The Brain Tumor Segmentation (BraTS) Challenge 2023: Glioma Segmentation in Sub-Saharan Africa Patient Population (BraTS-Africa) .

Autor:	Adewole M; Medical Artificial Intelligence Laboratory (MAI Lab), Lagos, Nigeria.; Department of Radiation Biology, Radiotherapy and Radiodiagnosis, University of Lagos, Lagos, Nigeria., Rudie JD; Department of Radiology, University of California, San Diego., Gbdamosi A; Medical Artificial Intelligence Laboratory (MAI Lab), Lagos, Nigeria.; Crestview Radiology Limited, Lagos, Nigeria., Toyobo O; Medical Artificial Intelligence Laboratory (MAI Lab), Lagos, Nigeria.; Crestview Radiology Limited, Lagos, Nigeria., Raymond C; Medical Artificial Intelligence Laboratory (MAI Lab), Lagos, Nigeria., Zhang D; Medical Artificial Intelligence Laboratory (MAI Lab), Lagos, Nigeria., Omidiji O; Medical Artificial Intelligence Laboratory (MAI Lab), Lagos, Nigeria.; Lagos University Teaching Hospital, Lagos, Nigeria., Akinola R; Lagos State University Teaching Hospital, Ikeja, Lagos, Nigeria., Suwaid MA; NSIA-Kano Diagnostic Center, Kano Nigeria., Emegoakor A; Nnamdi Azikiwe University Teaching Hospital, Nnewi, Anambra State, Nigeria., Ojo N; Federal Medical Centre, Abeokuta, Ogun State, Nigeria., Aguh K; Federal Medical Centre, Umahia, Abia State, Nigeria., Kalaiwo C; National Hospital Abuja, FCT, Nigeria., Babatunde G; Lagos University Teaching Hospital, Lagos, Nigeria., Ogunleye A; Lagos State University Teaching Hospital, Ikeja, Lagos, Nigeria., Gbadamosi Y; Lagos State University Teaching Hospital, Ikeja, Lagos, Nigeria., Iorpagher K; Benue State University Teaching Hospital, Markurdi, Benue State, Nigeria., Calabrese E; Duke University Medical Center, Department of Radiology, USA.; University of California San Francisco, CA, USA., Aboian M; Yale University, New Haven, CT, USA., Linguraru M; Children's National Hospital, Washington DC, USA.; George Washington University, Washington DC, USA., Albrecht J; Sage Bionetworks, USA., Wiestler B; Department of Neuroradiology, Technical University of Munich, Munich, Germany., Kofler F; Department of Neuroradiology, Technical University of Munich, Munich, Germany.; Helmholtz Research Center, Munich, Germany., Janas A; Yale University, New Haven, CT, USA., LaBella D; Duke University Medical Center, Department of Radiation Oncology, USA., Kzerooni AF; Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA.; Center for AI and Data Science for Integrated Diagnostics (AI2D) & Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA., Li HB; Department of Neuroradiology, Technical University of Munich, Munich, Germany.; Athinoula A Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA.; University of Zurich, Switzerland., Iglesias JE; Athinoula A Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA., Farahani K; Cancer Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD 20814, USA., Eddy J; Sage Bionetworks, USA., Bergquist T; Sage Bionetworks, USA., Chung V; Sage Bionetworks, USA., Shinohara RT; Center for AI and Data Science for Integrated Diagnostics (AI2D) & Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.; Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, USA., Wiggins W; Duke University Medical Center, Department of Radiology, USA., Reitman Z; Duke University Medical Center, Department of Radiation Oncology, USA., Wang C; Duke University Medical Center, Department of Radiation Oncology, USA., Liu X; Children's National Hospital, Washington DC, USA.; George Washington University, Washington DC, USA., Jiang Z; Children's National Hospital, Washington DC, USA.; George Washington University, Washington DC, USA., Familiar A; Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA., Van Leemput K; Department of Applied Mathematics and Computer Science, Technical University of Denmark, Denmark., Bukas C; Helmholtz Research Center, Munich, Germany., Piraud M; Helmholtz Research Center, Munich, Germany., Conte GM; Mayo Clinic, MN, USA., Johansson E; Precision FDA, U.S. Food and Drug Administration, Silver Spring, MD, USA., Meier Z; Booz Allen Hamilton, McLean, VA, USA., Menze BH; Department of Neuroradiology, Technical University of Munich, Munich, Germany.; University of Zurich, Switzerland., Baid U; Center for AI and Data Science for Integrated Diagnostics (AI2D) & Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.; Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA., Bakas S; Center for AI and Data Science for Integrated Diagnostics (AI2D) & Center for Biomedical Image Computing and Analytics (CBICA), University of Pennsylvania, Philadelphia, PA, USA.; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.; Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA., Dako F; Center for Global Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA., Fatade A; Medical Artificial Intelligence Laboratory (MAI Lab), Lagos, Nigeria.; Crestview Radiology Limited, Lagos, Nigeria., Anazodo UC; Medical Artificial Intelligence Laboratory (MAI Lab), Lagos, Nigeria.; Montreal Neurological Institute, McGill University, Montreal, Canada.; Department of Medicine, University of Cape Town, South Africa.; Department of Radiation Medicine, University of Cape Town, South Africa.
Jazyk:	angličtina
Zdroj:	ArXiv [ArXiv] 2023 May 30. Date of Electronic Publication: 2023 May 30.
Abstrakt:	Gliomas are the most common type of primary brain tumors. Although gliomas are relatively rare, they are among the deadliest types of cancer, with a survival rate of less than 2 years after diagnosis. Gliomas are challenging to diagnose, hard to treat and inherently resistant to conventional therapy. Years of extensive research to improve diagnosis and treatment of gliomas have decreased mortality rates across the Global North, while chances of survival among individuals in low- and middle-income countries (LMICs) remain unchanged and are significantly worse in Sub-Saharan Africa (SSA) populations. Long-term survival with glioma is associated with the identification of appropriate pathological features on brain MRI and confirmation by histopathology. Since 2012, the Brain Tumor Segmentation (BraTS) Challenge have evaluated state-of-the-art machine learning methods to detect, characterize, and classify gliomas. However, it is unclear if the state-of-the-art methods can be widely implemented in SSA given the extensive use of lower-quality MRI technology, which produces poor image contrast and resolution and more importantly, the propensity for late presentation of disease at advanced stages as well as the unique characteristics of gliomas in SSA (i.e., suspected higher rates of gliomatosis cerebri). Thus, the BraTS-Africa Challenge provides a unique opportunity to include brain MRI glioma cases from SSA in global efforts through the BraTS Challenge to develop and evaluate computer-aided-diagnostic (CAD) methods for the detection and characterization of glioma in resource-limited settings, where the potential for CAD tools to transform healthcare are more likely.
Databáze:	MEDLINE
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