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The structural complexity of the thalamus, due to its mixed composition of gray and white matter, make it challenging to disjoint and quantify each tissue contribution to the thalamic anatomy. This work promotes the use of partial-volume-based over probabilistic-based tissue segmentation approaches to better capture thalamic gray matter differences between patients at different stages of psychosis (early and chronic) and healthy controls. The study was performed on a cohort of 23 patients with schizophrenia, 41 with early psychosis and 69 age and sex-matched healthy subjects. Six tissue segmentation approaches were employed to obtain the gray matter concentration/probability images. The statistical tests were applied at three different anatomical scales: whole thalamus, thalamic subregions and voxel-wise. The results suggest that the partial volume model estimation of gray matter is more sensitive to detect atrophies within the thalamus of patients with psychosis. However all the methods detected gray matter deficit in the pulvinar, particularly in early stages of psychosis. This study demonstrates also that the gray matter decrease varies nonlinearly with age and between nuclei. While a gray matter loss was found in the pulvinar of patients in both stages of psychosis, reduced gray matter in the mediodorsal was only observed in early psychosis subjects. Finally, our analyses point to alterations in a sub-region comprising the lateral posterior and ventral posterior nuclei. The obtained results reinforce the hypothesis that thalamic gray matter assessment is more reliable when the tissues segmentation method takes into account the partial volume effect., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Purpose: The thalamus is an important brain structure and neurosurgical target, but its constituting nuclei are challenging to image non-invasively. Recently, susceptibility-weighted imaging (SWI) at ultra-high field has shown promising capabilities for thalamic nuclei mapping. In this work, several methodological improvements were explored to enhance SWI quality and contrast, and specifically its ability for thalamic imaging., Methods: High-resolution SWI was performed at 7T in healthy participants, and the following techniques were applied: (a) monitoring and retrospective correction of head motion and B 0 perturbations using integrated MR navigators, (b) segmentation and removal of venous vessels on the SWI data using vessel enhancement filtering, and (c) contrast enhancement by tuning the parameters of the SWI phase-magnitude combination. The resulting improvements were evaluated with quantitative metrics of image quality, and by comparison to anatomo-histological thalamic atlases., Results: Even with sub-millimeter motion and natural breathing, motion and field correction produced clear improvements in both magnitude and phase data quality (76% and 41%, respectively). The improvements were stronger in cases of larger motion/field deviations, mitigating the dependence of image quality on subject performance. Optimizing the SWI phase-magnitude combination yielded substantial improvements in image contrast, particularly in the thalamus, well beyond previously reported SWI results. The atlas comparisons provided compelling evidence of anatomical correspondence between SWI features and several thalamic nuclei, for example, the ventral intermediate nucleus. Vein detection performed favorably inside the thalamus, and vein removal further improved visualization., Conclusion: Altogether, the proposed developments substantially improve high-resolution SWI, particularly for thalamic nuclei imaging., (© 2020 International Society for Magnetic Resonance in Medicine.)

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.

The lack of possibility to directly visualize the Ventro-intermediate thalamic nucleus (Vim) on current routine MRI lead to application of indirect targeting methods in stereotactic neurosurgical procedures, such as Gamma Knife Surgery (GKS) and Deep Brain Stimulation (DBS), for treatment of drug-resistant tremor. Recently, our group proposed an automated robust and reproducible method across healthy subjects and tremor patients for parceling the thalamus in seven main groups of nuclei while exploring the local diffusion information from the spherical harmonics representation of the orientation distribution functions (ODFs) in k-means clustering framework. One among the resulting parcel is the Ventral-Lateral-Ventral group (VLV) enclosing all motor-related nuclei including the Vim. We aim at further automatic subdivision the VLV cluster. To this end, within the VLV, we first build a k-nn graph with edges corresponding to the respective ODFs distances and then, we perform a partition in 3 sub-clusters using the Normalized Cut algorithm. The outcome of the proposed subdivision was compared to the radiological response in the follow-up images of 17 patients treated for tremor with GKS unilaterally. The MRI protocol included pre-operative diffusion-weighted images with 64 (or 72) gradient direction, b=1000s/mm2 and voxel size of 2.2x2.2x2.2mm3, pre-operative and post-operative MPRAGEs with isotropic resolution of ~1mm3, all of them acquired at field of 3T. In general, the sub-partition followed a spatial-distribution pattern and for 12 out of 17 cases we observed that one specific sub-cluster encloses entirely or the major part of the contrast enhancement corresponding to the GKS target that appeared on the follow-up images.The evaluation of the sub-partition outcome was further extended in one additional tremor patient treated with DBS, bilaterally. Similar pre-operative MRI data as for the GKS-treated patients was acquired. We observed that in each hemisphere both initial targeting point and the final position of the electrode are inside the anticipated sub-cluster. This study shows that the diffusion-MRI-based sub-clustering of the VLV thalamic nuclei could potentially allow, in an automated manner, to narrow the area of Vim's localization. Our preliminary results will be further investigated in a larger cohort of patients (treated by either GKS or DBS) and on diffusion images with higher spatial resolution. [ABSTRACT FROM AUTHOR]