Validation of a semi-automated method to quantify lesion volume changes in multiple sclerosis on 2D proton-density-weighted scans based on image subtraction.

Background: The detection and quantification of changes in white matter lesions in the brain is important to monitor treatment effects in patients with multiple sclerosis (MS). Existing automatic tools predominantly require FLAIR images as input which are not always available, or only focus on new/enlarging activity. Therefore, we developed and validated a semi-automated method to quantify lesion volume changes based on 2D proton-density (PD)-weighted images and image subtraction. This semi-automated method provides insight in both "positive" activity (defined as new and enlarging lesions) and "negative" activity (disappearing and shrinking lesions). Methods: Yearly MRI scans of patients with early MS from the REFLEX/REFLEXION studies were used. The maximum follow-up period was 5 years. Two PD-weighted images were normalized, registered to a common halfway-space, intensity-matched, and subsequently subtracted. Within manual lesion masks, lesion changes were quantified using a subtraction intensity threshold and total lesion volume change (TLVC) was calculated. Reproducibility was measured by assessing transitivity, specifically, we calculated the intraclass correlation coefficient for the absolute agreement (ICC Results: Reproducibility was excellent, with ICC Discussion: The semi-automated method to quantify lesion volume changes has excellent reproducibility and overall good accuracy. The amount of atrophy and especially lesion volume (change) should be taken into account when applying this method, as an increase in these variables might affect the quality of the results. Conclusion: Overall, the semi-automated subtraction method allows a valid and reliable quantitative investigation of lesion volume changes over time in (early) MS for follow-up periods up to 5 years.