A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology

Juan Eugenio Iglesias*, Ricardo Insausti, Garikoitz Lerma-Usabiaga, Martina Bocchetta, Koen Van Leemput, Douglas N. Greve, Andre van der Kouwe, Bruce Fischl, César Caballero-Gaudes, Pedro M. Paz-Alonso

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

The human thalamus is a brain structure that comprises numerous, highly specific nuclei. Since these nuclei are
known to have different functions and to be connected to different areas of the cerebral cortex, it is of great
interest for the neuroimaging community to study their volume, shape and connectivity in vivo with MRI. In this
study, we present a probabilistic atlas of the thalamic nuclei built using ex vivo brain MRI scans and histological
data, as well as the application of the atlas to in vivo MRI segmentation. The atlas was built using manual
delineation of 26 thalamic nuclei on the serial histology of 12 whole thalami from six autopsy samples, combined
with manual segmentations of the whole thalamus and surrounding structures (caudate, putamen, hippocampus,
etc.) made on in vivo brain MR data from 39 subjects. The 3D structure of the histological data and corresponding
manual segmentations was recovered using the ex vivo MRI as reference frame, and stacks of blockface photographs
acquired during the sectioning as intermediate target. The atlas, which was encoded as an adaptive
tetrahedral mesh, shows a good agreement with previous histological studies of the thalamus in terms of volumes
of representative nuclei. When applied to segmentation of in vivo scans using Bayesian inference, the atlas shows
excellent test-retest reliability, robustness to changes in input MRI contrast, and ability to detect differential
thalamic effects in subjects with Alzheimer's disease. The probabilistic atlas and companion segmentation tool are
publicly available as part of the neuroimaging package FreeSurfer.
Original languageEnglish
JournalNeuroImage
Volume183
Pages (from-to)314–326
ISSN1053-8119
DOIs
Publication statusPublished - 2018

Keywords

  • Thalamus
  • Atlasing
  • Histology
  • Ex-vivo MRI
  • Segmentation
  • Bayesian inference

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