Thalamus Optimized Multi Atlas Segmentation (THOMAS): fast, fully automated segmentation of thalamic nuclei from structural MRI.

Jason H. Su, Francis T. Thomas, Willard S. Kasoff, Thomas Tourdias, Eun Young Choi, Brian K. Rutt, Manojkumar Saranathan
NeuroImage. 2019-07-01; 194: 272-282
DOI: 10.1016/j.neuroimage.2019.03.021

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Su JH(1), Thomas FT(2), Kasoff WS(3), Tourdias T(4), Choi EY(5), Rutt BK(6), Saranathan M(7).

Author information:
(1)Electrical Engineering, Stanford University, Stanford, CA, USA.
(2)Electrical & Computer Engineering, University of Arizona, Tucson, AZ, USA.
(3)Division of Neurosurgery, University of Arizona, Tucson, AZ, USA.
(4)Service de Neuroimagerie Diagnostique et Thérapeutique, Université de Bordeaux, Bordeaux, France.
(5)Neurosurgery, Stanford University, Stanford, CA, USA.
(6)Radiology, Stanford University, Stanford, CA, USA.
(7)Electrical & Computer Engineering, University of Arizona, Tucson, AZ, USA;
Medical Imaging, University of Arizona, Tucson, AZ, USA.

The thalamus and its nuclei are largely indistinguishable on standard T1 or T2
weighted MRI. While diffusion tensor imaging based methods have been proposed to
segment the thalamic nuclei based on the angular orientation of the principal
diffusion tensor, these are based on echo planar imaging which is inherently
limited in spatial resolution and suffers from distortion. We present a
multi-atlas segmentation technique based on white-matter-nulled MP-RAGE imaging
that segments the thalamus into 12 nuclei with computation times on the order of
10 min on a desktop PC; we call this method THOMAS (THalamus Optimized Multi
Atlas Segmentation). THOMAS was rigorously evaluated on 7T MRI data acquired from
healthy volunteers and patients with multiple sclerosis by comparing against
manual segmentations delineated by a neuroradiologist, guided by the Morel atlas.
Segmentation accuracy was very high, with uniformly high Dice indices: at least
0.85 for large nuclei like the pulvinar and mediodorsal nuclei and at least 0.7
even for small structures such as the habenular, centromedian, and lateral and
medial geniculate nuclei. Volume similarity indices ranged from 0.82 for the
smaller nuclei to 0.97 for the larger nuclei. Volumetry revealed that the volumes
of the right anteroventral, right ventral posterior lateral, and both right and
left pulvinar nuclei were significantly lower in MS patients compared to
controls, after adjusting for age, sex and intracranial volume. Lastly, we
evaluated the potential of this method for targeting the Vim nucleus for deep
brain surgery and focused ultrasound thalamotomy by overlaying the Vim nucleus
segmented from pre-operative data on post-operative data. The locations of the
ablated region and active DBS contact corresponded well with the segmented Vim
nucleus. Our fast, direct structural MRI based segmentation method opens the door
for MRI guided intra-operative procedures like thalamotomy and asleep DBS
electrode placement as well as for accurate quantification of thalamic nuclear
volumes to follow progression of neurological disorders.

Copyright © 2019 Elsevier Inc. All rights reserved.

DOI: 10.1016/j.neuroimage.2019.03.021
PMCID: PMC6536348 [Available on 2020-07-01]
PMID: 30894331 [Indexed for MEDLINE]

Auteurs Bordeaux Neurocampus