A systematic comparison of structural-, structural connectivity-, and functional connectivity-based thalamus parcellation techniques.
Brain Struct Funct. 2020-05-21; :
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Iglehart C(1), Monti M(2)(3), Cain J(2), Tourdias T(4), Saranathan M(5)(6).
(1)Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, USA.
(2)Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA.
(3)Neurosurgery Brain Research Center, University of California Los Angeles, Los Angeles, CA, USA.
(4)Service de Neuroimagerie Diagnostique Et Thérapeutique and INSERM U1215, Université de Bordeaux, Bordeaux, France.
(5)Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, USA.
(6)Department of Medical Imaging, University of Arizona, Tucson, AZ, USA.
The thalamus consists of several histologically and functionally distinct nuclei
increasingly implicated in brain pathology and important for treatment,
motivating the need for development of fast and accurate thalamic parcellation.
The contrast between thalamic nuclei as well as between the thalamus and
surrounding tissues is poor in T1- and T2-weighted magnetic resonance imaging
(MRI), inhibiting efforts to date to segment the thalamus using standard clinical
MRI. Automatic parcellation techniques have been developed to leverage thalamic
features better captured by advanced MRI methods, including magnetization
prepared rapid acquisition gradient echo (MP-RAGE), diffusion tensor imaging
(DTI), and resting-state functional MRI (fMRI). Despite operating on
fundamentally different image contrasts, these methods claim a high degree of
agreement with the Morel stereotactic atlas of the thalamus. However, no
comparison has been undertaken to compare the results of these disparate
parcellation methods. We have implemented state-of-the-art structural-,
diffusion-, and functional imaging-based thalamus parcellation techniques and
used them on a single set of subjects. We present the first systematic
qualitative and quantitative comparison of these methods. The results show that
DTI parcellation agrees more with structural parcellation in the larger thalamic
nuclei, while rsfMRI parcellation agrees more with structural parcellation in the
smaller nuclei. Structural parcellation is the most accurate in the delineation
of small structures such as the habenular, antero-ventral, and medial geniculate