Review: The international consensus classification of Focal Cortical Dysplasia – a critical update 2018
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Diagnostic Methods commission of the International League against Epilepsy (ILAE) released a first international consensus classification of Focal Cortical Dysplasia (FCD) in 2011. Since that time, this FCD classification has been widely used in clinical diagnosis and research (more than 740 papers cited in Pubmed between 1/1/2012 and 7/1/2017). Herein, we review the new data that will inform and revise the FCD classification. Many recent papers described molecular-genetic characteristics in FCD type II including multiple mutations in the mTOR pathway. In addition, the electro-clinico-imaging phenotype and surgical outcomes of FCD type II (in particular type IIb) were further defined and validated. These results pave the way for the design of an integrated clinico-pathological and genetic classification system, as recently recommended by the WHO for the classification of malignant brain tumours. On the other hand, little new information was acquired on FCD types I and III. Focal cortical dysplasia type I subtypes are still lacking a comprehensive description of clinical phenotypes, reproducible imaging characteristics, and specific molecular/genetic biomarkers. Associated FCD III subtypes also became rare in published literature. Despite temporal lobe epilepsy being the most common focal epilepsy in adults, we have not identified neurophysiological, imaging, histopathological and/or genetic biomarkers to reliably classify FCD III with or without hippocampal sclerosis. In respect of pathogenesis, FCD adjacent to a non-developmental, postnatally acquired lesion is difficult to explain and perhaps does not exist. This update may help foster shared efforts towards a better understanding of FCD, potential future updates of classification and novel targeted treatments.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it