Search

Recently, there has been increased interest worldwide in the use of conventional linear accelerator (linac)-based systems for delivery of stereotactic radiosurgery/radiotherapy (SRS/SRT) contrasting with historical delivery in specialised clinics with dedicated equipment. In order to gain an understanding and define the current status of SRS/SRT delivery in Australia and New Zealand (ANZ) we conducted surveys and provided a single-day workshop. Prior to the workshop ANZ medical physicists were invited to complete two surveys: a departmental survey regarding SRS/SRT practises and equipment; and an individual survey regarding opinions on current and future SRS/SRT practices. At the workshop conclusion, attendees completed a second opinion-based survey. Workshop discussion and survey data were utilised to identify areas of consensus, and areas where a community consensus was unclear. The workshop was held on the 8th Sept 2020 virtually due to pandemic-related travel restrictions and was attended by 238 radiation oncology medical physicists from 39 departments. The departmental survey received 32 responses; a further 89 and 142 responses were received to the pre-workshop and post-workshop surveys respectively. Workshop discussion indicated a consensus that for a department to offer an SRS/SRT service, a minimum case load should be considered depending on availability of training, peer-review, resources and equipment. It was suggested this service may be limited to brain metastases only, with less common indications reserved for departments with comprehensive SRS/SRT programs. Whilst most centres showed consensus with treatment delivery techniques and image guidance, opinions varied on the minimum target diameter and treatment margin that should be applied.

Stereotactic body radiation therapy (SBRT) is an emerging treatment for liver cancers whereby large doses of radiation can be delivered precisely to target lesions in 3–5 fractions. The target dose is limited by the dose that can be safely delivered to the non-tumour liver, which depends on the baseline liver functional reserve. Current liver SBRT guidelines assume uniform liver function in the non-tumour liver. However, the assumption of uniform liver function is false in liver disease due to the presence of cirrhosis, damage due to previous chemo- or ablative therapies or irradiation, and fatty liver disease. Anatomical information from magnetic resonance imaging (MRI) is increasingly being used for SBRT planning. While its current use is limited to the identification of target location and size, functional MRI techniques also offer the ability to quantify and spatially map liver tissue microstructure and function. This review summarises and discusses the advantages offered by functional MRI methods for SBRT treatment planning and the potential for adaptive SBRT workflows.

Magnetic resonance imaging (MRI) is increasingly used in the management of prostate cancer (PCa). Quantitative MRI (qMRI) parameters, derived from multi-parametric MRI, provide indirect measures of tumour characteristics such as cellularity, angiogenesis and hypoxia. Using Artificial Intelligence (AI), relevant information and patterns can be efficiently identified in these complex data to develop quantitative imaging biomarkers (QIBs) of tumour function and biology. Such QIBs have already demonstrated potential in the diagnosis and staging of PCa. In this review, we explore the role of these QIBs in monitoring treatment response during and after PCa radiotherapy (RT). Recurrence of PCa after RT is not uncommon, and early detection prior to development of metastases provides an opportunity for salvage treatments with curative intent. However, the current method of monitoring treatment response using prostate-specific antigen levels lacks specificity. QIBs, derived from qMRI and developed using AI techniques, can be used to monitor biological changes post-RT providing the potential for accurate and early diagnosis of recurrent disease.

Quantitative MRI (qMRI) parameters have been increasingly used to develop predictive models to accurately monitor treatment response in prostate cancer after radiotherapy. To reliably detect changes in signal due to treatment response, predictive models require qMRI parameters with high repeatability and reproducibility. The purpose of this study was to measure qMRI parameter uncertainties in both commercial and in-house developed phantoms to guide the development of robust predictive models for monitoring treatment response.ADC, T1, and R2* values were acquired across three 3 T scanners with a prostate-specific qMRI protocol using the NIST/ISMRM system phantom, RSNA/NIST diffusion phantom, and an in-house phantom. A B1 field map was acquired to correct for flip angle inhomogeneity in T1 maps. All sequences were repeated in each scan to assess within-session repeatability. Weekly scans were acquired on one scanner for three months with the in-house phantom. Between-session repeatability was measured with test-retest scans 6-months apart on all scanners with all phantoms. Accuracy, defined as percentage deviation from reference value for ADC and T1, was evaluated using the system and diffusion phantoms. Repeatability and reproducibility coefficients of variation (%CV) were calculated for all qMRI parameters on all phantoms.Overall, repeatability CV of ADC was2.40%, reproducibility CV was3.98%, and accuracy ranged between -8.0% to 2.7% across all scanners. Applying B1 correction on T1 measurements significantly improved the repeatability and reproducibility (p0.05) but increased error in accuracy (p0.001). Repeatability and reproducibility of R2* was4.5% and7.3% respectively in the system phantom across all scanners.Repeatability, reproducibility, and accuracy in qMRI parameters from a prostate-specific protocol was estimated using both commercial and in-house phantoms. Results from this work will be used to identify robust qMRI parameters for use in the development of predictive models to longitudinally monitor treatment response for prostate cancer in current and future clinical trials.

Introduction: The standard of care for locoregionally advanced rectal cancer is neoadjuvant therapy (NA CRT) prior to surgery, of which 10-30% experience a complete pathologic response (pCR). There has been interest in using imaging features, also known as radiomics features, to predict pCR and potentially avoid surgery. This systematic review aims to describe the spectrum of MRI studies examining high-performing radiomic features that predict NA CRT response.Areas covered: This article reviews the use of pre-therapy MRI in predicting NA CRT response for patients with locoregionally advanced rectal cancer (T3/T4 and/or N1+). The primary outcome was to identify MRI radiomic studies; secondary outcomes included the power and the frequency of use of radiomic features.Expert opinion: Advanced models incorporating multiple radiomics categories appear to be the most promising. However, there is a need for standardization across studies with regards to; the definition of NA CRT response, imaging protocols, and radiomics features incorporated. Further studies are needed to validate current radiomics models and to fully ascertain the value of MRI radiomics in the response prediction for locoregionally advanced rectal cancer.

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.

Summary Background Adjuvant radiotherapy has been shown to halve the risk of biochemical progression for patients with high-risk disease after radical prostatectomy. Early salvage radiotherapy could result in similar biochemical control with lower treatment toxicity. We aimed to compare biochemical progression between patients given adjuvant radiotherapy and those given salvage radiotherapy. Methods We did a phase 3, randomised, controlled, non-inferiority trial across 32 oncology centres in Australia and New Zealand. Eligible patients were aged at least 18 years and had undergone a radical prostatectomy for adenocarcinoma of the prostate with pathological staging showing high-risk features defined as positive surgical margins, extraprostatic extension, or seminal vesicle invasion; had an Eastern Cooperative Oncology Group performance status of 0–1, and had a postoperative prostate-specific antigen (PSA) concentration of 0·10 ng/mL or less. Patients were randomly assigned (1:1) using a minimisation technique via an internet-based, independently generated allocation to either adjuvant radiotherapy within 6 months of radical prostatectomy or early salvage radiotherapy triggered by a PSA of 0·20 ng/mL or more. Allocation sequence was concealed from investigators and patients, but treatment assignment for individual randomisations was not masked. Patients were stratified by radiotherapy centre, preoperative PSA, Gleason score, surgical margin status, and seminal vesicle invasion status. Radiotherapy in both groups was 64 Gy in 32 fractions to the prostate bed without androgen deprivation therapy with real-time review of plan quality on all cases before treatment. The primary endpoint was freedom from biochemical progression. Salvage radiotherapy would be deemed non-inferior to adjuvant radiotherapy if freedom from biochemical progression at 5 years was within 10% of that for adjuvant radiotherapy with a hazard ratio (HR) for salvage radiotherapy versus adjuvant radiotherapy of 1·48. The primary analysis was done on an intention-to-treat basis. This study is registered with ClinicalTrials.gov , NCT00860652 . Findings Between March 27, 2009, and Dec 31, 2015, 333 patients were randomly assigned (166 to adjuvant radiotherapy; 167 to salvage radiotherapy). Median follow-up was 6·1 years (IQR 4·3–7·5). An independent data monitoring committee recommended premature closure of enrolment because of unexpectedly low event rates. 84 (50%) patients in the salvage radiotherapy group had radiotherapy triggered by a PSA of 0·20 ng/mL or more. 5-year freedom from biochemical progression was 86% (95% CI 81–92) in the adjuvant radiotherapy group versus 87% (82–93) in the salvage radiotherapy group (stratified HR 1·12, 95% CI 0·65–1·90; pnon-inferiority=0·15). The grade 2 or worse genitourinary toxicity rate was lower in the salvage radiotherapy group (90 [54%] of 167) than in the adjuvant radiotherapy group (116 [70%] of 166). The grade 2 or worse gastrointestinal toxicity rate was similar between the salvage radiotherapy group (16 [10%]) and the adjuvant radiotherapy group (24 [14%]). Interpretation Salvage radiotherapy did not meet trial specified criteria for non-inferiority. However, these data support the use of salvage radiotherapy as it results in similar biochemical control to adjuvant radiotherapy, spares around half of men from pelvic radiation, and is associated with significantly lower genitourinary toxicity. Funding New Zealand Health Research Council, Australian National Health Medical Research Council, Cancer Council Victoria, Cancer Council NSW, Auckland Hospital Charitable Trust, Trans-Tasman Radiation Oncology Group Seed Funding, Cancer Research Trust New Zealand, Royal Australian and New Zealand College of Radiologists, Cancer Institute NSW, Prostate Cancer Foundation Australia, and Cancer Australia.

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.

To clarify the relative effects of duration of androgen suppression (AS) and radiation dose escalation (RDE) on distant progression (DP) in men with locally advanced prostate cancer.Participants with locally advanced prostate cancer in the TROG 03.04 RADAR trial were randomized to 6 or 18 months AS ± 18 months zoledronic acid (Z). The trial incorporated a RDE program by stratification at randomization and dosing options were 66, 70, or 74 Gy external beam radiation therapy (EBRT), or 46 Gy EBRT plus high-dose-rate brachytherapy boost (HDRB). The primary endpoint for this study was distant progression (DP). Secondary endpoints included local progression, bone progression, prostate cancer-specific mortality and all-cause mortality. Effect estimates for AS duration and RDE were derived using Fine and Gray competing risk models adjusting for use of Z, age, tumor stage, Gleason grade group, prostate-specific antigen, and treatment center. Cumulative incidence at 10 years was estimated for each RDE group.A total of 1051 out of 1071 randomized subjects were eligible for inclusion in this analysis. Compared with 6 months AS, 18 months AS significantly reduced DP independently of radiation dose (subhazard ratio 0.70; 95% confidence interval [CI], 0.56-0.87; P = .002). No statistically significant interaction between effect of AS duration and RT dose was observed (Wald test P = .76). In subgroup analyses, DP was significantly reduced by the longer duration of AS in the 70 Gy and HDRB groups but not in the 66 Gy and 74 Gy. Compared with 70 Gy, HDRB significantly reduced DP (subhazard ratio 0.68 [95% CI, 0.57-0.80]; P.0001) independently of AS duration. At 10 years, adjusted cumulative incidences were 26.1% (95% CI, 18.9%-33.2%), 26.7% (22.9%-30.6%), 24.9% (20.0%-29.8%) and 19.7% (15.5%-23.8%) for DPs in the respective radiation dose groups.Compared with 6 months AS, 18 months AS reduced DP independently of radiation dose. Men treated with HDRB gained a significant benefit from a longer duration of AS. Evidence of improved oncologic outcomes for HDRB compared with dose-escalated EBRT needs to be confirmed in a randomized trial.

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.

Education and training of medical physics require close integration of academic and clinically based training. During the COVID-19 pandemic, many countries experienced nationwide lockdown. Universities were compelled to move teaching and learning activities online. This chapter reviews various medical physics approaches to education that were implemented during the pandemic. It describes the experience of selected postgraduate medical physics programmes in Australia, Brazil, Europe, Malaysia, and the United Kingdom. While hospitals, being essential services, continued to run, albeit with much tighter control and safety measures, clinical training and hospital-based activities were discouraged, discontinued, or postponed. Virtual labs were organised as a temporary measure due to the COVID-19 restrictions. Although they were useful in enabling at least a minimum clinical exposure for students, they did not replace the hospital-based experience that is necessary for medical physics training.

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.

Research in artificial intelligence for radiology and radiotherapy has recently become increasingly reliant on the use of deep learning-based algorithms. While the performance of the models which these algorithms produce can significantly outperform more traditional machine learning methods, they do rely on larger datasets being available for training. To address this issue, data augmentation has become a popular method for increasing the size of a training dataset, particularly in fields where large datasets aren't typically available, which is often the case when working with medical images. Data augmentation aims to generate additional data which is used to train the model and has been shown to improve performance when validated on a separate unseen dataset. This approach has become commonplace so to help understand the types of data augmentation techniques used in state-of-the-art deep learning models, we conducted a systematic review of the literature where data augmentation was utilised on medical images (limited to CT and MRI) to train a deep learning model. Articles were categorised into basic, deformable, deep learning or other data augmentation techniques. As artificial intelligence models trained using augmented data make their way into the clinic, this review aims to give an insight to these techniques and confidence in the validity of the models produced.

Hypofractionation of prostate cancer radiotherapy achieves tumour control at lower total radiation doses, however, increased rectal and bladder toxicities have been observed. To realise the radiobiological advantage of hypofractionation whilst minimising harm, the potential reduction in dose to organs at risk was investigated for biofocused radiotherapy. Patient-specific tumour location and cell density information were derived from multiparametric imaging. Uniform-dose plans and biologically-optimised plans were generated for a standard schedule (78 Gy/39 fractions) and hypofractionated schedules (60 Gy/20 fractions and 36.25 Gy/5 fractions). Results showed that biologically-optimised plans yielded statistically lower doses to the rectum and bladder compared to isoeffective uniform-dose plans for all fractionation schedules. A reduction in the number of fractions increased the target dose modulation required to achieve equal tumour control. On average, biologically-optimised, moderately-hypofractionated plans demonstrated 15.3% (p-value

Advances in imaging have enabled the identification of prostate cancer foci with an initial application to focal dose escalation, with subvolumes created with image intensity thresholds. Through quantitative imaging techniques, correlations between image parameters and tumour characteristics have been identified. Mathematical functions are typically used to relate image parameters to prescription dose to improve the clinical relevance of the resulting dose distribution. However, these relationships have remained speculative or invalidated. In contrast, the use of radiobiological models during treatment planning optimisation, termed biological optimisation, has the advantage of directly considering the biological effect of the resulting dose distribution. This has led to an increased interest in the accurate derivation of radiobiological parameters from quantitative imaging to inform the models. This article reviews the progress in treatment planning using image-informed tumour biology, from focal dose escalation to the current trend of individualised biological treatment planning using image-derived radiobiological parameters, with the focus on prostate intensity-modulated radiotherapy (IMRT).

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.

A survey was conducted to establish the current utilisation of stereotactic ablative radiation therapy (SABR) services in NSW. The objective of the survey was to generate baseline data to inform requirements for a networked approach to the implementation of new radiation therapy techniques and technologies. All radiation therapy services in NSW were contacted by email with a request to complete a SABR service survey. Questions were designed to identify equipment used, treatment techniques in place, clinical sites treated with a SABR technique and plans to expand the current services offered. Each professional group was asked to identify areas of service delivery they would most like to improve. Sixteen responses were received representing 24 of 27 (89%) of NSW radiation therapy centres. The results indicate that most centres now treat with SABR, however the number of centres and the treatment sites are still increasing. VMAT treatments and 3D imaging are now commonplace. Liver was the most commonly reported treatment site where confidence in service delivery needed improvement. Data from the survey will be useful in formulating future collaborative and educational activities aimed at improving safety and efficacy in SABR service delivery to all patients in NSW and potentially the rest of the country.

BACKGROUND AND PURPOSE To evaluate the impact of treatment planning and delivery factors on treatment outcome as measured by post-treatment disease progression. MATERIALS AND METHODS Accruing 813 external beam radiotherapy participants during 2003-2007, the RADAR trial collected a comprehensive range of clinical treatment factor data for each participant. Both the Fine and Gray competing risks modelling and the Kaplan-Meier (KM) analysis were undertaken to determine the impact of these factors on local-composite progression (LCP), with 709 participants available for analysis. RESULTS Participants with treatments involving 7 or more beams experienced significantly higher incidence of LCP, with a sub-hazard ratio (relative to 3-beam participants) of 3.056 (CI: 1.446-6.458, p

Purpose High-dose-rate (HDR) prostate brachytherapy treatment is usually delivered in one or a few large dose fractions. Poor execution of a planned treatment could have significant clinical impact, as high doses are delivered in seconds, and mistakes in an individual fraction cannot be easily rectified. Given that most potential errors in HDR brachytherapy ultimately lead to a geographical miss, a more direct approach to verification of correct treatment delivery is to directly monitor the position of the source throughout the treatment. In this work, we report on the clinical implementation of our treatment verification system that uniquely combines the 2D source-tracking capability with 2D pretreatment imaging, using a single flat panel detector (FPD). Methods and Materials The clinical brachytherapy treatment couch was modified to allow integration of the FPD into the couch. This enabled the patient to be set up in the brachytherapy bunker in a position that closely matched that at treatment planning imaging. An anteroposterior image was acquired of the patient immediately before treatment delivery and was assessed by the Radiation Oncologist online, to reestablish the positions of the catheters relative to the prostate. Assessment of catheter positions was performed in the left-right and superior-inferior directions along the entire catheter length and throughout the treatment volume. Source tracking was then performed during treatment delivery, and the measured position of the source dwells were directly compared to the treatment plan for verification. Results The treatment verification system was integrated into the clinical environment without significant change to workflow. Two patient cases are presented in this work to provide clinical examples of this system, which is now in routine use for all patient treatments in our clinic. The catheter positions were visualized relative to the prostate, immediately before treatment delivery. For one of the patient cases presented in this work, they agreed with the treatment plan on average by 1.5 mm and were identifiable as a predominantly inferior shift. The source tracking was performed during treatment delivery, and for the same case, the mean deviation from the planned dwell positions was 1.9 mm (max = 4.9 mm) for 280 positions across all catheters. Conclusion We have implemented our noninvasive treatment verification system based on an FPD in the clinical environment. The device is integrated into a patient treatment couch, and the process is now included in the routine clinical treatment procedure with minor impact on workflow. The system which combines both 2D pretreatment imaging and HDR 2D source tracking provides a range of information that can be used for comprehensive treatment verification. The system has the potential to meaningfully improve safety standards by allowing widespread adoption of routine treatment verification in HDR brachytherapy.

Quality assurance (QA) for clinical trials is important. Lack of compliance can affect trial outcome. Clinical trial QA groups have different methods of dose distribution verification and analysis, all with the ultimate aim of ensuring trial compliance. The aim of this study was to gain a better understanding of different processes to inform future dosimetry audit reciprocity.Six clinical trial QA groups participated. Intensity modulated treatment plans were generated for three different cases. A range of 17 virtual 'measurements' were generated by introducing a variety of simulated perturbations (such as MLC position deviations, dose differences, gantry rotation errors, Gaussian noise) to three different treatment plan cases. Participants were blinded to the 'measured' data details. Each group analysed the datasets using their own gamma index (γ) technique and using standardised parameters for passing criteria, lower dose threshold, γ normalisation and global γ.For the same virtual 'measured' datasets, different results were observed using local techniques. For the standardised γ, differences in the percentage of points passing with γ 1 were also found, however these differences were less pronounced than for each clinical trial QA group's analysis. These variations may be due to different software implementations of γ.This virtual dosimetry audit has been an informative step in understanding differences in the verification of measured dose distributions between different clinical trial QA groups. This work lays the foundations for audit reciprocity between groups, particularly with more clinical trials being open to international recruitment.

Focal therapy for prostate cancer has been proposed as an alternative treatment to whole gland therapy, offering the opportunity for tumor dose escalation and/or reduced toxicity. Brachytherapy, either low-dose-rate or high-dose-rate, provides an ideal approach, offering both precision in dose delivery and opportunity for a highly conformal, non-uniform dose distribution. Whilst multiple consensus documents have published clinical guidelines for patient selection, there are insufficient data to provide clear guidelines on target volume delineation, treatment planning margins, treatment planning approaches, and many other technical issues that should be considered before implementing a focal brachytherapy program. Without consensus guidelines, there is the potential for a diversity of practices to develop, leading to challenges in interpreting outcome data from multiple centers. This article provides an overview of the technical considerations for the implementation of a clinical service, and discusses related topics that should be considered in the design of clinical trials to ensure precise and accurate methods are applied for focal brachytherapy treatments.

Purpose High dose rate prostate brachytherapy is a widely-practiced treatment, delivering large conformal doses in relatively few treatment fractions. Inter- and intra-fraction catheter displacements have been reported. Unrecognized displacement can have a significant impact on dosimetry. Knowledge of the implant geometry at the time of treatment is important for ensuring safe and effective treatment. In this work we demonstrate a method to reconstruct the catheter positions pre-treatment, using a ‘shift’ imaging technique, and perform registration with the treatment plan for verification relative to the prostate. Methods Two oblique ‘shift’ images were acquired of a phantom containing brachytherapy catheters, representing the patient immediately pre-treatment. Using a back projection approach, the catheter paths were reconstructed in 3D and registered with the planned catheter paths. The robustness of the reconstruction and registration process was investigated as a function of phantom rotation. Catheter displacement detection was performed and compared to known applied displacements. Results Reconstruction of the implant geometry in 3D immediately prior to treatment was achieved. A mean reconstruction uncertainty of 0.8 mm was determined for all catheters with a mean registration uncertainty of 0.5 mm. A catheter displacement detection threshold of 2.2 mm was demonstrated. Catheter displacements were all detected to within 0.5 mm of the applied displacements. Conclusion This technique is robust and sensitive to assess catheter displacements throughout the implant volume. This approach provides a method to detect, in 3D, changes in catheter positions relative to the prostate. The method has sufficient sensitivity to enable clinically significant decisions immediately prior to treatment delivery.

The performance of a support vector machine (SVM) algorithm was investigated to predict prostate tumour location using multi-parametric MRI (mpMRI) data. The purpose was to obtain information of prostate tumour location for the implementation of bio-focused radiotherapy. In vivo mpMRI data were collected from 16 patients prior to radical prostatectomy. Sequences included T2-weighted imaging, diffusion-weighted imaging and dynamic contrast enhanced imaging. In vivo mpMRI was registered with 'ground truth' histology, using ex vivo MRI as an intermediate registration step to improve accuracy. Prostate contours were delineated by a radiation oncologist and tumours were annotated on histology by a pathologist. Five patients with minimal imaging artefacts were selected for this study. A Gaussian kernel SVM was trained and tested on different patient data subsets. Parameters were optimised using leave-oneout cross validation. Signal intensities of mpMRI were used as features and histology annotations as true labels. Prediction accuracy, as well as area under the curve (AUC) of the receiver operating characteristics (ROC) curve, were used to assess performance. Results demonstrated the prediction accuracy ranged from 70.4 to 87.1% and AUC of ROC ranged from 0.81 to 0.94. Additional investigations showed the apparent diffusion coefficient map from diffusion weighted imaging was the most important imaging modality for predicting tumour location. Future work will incorporate additional patient data into the framework to increase the sensitivity and specificity of the model, and will be extended to incorporate predictions of biological characteristics of the tumour which will be used in bio-focused radiotherapy optimisation.

Low-risk prostate cancer can be treated by focal brachytherapy, in which small radioactive seeds are implanted directly into the prostate at targeted locactions. Treatment planning is complicated by post-operative displacement of the seeds from their intended location. This reduces the actual dose received by the prostate and increases the dose to surrounding tissue such as the urethra and rectum, potentially causing harmful side-effects. Current treatment planning methods do not explicitly incorporate the effect of post-operative seed displacement. To address this, the radiation dose rate function used during planning is modified to reflect displacement using convolution. This new dose rate model enables plans to be produced automatically and efficiently. Simulation experiments show that treatment plans made using the convolved dose rate function are more robust to seed displacement than those using the original unconvolved dose, preserving treatment efficacy but giving increased protection to surrounding tissue.

Aims This study aimed to develop a framework for optimising prostate intensity-modulated radiotherapy (IMRT) based on patient-specific tumour biology, derived from multiparametric MRI (mpMRI). The framework included a probabilistic treatment planning technique in the effort to yield dose distributions with an improved expected treatment outcome compared with uniform-dose planning approaches. Methods IMRT plans were generated for five prostate cancer patients using two inverse planning methods: uniform-dose to the planning target volume and probabilistic biological optimisation for clinical target volume tumour control probability (TCP) maximisation. Patient-specific tumour location and clonogen density information were derived from mpMRI and geometric uncertainties were incorporated in the TCP calculation. Potential reduction in dose to sensitive structures was assessed by comparing dose metrics of uniform-dose plans with biologically-optimised plans of an equivalent level of expected tumour control. Results The planning study demonstrated biological optimisation has the potential to reduce expected normal tissue toxicity without sacrificing local control by shaping the dose distribution to the spatial distribution of tumour characteristics. On average, biologically-optimised plans achieved 38.6% (p-value: p-value: Conclusions It was concluded that varying the dose distribution within the prostate to take account for each patient’s clonogen distribution was feasible. Lower doses to normal structures compared to uniform-dose plans was possible whilst providing robust plans against geometric uncertainties. Further validation in a larger cohort is warranted along with considerations for adaptive therapy and limiting urethral dose.

Objective: To investigate the association between multiparametric MRI (mpMRI) imaging features and hypoxia-related genetic profiles in prostate cancer. Methods: In vivo mpMRI was acquired from six patients prior to radical prostatectomy. Sequences included T2 weighted (T2W) imaging, diffusion-weighted imaging, dynamic contrast enhanced MRI and blood oxygen-level dependent imaging. Imaging data were co-registered with histology using three-dimensional deformable registration methods. Texture features were extracted from T2W images and parametric maps from functional MRI. Full transcriptome genetic profiles were obtained using next generation sequencing from the prostate specimens. Pearson correlation coefficients were calculated between mpMRI data and hypoxia-related gene expression levels. Results were validated using glucose transporter one immunohistochemistry (IHC). Results: Correlation analysis identified 34 candidate imaging features (six from the mpMRI data and 28 from T2W texture features). The IHC validation showed that 16 out of the 28 T2W texture features achieved weak but significant correlations (p < 0.05). Conclusions: Weak associations between mpMRI features and hypoxia gene expressions were found. This indicates the potential use of MRI in assessing hypoxia status in prostate cancer. Further validation is required due to the low correlation levels. Advances in knowledge: This is a pilot study using radiogenomics approaches to address hypoxia within the prostate, which provides an opportunity for hypoxia-guided selective treatment techniques.