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Prior-guided individualized thalamic parcellation based on local diffusion characteristics.

Chaohong Gao1,2,3, Xia Wu2, Yaping Wang1,2,3

  • 1Sino-Danish College, Sino-Danish Center for Education and Research, University of Chinese Academy of Sciences, Beijing, China.

Human Brain Mapping
|March 4, 2024
PubMed
Summary
This summary is machine-generated.

A new prior-guided parcellation (PG-par) method enables robust, individualized thalamic subnuclei mapping. This technique improves brain parcellation accuracy and reproducibility for personalized neuroscience research.

Keywords:
diffusion MRIindividualized brain mappingmachine learningorientation distribution functionthalamic parcellation

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Area of Science:

  • Neuroimaging
  • Brain Anatomy
  • Computational Neuroscience

Background:

  • The thalamus, with its numerous subnuclei, is vital for brain function, connecting cortex and subcortex.
  • Individualized parcellation of thalamic nuclei is essential for understanding cognition and guiding neuromodulation therapies.
  • Existing methods struggle with intersubject variability, hindering accurate individual-level thalamic boundary delineation.

Purpose of the Study:

  • To develop a robust method for prior-guided individualized thalamic parcellation (PG-par).
  • To improve the accuracy and reproducibility of mapping individual thalamic subnuclei.
  • To overcome limitations of current parcellation techniques in capturing intersubject variability.

Main Methods:

  • Construction of a probabilistic atlas of thalamic nuclei using diffusion MRI data and local diffusion characteristics.
  • Training subject-specific multiple classification models using a multilayer perceptron, guided by high-probability voxels from the atlas.
  • Application of trained models to predict parcellation labels for individual thalamic voxels.

Main Results:

  • The PG-par method demonstrated excellent reproducibility and sensitivity to individual variability in test-retest assessments.
  • PG-par outperformed traditional group atlas registration and individual clustering methods in parcellation accuracy.
  • The individualized parcellations showed superior correspondence with histological atlases compared to other methods.

Conclusions:

  • The proposed prior-guided individualized thalamic parcellation (PG-par) method offers a robust solution for personalized brain mapping.
  • This approach enhances the accuracy of thalamic subnuclei delineation, crucial for clinical applications and cognitive neuroscience.
  • PG-par advances personalized modeling of brain parcellation, paving the way for more precise neuromodulation strategies.