A Novel Deep Clustering Framework for Fine-Scale Parcellation of Amygdala Using dMRI Tractography

The amygdala plays a vital role in emotional processing and exhibits structural diversity that necessitates fine-scale parcellation for a comprehensive understanding of its anatomico-functional correlations. Diffusion MRI tractography is an advanced imaging technique that can estimate the brain's white matter structural connectivity to potentially reveal the topography of the amygdala for studying its subdivisions. In this work, we present a deep clustering pipeline to perform automated, fine-scale parcellation of the amygdala using diffusion MRI tractography. First, we incorporate a newly proposed deep learning approach to enable accurate segmentation of the amygdala directly on the dMRI data. Next, we design a novel streamline clustering-based structural connectivity feature for a robust representation of voxels within the amygdala. Finally, we improve the popular joint dimensionality reduction and k-means clustering approach to enable amygdala parcellation at a finer scale. With the proposed method, we obtain nine unique amygdala parcels. Experiments show that these parcels can be consistently identified across subjects and have good correspondence to the widely used coarse-scale amygdala parcellation.

Reconstructing the somatotopic organization of the corticospinal tract remains a challenge for modern tractography methods

The corticospinal tract (CST) is a critically important white matter fiber tract in the human brain that enables control of voluntary movements of the body. Diffusion MRI tractography is the only method that enables the study of the anatomy and variability of the CST pathway in human health. In this work, we explored the performance of six widely used tractography methods for reconstructing the CST and its somatotopic organization. We perform experiments using diffusion MRI data from the Human Connectome Project. Four quantitative measurements including reconstruction rate, the WM-GM interface coverage, anatomical distribution of streamlines, and correlation with cortical volumes to assess the advantages and limitations of each method. Overall, we conclude that while current tractography methods have made progress toward the well-known challenge of improving the reconstruction of the lateral projections of the CST, the overall problem of performing a comprehensive CST reconstruction, including clinically important projections in the lateral (hand and face area) and medial portions (leg area), remains an important challenge for diffusion MRI tractography.