ASH: An Automatic pipeline to generate realistic and individualized chronic Stroke volume conduction Head models

Maria Carla Piastra*, Joris Van Der Cruijsen, Vitória Piai, Floor E.M. Jeukens, Mana Manoochehri, Alfred C. Schouten, Ruud W. Selles, Thom Oostendorp

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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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.

Original languageEnglish
Article number044001
JournalJournal of neural engineering
Volume18
Issue number4
Early online date27 Apr 2021
DOIs
Publication statusPublished - Aug 2021

Keywords

  • Automatic pipeline
  • Chronic stroke
  • Lesion conductivity
  • Motor rehabilitation
  • Tdcs
  • Volume conduction head model

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