TY - JOUR
T1 - Neuroimaging Phenotyping and Assessment of Structural-Metabolic-Electrophysiological Alterations in the Temporal Neocortex of Focal Cortical Dysplasia IIIa
AU - Mo, Jiajie
AU - Wei, Wei
AU - Liu, Zhenyu
AU - Zhang, Jianguo
AU - Ma, Yanshan
AU - Sang, Lin
AU - Hu, Wenhan
AU - Zhang, Chao
AU - Wang, Yao
AU - Wang, Xiu
AU - Liu, Chang
AU - Zhao, Baotian
AU - Gao, Dongmei
AU - Tian, Jie
AU - Zhang, Kai
N1 - Publisher Copyright:
© 2021 International Society for Magnetic Resonance in Medicine
PY - 2021/9
Y1 - 2021/9
N2 - Background: Focal cortical dysplasia IIIa (FCD IIIa) is a common histopathological finding in temporal lobe epilepsy. However, subtle alterations in the temporal neocortex of FCD IIIa renders presurgical diagnosis and definition of the resective range challenging. Purpose: To explore neuroimaging phenotyping and structural-metabolic-electrophysiological alterations in FCD IIIa. Study Type: Retrospective. Subjects: One hundred and sixty-seven subjects aged 4–39 years, including 64 FCD IIIa patients, 89 healthy controls and 14 FCD I patients as disease controls. Field Strength/Sequence: 3 T, fast-spin-echo T2-weighted fluid-attenuated inversion recovery (FLAIR), synthetic T1-weighted magnetization prepared rapid acquisition gradient echo (MPRAGE). Assessment: Surface-based linear model was applied to reveal neuroimaging phenotyping in FCD IIIa and assess its relationship with clinical variables. Logistic regression was implemented to identify FCD IIIa patients. Epileptogenicity mapping (EM) was conducted to explore the structural-metabolic-electrophysiological alterations in temporal neocortex of FCD IIIa. Statistical Tests: Student's t-test was applied to determine the significance of paired differences. Calibration curves were plotted to assess the goodness-of-fit (GOF) of the models, combined with the Hosmer-Lemeshow test. Results: FCD IIIa exhibited widespread hyperintensities in temporal neocortex, and these alterations correlated with disease duration (Puncorrected < 0.01). Machine learning model accurately identified 84.4% of FCD IIIa patients, 92.1% of healthy controls and 92.9% of FCD I patients. Cross-modality analysis showed a significant negative correlation between FLAIR hyperintensity and positron emission tomography hypometabolism P < 0.01). Furthermore, epileptogenic cortices were located predominantly in brain regions with FLAIR hyperintensity and hypometabolism. Data Conclusion: FCD IIIa exhibited widespread temporal neocortex FLAIR hyperintensity. Automated machine learning of neuroimaging patterns is conducive for accurate identification of FCD IIIa. The degree and distribution of morphological alterations related to the extent of metabolic and epileptogenic abnormalities, lending support to its potential value for reduction of the radiative and invasive approaches during presurgical workup. Level of Evidence: 3. Technical Efficacy Stage: 2.
AB - Background: Focal cortical dysplasia IIIa (FCD IIIa) is a common histopathological finding in temporal lobe epilepsy. However, subtle alterations in the temporal neocortex of FCD IIIa renders presurgical diagnosis and definition of the resective range challenging. Purpose: To explore neuroimaging phenotyping and structural-metabolic-electrophysiological alterations in FCD IIIa. Study Type: Retrospective. Subjects: One hundred and sixty-seven subjects aged 4–39 years, including 64 FCD IIIa patients, 89 healthy controls and 14 FCD I patients as disease controls. Field Strength/Sequence: 3 T, fast-spin-echo T2-weighted fluid-attenuated inversion recovery (FLAIR), synthetic T1-weighted magnetization prepared rapid acquisition gradient echo (MPRAGE). Assessment: Surface-based linear model was applied to reveal neuroimaging phenotyping in FCD IIIa and assess its relationship with clinical variables. Logistic regression was implemented to identify FCD IIIa patients. Epileptogenicity mapping (EM) was conducted to explore the structural-metabolic-electrophysiological alterations in temporal neocortex of FCD IIIa. Statistical Tests: Student's t-test was applied to determine the significance of paired differences. Calibration curves were plotted to assess the goodness-of-fit (GOF) of the models, combined with the Hosmer-Lemeshow test. Results: FCD IIIa exhibited widespread hyperintensities in temporal neocortex, and these alterations correlated with disease duration (Puncorrected < 0.01). Machine learning model accurately identified 84.4% of FCD IIIa patients, 92.1% of healthy controls and 92.9% of FCD I patients. Cross-modality analysis showed a significant negative correlation between FLAIR hyperintensity and positron emission tomography hypometabolism P < 0.01). Furthermore, epileptogenic cortices were located predominantly in brain regions with FLAIR hyperintensity and hypometabolism. Data Conclusion: FCD IIIa exhibited widespread temporal neocortex FLAIR hyperintensity. Automated machine learning of neuroimaging patterns is conducive for accurate identification of FCD IIIa. The degree and distribution of morphological alterations related to the extent of metabolic and epileptogenic abnormalities, lending support to its potential value for reduction of the radiative and invasive approaches during presurgical workup. Level of Evidence: 3. Technical Efficacy Stage: 2.
KW - cross-modalities correlation
KW - focal cortical dysplasia
KW - neuroimaging phenotyping
KW - temporal neocortex
UR - https://www.scopus.com/pages/publications/85104780779
U2 - 10.1002/jmri.27615
DO - 10.1002/jmri.27615
M3 - 文章
C2 - 33891371
AN - SCOPUS:85104780779
SN - 1053-1807
VL - 54
SP - 925
EP - 935
JO - Journal of Magnetic Resonance Imaging
JF - Journal of Magnetic Resonance Imaging
IS - 3
ER -