Open AccessConstruction of Relational Topographies from the Quantitative Measurements of Functional Deep Brain Stimulation Using a ‘Roving Window’ Interpolation Algorithm
Author(s) -
Mahesh B. Shenai,
Harrison C. Walker,
Stephanie Guthrie,
Ray L. Watts,
Barton L. Guthrie
Publication year - 2009
Publication title -
stereotactic and functional neurosurgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.798
H-Index - 63
eISSN - 1423-0372
pISSN - 1011-6125
DOI - 10.1159/000260075
Subject(s) - deep brain stimulation , sagittal plane , coronal plane , interpolation (computer graphics) , computer science , stimulation , medicine , artificial intelligence , biomedical engineering , algorithm , neuroscience , psychology , parkinson's disease , radiology , motion (physics) , disease , pathology
The delivery of stimulus by a deep brain stimulation (DBS) contact electrode at a particular location may lead to a quantifiable physiologic effect, both intraoperatively and postoperatively. Consequently, measured data values can be attributed to discrete scattered points in neuroanatomic space, allowing for interpolative techniques to generate a topographic map of spatial patterns. Ultimately, by relating the topographies of various intraoperative measurements to the postoperative counterparts and neuroanatomic atlases, outcome-guided adjustments to electrode position can be pursued intraoperatively. In this study, 52 Parkinson's disease patients were tested with a postoperative trial of stimulation and thresholds were recorded for motor adverse effects. A 'roving window' interpolation algorithm was adapted to generate a topographic map of voltage threshold along selected axial, coronal and sagittal planes. By developing these relational topographies for a variety of intraoperative and postoperative effects, a multivariable approach towards DBS optimization emerges.