Monitoring disease activity and progression in primary progressive multiple sclerosis using MRI: sub-voxel registration to identify lesion changes and to detect cerebral atrophy

Objective To explore the potential usefulness of two new magnetic resonance imaging (MRI) analysis techniques for assessment of progressive cerebral atrophy and T2 lesion activity in primary progressive multiple sclerosis (PPMS), and thereby assess the relationship between MRI activity and atrophy in this patient group. Background Measurements of cerebral atrophy and net change in T2 lesion volumes are currently used as surrogate markers of disease progression in multiple sclerosis (MS). However, manual implementation of these techniques is time-consuming and the pathological specificity of T2 lesion change is low. Advances in serial scan registration have facilitated the development of a new, fully-automated technique to measure cerebral volume (SIENA; Structural Image Evaluation, using Normalisation, of Atrophy), and a technique to measure the total new T2 lesion volume selectively (MRI difference imaging). Method SIENA measures changes in cerebral size based on sub-voxel detection of shifts in edge contours. The lesion difference imaging method measures differences in lesion volumes over time as defined by a semi-automated outlining technique. The two new methods were validated against the T2 lesion volume contour technique and a previously described measure of partial brain volume (which uses six slices centred on the presumed area of greatest change around the lateral ventricles). All were applied to serially acquired MR images from a cohort of 39 patients with PPMS, who also underwent scoring on the expanded disability status scale (EDSS) twice, two years apart. Results The two measures reflecting cerebral atrophy correlated strongly (r = 0.58, p < 0.001). T2 lesion load measurements using the two techniques correlated very highly (r = 0.999, p < 0.001). 91 % of the total new T2 lesion volume was from enlargement of pre-existent lesions and only 9 % from new, discrete, lesions. No relationship was seen between the traditional measure of net gain in T2 lesion load and either measure of atrophy. However, the fully-automated measure of total new T2 load correlated with both measures of atrophy (SIENA technique, r= -0.37, p= 0.02; six slice measure, r = -0.41, p = 0.01). There was no relationship between the MRI measures and changes in the EDSS. Conclusion Both of the new image analysis techniques appear to be promising as sensitive markers for disease progression in PPMS. The correlation of total new T2 lesion volume with the progression of cerebral atrophy (which is known to be a consequence of axonal loss in progressive disease), compared with a lack of correlation with the traditional net gain in T2 lesion load is interesting and suggests that the total new T2 lesion volume may ultimately be the most useful measure.