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Radiomics features of hippocampal regions in magnetic resonance imaging can differentiate medial temporal lobe epilepsy patients from healthy controls

Authors
 Yae Won Park  ;  Yun Seo Choi  ;  Song E Kim  ;  Dongmin Choi  ;  Kyunghwa Han  ;  Hwiyoung Kim  ;  Sung Soo Ahn  ;  Sol-Ah Kim  ;  Hyeon Jin Kim  ;  Seung-Koo Lee  ;  Hyang Woon Lee 
Citation
 SCIENTIFIC REPORTS, Vol.10(1) : 19567, 2020-12 
Journal Title
SCIENTIFIC REPORTS
Issue Date
2020-12
MeSH
Adult ; Case-Control Studies ; Diagnosis, Computer-Assisted / methods ; Epilepsy, Temporal Lobe / diagnostic imaging* ; Epilepsy, Temporal Lobe / etiology ; Epilepsy, Temporal Lobe / psychology ; Female ; Hippocampus / diagnostic imaging* ; Humans ; Image Processing, Computer-Assisted / methods* ; Magnetic Resonance Imaging / methods* ; Male ; Middle Aged ; Neuropsychological Tests
Abstract
To investigative whether radiomics features in bilateral hippocampi from MRI can identify temporal lobe epilepsy (TLE). A total of 131 subjects with MRI (66 TLE patients [35 right and 31 left TLE] and 65 healthy controls [HC]) were allocated to training (n = 90) and test (n = 41) sets. Radiomics features (n = 186) from the bilateral hippocampi were extracted from T1-weighted images. After feature selection, machine learning models were trained. The performance of the classifier was validated in the test set to differentiate TLE from HC and ipsilateral TLE from HC. Identical processes were performed to differentiate right TLE from HC (training set, n = 69; test set; n = 31) and left TLE from HC (training set, n = 66; test set, n = 30). The best-performing model for identifying TLE showed an AUC, accuracy, sensitivity, and specificity of 0.848, 84.8%, 76.2%, and 75.0% in the test set, respectively. The best-performing radiomics models for identifying right TLE and left TLE subgroups showed AUCs of 0.845 and 0.840 in the test set, respectively. In addition, multiple radiomics features significantly correlated with neuropsychological test scores (false discovery rate-corrected p-values < 0.05). The radiomics model from hippocampus can be a potential biomarker for identifying TLE.
Files in This Item:
T202006392.pdf Download
DOI
10.1038/s41598-020-76283-z
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
Yonsei Authors
Kim, Hwiyoung(김휘영)
Park, Yae Won(박예원) ORCID logo https://orcid.org/0000-0001-8907-5401
Ahn, Sung Soo(안성수) ORCID logo https://orcid.org/0000-0002-0503-5558
Lee, Seung Koo(이승구) ORCID logo https://orcid.org/0000-0001-5646-4072
Han, Kyung Hwa(한경화)
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/182637
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