ArticleProceedings of SPIE--the International Society for Optical Engineering2018
Tests of clustering thalamic nuclei based on various dMRI models in the squirrel monkey brain.
Article in Proceedings of SPIE--the International Society for Optical Engineering, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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7 authors at 2 institutions in 1 country.
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Abstract
backgroundClustering thalamic nuclei is important for both research and clinical purposes. For example, ventral intermediate nuclei in thalami serve as targets in both deep brain stimulation neurosurgery and radiosurgery for treating patients suffering from movement disorders (e.g., Parkinson's disease and essential tremor). Diffusion magnetic resonance imaging (dMRI) is able to reflect tissue microstructure in the central nervous system via fitting different models, such as, the diffusion tensor (DT), constrained spherical deconvolution (CSD), neurite orientation dispersion and density imaging (NODDI), diffusion kurtosis imaging (DKI) and the spherical mean technique (SMT). PURPOSE: To test which of the above-mentioned dMRI models is better for thalamic parcellation, we proposed a framework of
methodAn ex vivo monkey brain was scanned in a 9.4T MRI scanner at 0.3mm resolution with b values of 3000, 6000, 9000 and 12000 s/mm
resultsClustering with the DKI model has slightly higher overall agreement rate but clustering with other dMRI models result in higher agreement rate in some nuclei.
conclusiondMRl models should be carefully selected to better parcellate the thalamus, depending on the specific purpose of the parcellation.
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