The objective of this study was to investigate the relationship between the extent of spontaneous remyelination and the distance from ventricular cerebrospinal fluid (CSF) in a group of multiple sclerosis patients. Dynamic remyelination was measured using longitudinal [11C]PiB positron emission tomography and found to be significantly reduced in periventricular white matter lesions, while becoming progressively more extensive with increasing distance from ventricles. Moreover, we found a positive correlation between periventricular remyelination and cortical thickness. These results suggest that CSF-linked factors might interfere with the spontaneous remyelination process in multiple sclerosis patients.
INTRODUCTION
Spontaneous remyelination partly fails in multiple sclerosis (MS) white matter (WM) lesions. Neuropathological studies1 suggest that the efficacy of this process might depend on lesion location, being particularly reduced in the vicinity of ventricular cerebrospinal fluid (CSF). However, to date this evidence has not been confirmed by in-vivo data. A recent study2 has demonstrated that it is possible to measure remyelination in vivo with positron emission tomography (PET) using the [11C]PiB radioligand. Here, we used this technique to explore the relationship between the extent of remyelination and the distance from ventricular CSF in a group of MS patientsMETHODS
Nineteen patients with MS and eight healthy controls (HC) underwent a MRI protocol using a 3T Siemens MAGNETOM Trio MRI scanner equipped with a 32-channel head coil, and a 90 min dynamic [11C]PiB PET exam acquired on a high resolution research tomograph HRRT, at baseline and, only for patients, after 2 to 4 months. MRI protocol included a 3D-T1 MPRAGE (1x1x1.1mm) and a T2-TSE (0.9x0.9x3mm). T2 hyperintense lesions were manually segmented and aligned to the T1 space. After performing a “lesion-filling” procedure3, WM, cortical grey matter, and CSF were segmented in all subjects using Freesurfer. Distance map from ventricular CSF into WM were calculated with FSL. PET images were quantified as previously described4, obtaining parametric maps of distribution volume ratio (DVR). For each patient, the T1 images acquired at the two time-points were aligned to each other to create a “halfway space” which was normalized to the MNI standard space using FNIRT. Derived transformations were then combined to align all images (DVR, distance map and lesion mask) to the standard space, passing through the halfway space. On the DVR images of patients, each lesional voxel was classified as demyelinated if its DVR value was < 1 standard deviation below the mean DVR value of all the voxels in HC that were localized at the same distance from the CSF2. Individual maps of demyelinated voxels at baseline, as well as maps of dynamically demyelinating voxels (defined as lesional voxels classified as myelinated at baseline and demyelinated at follow-up), and of remyelinating voxels (defined as lesional voxels classified as demyelinated at baseline and normally myelinated at follow-up), were generated (Figure 1). From these individual maps, we computed three probability maps: i) probability map of demyelinated voxels at baseline; ii) conditional probability map of dynamically demyelinating voxels obtained by normalizing the probability of a voxel to be demyelinated at follow-up by its probability to be normally myelinated at baseline iii) conditional probability map of dynamically remyelinating voxels obtained by normalizing the probability of a voxel to be myelinated at follow-up by its probability to be demyelinated at baseline. At the single subject level, the relationship between the probability of remyelination and the distance from ventricles was modelled using a segmented model composed of two linear segments with different slopes. To minimize partial volume effect, the first 3 mm around the ventricles were excluded from this analysis. The relationship between the probability of voxels to remyelinate near ventricular CSF and cortical thickness (CTh) was measured with Pearson correlation coefficient.RESULTS
Both the probability of voxels to be demyelinated at baseline and to dynamically demyelinate over the follow-up were higher in brain regions close to ventricular CSF compared to more distant regions (Figure 2A-B). The opposite effect was observed for the probability of voxel to remyelinate (Figure 2C). The model based on single subject analysis showed that the mean probability of voxels to remyelinate, which was 0.08±0.09 close to the ventricles, increased of 0.04±0.03 for each mm of distance from CSF up to a distance of 14.12±7.00 mm, where the gradient almost reached a plateau. An example of the model fit is presented in Figure 3. A higher probability of voxels to remyelinate close to the CSF significantly correlated with a higher CTh (r=0.56, p=0.013) (Figure 4).DISCUSSION & CONCLUSIONS
We demonstrated for the first time in vivo that spontaneous remyelination is significantly reduced in periventricular WM lesions in patients with MS, and becomes progressively more extensive with increasing distance from ventricles. These data suggest that the presence of potentially cytotoxic soluble mediators in the CSF could exert an inhibitory effect on the remyelination process around the ventricles5. This hypothesis is further supported by the positive correlation we found in our cohort between periventricular remyelination and CTh, suggesting that similar factors could influence tissue damage and repair in areas close to the CSF both in WM and in cortex.1. Patrikios, P. et al. Remyelination is extensive in a subset of multiple sclerosis patients. Brain 129, 3165–3172 (2006).
2. Bodini, B. et al. Dynamic Imaging of Individual Remyelination Profiles in Multiple Sclerosis. Ann. Neurol. 79, 726–738 (2016).
3. Chard, D. T., Jackson, J. S., Miller, D. H. & Wheeler-Kingshott, C. A. M. Reducing the impact of white matter lesions on automated measures of brain gray and white matter volumes. J. Magn. Reson. Imaging 32, 223–228 (2010).
4. Veronese, M. et al. Quantification of [11C]PIB PET for imaging myelin in the human brain: A test-retest reproducibility study in high-resolution research tomography. J. Cereb. Blood Flow Metab. 35, 1771–1782 (2015).
5. Jehna, M. et al. Periventricular lesions correlate with cortical thinning in multiple sclerosis. Ann. Neurol. 78, 530–539 (2015).
Fig 1: Individual map and distance map
Panel A shows the individual map of a representative subject. In red are the voxels classified as demyelinated at baseline; in blue are the voxels classified as dynamically demyelinating over the follow-up (i.e. lesional voxels defined as demyelinated only at follow-up); in green are the voxels classified as dynamically remyelinating over the follow-up (i.e. lesional voxels defined as demyelinated only at baseline). Panel B shows the distance map from ventricular CSF into the white matter
Fig 2: Probability maps and relationship with distance from ventricular CSF
Top row shows the probability maps of a lesional voxel to be A) demyelinated at baseline, B) dynamically demyelinating over the follow-up (i.e. lesional voxels defined as demyelinated only at follow-up), and C) dynamically remyelinating over the follow-up (i.e. lesional voxels defined as demyelinated only at baseline). Bottom row shows the relationship between the probability of a lesional voxel to be A) demyelinated B) demyelinating, and C) remyelinating according to its distance from ventricular CSF.
Fig 3: example of the segmented model fit
Green dots represent the probability of a voxel to remyelinate according to its distance from ventricular CSF in a representative MS patient. Solid black line represents the fitted segmented model
Fig 4: Correlation between the probability of remyelination close to ventricular CSF and cortical thickness
Black dots represent different subjects. Red line represent the regression line.