ASH

an Automatic pipeline to generate realistic and individualized chronic Stroke volume conduction Head models

Journal Article (2021)
Author(s)

Maria Carla Piastra (Radboud University Medical Center)

Joris Van Der Cruijsen (Erasmus MC)

Vitória Piai (Radboud University Medical Center)

Floor E.M. Jeukens (Student TU Delft)

Mana Manoochehri (TU Delft - Biomechatronics & Human-Machine Control)

Alfred C. Schouten (University of Twente, TU Delft - Biomechatronics & Human-Machine Control)

Ruud W. Selles (Erasmus MC)

Thom Oostendorp (Radboud University Medical Center)

Research Group
Biomechatronics & Human-Machine Control
DOI related publication
https://doi.org/10.1088/1741-2552/abf00b
More Info
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Publication Year
2021
Language
English
Research Group
Biomechatronics & Human-Machine Control
Issue number
4
Volume number
18
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Abstract

Objective. Large structural brain changes, such as chronic stroke lesions, alter the current pathways throughout the patients' head and therefore have to be taken into account when performing transcranial direct current stimulation simulations. Approach. We implement, test and distribute the first MATLAB pipeline that automatically generates realistic and individualized volume conduction head models of chronic stroke patients, by combining the already existing software SimNIBS, for the mesh generation, and lesion identification with neighborhood data analysis, for the lesion identification. To highlight the impact of our pipeline, we investigated the sensitivity of the electric field distribution to the lesion location and lesion conductivity in 16 stroke patients' datasets. Main results. Our pipeline automatically generates 1 mm-resolution tetrahedral meshes including the lesion compartment in less than three hours. Moreover, for large lesions, we found a high sensitivity of the electric field distribution to the lesion conductivity value and location. Significance. This work facilitates optimizing electrode configurations with the goal to obtain more focal brain stimulations of the target volumes in rehabilitation for chronic stroke patients.