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

Jiajie Mo1, Wenyu Dong1,2, Lin Sang3

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

Therapeutic Advances in Neurological Disorders
|November 29, 2023
PubMed
Summary

A new image postprocessing technique aids in identifying posterior cortex epilepsy (PCE) on MRI scans. This method improves visual detection of subtle abnormalities, potentially helping more patients receive timely surgical treatment for epilepsy.

Keywords:
MRI-negativecalculated mapinter-rater agreementmulticenterposterior cortex epilepsy

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Area of Science:

  • Neurology
  • Medical Imaging
  • Epilepsy Research

Background:

  • Posterior cortex epilepsy (PCE) originates in the occipital, parietal, or temporal lobes.
  • Diagnosis is challenging due to subtle imaging findings and electroclinical dissociation.
  • Advanced methods are needed for accurate PCE identification.

Purpose of the Study:

  • To develop a novel voxel-based image postprocessing method.
  • To enhance visual identification of neuroimaging abnormalities in PCE.
  • To improve diagnostic accuracy for MRI-negative PCE.

Main Methods:

  • Retrospective analysis of 165 PCE patients from five centers.
  • Included 37 patients with MRI-negative PCE.
  • Calculated postprocessing features (deformation, hyperintensity, hypometabolism) on multimodality data.
  • Blinded raters assessed neuroimaging abnormalities on postprocessed maps.

Main Results:

  • Average identification accuracy was 55.7% (range 43.2–62.2%).
  • Average correct lateralization was 74.1% (range 64.9–81.1%).
  • High inter-rater reliability indicated by Cronbach's alpha (0.766 for identification, 0.683 for lateralization).

Conclusions:

  • The developed image postprocessing method shows potential for improving visual detection of MRI-negative PCE.
  • This technique may increase the number of PCE patients eligible for surgical intervention.
  • Enhanced diagnostic capabilities can lead to better patient outcomes.