Yonsei University College of Medicine
Seoul, Republic of Korea
Sung Soo Ahn, M.D., Ph.D.
Associate Professor, Department of Radiology, Yonsei University, College of Medicine
Education
09/2010-02/2014 Graduate School of Yonsei University College of Medicine,
Doctor’s Degree, 02/2014
09/2007-08/2009 Graduate School of Yonsei University College of Medicine,
Master’s Degree, 08/2009
03/2000-02/2004 Yonsei University College of Medicine,
Doctor of Medicine, 02/2004
03/1998-02/2000 Yonsei University College of Natural Science,
Bachelor of Preliminary Medicine, 02/2000
Appointments
03/2021-current Associate Professor, Neuroradiology
Yonsei University Medical Center, Seoul, Korea
03/2015-02/2021 Assistant Professor, Neuroradiology
Yonsei University Medical Center
03/2019-02/2020 Visiting Scholar
University California San Francisco, California, USA
03/2012-02/2015 Clinical Assistant Professor, Neuroradiology
Yonsei University Medical Center
Recent Publications
[1] Park YW, Vollmuth P, Foltyn-Dumitru M, Sahm F, Ahn SS*, et al. The 2021 WHO Classification for Gliomas and Implications on Imaging Diagnosis: Part 2-Summary of Imaging Findings on Pediatric-Type Diffuse High-Grade Gliomas, Pediatric-Type Diffuse Low-Grade Gliomas, and Circumscribed Astrocytic Gliomas. J Magn Reson Imaging. 2023 Sep;58(3):690-708.
[2] Park YW, Vollmuth P, Foltyn-Dumitru M, Sahm F, Ahn SS*, et al. The 2021 WHO Classification for Gliomas and Implications on Imaging Diagnosis: Part 1-Key Points of the Fifth Edition and Summary of Imaging Findings on Adult-Type Diffuse Gliomas. J Magn Reson Imaging. 2023 Sep;58(3):677-689.
[3] Park YW, Kim S, Park CJ, Ahn SS*, et al. Adding radiomics to the 2021 WHO updates may improve prognostic prediction for current IDH-wildtype histological lower-grade gliomas with known EGFR amplification and TERT promoter mutation status. Eur Radiol. 2022 Dec;32(12):8089-8098
[4] Park YW, Han K, Park JE, Ahn SS*, et al. Leptomeningeal metastases in glioma revisited: incidence and molecular predictors based on postcontrast fluid-attenuated inversion recovery imaging. J Neurosurg. 2022 Nov 4;1-11.
[5] Joo B, Ahn SS*, et al. Fully automated radiomics-based machine learning models for multiclass classification of single brain tumors: Glioblastoma, lymphoma, and metastasis. J Neuroradiol. 2022 Nov 9;S0150-9861