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

Abstract

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. The CST exhibits a somatotopic organization, which means that the motor neurons that control specific body parts are arranged in order within the CST. Diffusion magnetic resonance imaging (MRI) tractography is increasingly used to study the anatomy of the CST. However, despite many advances in tractography algorithms over the past decade, modern, state-of-the-art methods still face challenges. In this study, we compare the performance of six widely used tractography methods for reconstructing the CST and its somatotopic organization. These methods include constrained spherical deconvolution (CSD) based probabilistic (iFOD1) and deterministic (SD-Stream) methods, unscented Kalman filter (UKF) tractography methods including multi-fiber (UKF2T) and single-fiber (UKF1T) models, the generalized q-sampling imaging (GQI) based deterministic tractography method, and the TractSeg method. We investigate CST somatotopy by dividing the CST into four subdivisions per hemisphere that originate in the leg, trunk, hand, and face areas of the primary motor cortex. A quantitative and visual comparison is performed using diffusion MRI data (N = 100 subjects) from the Human Connectome Project. Quantitative evaluations include the reconstruction rate of the eight anatomical subdivisions, the percentage of streamlines in each subdivision, and the coverage of the white matter-gray matter (WM-GM) interface. CST somatotopy is further evaluated by comparing the percentage of streamlines in each subdivision to the cortical volumes for the leg, trunk, hand, and face areas. Overall, UKF2T has the highest reconstruction rate and cortical coverage. It is the only method with a significant positive correlation between the percentage of streamlines in each subdivision and the volume of the corresponding motor cortex. However, our experimental results show that all compared tractography methods are biased toward generating many trunk streamlines (ranging from 35.10% to 71.66% of total streamlines across methods). Furthermore, the coverage of the WM-GM interface in the largest motor area (face) is generally low (under 40%) for all compared tractography methods. Different tractography methods give conflicting results regarding the percentage of streamlines in each subdivision and the volume of the corresponding motor cortex, indicating that there is generally no clear relationship, and that reconstruction of CST somatotopy is still a large challenge. 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 areas) and medial portions (leg area), remains an important challenge for diffusion MRI tractography.

Keywords: corticospinal tract; diffusion magnetic resonance imaging; motor cortex; somatotopic organization; tractography.

FIGURE 1

A schematic anatomical overview of the CST and its somatotopic organization (Ghimire et al., ; Pan et al., 2012). There are four major subdivisions shown: face fibers (yellow), hand fibers (blue), trunk fibers (green), and leg fibers (red). These subdivisions are responsible for controlling corresponding body muscles. CST, corticospinal tract.

FIGURE 2

Crossing region of the corpus callosum (pink), the Superior Longitudinal Fasciculus (cyan), and the CST in the centrum semiovale. (a) 3D oblique superior–anterior view of bundle streamlines and four motor areas, (b) oblique coronal cross‐section of five bundle streamlines. CST, corticospinal tract.

FIGURE 3

Each mask for tractography (green surface) fully covers the precentral cortex (red surface) and brainstem (blue surface). (b), (c), and (d) are the 3D renderings of the mask from the sagittal, axial, and coronal view, respectively.

FIGURE 4

Exclusion ROI. Streamlines passing through the middle green line will be removed. (b) Inclusion ROIs: The brainstem region (yellow) and the precentral cortex, which includes four anatomical motor areas from each hemisphere (red: leg, green: trunk, blue: hand, orange: face). ROI, region of interest.

FIGURE 5

(a) Visual comparison of the CST reconstructed using the six tractography methods. Three subjects are selected as examples: one with low tractography performance (105115), one with high tractography performance (133928), and one with typical tractography performance (100307). Each anatomical subdivision is visualized in a specific color (face: orange, hand: blue, trunk: green, leg: red). (b) Voxel‐based tract heatmaps of CST streamlines based on the 100 HCP subjects. The value of a voxel in the heatmaps represents the number of subjects that have fibers passing through the voxel. CST, corticospinal tract; HCP, Human Connectome Project.

FIGURE 6

The reconstruction rate of the complete CST was significantly different across the six compared tractography methods (ANOVA, p < .0001). Post hoc two‐group McNemar's tests with significant results are indicated by asterisks. *p < .05, **p < .01, ****p < .0001. Each bar indicates the mean value. ANOVA, analysis of variance; CST, corticospinal tract.

FIGURE 7

Reconstruction rate of each anatomical subdivision using different tractography methods. Each bar indicates the mean value.

FIGURE 8

WM–GM interface coverage of the CST. The coverage of the WM–GM interface was significantly different across the six compared tractography methods (ANOVA, p < .0001). Post hoc two‐group t tests with significant results are indicated by asterisks. ****p < .0001. On each violin plot, the central circle indicates the median, and the bottom and top edges of the box indicate the 25th and 75th percentiles, respectively. ANOVA, analysis of variance; CST, corticospinal tract; WM–GM, white matter–gray matter.

FIGURE 9

WM–GM interface coverage of the anatomical subdivisions. For all tractography methods, the coverage of the WM–GM interface was significantly different across the four anatomical subdivisions (ANOVA, p < .0001). Post hoc two‐group t tests with significant results are indicated by asterisks. **p < .01, ****p < .0001. On each violin plot, the central circle indicates the median, and the bottom and top edges of the box indicate the 25th and 75th percentiles, respectively. ANOVA, analysis of variance; WM–GM, white matter–gray matter.

FIGURE 10

Visualization of the white matter–gray matter interface surface including streamline termination points for each tractography method. Pink regions indicate at least one fiber termination point, while white regions indicate no fibers passed. Note the pink regions are mainly seen on gyral crowns, while sulcal regions are predominantly shown in white. One typical subject (100307) is selected. Each anatomical subdivision is visualized in a specific color (face: orange, hand: blue, trunk: green, leg: red).

FIGURE 11

(a) The percentage of motor cortical volume in each motor area. All percentages were significantly different across the four motor areas (ANOVA, p < .0001). Post hoc pairwise t tests with significant results are indicated by asterisks. ****p < .0001. Each bar indicates the mean value, and the error bar indicates the corresponding standard error. (b) Anatomical distribution of streamlines across anatomical subdivisions for each tractography method. For all tractography methods, the percentage of streamlines was significantly different across the four anatomical motor areas (ANOVA, p < .0001). Post hoc pairwise t tests with significant results are indicated by asterisks. ****p < .0001. On each violin plot, the central circle indicates the median, and the bottom and top edges of the box indicate the 25th and 75th percentiles, respectively. ANOVA, analysis of variance.

FIGURE 12

Correlations between the percentage of streamlines and the percentage of volume in each motor area. The correlation coefficient of each tractography method is reported.