ArticleJournal of neurosurgery. Pediatrics2019
Novel diffusion tractography methodology using Kalman filter prediction to improve preoperative benefit-risk analysis in pediatric epilepsy surgery.
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 3 papers.
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3 citing papers in PubMed, 5 citations in OpenAlex.
- ESM-AnatTractNet: Advanced deep learning model of true positive eloquent white matter tractography to improve preoperative evaluation of pediatric epilepsy surgery.Medical image analysis · 2026Article
- Novel Deep Learning Network Analysis of Electrical Stimulation Mapping-Driven Diffusion MRI Tractography to Improve Preoperative Evaluation of Pediatric Epilepsy.IEEE transactions on bio-medical engineering · 2020Article
- Dynamic tractography: Integrating cortico-cortical evoked potentials and diffusion imaging.NeuroImage · 2020Article
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8 authors at 3 institutions in 1 country.
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Abstract
objectiveIn this study the authors investigated the clinical reliability of diffusion weighted imaging maximum a posteriori probability (DWI-MAP) analysis with Kalman filter prediction in pediatric epilepsy surgery. This approach can yield a suggested resection margin as a dynamic variable based on preoperative DWI-MAP pathways. The authors sought to determine how well the suggested margin would have maximized occurrence of postoperative seizure freedom (benefit) and minimized occurrence of postoperative neurological deficits (risk).
methodsThe study included 77 pediatric patients with drug-resistant focal epilepsy (age 10.0 ± 4.9 years) who underwent resection of their presumed epileptogenic zone. In preoperative DWI tractography from the resected hemisphere, 9 axonal pathways, Ci=1-9, were identified using DWI-MAP as follows: C1-3 supporting face, hand, and leg motor areas; C4 connecting Broca's and Wernicke's areas; C5-8 connecting Broca's, Wernicke's, parietal, and premotor areas; and C9 connecting the occipital lobe and lateral geniculate nucleus. For each Ci, the resection margin, di, was measured by the minimal Euclidean distance between the voxels of Ci and the resection boundary determined by spatially coregistered postoperative MRI. If Ci was resected, di was assumed to be negative (calculated as -1 × average Euclidean distance between every voxel inside the resected Ci volume, ri). Kalman filter prediction was then used to estimate an optimal resection margin, d*i, to balance benefit and risk by approximating the relationship between di and ri. Finally, the authors defined the preservation zone of Ci that can balance the probability of benefit and risk by expanding the cortical area of Ci up to d*i on the 3D cortical surface.
resultsIn the whole group (n = 77), nonresection of the preoperative preservation zone (i.e., actual resection margin d*i greater than the Kalman filter-defined d*i) accurately predicted the absence of postoperative motor (d*1-3: 0.93 at seizure-free probability of 0.80), language (d*4-8: 0.91 at seizure-free probability of 0.81), and visual deficits (d*9: 0.90 at seizure-free probability of 0.75), suggesting that the preservation of preoperative Ci within d*i supports a balance between postoperative functional deficit and seizure freedom. The subsequent subgroup analyses found that preservation of preoperative Ci =1-4,9 within d*i =1-4,9 may provide accurate deficit predictions independent of age and seizure frequency, suggesting that the DWI-based surgical margin can be effective for surgical planning even in young children and across a range of epilepsy severity.
conclusionsIntegrating DWI-MAP analysis with Kalman filter prediction may help guide epilepsy surgery by visualizing the margins of the eloquent white matter pathways to be preserved.
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