A novel approach for improved tractography and quantitative analysis of probabilistic fibre tracking curves

Abstract

This paper presents a novel approach for improved diffusion tensor fibre tractography, aiming to tackle a number of the limitations of current fibre tracking algorithms, and describes a quantitative analysis tool for probabilistic tracking algorithms. We consider the sampled random paths generated by a probabilistic tractography algorithm from a seed point as a set of curves, and develop a statistical framework for analysing the curve-set geometrically that finds the average curve and dispersion measures of the curve-set statistically. This study is motivated firstly by the goal of developing a robust fibre tracking algorithm, combining the power of both deterministic and probabilistic tracking methods using average curves. These typical curves produce strong connections to every anatomically distinct fibre tract from a seed point and also convey important information about the underlying probability distribution. These single well-defined trajectories overcome a number of the limitations of deterministic and probabilistic approaches. A new clustering algorithm for branching curves is employed to separate fibres into branches before applying the averaging methods. Secondly, a quantitative analysis tool for probabilistic tracking methods is introduced using statistical measures of curve-sets. Results on phantom and in vivo data confirm the efficiency and effectiveness of the proposed approach for the tracking algorithm and the quantitative analysis of the probabilistic methods.

Psychoradiological patterns of small-world properties and a systematic review of connectome studies of patients with 6 major psychiatric disorders

“…The tracking procedure used in deterministic tractography terminates when it reaches regions with fibre crossings, 38 and this tends to reduce sensitivity. Probabilistic tractography overcomes this shortcoming, and offers a natural approach to modelling uncertainty by generating multiple curves originating from a seed point, 39 providing a more comprehensive picture of connectivity. The probabilistic algorithm has better test-retest reliability and is more robust than deterministic tractography in areas of high uncertainty (notably fibre crossings).…”

The Role of Probabilistic Tractography in the Surgical Treatment of Thalamic Gliomas

“…In patients 2, 3, and 5, an occipital, transtentorial approach through the quadrigeminal cistern may have been a good alternative as proposed by surgeon 1 ( Table 2). The technical limitations of probabilistic tractography also apply to our study 37,54,55 (eg, resolution of DTI, crossing fibers, thresholding, manual delineation of masks, false-positive connectivity within the tumor). Thalamic segmentation cannot determine the border of thalamic structures in complete consistency with the anatomy, but inaccuracy may not be greater than a few millimeters.…”

Morphological, Structural, and Functional Networks Highlight the Role of the Cortical-Subcortical Circuit in Individuals With Subjective Cognitive Decline

“…In terms of structural networks based on DTI, most previous structural networks were constructed using deterministic fibre tracking algorithms (Shu et al, 2018;Yan et al, 2018). In comparison, the probabilistic fibre tracking algorithm of this study considered the uncertainty of fibre direction estimation, thereby improving the accuracy of white matter fibre tracking (Ratnarajah et al, 2012). Regarding the distribution of hubs and consensus connections of structural network, our results indicated that the discriminative features of structural network based on DTI and the morphological network based on sMRI involved in overlapped and multiple cortical-subcortical brain regions, such as the frontal lobe, PhG, Tha, and BG.…”