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Evaluation of Automatic Segmentation of Thalamic Nuclei through Clinical Effects Using Directional Deep Brain Stimulation Leads: A Technical Note

Authors :
Marie T. Krüger
Rebecca Kurtev-Rittstieg
Georg Kägi
Yashar Naseri
Stefan Hägele-Link
Florian Brugger
Source :
Brain Sciences, Vol 10, Iss 9, p 642 (2020)
Publication Year :
2020
Publisher :
MDPI AG, 2020.

Abstract

Automatic anatomical segmentation of patients’ anatomical structures and modeling of the volume of tissue activated (VTA) can potentially facilitate trajectory planning and post-operative programming in deep brain stimulation (DBS). We demonstrate an approach to evaluate the accuracy of such software for the ventral intermediate nucleus (VIM) using directional leads. In an essential tremor patient with asymmetrical brain anatomy, lead placement was adjusted according to the suggested segmentation made by the software (Brainlab). Postoperatively, we used directionality to assess lead placement using side effect testing (internal capsule and sensory thalamus). Clinical effects were then compared to the patient-specific visualization and VTA simulation in the GUIDE™ XT software (Boston Scientific). The patient’s asymmetrical anatomy was correctly recognized by the software and matched the clinical results. VTA models matched best for dysarthria (6 out of 6 cases) and sensory hand side effects (5/6), but least for facial side effects (1/6). Best concordance was observed for the modeled current anterior and back spread of the VTA, worst for the current side spread. Automatic anatomical segmentation and VTA models can be valuable tools for DBS planning and programming. Directional DBS leads allow detailed postoperative assessment of the concordance of such image-based simulation and visualization with clinical effects.

Details

Language :
English
ISSN :
20763425
Volume :
10
Issue :
9
Database :
Directory of Open Access Journals
Journal :
Brain Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.6f4208a23ff6491c94dc96df12762b84
Document Type :
article
Full Text :
https://doi.org/10.3390/brainsci10090642