Prostate Radiotherapy Research Articles

The Quantitative Impact of Prostate Specific Membrane Antigen Positron Emission Tomography/Computed Tomography (PSMA PET/CT) staging in Newly Diagnosed Metastatic Prostate Cancer and Treatment-Decision Implications

Abstract Objectives To quantify the stage-shift with PSMA PET/CT imaging in metastatic prostate cancer and explore treatment implications. Methods Single-centre, retrospective analysis of patients with newly diagnosed [18F]PSMA-1007 or [68Ga]Ga-PSMA-11 PET/CT-detected metastatic prostate cancer who had baseline bone scintigraphy between January 2015 and May 2021. Patients were subclassified into oligometastatic and polymetastatic disease utilising the STAMPEDE2 trial (ISRCTN66357938/NCT06320067) definition. Patient, tumour, and treatment characteristics were collected. PSMA PET/CT concordance with conventional imaging (bone scintigraphy and low-dose CT of PET) was identified by number and site of metastases, and subgroup assigned. Spearman’s rank correlation and linear regression modelling determined the association between the imaging modalities. Results We analysed 62 patients with a median age was 72 years (range 48-86). On PSMA PET/CT, 31/62 (50%) patients had oligometastatic disease, and 31/62 (50%) had polymetastatic disease. Prostate radiotherapy was delivered in 20/31 (65%) patients with oligometastatic disease and 17/31 (55%) with polymetastatic disease. 23/62 (37%) patients were reclassified as M0 on conventional imaging. PSMA PET/CT had a 2.9-fold increase in detecting bone metastases. Bone metastases concordance was found in 10/50 (20%) by number and 30/33 (91%) by site. PSMA PET/CT had a 2.2-fold increase in detecting nodal metastases. Nodal metastases concordance was found in 5/46 (11%) by number and 25/26 (96%) by site. There was significant positive correlation between PSMA PET/CT and conventional imaging for detecting bone (R2= 0.25 [p < 0.001]) and nodal metastases (R2= 0.19 [p < 0.001]). 16/31 (52%) had oligometastatic disease concordance. Conclusion The magnitude of PSMA PET/CT-driven stage-shift is highly variable and unpredictable with implications on treatment decisions, future trial design and potentially clinical outcomes.

Cone-Beam CT to CT Image Translation Using a Transformer-Based Deep Learning Model for Prostate Cancer Adaptive Radiotherapy.

Cone-beam computed tomography (CBCT) is widely utilized in image-guided radiation therapy; however, its image quality is poor compared to planning CT (pCT), thus restricting its utility for adaptive radiotherapy (ART). Our objective was to enhance CBCT image quality utilizing a transformer-based deep learning model, SwinUNETR, which we compared with a conventional convolutional neural network (CNN) model, U-net. This retrospective study involved 260 patients undergoing prostate radiotherapy, with 245 patients used for training and 15 patients reserved as an independent hold-out test dataset. Employing a CycleGAN framework, we generated synthetic CT (sCT) images from CBCT images, employing SwinUNETR and U-net as generators. We evaluated sCT image quality and assessed its dosimetric impact for photon therapy through gamma analysis and dose-volume histogram (DVH) comparisons. The mean absolute error values for the CT numbers, calculated using all voxels within the patient's body contour and taking the pCT images as a reference, were 84.07, 73.49, and 64.69 Hounsfield units for CBCT, U-net, and SwinUNETR images, respectively. Gamma analysis revealed superior agreement between the dose on the pCT images and on the SwinUNETR-based sCT plans compared to those based on U-net. DVH parameters calculated on the SwinUNETR-based sCT deviated by < 1% from those in pCT plans. Our study showed that, compared to the U-net model, SwinUNETR could proficiently generate more precise sCT images from CBCT images, facilitating more accurate dose calculations. This study demonstrates the superiority of transformer-based models over conventional CNN-based approaches for CBCT-to-CT translation, contributing to the advancement of image synthesis techniques in ART.

Is Centralisation of Cancer Services Associated With Under-Treatment of Patients With High-Risk Prostate Cancer?-A National Population-Based Study.

Centralising prostate cancer surgical and radiotherapy services, requires some patients to travel longer to access treatment, but its impact on actual treatment utilisation and outcomes is unknown. Using national cancer registry records linked to administrative hospital data, we identified all patients with high risk and locally advanced prostate cancer diagnosed between 1 April 2019 and 31 March 2020 in the English National Health Service (n = 15,971). Estimated travel times from the patient residential areas to the nearest hospital providing surgery or radiotherapy were estimated for journeys by car and by public transport. Multivariable logistic regression was used to model relationships between travel time and receipt of care with adjustment for patient characteristics. 10,693 (67%) men received radical surgery or radiotherapy (RT) within 12 months of diagnosis. Average travel time to the nearest hospital providing prostatectomy or RT was 23.2 min by private car and 58.2 min by public transport. We found no association between travel time, either by car or public transport and the likelihood of receiving curative treatment. Patients living in the most socially deprived areas, those aged over 70, those with two or more comorbidities, and those of black ethnic origin, were less likely to receive curative treatment (p& =& 0.001 for all associations). The current configuration of national prostate cancer services is not associated with the likelihood of receiving curative treatment. Further increases in capacity will unlikely improve utilisation rates beyond addressing sociodemographic barriers.

Local Treatment (Primary Tumor and Metastases) in Metastatic Prostate Cancer

For patients with low-volume de novo metastatic hormone-sensitive prostate cancer, addition of an androgen receptor pathway inhibitor and prostate radiotherapy to the standard (SOC) improves survival in comparison to the next most effective strategy (SOC + ARPI). For the subgroup with prior definitive treatment of the primary tumor, long-term outcomes and genomic predictors of response to metastasis-directed therapy suggest that this might be a reasonable option in selected patients.

Assessing the Impact of the Prostate Cancer Patient Empowerment Program (PC-PEP) on Relationship Satisfaction, Quality of Life, and Support Group Participation: A Randomized Clinical Trial.

Background/Objectives: The Prostate Cancer Patient Empowerment Program (PC-PEP) is a 6-month, home-based intervention aimed at enhancing mental health in men undergoing curative prostate cancer treatment. This exploratory secondary analysis evaluates PC-PEP's impact on relationship satisfaction, quality of life, and support group attendance among partnered participants. Methods: In a crossover randomized clinical trial ClinicalTrials.gov identifier: NCT03660085) of 128 men aged 50-82 scheduled for curative prostate cancer surgery or radiotherapy, 119 participants in relationships were included. Of these, 59 received the 6-month PC-PEP intervention, while 60 were randomized to a waitlist-control arm, receiving standard care for 6 months before starting PC-PEP. The intervention included daily emails with video instructions on mental and physical health, diet, social support, fitness, stress reduction, and intimacy. Outcomes were assessed using the Dyadic Adjustment Scale (DAS) and the Functional Assessment of Cancer Therapy-Prostate (FACT-P). Results: While relationship satisfaction remained stable, a significant improvement in emotional well-being was observed at 12 months in participants undergoing radiation therapy (p = 0.045). The PC-PEP intervention also led to significantly higher support group attendance at both 6 months (p = 0.001) and 12 months (p = 0.003), emphasizing its role in fostering social support and community engagement. Conclusions: The PC-PEP program effectively maintains relationship satisfaction and enhances emotional well-being, particularly in patients with fewer physical side effects. Its design promotes comprehensive care by integrating physical, psychological, and social support, making it a valuable resource for improving the quality of life in prostate cancer patients and potentially applicable to other cancer types.

Prostate cancer and solid organ transplantation: patient management and outcomes.

To analyse the management and outcomes of individuals diagnosed with prostate cancer either before or after organ transplantation, as the impact of organ transplantation and associated immunosuppression on the incidence, progression, and mortality of prostate cancer remains an area of substantial clinical interest and uncertainty. We conducted a retrospective analysis of patients from two tertiary care centres who had solid organ transplantation and were diagnosed with prostate cancer before or after organ transplantation. Data collected included demographics and clinical information. The cohort consisted of 110 patients with a median (interquartile range [IQR]) age at prostate cancer diagnosis of 62 (56.6-67.2) years and a median (IQR) age at transplantation of 58.6 (52.7-65.3) years. Renal transplantation was the most common (54%). The median (IQR) prostate-specific antigen concentration at prostate cancer diagnosis was 6.2 (4.5-10) ng/mL, and the distribution of American Urological Association risk groups was: low risk, 36%; intermediate risk, 50%; and high risk, 14%. In all, 45 (41%) patients were diagnosed with prostate cancer prior to transplantation. Management included radical prostatectomy (RP; 62%), prostate radiotherapy (RT; 13%), and active surveillance (AS; 18%). During a median (IQR) follow-up of 5.8 (2.5-10) years from prostate cancer diagnosis, one (2%) patient developed metastatic disease. In all, 65 (59%) patients were diagnosed with prostate cancer subsequent to organ transplantation. Management included AS (29%), RT (45%), and RP (15%). During a median (IQR) follow-up of 5.3 (1-8.4) years, three patients (5%) developed metastatic disease. There were no deaths from prostate cancer. A diagnosis of localised prostate cancer should not preclude solid organ transplantation, and the presence of a transplant does not appear to substantially impact risk of prostate cancer progression.

FASTer Radiotherapy-The successes of a research led interventional clinic facilitating prostate radiotherapy trials

FASTer Radiotherapy-The successes of a research led interventional clinic facilitating prostate radiotherapy trials

Achieving accurate prostate auto-segmentation on CT in the absence of MR imaging

BackgroundMagnetic resonance imaging (MRI) is considered the gold standard for prostate segmentation. Computed tomography (CT)-based segmentation is prone to observer bias, potentially overestimating the prostate volume by ∼ 30 % compared to MRI. However, MRI accessibility is challenging for patients with contraindications or in rural areas globally with limited clinical resources. PurposeThis study investigates the possibility of achieving MRI-level prostate auto-segmentation accuracy using CT-only input via a deep learning (DL) model trained with CT-MRI registered segmentation. Methods and MaterialsA cohort of 111 definitive prostate radiotherapy patients with both CT and MRI images was retrospectively grouped into training (n = 37) and validation (n = 20) (where reference contours were derived from CT-MRI registration), and testing (n = 54) sets. Two commercial DL models were benchmarked against the reference contours in the training and validation sets. A custom DL model was incrementally retrained using the training dataset, quantitatively evaluated on the validation dataset, and qualitatively assessed by two different physician groups on the validation and testing datasets. A contour quality assurance (QA) model, established from the proposed model on the validation dataset, was applied to the test group to identify potential errors, confirmed by human visual inspection. ResultsTwo commercial models exhibited large deviations in the prostate apex with CT-only input (median: 0.77/0.78 for Dice similarity coefficient (DSC), and 0.80 cm/0.83 cm for 95 % directed Hausdorff Distance (HD95), respectively). The proposed model demonstrated superior geometric similarity compared to commercial models, particularly in the apex region, with improvements of 0.05/0.17 cm and 0.06/0.25 cm in median DSC/HD95, respectively. Physician evaluation on MRI-CT registration data rated 69 %-78 % of the proposed model’s contours as clinically acceptable without modifications. Additionally, 73 % of cases flagged by the contour quality assurance (QA) model were confirmed via visual inspection. ConclusionsThe proposed incremental learning strategy based on CT-MRI registration information enhances prostate segmentation accuracy when MRI availability is limited clinically.

The Role of Local Prostate and Metastasis-Directed Radiotherapy in the Treatment of Oligometastatic Prostate Cancer.

Background/Objectives: Oligometastatic prostate cancer (OMPC) represents an early stage of metastatic disease characterized by a limited number of lesions. Recent advancements in imaging and treatment have revived interest in personalized therapies, including metastasis-directed radiotherapy (OMDRT) and primary prostate radiotherapy (PPR). This study evaluates the impact of OMDRT timing and the role of PPR on survival outcomes in OMPC patients; Methods: In this retrospective cohort study, 82 patients with OMPC who underwent OMDRT between 2010 and 2019 were analyzed. Patients were classified based on OMDRT timing (early vs. late) and disease type (synchronous vs. metachronous). Progression-free survival (PFS) and overall survival (OS) were the primary endpoints, assessed via Kaplan-Meier analysis and Cox proportional hazards models; Results: Among the patients, 36 (43.9%) had synchronous and 46 (56.1%) had metachronous OMD. With a median follow-up of 32 months, the 5-year PFS and OS rates were 77.5% and 88.5%, respectively. Early OMDRT significantly improved PFS (HR 0.461, 95% CI: 0.257-0.826, p = 0.009) and OS (HR 0.219, 95% CI: 0.080-0.603, p = 0.003). Subgroup analysis showed the most favorable outcomes for synchronous OMD patients receiving early OMDRT, with a median PFS of 22.2 months and a 5-year survival rate of 42.1%. The treatment of the primary prostate provided a survival benefit in the OS of synchronous OMD patients (5-year 83.1% vs. 50%, p = 0.025), and there was a further improvement in OS after PPR (5-year 87.7% vs. 50%, p = 0.015). Conclusions: Early OMDRT significantly enhances survival outcomes in OMPC, in both synchronous and metachronous cases. The integration of PPR can further improve results, emphasizing the importance of early intervention and personalized treatment strategies. To more definitively clarify our findings across various clinical situations, further studies with larger cohorts or prospective designs are necessary.

Evaluating the Effects of Prostate Radiotherapy Intensified with Pelvic Nodal Radiotherapy and Androgen Deprivation Therapy on Myelosuppression: Single-Institution Experience.

Prostate cancer (PCa) management commonly involves the utilization of prostate radiotherapy (PRT), pelvic nodal radiotherapy (PNRT), and androgen deprivation therapy (ADT). However, the potential association of these treatment modalities with bone marrow (BM) suppression remains inadequately reported in the existing literature. This study is designed to comprehensively evaluate the risk of myelosuppression associated with PRT, shedding light on an aspect that has been underrepresented in prior research. We conducted a retrospective analysis of 600 patients with prostate cancer (PCa) treated with prostate radiotherapy (PRT) at a single oncology center between 2007 and 2017. Patients were categorized into four cohorts: PRT alone (n = 149), PRT + ADT, (n = 91), PRT + PNRT (n = 39), and PRT + PNRT + ADT (n = 321). To assess the risk of myelosuppression, we scrutinized specific blood parameters, such as hemoglobin (HGB), white blood cells (WBCs), neutrophils (NEUT), lymphocytes (LYM), and platelets (PLT) at baseline, mid-treatment (mRT), immediately post-RT (pRT), 1 month post-RT (1M-pRT), and 1 year post-RT (1Y-pRT). The inter-cohort statistical significance was evaluated with further stratification based on the utilized RT technique {3D conformal radiotherapy (3D-CRT), and intensity-modulated radiation therapy (IMRT)}. Significant statistical differences at baseline were observed in HGB and LYM values among all cohorts (p < 0.05). Patients in the PRT + PNRT + ADT cohort had significantly lower HGB at baseline and 1M-pRT. In patients undergoing ADT, BMS had a significant impact at 1M-pRT {odds ratio (OR) 9.1; 95% Confidence Interval (CI) 4.8-17.1} and at 1Y-pRT (OR 2.84; CI 1.14-7.08). The use of 3D-CRT was linked to reduced HGB levels in the PRT + PNRT + ADT group at 1 month pRT (p = 0.015). Similarly, PNRT significantly impacted BMS at 1M-pRT (OR 6.7; CI 2.6-17.2). PNRT increased the odds of decreased WBC counts at 1Y-pRT (OR 6.83; CI: 1.02-45.82). Treatment with any RT techniques (3D-CRT or IMRT), particularly in the PRT + PNRT and PRT + PNRT + ADT groups, significantly increased the odds of low LYM counts at all time points except immediately pRT (p < 0.05). Furthermore, NEUT counts were considerably lower at 1M-pRT (p < 0.05) in the PRT + PNRT + ADT group. PLT counts were significantly decreased by PRT + PNRT + ADT at mRT (OR 2.57; 95% CI: 1.42-4.66) but were not significantly impacted by the RT technique. Treatment with PRT, ADT, PNRT, and 3D-CRT is associated with BMS. Despite this statistically significant risk, no patient required additional interventions to manage the outcome. While its clinical impact appears limited, its importance cannot be underestimated in the context of increased integration of novel systemic agents with myelosuppressive properties. Longer follow-up should be considered in future studies.

Automated plan generation for prostate radiotherapy patients using deep learning and scripted optimization

Background and PurposeTreatment planning is a time-intensive task that could be automated. We aimed to develop a “single-click” workflow, fully deployed within a commercial treatment planning system (TPS), for autoplanning prostate radiotherapy treatment plans using predictions from a deep learning model (DLM). Materials and MethodsAutomatically generated treatment plans were created with a single script, executed from within a commercial TPS scripting environment, that performed two stages sequentially. Initially, a 3D dose distribution was predicted with a ResUNet DLM. The DLM was trained and validated using previously treated datasets (n = 120) which used 3D contours as inputs. Following this, dose predictions were converted into treatment plans by extracting dose-volume metrics from the predictions to use as objectives for the inverse optimizer within the TPS. An independent test dataset (n = 20) was used to evaluate the similarity between automated and clinical plans. ResultsFor planning target volumes, the median percentage difference and interquartile range between the automatically generated plans and clinical plans were 0.4% [0.2-1.1%] for the V100%, −0.5% [(−1.0)-(−0.2)%] for D99% and −0.5% [(−1.0)-(−0.2)%] for D95%. Bladder and rectum volume-at-dose objectives agreed within −6.1% [(−12.5)-0.9%]. The conversion of the DLM prediction into a treatment plan took 15 min [13-16 min]. ConclusionsAn automatic plan generation workflow that uses a DL model with scripted optimization was fully deployed in a commercial TPS. Autoplans were compared to previously treated clinical plans and were found to be non-inferior.

Poor Prognosis among Radiation-Associated Bladder Cancer Is Defined by Clinicogenomic Features.

Clinicogenomic analysis of radiation-associated bladder cancer uncovered mutational signatures that, in addition to a short tumor latency, smoking, and CDKN2A loss, are associated with a poor outcome. These clinical and genomic features provide a potential method to identify patients with prostate cancer who are at an increased risk for the development of aggressive bladder cancer following prostate RT.

128 Toxicity Comparison of Online-Adaptive CT-Guided Versus Cone-Beam-CT-Guided Non-Adaptive Prostate Radiation

128 Toxicity Comparison of Online-Adaptive CT-Guided Versus Cone-Beam-CT-Guided Non-Adaptive Prostate Radiation

3156: Longitudinal QOL after dose escalated ultra-hypo-fractionated prostate RT with an endorectal spacer.

3156: Longitudinal QOL after dose escalated ultra-hypo-fractionated prostate RT with an endorectal spacer.

2325: Reduction of PTV margins in online adaptive radiotherapy for prostate and cervix cancer patients

2325: Reduction of PTV margins in online adaptive radiotherapy for prostate and cervix cancer patients

1863: HyperSight CBCT directly suitable for offline adaptive radiotherapy for prostate, but not for lung

1863: HyperSight CBCT directly suitable for offline adaptive radiotherapy for prostate, but not for lung

1086: Urethra-sparing single-dose ablative prostate radiotherapy with real-time motion management

1086: Urethra-sparing single-dose ablative prostate radiotherapy with real-time motion management

3044: Patient Adherence with Prostate Radiotherapy Planning Protocols – Can we do Better?

3044: Patient Adherence with Prostate Radiotherapy Planning Protocols – Can we do Better?

1731: Rad-led Prehabilitation Clinic increases number of successful prostate radiotherapy CTplanning scans

1731: Rad-led Prehabilitation Clinic increases number of successful prostate radiotherapy CTplanning scans

2917: Patient specific in silico investigation of gated and MLC-tracked MR-guided prostate radiotherapy

2917: Patient specific in silico investigation of gated and MLC-tracked MR-guided prostate radiotherapy