<scp>MRI</scp> ‐negative epilepsy: A systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Objective Drug‐resistant focal epilepsy is commonly dichotomized based on magnetic resonance imaging (MRI) lesion visibility into positive (MRI‐pos) and negative (MRI‐neg). Yet, the criteria used to ascribe such categorization are variable. We used a systematic review and meta‐analysis to synthesize evidence for the designation of MRI‐neg status. Methods In accordance with Preferred Reporting Items for Systematic reviews and Meta‐Analyses (PRISMA) guidelines, the systematic review (1990–2025) across Embase, Cochrane, and Medline databases identified cohorts with MRI‐neg epilepsy. Unsupervised clustering stratified studies based on co‐occurrence of imaging modalities. Within identified classes, we assessed the consistency of reporting MRI parameters, rater expertise, post‐processing, and stereo–electroencephalography (SEEG). Meta‐analyses evaluated the effects of post‐processing on diagnostic yield and MRI‐neg status on post‐surgical outcome. Results We screened 2622 records and assessed the eligibility of 448 full‐text articles, 246 of which met the inclusion criteria for systematic review: 108 (44%) provided data only on MRI‐neg and 138 (56%) on mixed adult cohorts, for a total of 10.463 MRI‐neg and 7436 MRI‐pos patients. Compared to MRI‐pos, MRI‐neg patients underwent SEEG more frequently (75% vs 54%, p < 0.05), underwent surgery less frequently (73% vs 84%; odds ratio [OR] = 1.14, p < 0.001), and had less favorable outcomes (61% vs 72%, p < 0.05). Clustering identified three classes: MRI‐dominant , typified by consistent reporting of MRI parameters (ORs >3.11, p < 0.001), rater‐expertise (ORs >9.94, p < 0.001), and post‐processing (ORs >3.38, p < 0.03) , as opposed to Limited‐MRI (χ 2 = 41.08, p < 0.001); MRI‐and‐nuclear‐imaging class was typified by use of SEEG (ORs >3.33, p < 0.02). Meta‐analyses showed a 39% gain in diagnostic yield after post‐processing (11.10, 95% confidence interval [CI] 7.45–16.53) and a higher proportion of favorable surgical outcome in MRI‐pos compared to MRI‐neg (75% vs 58%; χ 2 = 19.10, p < 0.001). Time‐based sensitivity analyses did not affect results. Significance The designation of MRI‐neg is ambiguous, with most studies lacking details on imaging parameters and reader expertise. Given a 39% gain in diagnostic yield, MRI post‐processing should be performed systematically as part of a modern multimodal approach to epilepsy surgery before ascribing MRI‐neg status.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.028 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".