Clinical and imaging heterogeneity of polymicrogyria: a study of 328 patients
Bibliographic record
Abstract
Polymicrogyria is one of the most common malformations of cortical development and is associated with a variety of clinical sequelae including epilepsy, intellectual disability, motor dysfunction and speech disturbance. It has heterogeneous clinical manifestations and imaging patterns, yet large cohort data defining the clinical and imaging spectrum and the relative frequencies of each subtype are lacking. The aims of this study were to determine the types and relative frequencies of different polymicrogyria patterns, define the spectrum of their clinical and imaging features and assess for clinical/imaging correlations. We studied the imaging features of 328 patients referred from six centres, with detailed clinical data available for 183 patients. The ascertainment base was wide, including referral from paediatricians, geneticists and neurologists. The main patterns of polymicrogyria were perisylvian (61%), generalized (13%), frontal (5%) and parasagittal parieto-occipital (3%), and in 11% there was associated periventricular grey matter heterotopia. Each of the above patterns was further divided into subtypes based on distinguishing imaging characteristics. The remaining 7% were comprised of a number of rare patterns, many not described previously. The most common clinical sequelae were epileptic seizures (78%), global developmental delay (70%), spasticity (51%) and microcephaly (50%). Many patients presented with neurological or developmental abnormalities prior to the onset of epilepsy. Patients with more extensive patterns of polymicrogyria presented at an earlier age and with more severe sequelae than those with restricted or unilateral forms. The median age at presentation for the entire cohort was 4 months with 38% presenting in either the antenatal or neonatal periods. There were no significant differences between the prevalence of epilepsy for each polymicrogyria pattern, however patients with generalized and bilateral forms had a lower age at seizure onset. There was significant skewing towards males with a ratio of 3:2. This study expands our understanding of the spectrum of clinical and imaging features of polymicrogyria. Progression from describing imaging patterns to defining anatomoclinical syndromes will improve the accuracy of prognostic counselling and will aid identification of the aetiologies of polymicrogyria, including genetic causes.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".