Evidence map›Paper›PMID 30797207›Full record

ArticleJournal of neurosurgery. Pediatrics2019

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

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In one paragraph

Article in Journal of neurosurgery. Pediatrics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.0field-weighted citation impact, top 26% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 10 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 1 country.

Min-Hee LeeDepartments of1Pediatrics.
Nolan B O'Hara4Translational Neuroscience Program, Wayne State University School of Medicine; and.
Yasuo NakaiDepartments of1Pediatrics.
Aimee F LuatDepartments of1Pediatrics.
Csaba JuhaszDepartments of1Pediatrics.
Sandeep Sood3Neurosurgery.
Eishi AsanoDepartments of1Pediatrics.
Jeong-Won JeongDepartments of1Pediatrics.
Children's Hospital of Michigan · USNeurology, Inc · USPediatrics and Genetics · USWayne State University · US

Funding

Functional brain mapping in pediatric neurosurgeryR01NS064033 · NINDS · WAYNE STATE UNIVERSITY · PI EISHI ASANO · 2009 to 2026
$5.7M
Novel DWI Methods to Minimize Postoperative Deficits in Pediatric Epilepsy Surgery.R01NS089659 · NINDS · WAYNE STATE UNIVERSITY · PI JEONG, JEONG-WON · 2015 to 2025
$3.7M
NINDS NIH HHS R01 NS064033NINDS NIH HHS R01 NS089659
6 · The paper itself

Abstract

objectiveThis 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).

methodsThe 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, Δ1-9 (postoperative volume change of C1-9) and γ1-9 (preoperatively planned volume of C1-9 resected), predicted postoperative motor, language, and visual deficits.

resultsThe 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 Δ1-3 (from 0.62 to 0.79), 13% for Δ4-8 (from 0.69 to 0.78), 13% for Δ9 (from 0.77 to 0.87), 7% for γ1-3 (from 0.81 to 0.87), 1% for γ4-8 (from 0.86 to 0.87), and 24% for γ9 (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%.

conclusionsThe 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.

Indexed as

diffusion-weighted imaging tractographyepilepsyfunctional brain atlasfunctionally important regionsoutcome predictionsubcortical areas

Identifiers

PMID30797207
PMCPMC9019725
OpenAlexW2918106603

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.