TSPO-PET reveals higher inflammation in white matter disrupted by paramagnetic rim lesions in multiple sclerosis

Abstract

Identifying the role of compartmentalized inflammation within the central nervous system (CNS) and its association with chronic active lesions is essential for advancing our overall understanding of disease progression in multiple sclerosis (MS). In this study, we explore whether the inflammatory activity is higher in white matter (WM) tracts disrupted by paramagnetic rim lesions (PRLs) and if inflammation in PRL-disrupted WM tracts is associated with disability in people with MS. Forty-four MS patients and 11 healthy controls were included. 18 kDa-translocator protein positron emission tomography (TSPO-PET) with the ¹¹C-PK11195 radioligand was used to measure the neuroinflammatory activity. The Network Modification Tool was used to identify WM tracts disrupted by PRLs and non-PRLs that were delineated on MRI. The Expanded Disability Status Scale was used to measure disability. MS patients had higher inflammatory activity in whole-brain WM compared to healthy controls (p = 0.001). Compared to patients without PRLs, patients with PRLs exhibited higher levels of inflammatory activity in the WM tracts disrupted by any type of lesions (p = 0.02) or PRLs (p = 0.004). In patients with at least one PRL, inflammatory activity was higher in WM tracts highly disrupted by PRLs compared to WM tracts highly disrupted by non-PRLs (p = 0.009). Elevated inflammatory activity in highly disrupted WM tracts was associated with increased disability in patients with PRL (p = 0.03), but not in patients without PRL (p = 0.2). This study suggests that patients with PRLs may exhibit more diffuse WM inflammation in addition to higher inflammation along WM tracts disrupted by PRLs compared to non-PRLs, which could contribute to larger lesion volumes and faster disability progression. Imaging PRLs may serve to identify patients with both focal and diffuse inflammation, guiding therapeutic interventions aimed at reducing inflammation and preventing progressive disability in MS.

Keywords: PK-PET; disruption of WM tracts; multiple sclerosis; neuroinflammation.

Fig. 1.

(A) Statistics comparing voxel-wise DVR between MS patients and healthy controls. The statistics values were derived from the Student’s t-test analysis, which compared voxel-wise DVR between MS patients and healthy controls. Positive statistics values indicate higher DVR in MS patients compared to healthy controls. (B) The z-scored voxel-wise DVR metrics in patients with and without PRL, separately. The z-scoring was obtained using the voxel-wise DVR metrics in 11 healthy controls. (C) Statistics comparing voxel-wise DVR between MS patients with vs without PRL. The statistics values were derived from the Student’s t-test analysis, which compared voxel-wise DVR between MS patients with vs without PRL. Positive values indicate higher DVR in MS patients with PRL compared to those without PRL. The voxels within 1 mm proximity to CSF and cortex were excluded. (D) The average DVR metrics at the subject level for HC, all MS patients, MS patients with PRL, and MS patients without PRL. ANCOVA was used to compare the average DVR between MS patients and healthy controls as well as between the MS patients with vs without PRL. Age and sex were used as a covariate in the ANCOVA models. The BH-adjusted p-values (pBH) were presented in the figures.

Fig. 2.

Examples from three different MS patients representing the lesion mask (red), white matter voxels with low disruption (green) due to any type of WM lesion, and white matter voxels with high disruption (blue) due to any type of WM lesion.

Fig. 3.

The patient-level z-scored DVR metrics averaged across the WM tracts where i) there was no disruption due to MS lesions (i.e., disruption in the WM tracts is zero), ii) there was a low level of disconnection due to lesions (i.e. disruption in the WM tracts is between 0 and 0.1), and iii) there was a high level of disconnection due to lesions (i.e., disruption in the WM tracts is between 0.9 and 1). Patients without PRL (shown in yellow color) include 18 patients, while patients with PRL (shown in dark blue, blue, and light blue colors) include 26 patients. The voxel-wise z-scored DVR was created in the WM using the voxel-wise DVR in 11 healthy controls. Then, the patient-level averaged z-scored metrics were calculated for each MS patient separately. The disruption metrics were separated as disruption due to PRL and disruption due to non-PRL for patients with at least one PRL. The yellow color represents the patients without PRL and the blue colors represent the patients with at least one PRL. The comparisons between the patients with vs without PRL were performed with ANCOVA where age, sex, and MS type were controlled. In patients with PRL, a paired t-test was used to compare the average of z-scored DVR in the WM tracts with varying levels of disruption due to PRLs vs non-PRLs. The BH-adjusted p-values (pBH) were presented in the figures. The covariates such as age, sex, and MS type used in the linear models did not have a significant effect on the z-scored DVR metrics.

Fig. 4.

The scatterplots of EDSS and subject-level averaged z-scored DVR for patients without PRL (orange color) (n = 18), patients with PRL (blue color) (n = 26), and all patients (black color) (n = 44). We computed the subject-level averaged z-scored DVR in the WM tracts where (A) there was no disruption due to MS lesions (i.e. disruption in the WM tracts is zero), (B) there was a low level of disruption due to MS lesions (i.e. disruption in the WM tracts is between 0 and 0.1), and (C) there was a high level of disruption due to MS lesions (i.e. disruption in the WM tracts is between 0.9 and 1). The estimates and the p-values associated with EDSS were calculated using a linear model where the output was the subject-level averaged z-scored DVR and the inputs were EDSS, age, sex, and MS type. The BH-adjusted p-values (pBH) were presented in the figures.