Prediction of postoperative deficits using an improved diffusion-weighted imaging maximum a posteriori probability analysis in pediatric epilepsy surgery

Min Hee Lee, Nolan B. O’Hara, Yasuo Nakai, Aimee F. Luat, Csaba Juhasz, Sandeep Sood, Eishi Asano, Jeong Won Jeong

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

OBJECTIVE This study is aimed at improving the clinical utility of diffusion-weighted imaging maximum a posteriori probability (DWI-MAP) analysis, which has been reported to be useful for predicting postoperative motor, language, and visual field deficits in pediatric epilepsy surgery. The authors determined the additive value of a new clustering mapping method in which average direct-flip distance (ADFD) reclassifies the outliers of original DWI-MAP streamlines by referring to their minimum distances to the exemplar streamlines (i.e., medoids). METHODS The authors studied 40 children with drug-resistant focal epilepsy (mean age 8.7 ± 4.8 years) who had undergone resection of the presumed epileptogenic zone and had five categories of postoperative deficits (i.e., hemiparesis involving the face, hand, and/or leg; dysphasia requiring speech therapy; and/or visual field cut). In pre- and postoperative images of the resected hemisphere, DWI-MAP identified a total of nine streamline pathways: C1 = face motor area, C2 = hand motor area, C3 = leg motor area, C4 = Broca’s area–Wernicke’s area, C5 = premotor area–Broca’s area, C6 = premotor area–Wernicke’s area, C7 = parietal area–Wernicke’s area, C8 = premotor area–parietal area, and C9 = occipital lobe–lateral geniculate nucleus. For each streamline of the identified pathway, the minimal ADFD to the nine exemplars corrected the pathway membership. Binary logistic regression analysis was employed to determine how accurately two fractional predictors, D1–9 (postoperative volume change of C1–9) and g1–9 (preoperatively planned volume of C1–9 resected), predicted postoperative motor, language, and visual deficits. RESULTS The addition of ADFD to DWI-MAP analysis improved the sensitivity and specificity of regression models for predicting postoperative motor, language, and visual deficits by 28% for D1–3 (from 0.62 to 0.79), 13% for D4–8 (from 0.69 to 0.78), 13% for D9 (from 0.77 to 0.87), 7% for g1–3 (from 0.81 to 0.87), 1% for g4–8 (from 0.86 to 0.87), and 24% for g9 (from 0.75 to 0.93). Preservation of the eloquent pathways defined by preoperative DWI-MAP analysis with ADFD (up to 97% of C1–4,9) prevented postoperative motor, language, and visual deficits with sensitivity and specificity ranging from 88% to 100%. CONCLUSIONS The present study suggests that postoperative functional outcome substantially differs according to the extent of resected white matter encompassing eloquent cortex as determined by preoperative DWI-MAP analysis. The preservation of preoperative DWI-MAP–defined pathways may be crucial to prevent postoperative deficits. The improved DWI-MAP analysis may provide a complementary noninvasive tool capable of guiding the surgical margin to minimize the risk of postoperative deficits for children.

Original languageEnglish
Pages (from-to)648-659
Number of pages12
JournalJournal of Neurosurgery: Pediatrics
Volume23
Issue number5
DOIs
StatePublished - May 1 2019

Keywords

  • Diffusion-weighted imaging tractography
  • Epilepsy
  • Functional brain atlas
  • Functionally important regions
  • Outcome prediction
  • Subcortical areas

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