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Record W3118026954 · doi:10.3171/2020.7.peds20397

The utility of arterial spin labeling in the presurgical evaluation of poorly defined focal epilepsy in children

2020· article· en· W3118026954 on OpenAlexaff
Jack Lam, Patricia Tomaszewski, Guillaume Gilbert, Jeremy T. Moreau, Marie‐Christine Guiot, Steffen Albrecht, Jean‐Pierre Farmer, Jeffrey Atkinson, Christine Saint‐Martin, Pia Wintermark, Boris C. Bernhardt, Sylvain Baillet, Roy Dudley

Bibliographic record

VenueJournal of Neurosurgery Pediatrics · 2020
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsMcGill University Health CentreUniversity Health NetworkMcGill UniversityPhilips (Canada)Montreal Neurological Institute and Hospital
Fundersnot available
KeywordsIctalMedicineEpilepsy surgeryEpilepsyHistopathologyIctal-Interictal SPECT Analysis by SPMNuclear medicineRadiologyMagnetic resonance imagingPerfusionScalpElectroencephalographySurgeryPathology

Abstract

fetched live from OpenAlex

OBJECTIVE: The authors sought to assess the utility of arterial spin labeling (ASL) perfusion 3T-MRI for the presurgical evaluation of poorly defined focal epilepsy in pediatric patients. METHODS: Pseudocontinuous ASL perfusion 3T-MRI was performed in 25 consecutive children with poorly defined focal epilepsy. ASL perfusion abnormalities were detected qualitatively by visual inspection and quantitatively by calculating asymmetry index (AI) maps and significant z-score cluster maps based on successfully operated cases. ASL results were prospectively compared to scalp EEG, structural 3T-MRI, FDG-PET, ictal/interictal SPECT, magnetoencephalography (MEG), and intracranial recording results, as well as the final surgically proven epileptogenic zone (EZ) in operated patients who had at least 1 year of good (Engel class I/II) seizure outcome and positive histopathology results. RESULTS: Qualitative ASL perfusion abnormalities were found in 17/25 cases (68%), specifically in 17/20 MRI-positive cases (85.0%) and in none of the 5 MRI-negative cases. ASL was concordant with localizing scalp EEG findings in 66.7%, structural 3T-MRI in 90%, FDG-PET in 75%, ictal/interictal SPECT in 62.5%, and MEG in 75% of cases, and with intracranial recording results in 40% of cases. Eleven patients underwent surgery; in all 11 cases the EZ was surgically proven by positive histopathology results and the patient having at least 1 year of good seizure outcome. ASL results were concordant with this final surgically proven EZ in 10/11 cases (sensitivity 91%, specificity 50%). All 10 ASL-positive patients who underwent surgery had positive surgical pathology results and good long-term postsurgical seizure outcome at a mean follow-up of 39 months. Retrospective quantitative analysis based on significant z-score clusters found 1 true-positive result that was missed by qualitative analysis and 3 additional false-positive results (sensitivity 100%, specificity 23%). CONCLUSIONS: ASL supports the hypothesis regarding the EZ in poorly defined focal epilepsy cases in children. Due to its convenience and noninvasive nature, the authors recommend that ASL be added routinely to the presurgical MRI evaluation of epilepsy. Future optimized quantitative methods may improve the diagnostic yield of this technique.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.538

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.062
GPT teacher head0.331
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations29
Published2020
Admission routes1
Has abstractyes

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