Diffusion tensor imaging fiber tracking with local tissue property sensitivity: phantom and in vivo validation

Abstract

Diffusion tensor imaging (DTI) provides directional information that can be used to delineate brain white matter connections noninvasively via fiber tracking. The most commonly used methods for tractography are based on the streamline tracking algorithm for track propagation and a set of empirically and globally defined criteria for track termination. In this study, we propose a streamline tracking algorithm with high-order propagation accuracy and a single termination criterion based on tissue property to minimize user intervention and biases introduced during tracking process. These advantages and the agreement with histological reports are demonstrated in our tracking results in phantoms and in humans.

Fig. 1

Pseudo-speed in a continuous field becomes an indicator or measurement of local vector field coherence. Tracking speed will be slower in gray matter regions.

Fig. 2

A schematic illustration of the unified termination criterion based on the pseudo-speed. The red point represents a corrupted vector which could produce incorrect fiber forks when tracks pass nearby. With the unified termination criterion, track A survives a sharp turn because it has high tracking speed. Track B and C illustrate wrong forks which have less sharp turning angles than track A, but would terminate automatically in gray matter due to their slow tracking speed. Should a turning angle limit be used, track A could be terminated prematurely while tracks B or C could survive, leading to a premature termination or a false positive.

Fig. 3

Tracking results inside the half elliptical band. The top and bottom of the 3D band are transparent to demonstrate the track pathways inside the band. a) Euler's method with FA=0.15 thresholding and turning angle limit at 30°. b) Euler's method with FA=0.15 thresholding but without turning angle limit. The deviation is mainly caused by the noisy tensor field and accumulated propagation errors. Fewer tracks stay inside the white matter region as the streamline propagation goes on. c) Proposed fiber tracking method. Most fiber tracks are recovered from the noisy tensor field.

Fig. 4

Tracking the uncinate fascicles. Euler's method allowed 6 successful tracks (4a) while our method led to 34 successful tracks with improved spatial details (4b). The coronal slice is the same as the slice shown in Fig.5 and Fig. 6.

Fig. 4

Tracking the uncinate fascicles. Euler's method allowed 6 successful tracks (4a) while our method led to 34 successful tracks with improved spatial details (4b). The coronal slice is the same as the slice shown in Fig.5 and Fig. 6.

Fig. 5

The coronal slice location used to investigate the cross-sectional area circumscribed by tracked fibers.

Fig. 6

The regions where the tracks pass through the coronal slice in Fig. 5. The pixel arrangement is shown in Fig. 7.

Fig. 7

A graphic illustration of the cross-sectional area determination. The left column shows the cross-sectional pixels tracked by Euler's method, and the right column shows the cross-sectional pixels tracked by our method.