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Anatomical brain structures normalization for deep brain stimulation in movement disorders.

Dorian Vogel1, Ashesh Shah2, Jérôme Coste3

  • 1Institute for Medical Engineering and Medical Informatics, School of Life Sciences, University of Applied Sciences and Arts Northwestern Switzerland, Hofackerstrasse 30, 4132 Muttenz, Switzerland; Department of Biomedical Engineering, Linköping University, SE-581 85 Linköping, Sweden.

Neuroimage. Clinical
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Summary
This summary is machine-generated.

This study presents a new normalization pipeline for deep brain stimulation (DBS) patient imaging, comparing registration tools. ANTS demonstrated superior performance, enabling a more accurate diencephalon atlas for surgical planning.

Keywords:
AtlasDeep brain stimulation (DBS)Group analysisImage registrationPatient normalizationTemplateThalamus

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Area of Science:

  • Neurosurgery
  • Medical Imaging Analysis
  • Computational Neuroscience

Background:

  • Deep brain stimulation (DBS) requires precise patient-specific pre-operative planning for optimal outcomes.
  • Analyzing patient brain images collectively offers potential for systematic planning assistance.
  • Developing robust normalization pipelines is crucial for integrating multi-subject neuroimaging data.

Purpose of the Study:

  • To design and evaluate a normalization pipeline for deep brain stimulation (DBS) patient imaging.
  • To compare the performance of freely available non-linear registration tools (ANTS, FNIRT, DRAMMS).
  • To create a group-specific multi-modality iterative template for enhanced anatomical definition.

Main Methods:

  • A normalization pipeline was designed using a group-specific, multi-modality iterative template creation process.
  • Non-linear registrations were performed using ANTS, FNIRT, and DRAMMS on T1 and WAIR images from 19 DBS patients.
  • Registration accuracy was assessed by comparing expert-labeled thalamic and subthalamic structures.

Main Results:

  • The ANTS registration tool, utilizing High Variance settings, demonstrated the best performance.
  • FNIRT and DRAMMS did not achieve the same level of registration accuracy as ANTS.
  • The optimized pipeline facilitated the creation of a diencephalon atlas with 58 defined structures from 19 patients.

Conclusions:

  • ANTS is the preferred registration tool for normalizing deep brain stimulation patient imaging data.
  • The developed normalization pipeline and resulting atlas improve anatomical definition for surgical planning.
  • This systematic approach enhances the potential for collective analysis of DBS patient neuroimaging.