Association between measures of treatment quality and disease progression in prostate cancer radiotherapy: An exploratory analysis from the TROG 03.04 RADAR trial

Pretrial Quality Assurance for Hypofractionated Salvage Radiation Therapy After Prostatectomy in the Multi-Institutional PERYTON-trial

Purpose

The PERYTON trial is a multicenter randomized controlled trial that will investigate whether the treatment outcome of salvage external beam radiation therapy (sEBRT) will be improved with hypofractionated radiation therapy. A pretrial quality assurance (QA) program was undertaken to ensure protocol compliance within the PERYTON trial and to assess variation in sEBRT treatment protocols between the participating centers.

Methods and Materials

Completion of the QA program was mandatory for each participating center (N = 8) to start patient inclusion. The pretrial QA program included (1) a questionnaire on the center-specific sEBRT protocol, (2) a delineation exercise of the clinical target volume (CTV) and organs at risk, and (3) a treatment planning exercise. All contours were analyzed using the pairwise dice similarity coefficient (DSC) and the 50th and 95th percentile Hausdorff distance (HD50 and HD95, respectively). The submitted treatment plans were reviewed for protocol compliance.

Results

The results of the questionnaire showed that high-quality, state-of-the-art radiation therapy techniques were used in the participating centers and identified variations of the sEBRT protocols used concerning the position verification and preparation techniques. The submitted CTVs showed significant variation, with a range in volume of 29 cm3 to 167 cm3, a mean pairwise DSC of 0.52, and a mean HD50 and HD95 of 2.3 mm and 24.4 mm, respectively. Only in 1 center the treatment plan required adaptation before meeting all constraints of the PERYTON protocol.

Conclusions

The pretrial QA of the PERYTON trial demonstrated that high-quality, but variable, radiation techniques were used in the 8 participating centers. The treatment planning exercise confirmed that the dose constraints of the PERYTON protocol were feasible for all participating centers. The observed variation in CTV delineation led to agreement on a new (image-based) delineation guideline to be used by all participating centers within the PERYTON trial.

Implementation of Machine Learning Models to Ensure Radiotherapy Quality for Multicenter Clinical Trials: Report from a Phase III Lung Cancer Study

The outcome of the patient and the success of clinical trials involving RT is dependent on the quality assurance of the RT plans. Knowledge-based Planning (KBP) models using data from a library of high-quality plans have been utilized in radiotherapy to guide treatment. In this study, we report on the use of these machine learning tools to guide the quality assurance of multicenter clinical trial plans. The data from 130 patients submitted to RTOG1308 were included in this study. Fifty patient cases were used to train separate photon and proton models on a commercially available platform based on principal component analysis. Models evaluated 80 patient cases. Statistical comparisons were made between the KBP plans and the original plans submitted for quality evaluation. Both photon and proton KBP plans demonstrate a statistically significant improvement of quality in terms of organ-at-risk (OAR) sparing. Proton KBP plans, a relatively emerging technique, show more improvements compared with photon plans. The KBP proton model is a useful tool for creating proton plans that adhere to protocol requirements. The KBP tool was also shown to be a useful tool for evaluating the quality of RT plans in the multicenter clinical trial setting.

Development of binational radiation therapy quality indicator reports for prostate cancer treatment using registry data

INTRODUCTION

Quality indicators (QIs) are metrics which seek to allow comparison of clinicians' and institutes' practice to best evidence-based practice. The Australia and New Zealand Prostate Cancer Outcomes Registry (PCOR-ANZ) is a bi-national clinical quality registry with coverage estimated to be over 60% of the men newly diagnosed with prostate cancer. We outline the production and ambition of institute-level QI reports to benchmark performance for radiation therapy in the treatment of prostate cancer.

METHODS

An expert clinician panel was assembled to create a list of candidate QIs based on a comprehensive literature review, and on modified Delphi-method and expert-consensus voting. A separate implementation group-including, clinicians, epidemiologists, data managers and data scientists-employed an evidence- and consensus- based approach to generate an effective QI report designed for automated production and regular distribution to participating institutes. Feedback from the recipient clinicians was sought to enable refinement of these reports.

RESULTS

Seven QIs, including three related to post-treatment symptoms, were deemed feasible to analyse with the currently available data. Utilising an existing report template employed for benchmarking of surgical indicators, a novel radiation therapy report was generated using registry data in a secure analytical environment. The first, beta version of these reports have been produced and confidentially distributed. It is planned to automatically generate these reports biannually and iteratively refine them based on the clinician input.

CONCLUSION

QI reports for the treatment of prostate cancer by radiation oncologists have been produced using data from Australia and New Zealand patients. These are being disseminated to institutes on a six-monthly basis allowing comparisons to de-identified peers. The reports aim to facilitate improving patient outcomes, deepen engagement with the radiation oncology community and increase the breadth of PCOR-ANZ coverage. Additional QIs will be included in future iterations of these reports as data matures.

Automatic radiotherapy delineation quality assurance on prostate MRI with deep learning in a multicentre clinical trial

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

Impact of deviations in target volume delineation - Time for a new RTQA approach?

The international radiotherapy community has recognised that non-adherence to RT protocols can influence trial endpoints. However this conclusion is based on studies predominantly assessing the impact of deviations in dosimetric or treatment delivery protocol parameters rather than target volume delineation (TVD). This review evaluates the assessment of TVD within Radiation Therapy Quality Assurance (RTQA) programmes in clinical trials and the clinical impact of TVD protocol deviations. The implications for RTQA programmes are discussed. MEDLINE, PreMEDLINE, Embase, Cochrane Library, Web of Science, OpenGrey, WHO International Clinical Trials Registry Platform portal and ClinicalTrials.gov were searched. Full-length articles and conference abstracts were included to avoid publication bias. 5864 abstracts were screened for relevance; 94 full-length articles were reviewed and 5 relevant trials identified. Various classification systems were used to assess protocol deviations; 'unacceptable' or 'major' deviations in TVD occurred in 2.9-13.4% of assessed RT plans (when reported). It was often not possible to establish deviation rates specifically related to TVD as these were frequently combined with other types of protocol deviations. Details on the nature of unacceptable deviations was also not routinely reported and difficulties in establishing a 'consensus' for appropriate TVD for on-trial patients highlighted. Results suggest that deviations in TVD were associated with poorer outcomes for overall survival, local control and treatment-related toxicity; however the data were heterogeneous. RTQA of TVD was retrospective and feedback on the quality of TVD to recruiting centres was not standard. In summary, few trials have published outcomes on the impact of assessing the quality of TVD in trials. We propose that a new approach is now required. Unacceptable TVD deviations must be clearly defined at the time of protocol development to minimise interobserver variation, thereby promoting consistency in RTQA feedback. Prospective TVD reviews should be implemented for trials involving novel or complex RT techniques to identify deviations that require modification prior to treatment delivery. Furthermore, the consistent reporting of RTQA programme outcomes, both within and across trial groups, is of paramount importance to accelerate the evidence-base for the best RTQA approach when assessing TVD and to enable the impact on clinical outcomes within RT trials to be assessed.