Patient-tailored connectomics visualization for the assessment of white matter atrophy in traumatic brain injury

Abstract

Available approaches to the investigation of traumatic brain injury (TBI) are frequently hampered, to some extent, by the unsatisfactory abilities of existing methodologies to efficiently define and represent affected structural connectivity and functional mechanisms underlying TBI-related pathology. In this paper, we describe a patient-tailored framework which allows mapping and characterization of TBI-related structural damage to the brain via multimodal neuroimaging and personalized connectomics. Specifically, we introduce a graphically driven approach for the assessment of trauma-related atrophy of white matter connections between cortical structures, with relevance to the quantification of TBI chronic case evolution. This approach allows one to inform the formulation of graphical neurophysiological and neuropsychological TBI profiles based on the particular structural deficits of the affected patient. In addition, it allows one to relate the findings supplied by our workflow to the existing body of research that focuses on the functional roles of the cortical structures being targeted. A graphical means for representing patient TBI status is relevant to the emerging field of personalized medicine and to the investigation of neural atrophy.

Keywords: DTI; atrophy; connectomics; rehabilitation; traumatic brain injury.

Figure 1

Sample MR images for three TBI cases labeled as patient 1 (A), patient 2 (B), and patient 3 (C). Images are displayed in radiological convention. The sequence types shown include T₂, GRE T₂, and FLAIR. Red, green, and blue arrows identify the locations of three different insults.

Figure 2

Three-dimensional models of automatically segmented TBI pathology superposed on transparent models of the brain for each patient. Edema and hemorrhage are shown in green and red, respectively. To guide the eye in localizing three distinct lesions in the 3D models, color-coded (red, green, and blue) arrows are provided to identify the locations of the insults indicated in Figure 1 using corresponding colors. Each column (A, B, and C) corresponds to one of the three cases (1, 2 or 3, respectively).

Figure 3

FreeSurfer parcelation of a sample brain. Displayed are the surface corresponding to the WM–GM interface (A), the pial surface (B), and the inflated surface (C), with each parcelated anatomical region displayed in a different color according to the color labeling methodology described in the Section “Methods” (see also Appendix).

Figure 4

The connectogram (reconstructed connectomic profile) of patient 1. Each cortical structure is assigned a unique RGB color, as explained in the Section “Methods,” and the colors assigned to the parcelated regions on the outermost ring of the connectogram are identical to those of the corresponding cortical structures in Figure 3. Brown links between connectogram nodes indicate WM fibers between a region affected by pathology and another that was not affected, based on the automatic segmentations of pathology shown in Figure 2. Similarly, gray links indicate WM fibers between two regions that were both affected. Circular color maps are displayed below the connectogram for links (first two maps, white to brown and white to black) and for the metrics encoded on the five innermost rings of the connectogram. The range for each of these metrics is from their minimum to their maximum assumed value.

Figure 5

As in Figure 4, for patient 2.

Figure 6

As in Figure 4, for patient 3.

Figure 7

Connectogram of the atrophy profile for patient 1. Links displayed indicate connections that suffered large atrophy from the acute baseline to the chronic follow-up time point. Link transparency encodes the percentage change Δ in fiber density (see Methods), in the range [min{|Δ|}, max{|Δ|}], with larger changes (more negative values of Δ) being encoded by more opaque hues of blue. The lowest color opacity corresponds to the smallest absolute value of the percentage change that is greater than the chosen threshold of 20%, and the highest opacity corresponds to the maximum absolute value of the change in fiber density.

Figure 8

As in Figure 7, for patient 2.

Figure 9

As in Figure 7, for patient 3.