Reconstructing the somatotopic organization of the corticospinal tract remains a challenge for modern tractography methods
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Abstract (arXiv)
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.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 4 of its 160 references that are in the map. First posted on arXiv 9 Jun 2023.
Builds on
4 of 160 references.
References · 4
- 2018TractSeg - Fast and accurate white matter tract segmentationcited by 50
- 2015The White Matter Query Language: A Novel Approach for Describing Human White Matter Anatomycited by 13
- 2019Combined tract segmentation and orientation mapping for bundle-specific tractographycited by 10
- 2019Mitigating Gyral Bias in Cortical Tractography via Asymmetric Fiber Orientation Distributionscited by 3
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Citing papers per year: 2024: 4; 2025: 3.
7 papers.
- 2024TractGraphFormer: Anatomically Informed Hybrid Graph CNN-Transformer Network for Interpretable Sex and Age Prediction from Diffusion MRI Tractographycited by 6
- 2024Cross-domain Fiber Cluster Shape Analysis for Language Performance Cognitive Score Predictioncited by 5
- 2024The shape of the brain's connections is predictive of cognitive performance: an explainable machine learning studycited by 3
- 2024White Matter Geometry-Guided Score-Based Diffusion Model for Tissue Microstructure Imputation in Tractography Imagingcited by 2
- 2025TractCloud-FOV: Deep Learning-based Robust Tractography Parcellation in Diffusion MRI with Incomplete Field of Viewcited by 1
- 2025AGFS-Tractometry: A Novel Atlas-Guided Fine-Scale Tractometry Approach for Enhanced Along-Tract Group Statistical Comparison Using Diffusion MRI Tractographycited by 0
- 2025A Novel Dual-Stream Framework for dMRI Tractography Streamline Classification with Joint dMRI and fMRI Datacited by 0
- 2025A Novel Dual-Stream Framework for dMRI Tractography Streamline Classification with Joint dMRI and fMRI Data24 Nov 2025
- 2025AGFS-Tractometry: A Novel Atlas-Guided Fine-Scale Tractometry Approach for Enhanced Along-Tract Group Statistical Comparison Using Diffusion MRI Tractography12 Jul 2025
- 2025TractCloud-FOV: Deep Learning-based Robust Tractography Parcellation in Diffusion MRI with Incomplete Field of View28 Feb 2025
- 2024The shape of the brain's connections is predictive of cognitive performance: an explainable machine learning study19 Oct 2024
- 2024White Matter Geometry-Guided Score-Based Diffusion Model for Tissue Microstructure Imputation in Tractography Imaging28 Jul 2024
- 2024TractGraphFormer: Anatomically Informed Hybrid Graph CNN-Transformer Network for Interpretable Sex and Age Prediction from Diffusion MRI Tractography11 Jul 2024
- 2024Cross-domain Fiber Cluster Shape Analysis for Language Performance Cognitive Score Prediction27 Mar 2024