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Adewole M, Rudie JD, Gbdamosi A, Toyobo O, Raymond C, Zhang D, Omidiji O, Akinola R, Suwaid MA, Emegoakor A, Ojo N, Aguh K, Kalaiwo C, Babatunde G, Ogunleye A, Gbadamosi Y, Iorpagher K, Calabrese E, Aboian M, Linguraru M, Albrecht J, Wiestler B, Kofler F, Janas A, LaBella D, Kzerooni AF, Li HB, Iglesias JE, Farahani K, Eddy J, Bergquist T, Chung V, Shinohara RT, Wiggins W, Reitman Z, Wang C, Liu X, Jiang Z, Familiar A, Van Leemput K, Bukas C, Piraud M, Conte GM, Johansson E, Meier Z, Menze BH, Baid U, Bakas S, Dako F, Fatade A, Anazodo UC. The Brain Tumor Segmentation (BraTS) Challenge 2023: Glioma Segmentation in Sub-Saharan Africa Patient Population (BraTS-Africa). ArXiv 2023:arXiv:2305.19369v1. [PMID: 37396608 PMCID: PMC10312814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
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.
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Affiliation(s)
- Maruf Adewole
- Medical Artificial Intelligence Laboratory (MAI Lab), Lagos, Nigeria
- Department of Radiation Biology, Radiotherapy and Radiodiagnosis, University of Lagos, Lagos, Nigeria
| | - Jeffrey D Rudie
- Department of Radiology, University of California, San Diego
| | - Anu Gbdamosi
- Medical Artificial Intelligence Laboratory (MAI Lab), Lagos, Nigeria
- Crestview Radiology Limited, Lagos, Nigeria
| | - Oluyemisi Toyobo
- Medical Artificial Intelligence Laboratory (MAI Lab), Lagos, Nigeria
- Crestview Radiology Limited, Lagos, Nigeria
| | | | - Dong Zhang
- Medical Artificial Intelligence Laboratory (MAI Lab), Lagos, Nigeria
| | - Olubukola Omidiji
- Medical Artificial Intelligence Laboratory (MAI Lab), Lagos, Nigeria
- Lagos University Teaching Hospital, Lagos, Nigeria
| | - Rachel Akinola
- Lagos State University Teaching Hospital, Ikeja, Lagos, Nigeria
| | | | - Adaobi Emegoakor
- Nnamdi Azikiwe University Teaching Hospital, Nnewi, Anambra State, Nigeria
| | - Nancy Ojo
- Federal Medical Centre, Abeokuta, Ogun State, Nigeria
| | - Kenneth Aguh
- Federal Medical Centre, Umahia, Abia State, Nigeria
| | | | | | | | | | - Kator Iorpagher
- Benue State University Teaching Hospital, Markurdi, Benue State, Nigeria
| | - Evan Calabrese
- Duke University Medical Center, Department of Radiology, USA
- University of California San Francisco, CA, USA
| | | | - Marius Linguraru
- Children's National Hospital, Washington DC, USA
- George Washington University, Washington DC, USA
| | | | - Benedikt Wiestler
- Department of Neuroradiology, Technical University of Munich, Munich, Germany
| | - Florian Kofler
- Department of Neuroradiology, Technical University of Munich, Munich, Germany
- Helmholtz Research Center, Munich, Germany
| | | | - Dominic LaBella
- Duke University Medical Center, Department of Radiation Oncology, USA
| | - Anahita Fathi Kzerooni
- 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
| | - Hongwei Bran Li
- 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
| | - Juan Eugenio Iglesias
- Athinoula A Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Keyvan Farahani
- Cancer Imaging Program, National Cancer Institute, National Institutes of Health, Bethesda, MD 20814, USA
| | | | | | | | - Russell Takeshi Shinohara
- 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
| | - Walter Wiggins
- Duke University Medical Center, Department of Radiology, USA
| | - Zachary Reitman
- Duke University Medical Center, Department of Radiation Oncology, USA
| | - Chunhao Wang
- Duke University Medical Center, Department of Radiation Oncology, USA
| | - Xinyang Liu
- Children's National Hospital, Washington DC, USA
- George Washington University, Washington DC, USA
| | - Zhifan Jiang
- Children's National Hospital, Washington DC, USA
- George Washington University, Washington DC, USA
| | - Ariana Familiar
- Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, USA
| | - Koen Van Leemput
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Denmark
| | | | | | | | - Elaine Johansson
- Precision FDA, U.S. Food and Drug Administration, Silver Spring, MD, USA
| | | | - Bjoern H Menze
- Department of Neuroradiology, Technical University of Munich, Munich, Germany
- University of Zurich, Switzerland
| | - Ujjwal Baid
- 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
| | - Spyridon Bakas
- 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
| | - Farouk Dako
- Center for Global Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Abiodun Fatade
- Medical Artificial Intelligence Laboratory (MAI Lab), Lagos, Nigeria
- Crestview Radiology Limited, Lagos, Nigeria
| | - Udunna C Anazodo
- 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
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Ebisike PI, Habib SG, Hassan S, Suwaid MA, Hikima MS, Saleh MK, Jibo U, Yusuf L. Transorbital sonographic measurement of optic nerve sheath diameter among HIV-Positive patients in Northwestern Nigeria. Niger J Clin Pract 2020; 22:1570-1575. [PMID: 31719279 DOI: 10.4103/njcp.njcp_622_18] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Background Human immunodeficiency virus (HIV) is a pandemic disease affecting all regions across the globe and Nigeria having the second highest prevalence worldwide. Highly active antiretroviral therapy (HAART) has profound negative effect on the optic nerve even though (HAART) has improved the health status of the affected individuals and overall reduction in mortality. Imaging modality especially ultrasound has a great role in the assessment of the optic nerve because of its availability, affordability, and easy operability with reliable sensitivity. Subjects and Methods This cross-sectional study was conducted at the Department of Radiology and Ophthalmology, AKTH, Kano, from October 2017 to June 2018. A total of 143 consenting HIV-positive adults age 18-60 years on HAART were recruited. Optic nerve sheath diameter (ONSD) of each eye was measured using 11-14 MHz linear transducer. Ethical approval was obtained from the ethic and research committee of the hospital. Results The mean ONSD value of the right eye was 3.49 mm ± 1.04 standard deviation (SD) and 3.55 mm ± 1.11 SD for the left eye. The optic nerve diameter was found to be larger on the left eye and increased slightly with age (P < 0.05). There was nonsignificantly higher values of ONSD among female (3.59 mm ± 1.12 SD) when compared with males (3.332 mm ± 0.878) with P value >0.005. Conclusion ONSD values among HIV-positive patients are significantly higher in the left eye and among female subjects. Also, patients with HIV on HAART have thicker optic nerves when compared with general population in Kano, Nigeria.
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Affiliation(s)
- P I Ebisike
- Department of Ophthalmology, Bayero University/Aminu Kano Teaching Hospital, Kano, Nigeria
| | - S G Habib
- Department of Ophthalmology, Bayero University/Aminu Kano Teaching Hospital, Kano, Nigeria
| | - S Hassan
- Department of Ophthalmology, Bayero University/Aminu Kano Teaching Hospital, Kano, Nigeria
| | - M A Suwaid
- Department of Radiology, Bayero University/Aminu Kano Teaching Hospital, Kano, Nigeria
| | - M S Hikima
- Department of Radiology, Bayero University/Aminu Kano Teaching Hospital, Kano, Nigeria
| | - M K Saleh
- Department of Radiology, Bayero University/Aminu Kano Teaching Hospital, Kano, Nigeria
| | - U Jibo
- Department of Radiology, Bayero University/Aminu Kano Teaching Hospital, Kano, Nigeria
| | - L Yusuf
- Department of Radiology, Bayero University/Aminu Kano Teaching Hospital, Kano, Nigeria
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