Improving the clinical correlation of multiple sclerosis black hole volume change by paired-scan analysis

The change in T1-hypointense lesion (“black hole”) volume is an important marker of pathological progression in multiple sclerosis (MS). Black hole boundaries often have low contrast and are difficult to determine accurately and most (semi‐)automated segmentation methods first compute the T2-hyperintense lesions, which are a superset of the black holes and are typically more distinct, to form a search space for the T1w lesions. Two main potential sources of measurement noise in longitudinal black hole volume computation are partial volume and variability in the T2w lesion segmentation. A paired analysis approach is proposed herein that uses registration to equalize partial volume and lesion mask processing to combine T2w lesion segmentations across time. The scans of 247 MS patients are used to compare a selected black hole computation method with an enhanced version incorporating paired analysis, using rank correlation to a clinical variable (MS functional composite) as the primary outcome measure. The comparison is done at nine different levels of intensity as a previous study suggests that darker black holes may yield stronger correlations. The results demonstrate that paired analysis can strongly improve longitudinal correlation (from -0.148 to -0.303 in this sample) and may produce segmentations that are more sensitive to clinically relevant changes.