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The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs).
Kazerooni, Anahita Fathi; Khalili, Nastaran; Liu, Xinyang; Haldar, Debanjan; Jiang, Zhifan; Anwar, Syed Muhammed; Albrecht, Jake; Adewole, Maruf; Anazodo, Udunna; Anderson, Hannah; Bagheri, Sina; Baid, Ujjwal; Bergquist, Timothy; Borja, Austin J; Calabrese, Evan; Chung, Verena; Conte, Gian-Marco; Dako, Farouk; Eddy, James; Ezhov, Ivan; Familiar, Ariana; Farahani, Keyvan; Haldar, Shuvanjan; Iglesias, Juan Eugenio; Janas, Anastasia; Johansen, Elaine; Jones, Blaise V; Kofler, Florian; LaBella, Dominic; Lai, Hollie Anne; Van Leemput, Koen; Li, Hongwei Bran; Maleki, Nazanin; McAllister, Aaron S; Meier, Zeke; Menze, Bjoern; Moawad, Ahmed W; Nandolia, Khanak K; Pavaine, Julija; Piraud, Marie; Poussaint, Tina; Prabhu, Sanjay P; Reitman, Zachary; Rodriguez, Andres; Rudie, Jeffrey D; Sanchez-Montano, Mariana; Shaikh, Ibraheem Salman; Shah, Lubdha M; Sheth, Nakul; Shinohara, Russel Taki.
Affiliation
  • Kazerooni AF; Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, PA, USA.
  • Khalili N; Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, USA.
  • Liu X; Center for AI & Data Science for Integrated Diagnostics (AI2D) and Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.
  • Haldar D; Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, PA, USA.
  • Jiang Z; Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington DC, USA.
  • Anwar SM; Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, PA, USA.
  • Albrecht J; Department of Neurosurgery, Thomas Jefferson University Hospital, PA, USA.
  • Adewole M; Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington DC, USA.
  • Anazodo U; Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington DC, USA.
  • Anderson H; Sage Bionetworks, USA.
  • Bagheri S; Medical Artificial Intelligence (MAI) Lab, Crestview Radiology, Lagos, Nigeria.
  • Baid U; Montreal Neurological Institute (MNI), McGill University, Montreal, QC, Canada.
  • Bergquist T; Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, PA, USA.
  • Borja AJ; Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, PA, USA.
  • Calabrese E; Center for AI & Data Science for Integrated Diagnostics (AI2D) and Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.
  • Chung V; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Conte GM; Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Dako F; Sage Bionetworks, USA.
  • Eddy J; Department of Neurosurgery at the University of Southern California, CA, USA.
  • Ezhov I; Department of Radiology, Duke University Medical Center, USA.
  • Familiar A; Sage Bionetworks, USA.
  • Farahani K; Mayo Clinic, MN, USA.
  • Haldar S; Center for Global Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Iglesias JE; Sage Bionetworks, USA.
  • Janas A; Department of Informatics, Technical University Munich, Germany.
  • Johansen E; TranslaTUM - Central Institute for Translational Cancer Research, Technical University of Munich, Germany.
  • Jones BV; Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, PA, USA.
  • Kofler F; Cancer Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
  • LaBella D; Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, PA, USA.
  • Lai HA; Biomedical Engineering Rutgers University, New Brunswick, NJ, USA.
  • Van Leemput K; Athinoula A Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA.
  • Li HB; Yale University, New Haven, CT, USA.
  • Maleki N; PrecisionFDA, U.S. Food and Drug Administration, Silver Spring, MD, USA.
  • McAllister AS; Cincinnati Children's Hospital Medical Center.
  • Meier Z; Helmholtz AI, Helmholtz Munich, Germany.
  • Menze B; Department of Radiation Oncology, Duke University Medical Center, USA.
  • Moawad AW; Department of Radiology, Children's Health Orange County, CA, USA.
  • Nandolia KK; Department of Applied Mathematics and Computer Science, Technical University of Denmark, Denmark.
  • Pavaine J; Athinoula A Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA.
  • Piraud M; Yale University, New Haven, CT, USA.
  • Poussaint T; Department of Radiology, Nationwide Children's Hospital, OH.
  • Prabhu SP; Booz Allen Hamilton, McLean, VA, USA.
  • Reitman Z; Biomedical Image Analysis & Machine Learning, Department of Quantitative Biomedicine, University of Zurich, Switzerland.
  • Rodriguez A; Department of Neuroradiology, Technical University of Munich, Munich, Germany.
  • Rudie JD; Mercy Catholic Medical Center, Darby, PA, USA.
  • Sanchez-Montano M; Department of Diagnostic and Interventional Radiology, All India Institute of Medical Sciences, Rishikesh, India.
  • Shaikh IS; Department of Paediatric Radiology, Royal Manchester Children's Hospital, Manchester University Hospitals NHS Foundation Trust, University of Manchester, Manchester, UK.
  • Shah LM; Division of Informatics, Imaging & Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
  • Sheth N; Helmholtz AI, Helmholtz Munich, Germany.
  • Shinohara RT; Dana-Farber Brigham Cancer Center & Boston Children's Hospital, Boston, MA, USA.
ArXiv ; 2024 Mar 08.
Article in En | MEDLINE | ID: mdl-37292481
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. The MICCAI Brain Tumor Segmentation (BraTS) Challenge is a landmark community benchmark event with a successful history of 12 years of resource creation for the segmentation and analysis of adult glioma. Here we present the CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs 2023 challenge, which represents the first BraTS challenge focused on pediatric brain tumors with data acquired across multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. The BraTS-PEDs 2023 challenge focuses on benchmarking the development of volumentric segmentation algorithms for pediatric brain glioma through standardized quantitative performance evaluation metrics utilized across the BraTS 2023 cluster of challenges. Models gaining knowledge from the BraTS-PEDs multi-parametric structural MRI (mpMRI) training data will be evaluated on separate validation and unseen test mpMRI dataof high-grade pediatric glioma. The CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs 2023 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.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: ArXiv Year: 2024 Document type: Article Affiliation country: United States
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: ArXiv Year: 2024 Document type: Article Affiliation country: United States