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Tumour recurrences after treatment of head and neck squamous cell carcinoma (HNSCC) are more likely to originate from regions of high-baseline FDG-PET uptake. Mid-treatment functional imaging can potentially predict for higher risk of tumour recurrence. The aim of this study is to correlate the location of locoregional tumour recurrence with baseline FDG-PET metabolic volumes and mid-treatment FDG-PET metabolic volumes in patients with HNSCC following definitive radiotherapy.A total of 23 patients with 26 local and/or regional recurrences underwent baseline (W0-PET) and mid-treatment (W3-PET) 18F-FDG PET scans as part of their radiotherapy. FDG-PET-based metabolic volumes (MTV20%, MTV40%, MTV60%, MTV80%, SUV2.5, SUVpeak and PET_EDGE) were delineated onto the FDG-PET scans. The recurrence nidus was identified on FDG-PET at the time of recurrence (REC-PET). DIR-based fusion was performed for REC-PET to W0-PET, and REC-PET to W3-PET. The location of the recurrence nidus was correlated with the FDG-PET volumes. Further analysis included a comparison of the recurrence density to FDG-PET metabolic volumes.Most recurrences occurred within the MTV20%, MTV40% and SUV 2.5 volumes. Sixty-nine per cent of recurrences (18 of 26) occurred within both the W0 MTV40% and W3 MTV40% volumes. A higher recurrence density was seen for iso-SUV contours closer to the maximum SUV for both W0 and W3. For a number of the FDG-PET volumes, including MTV20%, MTV40% and SUV2.5, the recurrence density was improved for W3 compared to W0, however, this improvement was small in magnitude. The average volume of MTV40% contours was considerably smaller than MTV20% and SUV2.5 contours.The metabolic parameters of SUV2.5, MTV20% and MTV40% delineated on the baseline and mid-treatment FDG-PET scans encompassed the majority of recurrences. The MTV40% is significantly smaller, hence, we prefer this volume for future dose escalation studies.

Automated brain tumour segmentation from post-operative images is a clinically relevant yet challenging problem. In this study, an automated method for segmenting brain tumour into its subregions has been developed. The dataset consists of multimodal post-operative brain scans (T1 MRI, post-Gadolinium T1 MRI, and T2-FLAIR images) of 15 patients who were treated with post-operative radiation therapy, along with manual annotations of their tumour subregions. A 3D densely-connected U-net was developed for segmentation of brain tumour regions and extensive experiments were conducted to enhance model accuracy. A model was initially developed using the publicly available BraTS dataset consisting of pre-operative brain scans. This model achieved Dice Scores of 0.90, 0.83 and 0.78 for predicting whole tumour, tumour core, and enhancing tumour subregions when tested on BraTS20 blind validation dataset. The acquired knowledge from BraTS was then transferred to the local dataset. For augmentation purpose, the local dataset was registered to a dataset of MRI brain scans of healthy subjects. To improve the robustness of the model and enhance its accuracy, ensemble learning was used to combine the outputs of all the trained models. Even though the size of the dataset is very small, the final model can segment brain tumours with a high Dice Score of 0.83, 0.77 and 0.60 for whole tumour, tumour core and enhancing core respectively.

Background Analysis of Data to Advance Personalised Therapy with MR-Linac (ADAPT-MRL) is a multi-site, multinational, observational cohort registry designed to collect data on the use of the magnetic resonance linear accelerator (MR-Linac) for radiation therapy and patient outcomes. The registry will provide a linked repository of technical and clinical data that will form a platform for prospective studies and technology assessment. Methods Design: This registry aims to include an estimated 10,000 eligible participants across Australia and other countries over a 7- to 10-year period. Participants will undergo treatment and assessments in accordance with standard practice. Toxicity and survival outcomes will be assessed at baseline, during treatment, and with 3 monthly follow-up until 24 months, patient reported outcome measures will also be collected. Participants with a variety of cancers will be included. Discussion Data obtained from the ADAPT-MRL registry is expected to provide evidence on the safety and efficacy of the MR-Linac, a new technical innovation in radiation oncology. We expect this registry will generate data that will be used to optimise treatment techniques, MR-Linac software algorithms, evaluate participants’ outcomes and toxicities and to create a repository of adapted plans, anatomical and functional MR sequences linked to participants’ outcomes.

Machine learning technology has a growing impact on radiation oncology with an increasing presence in research and industry. The prevalence of diverse data including 3D imaging and the 3D radiation dose delivery presents potential for future automation and scope for treatment improvements for cancer patients. Harnessing this potential requires standardization of tools and data, and focused collaboration between fields of expertise. The rapid advancement of radiation oncology treatment technologies presents opportunities for machine learning integration with investments targeted towards data quality, data extraction, software, and engagement with clinical expertise. In this review, we provide an overview of machine learning concepts before reviewing advances in applying machine learning to radiation oncology and integrating these techniques into the radiation oncology workflows. Several key areas are outlined in the radiation oncology workflow where machine learning has been applied and where it can have a significant impact in terms of efficiency, consistency in treatment and overall treatment outcomes. This review highlights that machine learning has key early applications in radiation oncology due to the repetitive nature of many tasks that also currently have human review. Standardized data management of routinely collected imaging and radiation dose data are also highlighted as enabling engagement in research utilizing machine learning and the ability integrate these technologies into clinical workflow to benefit patients. Physicists need to be part of the conversation to facilitate this technical integration.

Purpose Reducing margins during treatment planning to decrease dose to healthy organs surrounding the prostate can risk inadequate treatment of subclinical disease. This study aimed to investigate whether lack of dose to subclinical disease is associated with increased disease progression by using high-quality prostate radiation therapy clinical trial data to identify anatomically localized regions where dose variation is associated with prostate-specific antigen progression (PSAP). Methods and Materials Planned dose distributions for 683 patients of the Trans-Tasman Radiation Oncology Group 03.04 Randomized Androgen Deprivation and Radiotherapy (RADAR) trial were deformably registered onto a single exemplar computed tomography data set. These were divided into high-risk and intermediate-risk subgroups for analysis. Three independent voxel-based statistical tests, using permutation testing, Cox regression modeling, and least absolute shrinkage selection operator feature selection, were applied to identify regions where dose variation was associated with PSAP. Results from the intermediate-risk RADAR subgroup were externally validated by registering dose distributions from the RT01 (n = 388) and Conventional or Hypofractionated High Dose Intensity Modulated Radiotherapy for Prostate Cancer Trial (CHHiP) (n = 253) trials onto the same exemplar and repeating the tests on each of these data sets. Results Voxel-based Cox regression revealed regions where reduced dose was correlated with increased prostate-specific androgen progression. Reduced dose in regions associated with coverage at the posterior prostate, in the immediate periphery of the posterior prostate, and in regions corresponding to the posterior oblique beams or posterior lateral beam boundary, was associated with increased PSAP for RADAR and RT01 patients, but not for CHHiP patients. Reduced dose to the seminal vesicle region was also associated with increased PSAP for RADAR intermediate-risk patients. Conclusions Ensuring adequate dose coverage at the posterior prostate and immediately surrounding posterior region (including the seminal vesicles), where aggressive cancer spread may be occurring, may improve tumor control. It is recommended that particular care be taken when defining margins at the prostate posterior, acknowledging the trade-off between quality of life due to rectal dose and the preferences of clinicians and patients.

Image registration is a process that underlies many new techniques in radiation oncology – from multimodal imaging and contour propagation in treatment planning to dose accumulation throughout treatment. Deformable image registration (DIR) is a subset of image registration subject to high levels of complexity in process and validation. A need for local guidance to assist in high‐quality utilisation and best practice was identified within the Australian community, leading to collaborative activity and workshops. This report communicates the current limitations and best practice advice from early adopters to help guide those implementing DIR in the clinic at this early stage. They are based on the state of image registration applications in radiotherapy in Australia and New Zealand (ANZ), and consensus discussions made at the ‘Deforming to Best Practice’ workshops in 2018. The current status of clinical application use cases is presented, including multimodal imaging, automatic segmentation, adaptive radiotherapy, retreatment, dose accumulation and response assessment, along with uptake, accuracy and limitations. Key areas of concern and preliminary suggestions for commissioning, quality assurance, education and training, and the use of automation are also reported. Many questions remain, and the radiotherapy community will benefit from continued research in this area. However, DIR is available to clinics and this report is intended to aid departments using or about to use DIR tools now., Deformable image registration is a powerful tool in radiotherapy; however, many questions remain around best practice. Key considerations and recommendations are given based on workshop consensus and expert opinion.

Introduction Variation in target volume delineation from clinical trial protocols has been shown to contribute to poorer patient outcomes. A clinical trial quality assurance framework can support compliance with trial protocol. Results of the TROG 08.03 RAVES benchmarking exercise considering variation from protocol, inter-observer variability and impact on dosimetry are reported in this paper. Methods Clinicians were required to contour and plan a benchmarking case according to trial protocol. Geometric pjmirometers including volume, Hausdorff Distance, Mean Distance to Agreement and DICE similarity coefficient were analysed for targets and organs at risk. Submitted volumes were compared to a STAPLE and consensus 'reference' volume for each structure. Dosimetric analysis was performed using dose volume histogram data. Results Benchmarking exercise submissions were received from 96 clinicians. In total 205 protocol variations were identified. The most common variation was inadequate contouring of the CTV in 84/205 (41%). The CTV volume ranged from 65.3 to 193.1 cm3 with a median of 113.2 cm3 . The most common dosimetric protocol variation related to rectal dosimetry. The mean submitted rectal volume receiving 40 Gy and 60 Gy, respectively, was 56.14% ± 5.55% and 30.25% ± 6.15%. When corrected to the protocol defined length the mean rectal volume receiving 40 Gy was 60.8% ± 7.92%, while the volume receiving 60 Gy was 33.86% ± 8.21%. Conclusion Variations from protocol were found in the RAVES benchmarking exercise, most notably in CTV and rectum delineation. Inter-observer variability was evident. Incorrect delineation of the rectum impacted on dosimetric compliance with protocol.

Background Subclinical left ventricular dysfunction detected by 2‐dimensional global longitudinal strain post breast radiotherapy has been described in patients with breast cancer. We hypothesized that left ventricular dysfunction postradiotherapy may be site specific, based on differential segmental radiotherapy dose received. Methods and Results Transthoracic echocardiograms were performed at baseline, 6 weeks, and 12 months postradiotherapy on 61 chemotherapy‐naïve women with left‐sided breast cancer undergoing tangential breast radiotherapy. Radiation received within basal, mid, and apical regions for the 6 left ventricular walls was quantified from the radiotherapy treatment planning system. Anterior, anteroseptal, and anterolateral walls received the highest radiation doses, while inferolateral and inferior walls received the lowest. There was a progressive increase in the radiation dose received from basal to apical regions. At 6 weeks, the most significant percentage deterioration in strain was seen in the apical region, with greatest reductions in the anterior wall followed by the anteroseptal and anterolateral walls, with a similar pattern persisting at 12 months. There was a within‐patient dose–response association between the segment‐specific percentage deterioration in strain at 6 weeks and 12 months and the radiation dose received. Conclusions Radiotherapy for left‐sided breast cancer causes differential segmental dysfunction, with myocardial segments that receive the highest radiation dose demonstrating greatest strain impairment. Percentage deterioration in strain observed 6 weeks postradiotherapy persisted at 12 months and demonstrated a dose–response relationship with radiotherapy dose received. Radiotherapy‐induced subclinical cardiac dysfunction is of importance because it could be additive to chemotherapy‐related cardiotoxicity in patients with breast cancer. Long‐term outcomes in patients with asymptomatic strain reduction require further investigation.

Volume delineation quality assurance (QA) is particularly important in clinical trial settings where consistent protocol implementation is required, as outcomes will affect future as well current patients. Currently, where feasible, this is conducted manually, which is time consuming and resource intensive. Although previous studies mostly focused on automating delineation QA on CT, magnetic resonance imaging (MRI) is being increasingly used in radiotherapy treatment. In this work, we propose to perform automatic delineation QA on prostate MRI for both the clinical target volume (CTV) and organs-at-risk (OARs) by using delineations generated by 3D Unet variants as benchmarks for QA. These networks were trained on a small gold standard atlas set and applied on a multicentre radiotherapy clinical trial dataset to generate benchmark delineations. Then, a QA stage was designed to recommend 'pass', 'minor correction' and 'major correction' for each manual delineation in the trial set by thresholding its Dice similarity coefficient to the network generated delineation. Among all 3D Unet variants explored, the Unet with anatomical gates in an AtlasNet architecture performed the best in delineation QA, achieving an area under the receiver operating characteristics curve of 0.97, 0.92, 0.89 and 0.97 for identifying unacceptable (major correction) delineations with a sensitivity of 0.93, 0.73, 0.74 and 0.90 at a specificity of 0.93, 0.86, 0.86 and 0.95 for bladder, prostate CTV, rectum and gel spacer respectively. To the best of our knowledge, this is the first study to propose automated delineation QA for a multicentre radiotherapy clinical trial with treatment planning MRI. The methods proposed in this work can potentially improve the accuracy and consistency of CTV and OAR delineation in radiotherapy treatment planning.

INTRODUCTION The magnetic resonance linear accelerator (MRL) offers improved soft tissue visualization to guide daily adaptive radiotherapy treatment. This manuscript aims to report initial experience using a 1.5 T MRL in the first 6 months of operation, including training, workflows, timings and dosimetric accuracy. METHODS All staff received training in MRI safety and MRL workflows. Initial sites chosen for treatment were stereotactic and hypofractionated prostate, thoraco-abdomino-pelvic metastasis, prostate bed and bladder. The Adapt To Shape (ATS) workflow was chosen to be the focus of treatment as it is the most robust solution for daily adaptive radiotherapy. A workflow was created addressing patient suitability, simulation, planning, treatment and peer review. Treatment times were recorded breaking down into the various stages of treatment. RESULTS A total of 37 patients were treated and 317 fractions delivered (of which 313 were delivered using an ATS workflow) in our initial 6 months. Average treatment times over the entire period were 50 and 38 min for stereotactic and non-stereotactic treatments respectively. Average treatment times reduced each month. The average difference between reference planned and ionization chamber measured dose was 0.0 ± 1.4%. CONCLUSION The MRL was successfully established in an Australian setting. A focus on training and creating a detailed workflow from patient selection, review and treatment are paramount to establishing new treatment programmes.

Segmentation of organs and structures, as either targets or organs-at-risk, has a significant influence on the success of radiation therapy. Manual segmentation is a tedious and time-consuming task for clinicians, and inter-observer variability can affect the outcomes of radiation therapy. The recent hype over deep neural networks has added many powerful auto-segmentation methods as variations of convolutional neural networks (CNN). This paper presents a descriptive review of the literature on deep learning techniques for segmentation in radiation therapy planning. The most common CNN architecture across the four clinical sub sites considered was U-net, with the majority of deep learning segmentation articles focussed on head and neck normal tissue structures. The most common data sets were CT images from an inhouse source, along with some public data sets. N-fold cross-validation was commonly employed; however, not all work separated training, test and validation data sets. This area of research is expanding rapidly. To facilitate comparisons of proposed methods and benchmarking, consistent use of appropriate metrics and independent validation should be carefully considered.

Subacute changes following breast radiotherapy have been demonstrated in discrete areas of the left ventricle (LV), with recent guidelines being developed to help determine dose to subvolumes of the LV. This study aims to determine doses to the 17 segments of the LV as per the American Heart Association (AHA) and other cardiac subvolumes, and to correlate mean heart (MHD) dose with various subvolume dosimetric indices. These results may direct focus to specific left ventricular segments in studies of radiation-related heart disease incorporating surveillance imaging, help to determine more precise dose response relationships, and potentially aid prediction of late radiation effects.The heart and cardiac subvolumes of 29 patients treated with tangential radiotherapy for left breast cancer were contoured. Delineation of cardiac subvolumes (cardiac chambers, cardiac valves and the 17 segments of the LV) was undertaken using a novel contouring method on planning CT data reformatted into the cardiac axis. Individual segments were then combined to determine doses to the basal, mid and apical left ventricular regions, and the anterior, septal, inferior and lateral ventricular walls. Radiotherapy doses (including maximum, mean, D1cc, V25) were determined. Correlation analyses were performed between MHD and various substructure dosimetric indices.Twenty five patients received tangential breast free breathing radiotherapy alone, and four patients received regional nodal irradiation including the internal mammary chain with deep inspiration breath hold (DIBH). For patients receiving breast only radiation, the median mean heart radiation dose was 2.62 Gy (range 1.52-3.90 Gy), and a heterogeneous dose distribution to the LV was noted, with the apical region receiving the highest median mean dose (14.99 Gy) compared with the mid and basal regions (3.10 Gy and 1.51 Gy respectively). The anterior LV wall received the highest median mean dose (9.21 Gy) with the remaining walls receiving similar mean doses (range 1.79-3.05 Gy). The anterior LV apical segment (segment 13) and apex (segment 17) received the highest individual median mean segment doses (26.73 Gy and 30.02 Gy respectively). Apical segments received the highest median mean doses (segments 13, 14, 15, 16), followed by the mid anterior (segment 7) and anteroseptal (segment 8) segments. Segments receiving the highest doses remained unchanged between the DIBH cohort and free breathing cohort. MHD showed a high correlation with the anterior wall r = 0.71, p 0.05 and entire left ventricle r = 0.82, p 0.05, but correlations varied from weak to high when MHD was correlated with segments receiving highest doses (range r = 0.43-0.76), p 0.05.In the setting of breast cancer radiotherapy, there are substantial RT dose variations within specific LV segments, with mid and apical anterior ventricular segments (segments 7, 13) and the apical region of the LV (segments 13, 14, 15, 16, 17) being consistently exposed to the highest radiation doses. Determining segmental and regional RT doses to the left ventricle may help guide focus in diagnostic cardiology in the post radiotherapy setting.

Introduction This study quantified inter-observer contouring variations for multiple male pelvic structures, many of which are of emerging relevance for prostate cancer radiotherapy progression and toxicity response studies. Methods Five prostate cancer patient datasets (CT and T2-weighted MR) were distributed to 13 observers for contouring. CT structures contoured included the clinical target volume (CTV), seminal vesicles, rectum, colon, bowel bag, bladder and peri-rectal space (PRS). MR contours included CTV, trigone, membranous urethra, penile bulb, neurovascular bundle and multiple pelvic floor muscles. Contouring variations were assessed using the intraclass correlation coefficient (ICC), Dice similarity coefficient (DSC), and multiple additional metrics. Results Clinical target volume (CT and MR), bladder, rectum and PRS contours showed excellent inter-observer agreement (median ICC = 0.97; 0.99; 1.00; 0.95; 0.90, DSC = 0.83 ± 0.05; 0.88 ± 0.05; 0.93 ± 0.03; 0.81 ± 0.07; 0.80 ± 0.06, respectively). Seminal vesicle contours were more variable (ICC = 0.75, DSC = 0.73 ± 0.14), while colon and bowel bag contoured volumes were consistent (ICC = 0.97; 0.97), but displayed poor overlap (DSC = 0.58 ± 0.22; 0.67 ± 0.21). Smaller MR structures showed significant inter-observer variations, with poor overlap for trigone, membranous urethra, penile bulb, and left and right neurovascular bundles (DSC = 0.44 ± 0.22; 0.41 ± 0.21; 0.66 ± 0.21; 0.16 ± 0.17; 0.15 ± 0.15). Pelvic floor muscles recorded moderate to strong inter-observer agreement (ICC = 0.50-0.97), although large outlier variations were observed. Conclusions Inter-observer contouring variation was significant for multiple pelvic structures contoured on MR.

This prospective study of weekly CT scanning and plan adaption during H&N IMRT reports on the frequency of plan adaptations based on dosimetric differences between original and re-optimised IMRT plans. The volumetric and geometric change occurring in target volumes and salivary glands is also described. Ten H&N cancer patients underwent weekly planning CT imaging and re-optimisation of the IMRT plan if PTV or OAR coverage was unacceptable. Comparisons of PTV and parotid gland dosimetry between the original and adaptive plans were made. Parotid and submandibular gland volume changes and shift were calculated. Eight of ten patients required one or more plan adaptations, with 41% of adaptations occurring by fraction ten. Salivary glands reduced in volume, with a medial shift of the lateral border of the parotid gland and a superior shift of the submandibular gland. Change in PTV coverage did not correlate with weight loss or nutritional score. Inadequate PTV coverage, requiring plan adaptation, occurs early in the course of IMRT. A weekly Adaptive RT (ART) protocol results in significant improvement of PTV coverage. Implementation of a clinical ART protocol should include imaging and dose calculation within the first ten fractions.

Introduction Magnetic resonance imaging (MRI) is increasingly used for target volume delineation in radiotherapy due to its superior soft tissue visualisation compared to computed tomography (CT). The aim of this study was to assess the impact of a radiologist‐led workshop on inter‐observer variability in volume delineation on MRI. Methods Data from three separate studies evaluating the impact of MRI in lung, breast and cervix were collated. At pre‐workshop evaluation, observers involved in each clinical site were instructed to delineate specified volumes. Radiologists specialising in each cancer site conducted an interactive workshop on interpretation of images and anatomy for each clinical site. At post‐workshop evaluation, observers repeated delineation a minimum of 2 weeks after the workshops. Inter‐observer variability was evaluated using dice similarity coefficient (DSC) and volume similarity (VOLSIM) index comparing reference and observer volumes. Results Post‐workshop primary gross tumour volumes (GTV) were smaller than pre‐workshop volumes for lung with a mean percentage reduction of 10.4%. Breast clinical target volumes (CTV) were similar but seroma volumes were smaller post‐workshop on both supine (65% reduction) and prone MRI (73% reduction). Based on DSC scores, improvement in inter‐observer variability was seen for the seroma cavity volume on prone MRI with a reduction in DSC score range from 0.4–0.8 to 0.7–0.9. Breast CTV demonstrated good inter‐observer variability scores (mean DSC 0.9) for both pre‐ and post‐workshop. Post‐workshop observer delineated cervix GTV was smaller than pre‐workshop by 26.9%. Conclusion A radiologist‐led workshop did not significantly reduce inter‐observer variability in volume delineation for the three clinical sites. However, some improvement was noted in delineation of breast CTV, seroma volumes and cervix GTV.

Background and Purpose: Four-dimensional (4D) computed tomography (CT) is widely used in radiotherapy (RT) planning and remains the current standard for motion evaluation. We assess a 4D magnetic resonance imaging (MRI) sequence in terms of motion and image quality in a phantom, healthy volunteers and patients undergoing RT. Materials and Methods: The 4D-MRI sequence is a prototype T1-weighted 3D gradient echo with radial acquisition with self-gating. The accuracy of the 4D-MRI respiratory sorting based method was assessed using a MRI-CT compatible respiratory simulation phantom. In volunteers, abdominal viscera were evaluated for artefact, noise, structure delineation and overall image quality using a previously published four-point scoring system. In patients undergoing abdominal RT, the tumour (or a surrogate) was utilized to assess the range of motion on both 4D-CT and 4D-MRI. Furthermore, imaging quality was evaluated for both 4D-CT and 4D-MRI. Results: In phantom studies 4D-MRI demonstrated amplitude of motion error of less than 0.2 mm for five, seven and ten bins. 4D-MRI provided excellent image quality for liver, kidney and pancreas. In patients, the median amplitude of motion seen on 4D-CT and 4D-MRI was 11.2 mm (range 2.8–20.3 mm) and 10.1 mm (range 0.7–20.7 mm) respectively. The median difference in amplitude between 4D-CT and 4D-MRI was −0.6 mm (range −3.4–5.2 mm). 4D-MRI demonstrated superior edge detection (median score 3 versus 1) and overall image quality (median score 2 versus 1) compared to 4D-CT. Conclusions: The prototype 4D-MRI sequence demonstrated promising results and may be used in abdominal targeting, motion gating, and towards implementing MRI-based adaptive RT. Keywords: MRI, Motion management, 4D-MRI, abdominal radiotherapy, Four dimensional magnetic resonance imaging

Background and purpose This study aimed to identify anatomically-localised regions where planned radiotherapy dose is associated with gastrointestinal toxicities in healthy tissues throughout the pelvic anatomy. Materials and methods Planned dose distributions for up to 657 patients of the Trans Tasman Radiation Oncology Group 03.04 RADAR trial were deformably registered onto a single exemplar computed tomography dataset. Voxel-based multiple comparison permutation dose difference testing, Cox regression modelling and LASSO feature selection were used to identify regions where dose-increase was associated with grade ≥2 rectal bleeding (RB) or tenesmus, according to the LENT/SOMA scale. This was externally validated by registering dose distributions from the RT01 (n = 388) and CHHiP (n = 241) trials onto the same exemplar and repeating the tests on each of these data sets, and on all three datasets combined. Results Voxel-based Cox regression and permutation dose difference testing revealed regions where increased dose was correlated with gastrointestinal toxicity. Grade ≥2 RB was associated with posteriorly extended lateral beams that manifested high doses (>55 Gy) in a small rectal volume adjacent to the clinical target volume. A correlation was found between grade ≥2 tenesmus and increased low-intermediate dose (∼25 Gy) at the posterior beam region, including the posterior rectum and perirectal fat space (PRFS). Conclusions The serial response of the rectum with respect to RB has been demonstrated in patients with posteriorly extended lateral beams. Similarly, the parallel response of the PRFS with respect to tenesmus has been demonstrated in patients treated with the posterior beam.

Objectives Rigid image registration (RIR) and deformable image registration (DIR) are widely used in radiotherapy. This project aims to capture current international approaches to image registration. Methods A survey was designed to identify variations in use, resources, implementation, and decision-making criteria for clinical image registration. This was distributed to radiotherapy centers internationally in 2018. Results There were 57 responses internationally, from the Americas (46%), Australia/New Zealand (32%), Europe (12%), and Asia (10%). Rigid image registration and DIR were used clinically for computed tomography (CT)-CT registration (96% and 51%, respectively), followed by CT-PET (81% and 47%), CT-CBCT (84% and 19%), CT-MR (93% and 19%), MR-MR (49% and 5%), and CT-US (9% and 0%). Respondent centers performed DIR using dedicated software (75%) and treatment planning systems (29%), with 84% having some form of DIR software. Centers have clinically implemented DIR for atlas-based segmentation (47%), multi-modality treatment planning (65%), and dose deformation (63%). The clinical use of DIR for multi-modality treatment planning and accounting for retreatments was considered to have the highest benefit-to-risk ratio (69% and 67%, respectively). Conclusions This survey data provides useful insights on where, when, and how image registration has been implemented in radiotherapy centers around the world. DIR is mainly in clinical use for CT-CT (51%) and CT-PET (47%) for the head and neck (43-57% over all use cases) region. The highest benefit-risk ratio for clinical use of DIR was for multi-modality treatment planning and accounting for retreatments, which also had higher clinical use than for adaptive radiotherapy and atlas-based segmentation.

Introduction Inter-observer variability (IOV) in target volume and organ-at-risk (OAR) delineation is a source of potential error in radiation therapy treatment. The aims of this study were to identify interventions shown to reduce IOV in volume delineation. Methods Medline and Pubmed databases were queried for relevant articles using various keywords to identify articles which evaluated IOV in target or OAR delineation for multiple (>2) observers. The search was limited to English language articles and to those published from 1 January 2000 to 31 December 2014. Reference lists of identified articles were scrutinised to identify relevant studies. Studies were included if they reported IOV in contouring before and after an intervention including the use of additional or alternative imaging. Results Fifty-six studies were identified. These were grouped into evaluation of guidelines (n = 9), teaching (n = 9), provision of an autocontour (n = 7) and the impact of imaging (n = 31) on IOV. Guidelines significantly reduced IOV in 7/9 studies. Teaching interventions reduced IOV in 8/9 studies, statistically significant in 4. The provision of an autocontour improved consistency of contouring in 6/7 studies, statistically significant in 5. The effect of additional imaging on IOV was variable. Pre-operative CT was useful in reducing IOV in contouring breast and liver cancers, PET scans in lung cancer, rectal cancer and lymphoma and MRI scans in OARs in head and neck cancers. Conclusion Inter-observer variability in volume delineation can be reduced with the use of guidelines, provision of autocontours and teaching. The use of multimodality imaging is useful in certain tumour sites.

Objectives: The use of MRI is becoming more prevalent in cervical cancer external beam radiotherapy (RT). The aim of this study was to investigate the impact of dosimetric differences between CT and MRI-derived target volumes for cervical cancer external beam RT. Methods: An automated planning technique for volumetric modulated arc therapy was developed. Two automated planning plans were generated for 18 cervical cancer patients where planning target volumes (PTVs) were generated based on CT or MRI data alone. Dose metrics for planning target volumes and organs at risk (OARs) were compared to analyse any differences based on imaging modality. Results: All treatment plans were clinically acceptable. Bladder doses (V40) were lower in MRI-based plans (p = 0.04, 53.6 ± 17.2 % vs 60.3 ± 13.1 % for MRI vs CT, respectively). The maximum dose for left iliac crest showed lower doses in CT-based plans (p = 0.02, 47.8 ± 0.7 Gy vs 47.4 ± 0.4 Gy MRI vs CT, respectively). No significant differences were seen for other OARs. Conclusions: The dosimetric differences of CT- and MRI-based contouring variability for this study was small. CT remains the standard imaging modality for volume delineation for these patients. Advances in knowledge: This is the first study to evaluate the dosimetric implications of imaging modality on target and OAR doses in cervical cancer external beam RT.

Introduction: Inter-observer variability (IOV) in target volume delineation is a source of error in head and neck radiotherapy. Diffusion-weighted imaging (DWI) has been shown to be useful in detecting recurrent head and neck cancer. This study aims to determine whether DWI improves target volume delineation and IOV. Methods: Four radiation oncologists delineated the gross tumour volume (GTV) for ten head and neck cancer patients. Delineation was performed on CT alone as well as fused image sets which incorporated fluorodeoxyglucose (FDG)-positron emission tomography (PET) and magnetic resonance imaging (MRI) in the form of CT/PET, CT/PET/T2W and CT/PET/T2W/DWI image sets. Analysis of the variability of contour volumes was completed by comparison to the simultaneous truth and performance level estimation (STAPLE) volumes. The DICE Similarity Coefficient (DSC) and other IOV metrics for each observer's contour were compared to the STAPLE for each patient and image dataset. A DWI usability scoresheet for delineation was completed. Results: The CT/PET/T2W/DWI mean GTV volume of 13.37 (10.35–16.39)cm was shown to be different to the mean GTV of 10.92 (8.32–13.51)cm when using CT alone (P < 0.001). The GTV DSC amongst observers for CT alone was 0.72 (0.65–0.79), CT/PET was 0.73 (0.67–0.80), CT/PET/T2W was 0.71 (0.64–0.77) and CT/PET/T2W/DWI was 0.69 (0.61–0.75). Conclusion: Mean GTVs with the addition of DWI had slightly larger volumes compared to standard CT and CT/PET volumes. DWI may add supplemental visual information for GTV delineation while having a small impact on IOV, therefore potentially improving target volume delineation.

PURPOSE To demonstrate selection of a small representative subset of images from a pool of images comprising a potential atlas (PA) pelvic CT set to be used for autosegmentation of a separate target image set. The aim is to balance the need for the atlas set to represent anatomical diversity with the need to minimize resources required to create a high quality atlas set (such as multiobserver delineation), while retaining access to additional information available for the PA image set. METHODS Preprocessing was performed for image standardization, followed by image registration. Clustering was used to select the subset that provided the best coverage of a target dataset as measured by postregistration image intensity similarities. Tests for clustering robustness were performed including repeated clustering runs using different starting seeds and clustering repeatedly using 90% of the target dataset chosen randomly. Comparisons of coverage of a target set (comprising 711 pelvic CT images) were made for atlas sets of five images (chosen from a PA set of 39 pelvic CT and MR images) (a) at random (averaged over 50 random atlas selections), (b) based solely on image similarities within the PA set (representing prospective atlas development), (c) based on similarities within the PA set and between the PA and target dataset (representing retrospective atlas development). Comparisons were also made to coverage provided by the entire PA set of 39 images. RESULTS Exemplar selection was highly robust with exemplar selection results being unaffected by choice of starting seed with very occasional change to one of the exemplar choices when the target set was reduced. Coverage of the target set, as measured by best normalized cross-correlation similarity of target images to any exemplar image, provided by five well-selected atlas images (mean = 0.6497) was more similar to coverage provided by the entire PA set (mean = 0.6658) than randomly chosen atlas subsets (mean = 0.5977). This was true both of the mean values and the shape of the distributions. Retrospective selection of atlases (mean = 0.6497) provided a very small improvement over prospective atlas selection (mean = 0.6431). All differences were significant (P

Poster: "2015 ASM / R-0116 / Relationship between CT-Derived Gross Tumour Volume (GTV) and the FDG-PET/CT-Derived Metabolic Tumour Volume (MTV): An Exploratory Study in Non-Small Cell Lung Cancer Patients Treated with Radical Radiotherapy " by: " A. Oar , M. Jameson, I. Ho-Shon, P. Phan, L. Holloway, D. Wang, J. Descallar, A. Pramana, S. Vinod, M. Field, E.-S. Koh; Sydney/AU"

There are a number of different dwell positions and time optimisation options available in the Oncentra® Brachy (Elekta Brachytherapy Solutions, Veenendaal, The Netherlands) brachytherapy treatment planning system. The purpose of this case study was to compare graphical (GRO) and inverse planning by simulated annealing (IPSA) optimisation techniques for interstitial head and neck (HN) and prostate plans considering dosimetry, modelled radiobiology outcome and planning time. Four retrospective brachytherapy patients were chosen for this study, two recurrent HN and two prostatic boosts. Manual GRO and IPSA plans were generated for each patient. Plans were compared using dose–volume histograms (DVH) and dose coverage metrics including; conformity index (CI), homogeneity index (HI) and conformity number (CN). Logit and relative seriality models were used to calculate tumour control probability (TCP) and normal tissue complication probability (NTCP). Approximate planning time was also recorded. There was no significant difference between GRO and IPSA in terms of dose metrics with mean CI of 1.30 and 1.57 (P > 0.05) respectively. IPSA achieved an average HN TCP of 0.32 versus 0.12 for GRO while for prostate there was no significant difference. Mean GRO planning times were greater than 75 min while average IPSA planning times were less than 10 min. Planning times for IPSA were greatly reduced compared to GRO and plans were dosimetrically similar. For this reason, IPSA makes for a useful planning tool in HN and prostate brachytherapy.

Introduction We investigated the endorectal balloon (ERB) as a method to improve post-prostatectomy clinical target volume (CTV) stability. Methods Seventy cone-beam CT (CBCT) obtained during radiotherapy treatment from seven patients treated with an ERB and 68 CBCT from seven patients treated without an ERB were contoured according to published guidelines. CTV was subdivided into superior and inferior CTV; whole rectal volume was subdivided into superior and inferior rectum and anal volume. Concordance index (CI) of CBCT treatment volumes compared with planning volumes was calculated and displacements were measured. Results Whole rectal, superior and inferior rectum and anal CI were significantly improved with the ERB by 21%, 17%, 26% and 17% respectively (P

Many similarity metrics exist for inter-observer contouring variation studies, however no correlation between metric choice and prostate cancer radiotherapy dosimetry has been explored. These correlations were investigated in this study. Two separate trials were undertaken, the first a thirty-five patient cohort with three observers, the second a five patient dataset with ten observers. Clinical and planning target volumes (CTV and PTV), rectum, and bladder were independently contoured by all observers in each trial. Structures were contoured on T2-weighted MRI and transferred onto CT following rigid registration for treatment planning in the first trial. Structures were contoured directly on CT in the second trial. STAPLE and majority voting volumes were generated as reference gold standard volumes for each structure for the two trials respectively. VMAT treatment plans (78 Gy to PTV) were simulated for observer and gold standard volumes, and dosimetry assessed using multiple radiobiological metrics. Correlations between contouring similarity metrics and dosimetry were calculated using Spearman's rank correlation coefficient. No correlations were observed between contouring similarity metrics and dosimetry for CTV within either trial. Volume similarity correlated most strongly with radiobiological metrics for PTV in both trials, including TCPPoisson (ρ = 0.57, 0.65), TCPLogit (ρ = 0.39, 0.62), and EUD (ρ = 0.43, 0.61) for each respective trial. Rectum and bladder metric correlations displayed no consistency for the two trials. PTV volume similarity was found to significantly correlate with rectum normal tissue complication probability (ρ = 0.33, 0.48). Minimal to no correlations with dosimetry were observed for overlap or boundary contouring metrics. Future inter-observer contouring variation studies for prostate cancer should incorporate volume similarity to provide additional insights into dosimetry during analysis.

Introduction Correct target positioning is crucial for accurate dose delivery in breast radiotherapy resulting in utilisation of daily imaging. However, the radiation dose from daily imaging is associated with increased probability of secondary induced cancer. The aim of this study was to quantify doses associated with three imaging modalities and investigate the correlation of dose and varying breast size in breast radiotherapy. Methods Planning computed tomography (CT) data sets of 30 breast cancer patients were utilised to simulate the dose received by various organs from a megavoltage computed tomography (MV-CT), megavoltage electronic portal image (MV-EPI) and megavoltage cone-beam computed tomography (MV-CBCT). The mean dose to organs adjacent to the target volume (contralateral breast, lungs, spinal cord and heart) were analysed. Pearson correlation analysis was performed to determine the relationship between imaging dose and primary breast volume and the lifetime attributable risk (LAR) of induced secondary cancer was calculated for the contralateral breast. Results The highest contralateral breast mean dose was from the MV-CBCT (1.79 Gy), followed by MV-EPI (0.22 Gy) and MV-CT (0.11 Gy). A similar trend was found for all organs at risk (OAR) analysed. The primary breast volume inversely correlated with the contralateral breast dose for all three imaging modalities. As the primary breast volume increases, the likelihood of a patient developing a radiation-induced secondary cancer to the contralateral breast decreases. MV-CBCT showed a stronger relationship between breast size and LAR of developing a radiation-induced contralateral breast cancer in comparison with the MV-CT and MV-EPI. Conclusions For breast patients, imaging dose to OAR depends on imaging modality and treated breast size. When considering the use of imaging during breast radiotherapy, the patient's breast size and contralateral breast dose should be taken into account.

Purpose Human cortical bone has a rapid T2∗ decay, and it can be visualized using ultrashort echo time (UTE) techniques in magnetic resonance imaging (MRI). These sequences operate at the limits of gradient and transmit-receive signal performance. Development of multicompartment anthropomorphic phantoms that can mimic human cortical bone can assist with quality assurance and optimization of UTE sequences. The aims of this study were to (a) characterize the MRI signal properties of a photopolymer resin that can be 3D printed, (b) develop multicompartment phantoms based on the resin, and (c) demonstrate the feasibility of using these phantoms to mimic human anatomy in the assessment of UTE sequences. Methods A photopolymer resin (Prismlab China Ltd, Shanghai, China) was imaged on a 3 Tesla MRI system (Siemens Skyra) to characterize its MRI properties with emphasis on T2∗ signal and longevity. Two anthropomorphic phantoms, using the 3D printed resin to simulate skeletal anatomy, were developed and imaged using UTE sequences. A skull phantom was developed and used to assess the feasibility of using the resin to develop a complex model with realistic morphological human characteristics. A tibia model was also developed to assess the suitability of the resin at mimicking a simple multicompartment anatomical model and imaged using a three-dimensional UTE sequence (PETRA). Image quality measurements of signal-to-noise ratio (SNR) and contrast factor were calculated and these were compared to in vivo values. Results The T2∗ and T1 (mean ± standard deviation) of the photopolymer resin was found to be 411 ± 19 μs and 74.39 ± 13.88 ms, respectively, and demonstrated no statistically significant change during 4 months of monitoring. The resin had a similar T2∗ decay to human cortical bone; however, had lower T1 properties. The bone water concentration of the resin was 59% relative to an external water reference phantom, and this was higher than in vivo values reported for human cortical bone. The multicompartment anthropomorphic head phantom was successfully produced and able to simulate realistic air cavities, bony anatomy, and soft tissue. Image quality assessment in the tibia phantom using the PETRA sequence showed the suitability of the resin to mimic human anatomy with high SNR and contrast making it suitable for tissue segmentation. Conclusions A solid resin material, which can be 3D printed, has been found to have similar magnetic resonance signal properties to human cortical bone. Phantoms replicating skeletal anatomy were successfully produced using this resin and demonstrated their use for image quality and segmentation assessment of ultrashort echo time sequences.

Background and purpose Contouring variation is a well know uncertainty in modern radiotherapy. This study investigates the relationship between contouring variation, tumor control probability (TCP) and equivalent uniform dose (EUD) for conformal non-small cell lung cancer (NSCLC) radiotherapy. Material and methods Seven patients were retrospectively recruited to the study and multiple PTV contours were generated based on CT and PET imaging by three observers. Plans were created for each PTV volume. Volumes were analyzed geometrically using volume, location, dimension and conformity index (CI). Radiobiological plan analysis consisted of two TCP models and EUD. Spearman's correlation coefficient ( ρ ) was used to quantify the association between geometric variation and radiobiological metrics. Results The variation in CI and TCP for the study was 0.66–0.90% and 0.19–0.68%. Changes in lateral dimension and volume were significantly correlated with TCP and EUD with an average ρ of −0.49 and 0.43 ( p Conclusions TCP and geometric contour variation show significant correlation. This correlation was most significant for changes in lateral dimensions of PTV volumes. This association may be used in the assessment of contouring protocol violations in multicenter clinical trials and aid in the design of future contouring studies.