Skip to main content
Download PDF
- Main
Diffusion Tensor Imaging-Based Thalamic Segmentation in Deep Brain Stimulation for Chronic Pain Conditions
Published Web Location
https://doi.org/10.1159/000448079Abstract
Background/aims
Thalamic deep brain stimulation (DBS) for the treatment of medically refractory pain has largely been abandoned on account of its inconsistent and oftentimes poor efficacy. Our aim here was to use diffusion tensor imaging (DTI)-based segmentation to assess the internal thalamic nuclei of patients who have undergone thalamic DBS for intractable pain and retrospectively correlate lead position with clinical outcome.Methods
DTI-based segmentation was performed on 5 patients who underwent sensory thalamus DBS for chronic pain. Postoperative computed tomography images obtained for electrode placement were fused with preoperative magnetic resonance images that had undergone DTI-based thalamic segmentation. Sensory thalamus maps of 4 patients were analyzed for lead positioning and interpatient variability.Results
Four patients who experienced significant pain relief following DBS demonstrated contact positions within the DTI-determined sensory thalamus or in its vicinity, whereas 1 patient who did not respond to stimulation did not. Only 4 voxels (2%) within the sensory thalamus were mutually shared among patients; 108 voxels (58%) were uniquely represented.Conclusions
DTI-based segmentation of the thalamus can be used to confirm thalamic lead placement relative to the sensory thalamus and may serve as a useful tool to guide thalamic DBS electrode implantation in the future.Many UC-authored scholarly publications are freely available on this site because of the UC's open access policies. Let us know how this access is important for you.
Main Content
For improved accessibility of PDF content, download the file to your device.
Enter the password to open this PDF file:
File name:
-
File size:
-
Title:
-
Author:
-
Subject:
-
Keywords:
-
Creation Date:
-
Modification Date:
-
Creator:
-
PDF Producer:
-
PDF Version:
-
Page Count:
-
Page Size:
-
Fast Web View:
-
Preparing document for printing…
0%