability of CMOS Active Pixel Sensors (APSs) to track individual protons as they go through a number of CMOS layers, forming an energy-range telescope. Measurements performed at the iThemba Laboratories will be presented and analysed in terms of correlation, to confirm capability of proton tracking for CMOS APSs.