Intraoperative changes in large-scale thalamic circuitry following laser ablation of hypothalamic hamartomas
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Gelastic seizures due to hypothalamic hamartomas (HH) are challenging to treat, in part due to an incomplete understanding of seizure propagation pathways. Although magnetic resonance imaging-guided laser interstitial thermal therapy (MRgLITT) is a promising intervention to disconnect HH from ictal propagation networks, the optimal site of ablation to achieve seizure freedom is not known. In this study, we investigated intraoperative post-ablation changes in resting-state functional connectivity to identify large-scale networks associated with successful disconnection of HH. METHODS: Children who underwent MRgLITT for HH at two institutions were consecutively recruited and followed for a minimum of one year. Seizure freedom was defined as Engel score of 1A at the last available follow-up. Immediate pre- and post- ablation resting-state functional MRI scans were acquired while maintaining a constant depth of general anesthetic. Multivariable generalized linear models were used to identify intraoperative changes in large-scale connectivity associated with seizure outcomes. RESULTS: Twelve patients underwent MRgLITT for HH, five of whom were seizure-free at their last follow-up. Intraprocedural changes in thalamocortical circuitry involving the anterior cingulate cortex were associated with seizure-freedom. Children who were seizure-free demonstrated an increase and decrease in connectivity to the pregenual and dorsal anterior cingulate cortices, respectively. In addition, children who became seizure-free demonstrated increased thalamic connectivity to the periaqueductal gray immediately following MRgLITT. DISCUSSION: Successful disconnection of HH is associated with intraoperative, large-scale changes in thalamocortical connectivity. These changes provide novel insights into the large-scale basis of gelastic seizures and may represent intraoperative biomarkers of treatment success.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".