Pediatric central nervous system tumors are the leading cause of cancer-related deaths in children. The five-year survival rate for high-grade glioma in children is less than 20%. The development of new treatments is dependent upon multi-institutional collaborative clinical trials requiring reproducible and accurate centralized response assessment. We present the results of the BraTS-PEDs 2023 challenge, the first Brain Tumor Segmentation (BraTS) challenge focused on pediatric brain tumors. This challenge utilized data acquired from multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. BraTS-PEDs 2023 aimed to evaluate volumetric segmentation algorithms for pediatric brain gliomas from magnetic resonance imaging using standardized quantitative performance evaluation metrics employed across the BraTS 2023 challenges. The top-performing AI approaches for pediatric tumor analysis included ensembles of nnU-Net and Swin UNETR, Auto3DSeg, or nnU-Net with a self-supervised framework. The BraTS-PEDs 2023 challenge fostered collaboration between clinicians (neuro-oncologists, neuroradiologists) and AI/imaging scientists, promoting faster data sharing and the development of automated volumetric analysis techniques. These advancements could significantly benefit clinical trials and improve the care of children with brain tumors.
LGG-52. Volumetry-based response characterization of recurrent pediatric low-grade gliomas in PNOC clinical Neuro-oncology trials
Abstract BACKGROUND: Endpoints in clinical trials using novel treatments are evaluated by RANO criteria, which provide an estimate of tumor size from two-dimensional measurements along the most prominent axial slice. However, pediatric low-grade gliomas (pLGG) commonly have variegated shapes with solid and cystic components, potentially resulting in misevaluation of true tumor volume and thus, ultimately, trial outcome. OBJECTIVES: We aim to characterize treatment response through volumetric assessment of progressive/recurrent pLGGs treated with single-agent everolimus on PNOC001 clinical trial. We seek to identify clinically relevant criteria that provide added value to response assessment beyond 2D measurements. METHODS: In a cohort of 44 patients we performed 3D-segmentation of solid, cystic and whole tumor within our PACS-framework and compared results to previously carried-out central imaging review by RANO criteria which had yielded 15 PD, 27 SD, 2 PR and 0 CR. RESULTS: 8 tumors were solid only and 36 had a mixed solid-cystic appearance. When evaluating the entire tumor (i.e. solid and cystic components combined) and using the same RANO cutoff criteria, one case changed from PR to SD, one changed from SD to PR, 3 changed from SD to PD, and 7 changed from PD to SD, resulting in an overall discordance of 27% of cases. CONCLUSION: We propose that incorporation of volumetrics into response assessment provides additional and potentially more accurate information beyond RANO-based measurements. It is crucial to note that the above-reported changes represent numerical discrepancies as opposed to true-to-reality changes in clinical outcome. Determining representative thresholds for the deployment of volumetric measures in clinical trials will be critical. Future work will include data from the PNOC002 clinical trial and evaluate inter-reader agreement and reader discordance. With the availability of PACS-based 3D-tools in neuroradiology practice, well-defined volumetric criteria could be incorporated prospectively into treatment response analysis in clinical trials.