Incorporation of quantitative MRI in a model to predict temporal lobe epilepsy surgery outcome

Marcia Morita-Sherman, Manshi Li, Boney Joseph, Clarissa Yasuda, Deborah Vegh, Brunno Mac Hado De Campos, Marina K.M. Alvim, Shreya Louis, William Bingaman, Imad Najm, Stephen Jones, Xiaofeng Wang, Ingmar Blümcke, Benjamin H. Brinkmann, Gregory Worrell, Fernando Cendes, Lara Jehi

Research output: Contribution to journalArticlepeer-review

Abstract

Quantitative volumetric brain MRI measurement is important in research applications, but translating it into patient care is challenging. We explore the incorporation of clinical automated quantitative MRI measurements in statistical models predicting outcomes of surgery for temporal lobe epilepsy. Four hundred and thirty-five patients with drug-resistant epilepsy who underwent temporal lobe surgery at Cleveland Clinic, Mayo Clinic and University of Campinas were studied. We obtained volumetric measurements from the pre-operative T1-weighted MRI using NeuroQuant, a Food and Drug Administration approved software package. We created sets of statistical models to predict the probability of complete seizure-freedom or an Engel score of I at the last follow-up. The cohort was randomly split into training and testing sets, with a ratio of 7:3. Model discrimination was assessed using the concordance statistic (C-statistic). We compared four sets of models and selected the one with the highest concordance index. Volumetric differences in pre-surgical MRI located predominantly in the frontocentral and temporal regions were associated with poorer outcomes. The addition of volumetric measurements to the model with clinical variables alone increased the model's C-statistic from 0.58 to 0.70 (right-sided surgery) and from 0.61 to 0.66 (left-sided surgery) for complete seizure freedom and from 0.62 to 0.67 (right-sided surgery) and from 0.68 to 0.73 (left-sided surgery) for an Engel I outcome score. 57% of patients with extra-temporal abnormalities were seizure-free at last follow-up, compared to 68% of those with no such abnormalities (P-value = 0.02). Adding quantitative MRI data increases the performance of a model developed to predict post-operative seizure outcomes. The distribution of the regions of interest included in the final model supports the notion that focal epilepsies are network disorders and that subtle cortical volume loss outside the surgical site influences seizure outcome.

Original languageEnglish (US)
Article numberfcab164
JournalBrain Communications
Volume3
Issue number3
DOIs
StatePublished - 2021

Keywords

  • prediction of epilepsy surgery outcome
  • quantitative MRI
  • temporal lobe epilepsy
  • volumetric measurements

ASJC Scopus subject areas

  • Psychiatry and Mental health
  • Biological Psychiatry
  • Cellular and Molecular Neuroscience
  • Neurology

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