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MRI-negative epilepsy: A systematic review and meta-analysis.
Ravnoor S Gill1, Francesco Deleo2, Boris Bernhardt3
1Neuroimaging of Epilepsy Laboratory and Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Canada.
The designation of MRI-negative epilepsy is inconsistent. Systematic MRI post-processing improves diagnostic yield by 39% and is crucial before classifying epilepsy as MRI-negative.
Area of Science:
- Neurology
- Radiology
- Epileptology
Background:
- Drug-resistant focal epilepsy is often categorized as MRI-positive or MRI-negative based on lesion visibility.
- The criteria for classifying epilepsy as MRI-negative are inconsistent across studies.
- This ambiguity impacts diagnostic accuracy and treatment strategies.
Purpose of the Study:
- To systematically review and synthesize evidence regarding the designation of MRI-negative epilepsy.
- To assess the consistency of reporting imaging parameters, rater expertise, and post-processing in studies of MRI-negative epilepsy.
- To evaluate the impact of MRI post-processing on diagnostic yield and surgical outcomes.
Main Methods:
- A systematic review and meta-analysis adhering to PRISMA guidelines (1990-2025) was conducted.
- Studies were identified across Embase, Cochrane, and Medline databases.
- Unsupervised clustering stratified studies by imaging modalities; meta-analyses assessed post-processing effects and MRI-negative status on outcomes.
Main Results:
- 246 articles were included, encompassing 10,463 MRI-negative and 7,436 MRI-positive patients.
- MRI-negative patients underwent SEEG more frequently but had less frequent surgery and less favorable outcomes.
- Clustering revealed distinct study classes based on imaging modality reporting and expertise; post-processing yielded a 39% gain in diagnostic yield.
Conclusions:
- The classification of MRI-negative epilepsy lacks standardized criteria, with frequent omissions in reporting imaging parameters and reader expertise.
- Systematic MRI post-processing is essential for improving diagnostic yield and should be a routine part of multimodal epilepsy evaluations.
- Accurate classification is critical for optimizing epilepsy surgery and patient outcomes.
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