Prognostic utility of RECIP 1.0 with manual and AI-based segmentations in biochemically recurrent prostate cancer from [68Ga]Ga-PSMA-11 PET images.

PURPOSE: This study aimed to (i) validate the Response Evaluation Criteria in PSMA (RECIP 1.0) criteria in a cohort of biochemically recurrent (BCR) prostate cancer (PCa) patients and (ii) determine if this classification could be performed fully automatically using a trained artificial intelligence (AI) model. METHODS: One hundred ninety-nine patients were imaged with [68Ga]Ga-PSMA-11 PET/CT once at the time of biochemical recurrence and then a second time a median of 6.0 months later to assess disease progression. Standard-of-care treatments were administered to patients in the interim. Whole-body tumour volume was quantified semi-automatically (TTVman) in all patients and using a novel AI method (TTVAI) in a subset (n = 74, the remainder were used in the training process of the model). Patients were classified as having progressive disease (RECIP-PD), or non-progressive disease (non RECIP-PD). Association of RECIP classifications with patient overall survival (OS) was assessed using the Kaplan-Meier method with the log rank test and univariate Cox regression analysis with derivation of hazard ratios (HRs). Concordance of manual and AI response classifications was evaluated using the Cohen's kappa statistic. RESULTS: Twenty-six patients (26/199 = 13.1%) presented with RECIP-PD according to semi-automated delineations, which was associated with a significantly lower survival probability (log rank p < 0.005) and higher risk of death (HR = 3.78 (1.96-7.28), p < 0.005). Twelve patients (12/74 = 16.2%) presented with RECIP-PD according to AI-based segmentations, which was also associated with a significantly lower survival (log rank p = 0.013) and higher risk of death (HR = 3.75 (1.23-11.47), p = 0.02). Overall, semi-automated and AI-based RECIP classifications were in fair agreement (Cohen's k = 0.31). CONCLUSION: RECIP 1.0 was demonstrated to be prognostic in a BCR PCa population and is robust to two different segmentation methods, including a novel AI-based method. RECIP 1.0 can be used to assess disease progression in PCa patients with less advanced disease. This study was registered with the Australian New Zealand Clinical Trials Registry (ACTRN12615000608561) on 11 June 2015.

Delineation and agreement of FET PET biological volumes in glioblastoma: results of the nuclear medicine credentialing program from the prospective, multi-centre trial evaluating FET PET In Glioblastoma (FIG) study-TROG 18.06.

PURPOSE: The O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) PET in Glioblastoma (FIG) trial is an Australian prospective, multi-centre study evaluating FET PET for glioblastoma patient management. FET PET imaging timepoints are pre-chemoradiotherapy (FET1), 1-month post-chemoradiotherapy (FET2), and at suspected progression (FET3). Before participant recruitment, site nuclear medicine physicians (NMPs) underwent credentialing of FET PET delineation and image interpretation. METHODS: Sites were required to complete contouring and dynamic analysis by ≥ 2 NMPs on benchmarking cases (n = 6) assessing biological tumour volume (BTV) delineation (3 × FET1) and image interpretation (3 × FET3). Data was reviewed by experts and violations noted. BTV definition includes tumour-to-background ratio (TBR) threshold of 1.6 with crescent-shaped background contour in the contralateral normal brain. Recurrence/pseudoprogression interpretation (FET3) required assessment of maximum TBR (TBRmax), dynamic analysis (time activity curve [TAC] type, time to peak), and qualitative assessment. Intraclass correlation coefficient (ICC) assessed volume agreement, coefficient of variation (CoV) compared maximum/mean TBR (TBRmax/TBRmean) across cases, and pairwise analysis assessed spatial (Dice similarity coefficient [DSC]) and boundary agreement (Hausdorff distance [HD], mean absolute surface distance [MASD]). RESULTS: Data was accrued from 21 NMPs (10 centres, n ≥ 2 each) and 20 underwent review. The initial pass rate was 93/119 (78.2%) and 27/30 requested resubmissions were completed. Violations were found in 25/72 (34.7%; 13/12 minor/major) of FET1 and 22/74 (29.7%; 14/8 minor/major) of FET3 reports. The primary reasons for resubmission were as follows: BTV over-contour (15/30, 50.0%), background placement (8/30, 26.7%), TAC classification (9/30, 30.0%), and image interpretation (7/30, 23.3%). CoV median and range for BTV, TBRmax, and TBRmean were 21.53% (12.00-30.10%), 5.89% (5.01-6.68%), and 5.01% (3.37-6.34%), respectively. BTV agreement was moderate to excellent (ICC = 0.82; 95% CI, 0.63-0.97) with good spatial (DSC = 0.84 ± 0.09) and boundary (HD = 15.78 ± 8.30 mm; MASD = 1.47 ± 1.36 mm) agreement. CONCLUSION: The FIG study credentialing program has increased expertise across study sites. TBRmax and TBRmean were robust, with considerable variability in BTV delineation and image interpretation observed.

Fully automatic prognostic biomarker extraction from metastatic prostate lesion segmentations in whole-body [68Ga]Ga-PSMA-11 PET/CT images.

PURPOSE: This study aimed to develop and assess an automated segmentation framework based on deep learning for metastatic prostate cancer (mPCa) lesions in whole-body [68Ga]Ga-PSMA-11 PET/CT images for the purpose of extracting patient-level prognostic biomarkers. METHODS: Three hundred thirty-seven [68Ga]Ga-PSMA-11 PET/CT images were retrieved from a cohort of biochemically recurrent PCa patients. A fully 3D convolutional neural network (CNN) is proposed which is based on the self-configuring nnU-Net framework, and was trained on a subset of these scans, with an independent test set reserved for model evaluation. Voxel-level segmentation results were assessed using the dice similarity coefficient (DSC), positive predictive value (PPV), and sensitivity. Sensitivity and PPV were calculated to assess lesion level detection; patient-level classification results were assessed by the accuracy, PPV, and sensitivity. Whole-body biomarkers total lesional volume (TLVauto) and total lesional uptake (TLUauto) were calculated from the automated segmentations, and Kaplan-Meier analysis was used to assess biomarker relationship with patient overall survival. RESULTS: At the patient level, the accuracy, sensitivity, and PPV were all > 90%, with the best metric being the PPV (97.2%). PPV and sensitivity at the lesion level were 88.2% and 73.0%, respectively. DSC and PPV measured at the voxel level performed within measured inter-observer variability (DSC, median = 50.7% vs. second observer = 32%, p = 0.012; PPV, median = 64.9% vs. second observer = 25.7%, p < 0.005). Kaplan-Meier analysis of TLVauto and TLUauto showed they were significantly associated with patient overall survival (both p < 0.005). CONCLUSION: The fully automated assessment of whole-body [68Ga]Ga-PSMA-11 PET/CT images using deep learning shows significant promise, yielding accurate scan classification, voxel-level segmentations within inter-observer variability, and potentially clinically useful prognostic biomarkers associated with patient overall survival. TRIAL REGISTRATION: This study was registered with the Australian New Zealand Clinical Trials Registry (ACTRN12615000608561) on 11 June 2015.

Matched linac stereotactic radiotherapy: An assessment of delivery similarity and distributive patient-specific quality assurance feasibility.

Matching multiple linacs to common baseline data allows patients to be treated, and patient-specific quality assurance (PSQA) to be completed on any linac. Stereotactic body radiotherapy (SBRT) requires higher levels of accuracy and quality assurance than routine radiotherapy. The achieved linac matching must therefore be evaluated before distributive treatment or PSQA models can be implemented safely. This investigation aimed to propose metrics for defining linacs to be matched for SBRT deliveries, assess 12 linacs against these criteria, and determine if a distributive PSQA model could be implemented by reviewing the rates of false PSQA results. Ten SBRT spine plans were delivered by 12 matched Elekta linacs and measured using one of seven SRS MapCHECK devices. For gamma criteria of (3%, 2 mm), 96.9% of equivalent location detectors, showed a range of gamma ≤ 1.0 and 99.9% showed a standard deviation of ≤ 0.5. For criteria of (3%,1 mm) and (2%,1 mm), these ranges decreased to 92.1% and 80.2% while the standard deviations decreased to 99.3% and 95.7%, respectively. The dose differences showed that 43.6%, 82.7%, and 91.4% of detectors had a dose range of ≤ 3.0%, ≤ 5.0%, and ≤ 6.0%, respectively. Standard deviations of dose differences were 1.5%, 2.5%, and 3.0% for 94.1%, 98.3%, and 99.5% of detectors, respectively. For the fleet of linacs, distributive PSQA yielded false results for 0.0%, 17.7%, and 33.0% of plans, equivalent to 1.2%, 3.5%, and 9.4% of detectors when using gamma criteria of (3%,2 mm), (3%,1 mm), or (2%,1 mm), respectively. These linacs could be considered matched for SBRT treatments and implement a distributive PSQA model when gamma analysis was completed with a criterion of (3%, 2 mm). For stricter criterion of (3%,1 mm) or (2%,1 mm), they did not meet the proposed metrics.

Recommended dose voxel size and statistical uncertainty parameters for precision of Monte Carlo dose calculation in stereotactic radiotherapy.

Monte Carlo (MC)-based treatment planning requires a choice of dose voxel size (DVS) and statistical uncertainty (SU). These parameters effect both the precision of displayed dose distribution and time taken to complete a calculation. For efficient, accurate, and precise treatment planning in a clinical setting, optimal values should be selected. In this investigation, 30 volumetric modulated arc therapy (VMAT) stereotactic radiotherapy (SRT) treatment plans, 10 brain, 10 lung, and 10 spine were calculated in the Monaco 5.11.02 treatment planning system (TPS). Each plan was calculated with a DVS of 0.1 and 0.2 cm using SU values of 0.50%, 0.75%, 1.00%, 1.50%, and 2.00%, along with a ground truth calculation using a DVS of 0.1 cm and SU of 0.15%. The variance at each relative dose level was calculated for all SU settings to assess their relationship. The variation from the ground truth calculation for each DVS and SU combination was determined for a range of DVH metrics and plan quality indices along with the time taken to complete the calculations. Finally, the effect of defining the maximum dose using a volume of 0.035 cc was compared to 0.100 cc when considering DVS and SU settings. Changes in the DVS produced greater variations from the ground truth calculation than changes in SU across the values tested. Plan quality metrics and mean dose values showed less sensitivity to changes in SU than DVH metrics. From this study, it was concluded that while maintaining an average calculation time of <10 min, 75% of plans could be calculated with variations of <2.0% from their ground truth values when using an SU setting of 1.50% and a DVS of 0.1 cm in the case of brain or spine plans, and a 0.2 cm DVS in the case of lung plans.

Quality assurance of Cyberknife robotic stereotactic radiosurgery using an angularly independent silicon detector.

PURPOSE: The aim of this work was to evaluate the use of an angularly independent silicon detector (edgeless diodes) developed for dosimetry in megavoltage radiotherapy for Cyberknife in a phantom and for patient quality assurance (QA). METHOD: The characterization of the edgeless diodes has been performed on Cyberknife with fixed and IRIS collimators. The edgeless diode probes were tested in terms of basic QA parameters such as measurements of tissue-phantom ratio (TPR), output factor and off-axis ratio. The measurements were performed in both water and water-equivalent phantoms. In addition, three patient-specific plans have been delivered to a lung phantom with and without motion and dose measurements have been performed to verify the ability of the diodes to work as patient-specific QA devices. The data obtained by the edgeless diodes have been compared to PTW 60016, SN edge, PinPoint ionization chamber, Gafchromic EBT3 film, and treatment planning system (TPS). RESULTS: The TPR measurement performed by the edgeless diodes show agreement within 2.2% with data obtained with PTW 60016 diode for all the field sizes. Output factor agrees within 2.6% with that measured by SN EDGE diodes corrected for their field size dependence. The beam profiles' measurements of edgeless diodes match SN EDGE diodes with a measured full width half maximum (FWHM) within 2.3% and penumbra widths within 0.148 mm. Patient-specific QA measurements demonstrate an agreement within 4.72% in comparison with TPS. CONCLUSION: The edgeless diodes have been proved to be an excellent candidate for machine and patient QA for Cyberknife reproducing commercial dosimetry device measurements without need of angular dependence corrections. However, further investigation is required to evaluate the effect of their dose rate dependence on complex brain cancer dose verification.

Sustainability of the Australian radiation oncology workforce: A survey of radiation therapists and radiation oncology medical physicists.

This study aimed to determine and compare Radiation Therapists' (RTs') and Radiation Oncology Medical Physicists' (ROMPs') perspectives about their profession and workplace, satisfaction with career progression opportunities, and leaving the current workplace. RTs and ROMPs who were currently or had previously worked in Australia were invited to complete an online survey. Univariate and multivariate methods were used for analysis. Participants were 342 RTs and 112 ROMPs with estimated response rates of 14% and 26% respectively. Both professions rated workload poorly and identified the need for improvement in: communication between professions' members, support for junior staff/new graduates, staff morale, on-site training and multidisciplinary communication. RTs, more than ROMPs, perceived their profession was recognised and respected, but RTs were less likely to be satisfied with career progression/advancement, job promotion prospects and opportunities to specialise. At least 20% of RTs and ROMPs were thinking about leaving their workplace and 13% of RTs and 8% of ROMPs were thinking about leaving their profession. Different factors contributed to workforce satisfaction and retention within each profession. Staff satisfaction and career progression are critical to retain RTs and ROMPs. Further research is required to explore strategies to address workplace dissatisfaction, recruitment and retention.

Development of a 3D printed phantom for commissioning and quality assurance of multiple brain targets stereotactic radiosurgery.

Single plan techniques for multiple brain targets (MBT) stereotactic radiosurgery (SRS) are now routine. Patient specific quality assurance (QA) for MBT poses challenges due to the limited capabilities of existing QA tools which necessitates several plan redeliveries. This study sought to develop an SRS QA phantom that enables flexible MBT patient specific QA in a single delivery, along with complex SRS commissioning. PLA marble and PLA StoneFil materials were selected based on the literature and previous research conducted in our department. The HU numbers were investigated to determine the appropriate percentage infill for skull and soft-tissue equivalence. A Prusa MK3S printer in conjunction with the above-mentioned filaments were used to print the SRS QA phantom. Quality control (QC) was performed on the printed skull, film inserts and plugs for point dose measurements. EBT3 film and point dose measurements were performed using a CC04 ionisation chamber. QC demonstrated that the SRS QA phantom transverse, coronal and sagittal film planes were orthogonal within 0.5°. HU numbers for the skull, film inserts and plugs were 858 ± 20 and 35 ± 12 respectively. Point and EBT3 film dose measurements were within 2.5% and 3%/2 mm 95% gamma pass rate, respectively except one Gross Tumour Volume (GTV) that had a slightly lower gamma pass rate. Dose distributions to five GTVs were measured with EBT3 film in a single plan delivery on CyberKnife. In conclusion, an SRS QA phantom was designed, and 3D printed and its use for performing complex MBT patient specific QA in a single delivery was demonstrated.

The prognostic value of F18 Fluorothymidine positron emission tomography for assessing the response of malignant pleural mesothelioma to chemotherapy - A prospective cohort study.

INTRODUCTION: Malignant pleural mesothelioma is difficult to prognosticate. F18-Fluorodeoxyglucose positron emission tomography (FDG PET) shows promise for response assessment but is confounded by talc pleurodesis. F18-Fluorothymidine (FLT) PET is an alternative tracer specific for proliferation. We compared the prognostic value of FDG and FLT PET and determined the influence of talc pleurodesis on these parameters. METHODS: Overall, 29 prospectively recruited patients had FLT PET, FDG PET and CT-scans performed prior to and post one chemotherapy cycle; 10 had prior talc pleurodesis. Patients were followed for overall survival. CT response was assessed using mRECIST. Radiomic features were extracted using the MiM software platform. Changes in maximum SUV (SUVmax), mean SUV (SUVmean), FDG total lesion glycolysis (TLG), FLT total lesion proliferation (TLP) and metabolic tumour volume (MTV) after one chemotherapy cycle. RESULTS: Cox univariate analysis demonstrated FDG PET radiomics were confounded by talc pleurodesis, and that percentage change in FLT MTV was predictive of overall survival. Cox multivariate analysis showed a 10% increase in FLT tumour volume corresponded with 9.5% worsened odds for overall survival (P = 0.028, HR = 1.095, 95% CI [1.010, 1.187]). No other variables were significant on multivariate analysis. CONCLUSION: This is the first prospective study showing the statistical significance of FLT PET tumour volumes for measuring mesothelioma treatment response. FLT may be better than FDG for monitoring mesothelioma treatment response, which could help optimise mesothelioma treatment regimes.

Development and optimisation of grid inserts for a preclinical radiotherapy system and corresponding Monte Carlo beam simulations.

Objective. To develop a physical grid collimator compatible with the X-RAD preclinical radiotherapy system and create a corresponding Monte Carlo (MC) model.Approach. This work presents a methodology for the fabrication of a grid collimator designed for utilisation on the X-RAD preclinical radiotherapy system. Additionally, a MC simulation of the grid is developed, which is compatible with the X-RAD treatment planning system. The grid was manufactured by casting a low melting point alloy, cerrobend, into a silicone mould. The silicone was moulded around a 3D-printed replica of the grid, enabling the production of diverging holes with precise radii and spacing. A MC simulation was conducted on an equivalent 3D grid model and validated using 11 layers of GAFChromic EBT-3 film interspersed in a 3D-printed water-equivalent phantom. A 3D dose distribution was constructed from the film layers, enabling a direct comparison with the MC Simulation.Main results. The film and the MC dose distribution demonstrated a gamma passing rate of 99% for a 1%, 0.5 mm criteria with a 10% threshold applied. The peak-to-valley dose ratio and output factor at the surface were determined to be 20.4 and 0.79, respectively.Significance. The pairing of the grid collimator with a MC simulation can significantly enhance the practicality of grid therapy on the X-RAD. This combination enables further exploration of the biological implications of grid therapy, supported by a knowledge of the complex dose distributions. Moreover, this methodology can be adapted for use in other systems and scenarios.

Towards optimal heterogeneous prostate radiotherapy dose prescriptions based on patient-specific or population-based biological features.

BACKGROUND: Escalation of prescribed dose in prostate cancer (PCa) radiotherapy enables improvement in tumor control at the expense of increased toxicity. Opportunities for reduction of treatment toxicity may emerge if more efficient dose escalation can be achieved by redistributing the prescribed dose distribution according to the known heterogeneous, spatially-varying characteristics of the disease. PURPOSE: To examine the potential benefits, limitations and characteristics of heterogeneous boost dose redistribution in PCa radiotherapy based on patient-specific and population-based spatial maps of tumor biological features. METHOD: High-resolution prostate histology images, from a cohort of 63 patients, annotated with tumor location and grade, provided patient-specific "maps" and a population-based "atlas" of cell density and tumor probability. Dose prescriptions were derived for each patient based on a heterogeneous redistribution of the boost dose to the intraprostatic lesions, with the prescription maximizing patient tumor control probability (TCP). The impact on TCP was assessed under scenarios where the distribution of population-based biological data was ignored, partially included, or fully included in prescription generation. Heterogeneous dose prescriptions were generated for three combinations of maps and atlas, and for conventional fractionation (CF), extreme hypo-fractionation (EH), moderate hypo-fractionation (MH), and whole Pelvic RT + SBRT Boost (WPRT + SBRT). The predicted efficacy of the heterogeneous prescriptions was compared with equivalent homogeneous dose prescriptions. RESULTS: TCPs for heterogeneous dose prescriptions were generally higher than those for homogeneous dose prescriptions. TCP escalation by heterogeneous dose prescription was the largest for CF. When only using population-based atlas data, the generated heterogeneous dose prescriptions of 55 to 58 patients (out of 63) had a higher TCP than for the corresponding homogeneous dose prescriptions. The TCPs of the heterogeneous dose prescriptions generated with the population-based atlas and tumor probability maps did not differ significantly from those using patient-specific biological information. The generated heterogeneous dose prescriptions achieved significantly higher TCP than homogeneous dose prescriptions in the posterior section of the prostate. CONCLUSION: Heterogeneous dose prescriptions generated via biologically-optimized dose redistribution can produce higher TCP than the homogeneous dose prescriptions for the majority of the patients in the studied cohort. For scenarios where patient-specific biological information was unavailable or partially available, the generated heterogeneous dose prescriptions can still achieve TCP improvement relative to homogeneous dose prescriptions.

Assessing focal spot alignment in clinical linear accelerators: a comprehensive evaluation with triplet phantoms.

A fundamental parameter to evaluate the beam delivery precision and stability on a clinical linear accelerator (linac) is the focal spot position (FSP) measured relative to the collimator axis of the radiation head. The aims of this work were to evaluate comprehensive data on FSP acquired on linacs in clinical use and to establish the ability of alternative phantoms to detect effects on patient plan delivery related to FSP. FSP measurements were conducted using a rigid phantom holding two ball-bearings at two different distances from the radiation source. Images of these ball-bearings were acquired using the electronic portal imaging device (EPID) integrated with each linac. Machine QA was assessed using a radiation head-mounted PTW STARCHECK phantom. Patient plan QA was investigated using the SNC ArcCHECK phantom positioned on the treatment couch, irradiated with VMAT plans across a complete 360° gantry rotation and three X-ray energies. This study covered eight Elekta linacs, including those with 6 MV, 18 MV, and 6 MV flattening-filter-free (FFF) beams. The largest range in the FSP was found for 6 MV FFF. The FSP of one linac, retrofitted with 6 MV FFF, displayed substantial differences in FSP compared to 6 MV FFF beams on other linacs, which all had FSP ranges less than 0.50 mm and 0.25 mm in the lateral and longitudinal directions, respectively. The PTW STARCHECK phantom proved effective in characterising the FSP, while the SNC ArcCHECK measurements could not discern FSP-related features. Minor variations in FSP may be attributed to adjustments in linac parameters, component replacements necessary for beam delivery, and the wear and tear of various linac components, including the magnetron and gun filament. Consideration should be given to the ability of any particular phantom to detect a subsequent impact on the accuracy of patient plan delivery.

Construction and validation of an infant chest phantom for paediatric computed tomography.

Paediatric imaging protocols should be carefully optimised to maintain the desired image quality while minimising the delivered patient dose. A paediatric chest phantom was designed, constructed and evaluated to optimise chest CT examinations for infants. The phantom was designed to enable dosimetry and image quality measurements within the anthropomorphic structure. It was constructed using tissue equivalent materials to mimic thoracic structures of infants, aged 0-6 months. The phantom materials were validated across a range of diagnostic tube voltages with resulting CT numbers found equivalent to paediatric tissues observed via a survey of clinical paediatric chest studies. The phantom has been successfully used to measure radiation dose and evaluate various image quality parameters for paediatric specific protocols.

The impact of fluorine-18-fluoroethyltyrosine positron emission tomography scan timing on radiotherapy planning in newly diagnosed patients with glioblastoma.

Background and purpose: Glioblastoma is one of the most common and aggressive primary brain tumours in adults. Though radiation therapy (RT) techniques have progressed significantly in recent decades, patient survival has seen little improvement. However, an area of promise is the use of fluorine-18-fluoroethyltyrosine positron-emission-tomography (18F-FET PET) imaging to assist in RT target delineation. This retrospective study aims to assess the impact of 18F-FET PET scan timing on the resultant RT target volumes and subsequent RT plans in post-operative glioblastoma patients. Materials and Methods: The imaging and RT treatment data of eight patients diagnosed with glioblastoma and treated at a single institution were analysed. Before starting RT, each patient had two 18F-FET-PET scans acquired within seven days of each other. The information from these 18F-FET-PET scans aided in the creation of two novel target volume sets. The new volumes and plans were compared with each other and the originals. Results: The median clinical target volume (CTV) 1 was statistically smaller than CTV 2. The median Dice score for the CTV1/CTV2 was 0.98 and, of the voxels that differ (median 6.5 cc), 99.7% were covered with a 5 mm expansion. Overall organs at risk (OAR) and target dosimetry were similar in the PTV1 and PTV2 plans. Conclusion: Provided the 18F-FET PET scan is acquired within two weeks of the RT planning and a comprehensive approach is taken to CTV delineation, the timing of scan acquisition has minimal impact on the resulting RT plan.

Mechanistic in silico explorations of the immunogenic and synergistic effects of radiotherapy and immunotherapy: a critical review.

Immunotherapy is a rapidly evolving field, with many models attempting to describe its impact on the immune system, especially when paired with radiotherapy. Tumor response to this combination involves a complex spatiotemporal dynamic which makes either clinical or pre-clinical in vivo investigation across the resulting extensive solution space extremely difficult. In this review, several in silico models of the interaction between radiotherapy, immunotherapy, and the patient's immune system are examined. The study included only mathematical models published in English that investigated the effects of radiotherapy on the immune system, or the effect of immuno-radiotherapy with immune checkpoint inhibitors. The findings indicate that treatment efficacy was predicted to improve when both radiotherapy and immunotherapy were administered, compared to radiotherapy or immunotherapy alone. However, the models do not agree on the optimal schedule and fractionation of radiotherapy and immunotherapy. This corresponds to relevant clinical trials, which report an improved treatment efficacy with combination therapy, however, the optimal scheduling varies between clinical trials. This discrepancy between the models can be attributed to the variation in model approach and the specific cancer types modeled, making the determination of the optimum general treatment schedule and model challenging. Further research needs to be conducted with similar data sets to evaluate the best model and treatment schedule for a specific cancer type and stage.

Dosimetric comparison of proton therapy and CyberKnife in stereotactic body radiation therapy for liver cancers.

Stereotactic body radiation therapy (SBRT) has been increasingly used for the ablation of liver tumours. CyberKnife and proton beam therapy (PBT) are two advanced treatment technologies suitable to deliver SBRT with high dose conformity and steep dose gradients. However, there is very limited data comparing the dosimetric characteristics of CyberKnife to PBT for liver SBRT. PBT and CyberKnife plans were retrospectively generated using 4DCT datasets of ten patients who were previously treated for hepatocellular carcinoma (HCC, N = 5) and liver metastasis (N = 5). Dose volume histogram data was assessed and compared against selected criteria; given a dose prescription of 54 Gy in 3 fractions for liver metastases and 45 Gy in 3 fractions for HCC, with previously published consensus-based normal tissue dose constraints. Comparison of evaluation parameters showed a statistically significant difference for target volume coverage and liver, lungs and spinal cord (p < 0.05) dose, while chest wall and skin did not indicate a significant difference between the two modalities. A number of optimal normal tissue constraints was violated by both the CyberKnife and proton plans for the same patients due to proximity of tumour to chest wall. PBT resulted in greater organ sparing, the extent of which was mainly dependent on tumour location. Tumours located on the liver periphery experienced the largest increase in organ sparing. Organ sparing for CyberKnife was comparable with PBT for small target volumes.

Uncertainty estimation using a 3D probabilistic U-Net for segmentation with small radiotherapy clinical trial datasets.

BACKGROUND AND OBJECTIVES: Bio-medical image segmentation models typically attempt to predict one segmentation that resembles a ground-truth structure as closely as possible. However, as medical images are not perfect representations of anatomy, obtaining this ground truth is not possible. A surrogate commonly used is to have multiple expert observers define the same structure for a dataset. When multiple observers define the same structure on the same image there can be significant differences depending on the structure, image quality/modality and the region being defined. It is often desirable to estimate this type of aleatoric uncertainty in a segmentation model to help understand the region in which the true structure is likely to be positioned. Furthermore, obtaining these datasets is resource intensive so training such models using limited data may be required. With a small dataset size, differing patient anatomy is likely not well represented causing epistemic uncertainty which should also be estimated so it can be determined for which cases the model is effective or not. METHODS: We use a 3D probabilistic U-Net to train a model from which several segmentations can be sampled to estimate the range of uncertainty seen between multiple observers. To ensure that regions where observers disagree most are emphasised in model training, we expand the Generalised Evidence Lower Bound (ELBO) with a Constrained Optimisation (GECO) loss function with an additional contour loss term to give attention to this region. Ensemble and Monte-Carlo dropout (MCDO) uncertainty quantification methods are used during inference to estimate model confidence on an unseen case. We apply our methodology to two radiotherapy clinical trial datasets, a gastric cancer trial (TOPGEAR, TROG 08.08) and a post-prostatectomy prostate cancer trial (RAVES, TROG 08.03). Each dataset contains only 10 cases each for model development to segment the clinical target volume (CTV) which was defined by multiple observers on each case. An additional 50 cases are available as a hold-out dataset for each trial which had only one observer define the CTV structure on each case. Up to 50 samples were generated using the probabilistic model for each case in the hold-out dataset. To assess performance, each manually defined structure was matched to the closest matching sampled segmentation based on commonly used metrics. RESULTS: The TOPGEAR CTV model achieved a Dice Similarity Coefficient (DSC) and Surface DSC (sDSC) of 0.7 and 0.43 respectively with the RAVES model achieving 0.75 and 0.71 respectively. Segmentation quality across cases in the hold-out datasets was variable however both the ensemble and MCDO uncertainty estimation approaches were able to accurately estimate model confidence with a p-value < 0.001 for both TOPGEAR and RAVES when comparing the DSC using the Pearson correlation coefficient. CONCLUSIONS: We demonstrated that training auto-segmentation models which can estimate aleatoric and epistemic uncertainty using limited datasets is possible. Having the model estimate prediction confidence is important to understand for which unseen cases a model is likely to be useful.

[18]F-fluoroethyl-l-tyrosine positron emission tomography for radiotherapy target delineation: Results from a Radiation Oncology credentialing program.

Background and purpose: The [18]F-fluoroethyl-l-tyrosine (FET) PET in Glioblastoma (FIG) study is an Australian prospective, multi-centre trial evaluating FET PET for newly diagnosed glioblastoma management. The Radiation Oncology credentialing program aimed to assess the feasibility in Radiation Oncologist (RO) derivation of standard-of-care target volumes (TVMR) and hybrid target volumes (TVMR+FET) incorporating pre-defined FET PET biological tumour volumes (BTVs). Materials and methods: Central review and analysis of TVMR and TVMR+FET was undertaken across three benchmarking cases. BTVs were pre-defined by a sole nuclear medicine expert. Intraclass correlation coefficient (ICC) confidence intervals (CIs) evaluated volume agreement. RO contour spatial and boundary agreement were evaluated (Dice similarity coefficient [DSC], Jaccard index [JAC], overlap volume [OV], Hausdorff distance [HD] and mean absolute surface distance [MASD]). Dose plan generation (one case per site) was assessed. Results: Data from 19 ROs across 10 trial sites (54 initial submissions, 8 resubmissions requested, 4 conditional passes) was assessed with an initial pass rate of 77.8 %; all resubmissions passed. TVMR+FET were significantly larger than TVMR (p < 0.001) for all cases. RO gross tumour volume (GTV) agreement was moderate-to-excellent for GTVMR (ICC = 0.910; 95 % CI, 0.708-0.997) and good-to-excellent for GTVMR+FET (ICC = 0.965; 95 % CI, 0.871-0.999). GTVMR+FET showed greater spatial overlap and boundary agreement compared to GTVMR. For the clinical target volume (CTV), CTVMR+FET showed lower average boundary agreement versus CTVMR (MASD: 1.73 mm vs. 1.61 mm, p = 0.042). All sites passed the planning exercise. Conclusions: The credentialing program demonstrated feasibility in successful credentialing of 19 ROs across 10 sites, increasing national expertise in TVMR+FET delineation.

Radiotherapy of abdomen with precise renal assessment with SPECT/CT imaging (RAPRASI): design and methodology of a prospective trial to improve the understanding of kidney radiation dose response.

BACKGROUND: The kidneys are a principal dose-limiting organ in radiotherapy for upper abdominal cancers. The current understanding of kidney radiation dose response is rudimentary. More precise dose-volume response models that allow direct correlation of delivered radiation dose with spatio-temporal changes in kidney function may improve radiotherapy treatment planning for upper-abdominal tumours. METHODS/DESIGN: The Radiotherapy of Abdomen with Precise Renal Assessment with SPECT/CT Imaging (RAPRASI) is an observational clinical research study with participating sites at Sir Charles Gairdner Hospital (SCGH) in Perth, Australia and the Peter MacCallum Cancer Centre (PMCC) in Melbourne, Australia. Eligible patients are those with upper gastrointestinal cancer, without metastatic disease, undergoing conformal radiotherapy that will involve incidental radiation to one or both kidneys. For each patient, total kidney function is being assessed before commencement of radiotherapy treatment and then at 4, 12, 26, 52 and 78 weeks after the first radiotherapy fraction, using two procedures: a Glomerular Filtration Rate (GFR) measurement using the 51Cr-ethylenediamine tetra-acetic acid (EDTA) clearance; and a regional kidney perfusion measurement assessing renal uptake of 99mTc-dimercaptosuccinic acid (DMSA), imaged with a Single Photon Emission Computed Tomography / Computed Tomography (SPECT/CT) system. The CT component of the SPECT/CT provides the anatomical reference of the kidney's position. The data is intended to reveal changes in regional kidney function over the study period after the radiotherapy. These SPECT/CT scans, co-registered with the radiotherapy treatment plan, will provide spatial correlation between the radiation dose and regional renal function as assessed by SPECT/CT. From this correlation, renal response patterns will likely be identified with the purpose of developing a predictive model. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry: ACTRN12609000322235.

Comparison of TLD calibration methods for 192Ir dosimetry.

For the purpose of dose measurement using a high-dose rate (192)Ir source, four methods of thermoluminescent dosimeter (TLD) calibration were investigated. Three of the four calibration methods used the (192)Ir source. Dwell times were calculated to deliver 1 Gy to the TLDs irradiated either in air or water. Dwell time calculations were confirmed by direct measurement using an ionization chamber. The fourth method of calibration used 6 MV photons from a medical linear accelerator, and an energy correction factor was applied to account for the difference in sensitivity of the TLDs in (192)Ir and 6 MV. The results of the four TLD calibration methods are presented in terms of the results of a brachytherapy audit where seven Australian centers irradiated three sets of TLDs in a water phantom. The results were in agreement within estimated uncertainties when the TLDs were calibrated with the (192)Ir source. Calibrating TLDs in a phantom similar to that used for the audit proved to be the most practical method and provided the greatest confidence in measured dose. When calibrated using 6 MV photons, the TLD results were consistently higher than the (192)Ir-calibrated TLDs, suggesting this method does not fully correct for the response of the TLDs when irradiated in the audit phantom.