Accurate Bayesian segmentation of thalamic nuclei using diffusion MRI and an improved histological atlas

Abstract

The human thalamus is a highly connected brain structure, which is key for the control of numerous functions and is involved in several neurological disorders. Recently, neuroimaging studies have increasingly focused on the volume and connectivity of the specific nuclei comprising this structure, rather than looking at the thalamus as a whole. However, accurate identification of cytoarchitectonically designed histological nuclei on standard in vivo structural MRI is hampered by the lack of image contrast that can be used to distinguish nuclei from each other and from surrounding white matter tracts. While diffusion MRI may offer such contrast, it has lower resolution and lacks some boundaries visible in structural imaging. In this work, we present a Bayesian segmentation algorithm for the thalamus. This algorithm combines prior information from a probabilistic atlas with likelihood models for both structural and diffusion MRI, allowing label boundaries to be informed by both modalities. We present an improved probabilistic atlas, incorporating 26 thalamic nuclei identified from histology and 45 white matter tracts identified in ultra-high gradient strength diffusion imaging. We present a family of likelihood models for diffusion tensor imaging, ensuring compatibility with the vast majority of neuroimaging datasets that include diffusion MRI data. The use of these diffusion likelihood models greatly improves identification of nuclei versus segmentation based solely on structural MRI. Dice comparison of 5 manually identifiable groups of nuclei to ground truth segmentations show improvements of up to 10 percentage points. Additionally, our chosen model shows a high degree of reliability, with median test-retest Dice scores above 0.85 for four out of five nuclei groups, whilst also offering improved detection of differential thalamic involvement in Alzheimer's disease (AUROC 83.36%). The probabilistic atlas and segmentation tool will be made publicly available as part of the neuroimaging package FreeSurfer.

Mild traumatic brain injury is associated with increased thalamic subregion volume in the subacute period following injury

“…Lateralised whole and regional thalamic segmentations were estimated using a Bayesian joint structural and DWI data segmentation method, which combines information from a previous probabilistic atlas incorporating histologically identified nuclei together with likelihood models for both structural and diffusion data (Tregidgo et al, 2023). The algorithm requires the bias field corrected image and whole brain parcellation yielded by the recon-all pipeline, and a diffusion tensor imaging (DTI) model as fitted by TRACULA (Maffei et al, 2021; Yendiki et al, 2011).…”

“…To avoid over-inflation of statistical estimates for smaller subnuclei volumes, the 24 nuclei labels from each hemisphere were merged to create subregions. Label merging decisions were informed by the histological atlas utilised in the development of the segmentation method (Morel et al, 1997; Tregidgo et al, 2023). The thalamic subgroups utilised are also broadly consistent with commonly employed grouping based on anatomical location (Grodd et al, 2020).…”

“…One key limitation of previous thalamic volumetric studies is the treatment of the thalamus as a uniform structure. While there is commonality in cellular properties across the entire thalamus, it is structurally heterogenous, with at least 50 subnuclei identified depending on the degree and method of classification (Tregidgo et al, 2023). These subnuclei contribute variably to function, enabled by differences in connectivity targets, neurochemical receptors and transporters, and aspects of cytoarchitecture (Antonucci et al, 2021; Keun et al, 2021).…”

Thalamic contributions to psychosis susceptibility: Evidence from co‐activation patterns accounting for intra‐seed spatial variability (μCAPs)

“…However, the thalamus is also a complex, multi-faceted area divided into several subnuclei, including the dorsal thalamus, ventral thalamus, and the intralaminar nuclei (Herrero et al, 2002;Tregidgo et al, 2023).…”

“…However, the thalamus is also a complex, multi‐faceted area divided into several subnuclei, including the dorsal thalamus, ventral thalamus, and the intralaminar nuclei (Herrero et al, 2002; Tregidgo et al, 2023). Studying the subnuclei of the thalamus is essential for understanding the neural mechanisms underlying several brain functions and how they may relate.…”