Multimodal imaging-based diagnostic approach for MRI-negative posterior cortex epilepsy

Author:

Mo Jiajie1ORCID,Dong Wenyu12,Sang Lin3,Zheng Zhong3,Guo Qiang4,Zhou Xiuming4,Zhou Wenjing5,Wang Haixiang5,Meng Xianghong6,Yao Yi7,Wang Fengpeng7,Hu Wenhan8192,Zhang Kai10,Shao Xiaoqiu11

Affiliation:

1. Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China

2. China National Clinical Research Center for Neurological Disease, NCRC-ND, Beijing, China

3. Department of Neurosurgery, Beijing Fengtai Hospital, Beijing, China

4. Epilepsy Center, Guangdong Sanjiu Brain Hospital, Guangzhou, China

5. Epilepsy Center, Tsinghua University Yuquan Hospital, Beijing, China

6. Department of Neurosurgery, Shenzhen University General Hospital, Shenzhen University, Shenzhen, China

7. Department of Functional Neurosurgery, Xiamen Humanity Hospital, Fujian Medical University, Xiamen, China

8. Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China

9. Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China

10. Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing 100070, China

11. Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, Beijing 100070, China

Abstract

Background: Posterior cortex epilepsy (PCE) primarily comprises seizures originating from the occipital, parietal, and/or posterior edge of the temporal lobe. Electroclinical dissociation and subtle imaging representation render the diagnosis of PCE challenging. Improved methods for accurately identifying patients with PCE are necessary. Objectives: To develop a novel voxel-based image postprocessing method for better visual identification of the neuroimaging abnormalities associated with PCE. Design: Multicenter, retrospective study. Methods: Clinical and imaging features of 165 patients with PCE were retrospectively reviewed and collected from five epilepsy centers. A total of 37 patients (32.4% female, 20.2 ± 8.9 years old) with magnetic resonance imaging (MRI)-negative PCE were finally included for analysis. Image postprocessing features were calculated over a neighborhood for each voxel in the multimodality data. The postprocessed maps comprised structural deformation, hyperintense signal, and hypometabolism. Five raters from three different centers were blinded to the clinical diagnosis and determined the neuroimaging abnormalities in the postprocessed maps. Results: The average accuracy of correct identification was 55.7% (range from 43.2 to 62.2%) and correct lateralization was 74.1% (range from 64.9 to 81.1%). The Cronbach’s alpha was 0.766 for the correct identification and 0.683 for the correct lateralization with similar results of the interclass correlation coefficient, thus indicating reliable agreement between the raters. Conclusion: The image postprocessing method developed in this study can potentially improve the visual detection of MRI-negative PCE. The technique could lead to an increase in the number of patients with PCE who could benefit from the surgery.

Funder

Capita’s Funds for Health Improvement and Research

Publisher

SAGE Publications

Subject

Neurology (clinical),Neurology,Pharmacology

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