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The Brain Tumor Segmentation in Pediatrics (BraTS-PEDs) Challenge: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)

Anahita Fathi Kazerooni, Nastaran Khalili, Xinyang Liu, Deep Gandhi, Zhifan Jiang, Syed Muhammed Anwar, Jake Albrecht, Maruf Adewole, Udunna Anazodo, Hannah Anderson, Ujjwal Baid, Timothy Bergquist, Austin J. Borja, Evan Calabrese, Verena Chung, Gian-Marco Conte, Farouk Dako, James Eddy, Ivan Ezhov, Ariana Familiar, Keyvan Farahani, Andrea Franson, Anurag Gottipati, Shuvanjan Haldar, Juan Eugenio Iglesias, Anastasia Janas, Elaine Johansen, Blaise V Jones, Neda Khalili, Florian Kofler, Dominic LaBella, Hollie Anne Lai, Koen Van Leemput, Hongwei Bran Li, Nazanin Maleki, Aaron S McAllister, Zeke Meier, Bjoern Menze, Ahmed W Moawad, Khanak K Nandolia, Julija Pavaine, Marie Piraud, Tina Poussaint, Sanjay P Prabhu, Zachary Reitman, Jeffrey D Rudie, Mariana Sanchez-Montano, Ibraheem Salman Shaikh, Nakul Sheth, Wenxin Tu, Chunhao Wang, Jeffrey B Ware, Benedikt Wiestler, Anna Zapaishchykova, Miriam Bornhorst, Michelle Deutsch, Maryam Fouladi, Margot Lazow, Leonie Mikael, Trent Hummel, Benjamin Kann, Peter de Blank, Lindsey Hoffman, Mariam Aboian, Ali Nabavizadeh, Roger Packer, Spyridon Bakas, Adam Resnick, Brian Rood, Arastoo Vossough, Marius George Linguraru

TL;DR

The BraTS-PEDs paper addresses the critical need for standardized pediatric brain tumor segmentation benchmarks by establishing a retrospective, multi-institution mpMRI dataset and a containerized evaluation framework. It outlines data provenance, preprocessing, and a four-subregion labeling schema (ET, NET, CC, ED) aligned with RAPNO guidance, coupled with a rigorous evaluation protocol across training, validation, and testing phases. The work enables fair cross-institution comparisons and reproducible performance assessments, leveraging platforms like CaPTk, FeTS, and Synapse/MedPerf within MICCAI 2024. By expanding data sources and refining processing pipelines, BraTS-PEDs aims to accelerate development of automated segmentation tools to support pediatric clinical trials and treatment planning, ultimately improving care for children with brain tumors.

Abstract

Pediatric tumors of the central nervous system are the most common cause of cancer-related death in children. The five-year survival rate for high-grade gliomas in children is less than 20%. Due to their rarity, the diagnosis of these entities is often delayed, their treatment is mainly based on historic treatment concepts, and clinical trials require multi-institutional collaborations. Here we present the CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs challenge, focused on pediatric brain tumors with data acquired across multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. The CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs challenge brings together clinicians and AI/imaging scientists to lead to faster development of automated segmentation techniques that could benefit clinical trials, and ultimately the care of children with brain tumors.

The Brain Tumor Segmentation in Pediatrics (BraTS-PEDs) Challenge: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs)

TL;DR

The BraTS-PEDs paper addresses the critical need for standardized pediatric brain tumor segmentation benchmarks by establishing a retrospective, multi-institution mpMRI dataset and a containerized evaluation framework. It outlines data provenance, preprocessing, and a four-subregion labeling schema (ET, NET, CC, ED) aligned with RAPNO guidance, coupled with a rigorous evaluation protocol across training, validation, and testing phases. The work enables fair cross-institution comparisons and reproducible performance assessments, leveraging platforms like CaPTk, FeTS, and Synapse/MedPerf within MICCAI 2024. By expanding data sources and refining processing pipelines, BraTS-PEDs aims to accelerate development of automated segmentation tools to support pediatric clinical trials and treatment planning, ultimately improving care for children with brain tumors.

Abstract

Pediatric tumors of the central nervous system are the most common cause of cancer-related death in children. The five-year survival rate for high-grade gliomas in children is less than 20%. Due to their rarity, the diagnosis of these entities is often delayed, their treatment is mainly based on historic treatment concepts, and clinical trials require multi-institutional collaborations. Here we present the CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs challenge, focused on pediatric brain tumors with data acquired across multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. The CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs challenge brings together clinicians and AI/imaging scientists to lead to faster development of automated segmentation techniques that could benefit clinical trials, and ultimately the care of children with brain tumors.
Paper Structure (8 sections, 1 figure)

This paper contains 8 sections, 1 figure.

Table of Contents

  1. Introduction
  2. Challenge Design
  3. Data
  4. Imaging Data Description
  5. Common errors of automated segmentations
  6. Performance Evaluation
  7. Participation Timeline
  8. Discussion

Figures (1)

  • Figure 1: Graphical representation of data processing and annotations in pediatric brain tumors. Top panel presents the processing pipeline, and the bottom panel illustrates the annotated tumor subregions along with mpMRI structural scans (T1, T1CE, T2, and T2-FLAIR). Tumor subregions include the enhancing tumor (ET - red), non-enhancing tumor (NET - green), cystic component (CC - yellow), and edema (ED - teal) regions.