Assessing the Heterogeneity of Response of [68Ga] Ga-PSMA-11 PET/CT Lesions in Patients With Biochemical Recurrence of Prostate Cancer.

INTRODUCTION: Treatment of men with metastatic prostate cancer can be difficult due to the heterogeneity of response of lesions. [68Ga]Ga-PSMA-11 (PSMA) PET/CT assists with monitoring and directing clinical intervention; however, the impact of response heterogeneity has yet to be related to outcome measures. The aim of this study was to assess the impact of quantitative imaging information on the value of PSMA PET/CT to assess patient outcomes in response evaluation. PATIENTS AND METHODS: Baseline and follow-up (6 months) PSMA PET/CT of 162 men with oligometastatic PC treated with standard clinical care were acquired between 2015 and 2016 for analysis. An augmentative software medical device was used to track lesions between scans and quantify lesion change to categorize them as either new, increasing, stable, decreasing, or disappeared. Quantitative imaging features describing the size, intensity, extent, change, and heterogeneity of change (based on percent change in SUVtotal) among lesions were extracted and evaluated for association with overall survival (OS) using Cox regression models. Model performance was evaluated using the c-index. RESULTS: Forty-one (25%) of subjects demonstrated heterogeneous response at follow-up, defined as having at least 1 new or increasing lesion and at least 1 decreasing or disappeared lesion. Subjects with heterogeneous response demonstrated significantly shorter OS than subjects without (median OS = 76.6 months vs. median OS not reached, P < .05, c-index = 0.61). In univariate analyses, SUVtotal at follow-up was most strongly associated with OS (HR = 1.29 [1.19, 1.40], P < .001, c-index = 0.73). Multivariable models applied using heterogeneity of change features demonstrated higher performance (c-index = 0.79) than models without (c-index = 0.71-0.76, P < .05). CONCLUSION: Augmentative software tools enhance the evaluation change on serial PSMA PET scans and can facilitate lesional evaluation between timepoints. This study demonstrates that a heterogeneous response at a lesional level may impact adversely on patient outcomes and supports further investigation to evaluate the role of imaging to guide individualized patient management to improve clinical outcomes.

Insights into the dosimetric and geometric characteristics of stereotactic radiosurgery for multiple brain metastases: A systematic review.

BACKGROUND: GammaKnife (GK) and CyberKnife (CK) have been the mainstay stereotactic radiosurgery (SRS) solution for multiple brain metastases (MBM) for several years. Recent technological advancement has seen an increase in single-isocentre C-arm linac-based SRS. This systematic review focuses on dosimetric and geometric insights into contemporary MBM SRS and thereby establish if linac-based SRS has matured to match the mainstay SRS delivery systems. METHODS: The PubMed, Web of Science and Scopus databases were interrogated which yielded 891 relevant articles that narrowed to 20 articles after removing duplicates and applying the inclusion and exclusion criteria. Primary studies which reported the use of SRS for treatment of MBM SRS and reported the technical aspects including dosimetry were included. The review was limited to English language publications from January 2015 to August 2023. Only full-length papers were included in the final analysis. Opinion papers, commentary pieces, letters to the editor, abstracts, conference proceedings and editorials were excluded. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. The reporting of conformity indices (CI) and gradient indices, V12Gy, monitor units and the impact of translational and rotational shifts were extracted and analysed. RESULTS: The single-isocentre technique for MBM dominated recent SRS studies and the most studied delivery platforms were Varian. The C-arm linac-based SRS plan quality and normal brain tissue sparing was comparable to GK and CK and in some cases better. The most used nominal beam energy was 6FFF, and optimised couch and collimator angles could reduce mean normal brain dose by 11.3%. Reduction in volume of the healthy brain receiving a certain dose was dependent on the number and size of the metastases and the relative geometric location. GK and CK required 4.5-8.4 times treatment time compared with linac-based SRS. Rotational shifts caused larger changes in CI in C-arm linac-based single-isocentre SRS. CONCLUSION: C-arm linac-based SRS produced comparable MBM plan quality and the delivery is notably shorter compared to GK and CK SRS.

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.

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.

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.

[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.

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.

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.

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.

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.

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.

Focal Boost in Prostate Cancer Radiotherapy: A Review of Planning Studies and Clinical Trials.

BACKGROUND: Focal boost radiotherapy was developed to deliver elevated doses to functional sub-volumes within a target. Such a technique was hypothesized to improve treatment outcomes without increasing toxicity in prostate cancer treatment. PURPOSE: To summarize and evaluate the efficacy and variability of focal boost radiotherapy by reviewing focal boost planning studies and clinical trials that have been published in the last ten years. METHODS: Published reports of focal boost radiotherapy, that specifically incorporate dose escalation to intra-prostatic lesions (IPLs), were reviewed and summarized. Correlations between acute/late ≥G2 genitourinary (GU) or gastrointestinal (GI) toxicity and clinical factors were determined by a meta-analysis. RESULTS: By reviewing and summarizing 34 planning studies and 35 trials, a significant dose escalation to the GTV and thus higher tumor control of focal boost radiotherapy were reported consistently by all reviewed studies. Reviewed trials reported a not significant difference in toxicity between focal boost and conventional radiotherapy. Acute ≥G2 GU and late ≥G2 GI toxicities were reported the most and least prevalent, respectively, and a negative correlation was found between the rate of toxicity and proportion of low-risk or intermediate-risk patients in the cohort. CONCLUSION: Focal boost prostate cancer radiotherapy has the potential to be a new standard of care.

Quantitative [68Ga]Ga-PSMA-11 PET biomarkers for the analysis of lesion-level progression in biochemically recurrent prostate cancer: a multicentre study.

[68Ga]Ga-PSMA-11 PET has become the standard imaging modality for biochemically recurrent (BCR) prostate cancer (PCa). However, its prognostic value in assessing response at this stage remains uncertain. The study aimed to assess the prognostic significance of radiographic patient-level patterns of progression derived from lesion-level biomarker quantitation in metastatic disease sites. A total of 138 BCR PCa patients with both baseline and follow-up [68Ga]Ga-PSMA-11 PET scans were included in this analysis. Tumour response was quantified at the lesion level using commonly used quantitative parameters (SUVmean, SUVmax, SUVpeak, volume), and patients were classified as systemic, mixed, or no-progression based on these response classifications. A total of 328 matched lesions between baseline and follow-up scans were analysed. The results showed that systemic progressors had a significantly higher risk of death than patients with no progression with SUVmean demonstrating the highest prognostic value (HR = 5.70, 95% CI = 2.63-12.37, p < 0.001, C-Index = 0.69). Moreover, progressive disease as measured by SUVmean using the radiographic PSMA PET Progression Criteria (rPPP) was found to be significantly prognostic for patient overall survival (HR = 3.67, 95% CI = 1.82-7.39, p < 0.001, C-Index = 0.65). This work provides important evidence supporting the prognostic utility of PSMA response quantitation in the BCR setting.

Prospective inter- and intra-tracer repeatability analysis of radiomics features in [68Ga]Ga-PSMA-11 and [18F]F-PSMA-1007 PET scans in metastatic prostate cancer.

OBJECTIVE: This study aimed to quantify both the intra- and intertracer repeatability of lesion-level radiomics features in [68Ga]Ga-prostate-specific membrane antigen (PSMA)-11 and [18F]F-PSMA-1007 positron emission tomography (PET) scans. METHODS: Eighteen patients with metastatic prostate cancer (mPCa) were prospectively recruited for the study and randomised to one of three test-retest groups: (i) intratracer [68Ga]Ga-PSMA-11 PET, (ii) intratracer [18F]F-PSMA-1007 PET or (iii) intertracer between [68Ga]Ga-PSMA-11 and [18F]F-PSMA-1007 PET. Four conventional PET metrics (standardised uptake value (SUV)max, SUVmean, SUVtotal and volume) and 107 radiomics features were extracted from 75 lesions and assessed using the repeatability coefficient (RC) and the ICC. Radiomic feature repeatability was also quantified after the application of 16 filters to the PET image. RESULTS: Test-retest scans were taken a median of 5 days apart (range: 2-7 days). SUVmean demonstrated the lowest RC limits of the conventional features, with RCs of 7.9%, 14.2% and 24.7% for the [68Ga]Ga-PSMA-11 PET, [18F]F-PSMA-1007 PET, and intertracer groups, respectively. 69%, 66% and 9% of all radiomics features had good or excellent ICC values (ICC ≥ 0.75) for the same groups. Feature repeatability therefore diminished considerably for the intertracer group relative to intratracer groups. CONCLUSION: In this study, robust biomarkers for each tracer group that can be used in subsequent clinical studies were identified. Overall, the repeatability of conventional and radiomic features were found to be substantially lower for the intertracer group relative to both intratracer groups, suggesting that assessing patient response quantitatively should be done using the same radiotracer where possible. ADVANCES IN KNOWLEDGE: Intertracer biomarker repeatability limits are significantly larger than intratracer limits.

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.

Comparison of the accuracy of Monte Carlo and Ray Tracing dose calculation algorithms for multiple target brain treatments on CyberKnife.

Single plan multiple brain targets (MBT) stereotactic radiosurgery dose difference between Monte Carlo (MC) and Ray Tracing (RT) algorithms has not been studied. A retrospective study and dose measurements were performed to access factors influencing dose differences. Fifty-three RT treatment plans with a total of 209 brain metastases were extracted from Precision Treatment Planning System (TPS). These plans were generated using fixed cones and were delivered using the CyberKnife M6 system. The same treatment plans were recalculated using MC algorithm and keeping the beam parameters unchanged. MC calculated plan parameters were extracted and dose differences were normalised to MC calculated dose. Correlations were investigated. RT and MC calculated off-centre-ratio (OCR) and tissue-phantom-ratio (TPRs) were exported from the TPS and compared with measured. Plans with 5 gross tumour volumes (GTVs) were created on a phantom and dose measured using a CC04 ionisation chamber and microdiamond detector for comparison with calculated doses. Calculated and measured TPR agreed within ± 1% beyond depth of maximum dose. The OCR showed differences up to 4.3% in the penumbra and out-of-field (OOF) regions. Largest RT and MC calculated GTV mean dose difference was - 5.7%. An increase in the number of GTVs and reduction in the geometric separation of metastases were associated with increased differences between RT and MC calculated doses. In conclusion, calculated dose disagreement in MBT depends on the number of GTVs per plan, number of GTVs within a certain separation distance and plan complexity. MC dose calculation is recommended for complex CyberKnife SRS of MBT.

Clinical target volume delineation quality assurance for MRI-guided prostate radiotherapy using deep learning with uncertainty estimation.

BACKGROUND AND PURPOSE: Previous studies on automatic delineation quality assurance (QA) have mostly focused on CT-based planning. As MRI-guided radiotherapy is increasingly utilized in prostate cancer treatment, there is a need for more research on MRI-specific automatic QA. This work proposes a clinical target volume (CTV) delineation QA framework based on deep learning (DL) for MRI-guided prostate radiotherapy. MATERIALS AND METHODS: The proposed workflow utilized a 3D dropblock ResUnet++ (DB-ResUnet++) to generate multiple segmentation predictions via Monte Carlo dropout which were used to compute an average delineation and area of uncertainty. A logistic regression (LR) classifier was employed to classify the manual delineation as pass or discrepancy based on the spatial association between the manual delineation and the network's outputs. This approach was evaluated on a multicentre MRI-only prostate radiotherapy dataset and compared with our previously published QA framework based on AN-AG Unet. RESULTS: The proposed framework achieved an area under the receiver operating curve (AUROC) of 0.92, a true positive rate (TPR) of 0.92 and a false positive rate of 0.09 with an average processing time per delineation of 1.3 min. Compared with our previous work using AN-AG Unet, this method generated fewer false positive detections at the same TPR with a much faster processing speed. CONCLUSION: To the best of our knowledge, this is the first study to propose an automatic delineation QA tool using DL with uncertainty estimation for MRI-guided prostate radiotherapy, which can potentially be used for reviewing prostate CTV delineation in multicentre clinical trials.

Risk of cardiac implantable device malfunction in cancer patients receiving proton therapy: an overview.

Age is a risk factor for both cardiovascular disease and cancer, and as such radiation oncologists frequently see a number of patients with cardiac implantable electronic devices (CIEDs) receiving proton therapy (PT). CIED malfunctions induced by PT are nonnegligible and can occur in both passive scattering and pencil beam scanning modes. In the absence of an evidence-based protocol, the authors emphasise that this patient cohort should be managed differently to electron- and photon- external beam radiation therapy (EBRT) patients due to distinct properties of proton beams. Given the lack of a PT-specific guideline for managing this cohort and limited studies on this important topic; the process was initiated by evaluating all PT-related CIED malfunctions to provide a baseline for future reporting and research. In this review, different modes of PT and their interactions with a variety of CIEDs and pacing leads are discussed. Effects of PT on CIEDs were classified into a variety of hardware and software malfunctions. Apart from secondary neutrons, cumulative radiation dose, dose rate, CIED model/manufacturer, distance from CIED to proton field, and materials used in CIEDs/pacing leads were all evaluated to determine the probability of malfunctions. The importance of proton beam arrangements is highlighted in this study. Manufacturers should specify recommended dose limits for patients undergoing PT. The establishment of an international multidisciplinary team dedicated to CIED-bearing patients receiving PT may be beneficial.

Correction factors for commissioning and patient specific quality assurance of stereotactic fields in a Monte Carlo based treatment planning system : TPS correction factors.

Validation of small field dosimetry is crucial for stereotactic radiosurgery (SRS) and stereotactic body radiotherapy (SBRT). Accurate and considered measurement of linear accelerator dose must be compared to precise and accurate calculation by the treatment planning system (TPS). Monte Carlo calculated distributions contain statistical noise, reducing the reliance that should be given to single voxel doses. The average dose to a small volume of interest (VOI) can minimise the influence of noise, but for small fields introduces significant volume averaging. Similar challenges present during measurement of composite dose from clinical plans when a small volume ionisation chamber is used. This study derived correction factors for VOI averaged TPS doses calculated for small fields, allowing correction to an isocentre dose following account for statistical noise. These factors were used to determine an optimal VOI to represent small volume ionisation chambers during patient specific quality assurance (PSQA). A retrospective comparison of 82 SRS and 28 SBRT PSQA measurements to TPS calculated doses from varying VOI was completed to evaluate the determined volumes. Small field commissioning correction factors of under 5% were obtained for field sizes of 8 mm and larger. Optimal spherical VOI with radius between 1.5 and 1.8 mm and 2.5 to 2.9 mm were determined for IBA CC01 and CC04 ionisation chambers respectively. Review of PSQA confirmed an optimal agreement between CC01 measured doses and a volume of 1.5 to 1.8 mm while CC04 measured doses showed no variation with VOI.