White matter tract-specific quantitative analysis in multiple sclerosis: Comparison of optic radiation reconstruction techniques

Abstract

The posterior visual pathway is commonly affected by multiple sclerosis (MS) pathology that results in measurable clinical and electrophysiological impairment. Due to its highly structured retinotopic mapping, the visual pathway represents an ideal substrate for investigating patho-mechanisms in MS. Therefore, a reliable and robust imaging segmentation method for in-vivo delineation of the optic radiations (OR) is needed. However, diffusion-based tractography approaches, which are typically used for OR segmentation are confounded by the presence of focal white matter lesions. Current solutions require complex acquisition paradigms and demand expert image analysis, limiting application in both clinical trials and clinical practice. In the current study, using data acquired in a clinical setting on a 3T scanner, we optimised and compared two approaches for optic radiation (OR) reconstruction: individual probabilistic tractography-based and template-based methods. OR segmentation results were applied to subjects with MS and volumetric and diffusivity parameters were compared between OR segmentation techniques. Despite differences in reconstructed OR volumes, both OR lesion volume and OR diffusivity measurements in MS subjects were highly comparable using optimised probabilistic tractography-based, and template-based, methods. The choice of OR reconstruction technique should be determined primarily by the research question and the nature of the available dataset. Template-based approaches are particularly suited to the semi-automated analysis of large image datasets and have utility even in the absence of dMRI acquisitions. Individual tractography methods, while more complex than template based OR reconstruction, permit measurement of diffusivity changes along fibre bundles that are affected by specific MS lesions or other focal pathologies.

Fig 1. Optic radiation reconstruction pipeline using probabilistic tractography with ConTrack [33].

Fig 2

(A1-A3) Template-OR constructed from 35 healthy controls using ConTrack probabilistic tractography [33], represented as a probability map; (B1-B3) OR probability map derived from the Jülich histological atlas [8] (Histology-OR); (C1-C3) OR binary template thresholded at 0.32 from probability map shown in A; (D1-D3) 3D view of OR binary template.

Fig 3. Comparison of Template-OR (Red) and PT-OR (Blue) for all 35 healthy controls in subjects’ native space.

Prior to non-linearly mapping the Template-OR from ICBM space to the subjects’ native space, the probability weighted template-OR (in ICBM space) was thresholded at 32% and binarised. DSC are labelled at the bottom right corner of each pair of ORs.

Fig 4. Comparison of OR volume estimation by PT-OR, Template-OR and Histology-OR.

Fig 5. Inter-subject variability of OR volume estimated by PT-OR (blue), template-OR (Green) and Histology-OR.

Fig 6. Lesion distribution along the optic radiation in subjects with multiple sclerosis.

Fig 7. Comparison of OR lesion volume estimated by PT-OR, Template-OR and Histology-OR.

The total lesion volume is shown as logarithmic values.

Fig 8. Correlations between OR volumes and OR lesion volumes.

Fig 9. Comparison of OR diffusivity metrics between PT-OR and Template-OR approaches.

Row (a), (c), (e) are scatter plots with linear fitting; x-axis is PT-OR measurement and y-axis is Template-OR measurement. r is the Pearson’s correlation coefficient. Row (b), (d), (f) are Bland-Altman plots for comparing two methods. x-axis is the mean of PT-OR and Template-OR measurements. y-axis is the difference between PT-OR and Template-OR measurements.

Fig 10. Comparison of OR diffusivity metrics between PT-OR and Histology-OR approaches.

Row (a), (c), (e) are scatter plots with linear fitting; x-axis is PT-OR measurement and y-axis is Histology-OR measurement. r is the Pearson’s correlation coefficient. Row (b), (d), (f) are Bland-Altman plots for comparing two methods. x-axis is the mean of PT-OR and Histology-OR measurements. y-axis is the difference between PT-OR and Histology-OR measurements.

Fig 11. Comparison of OR diffusivity metrics between Template-OR and Histology-OR approaches.

Row (a), (c), (e) are scatter plots with linear fitting; x-axis is Template-OR measurement and y-axis is Histology-OR measurement. r is the Pearson’s correlation coefficient. Row (b), (d), (f) are Bland-Altman plots for comparing two methods. x-axis is the mean of Template-OR and Histology-OR measurements. y-axis is the difference between Template-OR and Histology-OR measurement.