Robust thalamic nuclei segmentation method based on local diffusion magnetic resonance properties

Abstract

The thalamus is an essential relay station in the cortical–subcortical connections. It is characterized by a complex anatomical architecture composed of numerous small nuclei, which mediate the involvement of the thalamus in a wide range of neurological functions. We present a novel framework for segmenting the thalamic nuclei, which explores the orientation distribution functions (ODFs) from diffusion magnetic resonance images at 3 T. The differentiation of the complex intra-thalamic microstructure is improved by using the spherical harmonic (SH) representation of the ODFs, which provides full angular characterization of the diffusion process in each voxel. The clustering was performed using the k-means algorithm initialized in a data-driven manner. The method was tested on 35 healthy volunteers and our results show a robust, reproducible and accurate segmentation of the thalamus in seven nuclei groups. Six of them closely matched the anatomy and were labeled as anterior, ventral anterior, medio-dorsal, ventral latero-ventral, ventral latero-dorsal and pulvinar, while the seventh cluster included the centro-lateral and the latero-posterior nuclei. Results were evaluated both qualitatively, by comparing the segmented nuclei to the histological atlas of Morel, and quantitatively, by measuring the clusters’ extent and the clusters’ spatial distribution across subjects and hemispheres. We also showed the robustness of our approach across different sequences and scanners, as well as intra-subject reproducibility of the segmented clusters using additional two scan–rescan datasets. We also observed an overlap between the path of the main long-connection tracts passing through the thalamus and the spatial distribution of the nuclei identified with our clustering algorithm. Our approach, based on SH representations of the ODFs, outperforms the one based on angular differences between the principle diffusion directions, which is considered so far as state-of-the-art method. Our findings show an anatomically reliable segmentation of the main groups of thalamic nuclei that could be of potential use in many clinical applications.Electronic supplementary materialThe online version of this article (doi:10.1007/s00429-016-1336-4) contains supplementary material, which is available to authorized users.

Partial‐volume modeling reveals reduced gray matter in specific thalamic nuclei early in the time course of psychosis and chronic schizophrenia

“…For each subject, the left and right thalamus were segmented by combining T1w and diffusion‐weighted MRI ( DWI ), following the method described in (Battistella et al, 2017). Sub‐cortical regions were segmented from T1w images by using FreeSurfer (Fischl et al, 2002).…”

Advanced Imaging and Direct Targeting of the Motor Thalamus and Dentato-Rubro-Thalamic Tract for Tremor: A Systematic Review

“…More recently, the same group’s segmentation was automated using a multiatlas segmentation method by Su et al [59] and tested on 20 healthy controls and 15 patients with multiple sclerosis, with Dice coefficient of 0.79 for ventral lateral posterior nucleus (compared to manual segmentation guided by Morel atlas). Najdenovska et al [6] recently reported 9 healthy controls, and 2 ET patients analyzed with 7T SWI imaging based on the work of Abosch et al [18] In their study, the manually delineated Vim at 7T correlated well with the Vim target chosen by Guiot’s method [60] and with automated multiatlas and DTI-based segmentation by their group’s previously reported method (see Battistella et al [25] below). Guiot’s point was within or at the edge of the 7T-visible Vim in all cases and in the ventral portion in 7 of 9 cases.…”

“…On inspection, these corresponded roughly with Morel nuclear clusters (although not individual nuclei), and pDTT with seeds in these 5 clusters seemed to reproduce the expected connectivity of those regions, including connection of the ventrolateral cluster to the premotor cortex. More recently, Battistella et al [25] presented an algorithm for automated parcellation of the thalamus into 7 nuclear groups, including a ventrolateral group, and showed consistent parcellation across all subjects, although no clinical correlation or quantitative comparison to an anatomic atlas was made.…”

“…Furthermore, these methods rely on aniso­tropic properties of white matter, whereas the thalamus is a largely gray-matter structure, resulting in noisy estimates of the principal tensor orientation. Not surprisingly, the most stable method [25] is confined to 7 nuclei, 1 of which is a composite of anatomic nuclei and does not correspond to a physical nucleus.…”

“…In recent years, a wide variety of MRI-based techniques have been used to parcellate the thalamus and directly visualize the Vim. These include the use of ultrahigh-field strength MRI [18, 19], novel MRI sequences at standard clinical field strengths [20, 21], clustering based on local or global diffusion-tensor properties [22-25], structural connectivity [26, 27], or functional connectivity [28, 29]. A related focus has been the direct identification of the dentato-rubro-thalamic tract (DRTT) either prior to, or just at, its entrance into the thalamus.…”