Author Of 4 Presentations
P0156 - Serum neurofilament light levels correlate with reduced grey matter volume in advanced multiple sclerosis. (ID 770)
Abstract
Background
Grey matter (GM) pathology is associated with physical and cognitive impairment in patients with multiple sclerosis (pwMS). Increased levels of serum Neurofilament light (sNfL), indicating neuro-axonal damage, have been described in MS and were related to the development of global brain atrophy. However, the relation of sNFL to MRI-based measures of distinct brain volumes, in particular the grey matter, is still poorly investigated.
Objectives
To investigate the association of sNfL with compartmental brain volumes in pwMS in a cross-sectional and longitudinal manner.
Methods
We included 109 pwMS (mean age = 38.1 years, standard deviation (SD) ±11.7 years, 63.3% female) and 17 sex- and age-matched non-inflammatory neurological controls (NC) (mean age = 39.2 years, SD± 9.8 years). The MS cohort consisted of 16 clinically isolated syndrome (CIS), 72 relapsing-remitting MS (RRMS) and 21 progressive MS (PMS) patients. sNfL levels were measured by an ultrasensitive Single Molecule Array (Simoa®). In MS, we assessed whole and compartmental normalized and lesion-filled brain volumes and T2-lesion loads based on 3T MRI data, using T2-FLAIR and T1-weighted 1mm isotropic structural scans, processed with SienaX (part of FSL, fsl.fmrib.ox.ac.uk).
Results
In the entire cohort sNfL levels correlated with age (r = 0.329, p < 0.001). sNfL was significantly elevated in RRMS (p = 0.019) and PMS (p < 0.010) compared to NC, as well as in PMS compared to CIS (p = 0.035). Similarly, we found decreased brain volumes in PMS vs. CIS and RRMS. This was evident for whole brain, white matter (WM), total GM and cortical GM (p ≤ 0.001). Likewise, WM lesion volume was elevated in PMS vs. CIS (p = 0.001) and RRMS (p = 0.022). In deep GM areas, including basal ganglia and thalamus, volumes were decreased in PMS vs. CIS (p = 0.001 and 0.012 respectively) and PMS vs. RRMS (p = 0.038 and 0.015 respectively).
Only in patients with PMS we found sNfL to be negatively correlated with volumes of the whole brain after correcting for age (r = –0.571, p = 0.008). This was mainly driven by the correlation with total GM (r = –0.615, p = 0.004) and cortical GM (r = –0.664, p = 0.001). Regarding deep grey matter, only in PMS we observed a negative correlation of sNfL with basal ganglia volume (r = –0.571, p = 0.011). There was no correlation of sNfL with thalamus volume in any subgroup.
Conclusions
Although sNfL is already increased in earlier phases of MS, our data indicates that its relation to brain tissue damage, in particular GM pathology, might only become apparent in more advanced progressive forms of the disease. Further analysis of longitudinal MRI and clinical data is currently ongoing to confirm and extend our results.
P0609 - Multimodal MRI of the Brain to Improve Prediction of Disease Progression in Multiple Sclerosis (ID 1428)
Abstract
Background
One of the challenges in multiple sclerosis (MS) research is to improve prediction of disease progression. While information from conventional MRI of the brain is essential in the diagnosis of MS, it only allows prognosis to some extent. Given the complexity of the disease, a combined analysis of structural and functional MRI changes appears more promising to identify markers associated with disease progression.
Objectives
We thus investigated how multimodal MRI can contribute to predicting disease progression in a single-centre cohort of patients with MS (PwMS).
Methods
We analyzed multimodal MRI-data from 123 PwMS (71 women; age (years): M=37.2, SD=10.4; nCIS=16; nRRMS=98; nPMS=9). All patients had undergone clinical and 3T MRI evaluations between 2015 and 2016 (baseline, BL) and clinical re-evaluations 2 years later (SD=1.0; follow-up, FU). Brain-volume, T2 lesion load, fractional anisotropy (FA) and resting-state functional connectivity (rsFC) of the default-mode (DMN) and sensorimotor network (SMN) at BL were correlated with the patients’ disease severity score progression (absolute Expanded Disability Status Scale (EDSS) score change from BL to FU).
Results
Across the entire cohort, median EDSS scores were significantly higher at FU (Med=1; IQR=2.5) than at BL (Med=1; IQR=2; p=0.04), with a low rate of disease severity score progression (assessed by EDSS BL – EDSS FU/ FU duration; Med = 0; IQR = 0.5). Neither normalized brain volume (NBV) nor T2 lesion load, extracted mean scores of whole brain FA or rsFC within DMN or SMN significantly correlated with disease severity score progression. Whole brain voxel-based analyses (controlled for age and disease duration) indicated trends for decreased FA within the corpus callosum (CC) and the corticospinal tract (CST) and decreased rsFC within the anterior cingulate cortex (ACC) and the hand motor area to be associated with disease progression. Subsequent ROI analyses revealed a significant decrease in mean FA in the CC genu (p=0.024), the CC forceps minor (p=0.020) and right CST (p=0.020) related to disease progression. Moreover, ROI analyses showed a decrease in mean rsFC in the left hand motor area (p=0.012) and the ACC (p=0.005) with increased disease progression.
Conclusions
Our results show that even within a relatively low rate of clinical disease progression over short term FU, subtle microstructural and functional changes may represent more sensitive predictors compared to gross morphological measures obtained from conventional MRI.
P0822 - Processing speed improves prediction of physical impairment in patients with multiple sclerosis (ID 743)
Abstract
Background
In recent years, a few studies found correlations between processing speed and physical disability in patients with multiple sclerosis (pwMS). However, it remains unclear if this specific cognitive subdomain improves prediction of physical impairment in pwMS.
Objectives
The aim of this study was to investigate, if cognitive performance at baseline improves prediction of physical impairment at follow-up, controlling for demographics, clinical and MRI data.
Methods
We investigated pwMS who had undergone clinical, cognitive and MRI assessment at two timepoints (baseline and follow-up). Physical impairment was measured using the Expanded Disability Status Scale (EDSS) and was defined by an EDSS-Score above 3.0. Cognitive performance was assessed by the Z-score of the Symbol Digit Modality Test (SDMT), measuring processing speed.
Results
109 pwMS took part at baseline (70 female; 34 clinically isolated syndrome (CIS), 64 relapsing-remitting MS (RRMS), 8 secondary-progressive MS (SPMS), 1 SPMS with relapses, 2 primary-progressive MS (PPMS)) and follow-up assessment (20 CIS, 70 RRMS, 14 SPMS, 3 SPMS with relapses, 2 PPMS). Their mean age at baseline was 36 years (10 SD) and the mean follow-up duration was seven years (3.8 SD). At baseline, MS patients had a mean SDMT Z-score of -1.16 (1.19 SD). The median EDSS at baseline and follow-up was 2.0 (range 0 - 8). A binary-logistic regression (Nagelkerke R2= .560, p < 0.001) that included age, disease duration, clinical phenotype, baseline physical impairment, cognitive performance, lesion load and normalized gray matter volume at baseline showed that processing speed (OR: 0.392, p = .007) and age (OR: 1.094, p = .035) at baseline were the only significant independent predictors of physical impairment at follow-up. MRI data at baseline correlated with EDSS at FU, but did not add to this prediction.
Conclusions
Processing speed at baseline independently improved prediction of physical impairment in pwMS after seven years. This highlights the importance of cognitive assessment in addition to the rating of physical impairment. In future, neuropsychological examination could further support determination of the degree of disability in pwMS.
P1144 - Comparison of deep grey matter iron deposition assessed by 3T MRI R2* relaxometry in Multiple Sclerosis, Alzheimer´s disease and in normal controls (ID 1479)
Abstract
Background
Increased brain iron deposition has been described in different nosologic entities such as Multiple Sclerosis (MS) and Alzheimer’s disease (AD). However, it is still unclear whether abnormal brain iron accumulation contributes to the pathology of these diseases or merely reflects an epiphenomenon.
Objectives
To investigate deep grey matter iron deposition and its association with morphological brain changes and clinical data in patients with MS, AD and in normal controls (NC).
Methods
Participants with MS (n=196, mean age: 39±11 years), AD (n=116, mean age: 73±9 years) and NC (n=164, mean age: 66±11 years), underwent comprehensive clinical examination and brain MRI at 3T. Iron concentrations in deep grey areas (basal ganglia (BG), thalamus, hippocampus) were quantified by R2* relaxometry. Normalized brain volumes, T2 lesion load (LL) in MS and White Matter Hyperintensity (WMH) volumes in AD and NC were determined on T2-FLAIR and T1-weighted sequences, respectively.
Results
R2* relaxation rates increased with age in the BG. This relationship was strongest in MS (r=0.63, p<0.001), followed by AD (r=0.25, p=0.005) and NC (r=0.25, p=0.001). Higher BG R2* relaxation rates were associated with lower brain volumes, particularly concerning grey matter in MS (r= -0.51, p<0.001) and NC (r= -0.23, p=0.002) but not in AD. BG R2* relaxation rates correlated to T2 LL (r=0.45, p<0.001) in MS, but were unrelated to WMH volume in AD and NC. In MS, BG R2* relaxation rates further correlated with higher EDSS scores (r=0.28, p<0.001) and increased disease duration (r=0.35, p<0.001). Multivariate linear regression analysis revealed, that in MS age (beta=0.53, p<0.001) and T2 LL (beta=0.33, p<0.001) independently predicted BG R2* relaxation rates. In contrast, age was the only variable independently predicting BG R2* relaxation rates in AD (beta=0.26, p=0.011) and NC (beta= 0.32, p=0.026).
Conclusions
This comparative study confirms that age is a main driving factor for deep grey matter iron accumulation in MS, AD and NC. However, only in MS we found evidence for increased BG iron deposition to be associated with morphologic brain changes, supporting the notion that a dysbalanced iron homeostasis is involved in MS pathology. Further analyses on longitudinal MRI and clinical data are currently ongoing to confirm and extent our findings.
Presenter Of 1 Presentation
P0609 - Multimodal MRI of the Brain to Improve Prediction of Disease Progression in Multiple Sclerosis (ID 1428)
Abstract
Background
One of the challenges in multiple sclerosis (MS) research is to improve prediction of disease progression. While information from conventional MRI of the brain is essential in the diagnosis of MS, it only allows prognosis to some extent. Given the complexity of the disease, a combined analysis of structural and functional MRI changes appears more promising to identify markers associated with disease progression.
Objectives
We thus investigated how multimodal MRI can contribute to predicting disease progression in a single-centre cohort of patients with MS (PwMS).
Methods
We analyzed multimodal MRI-data from 123 PwMS (71 women; age (years): M=37.2, SD=10.4; nCIS=16; nRRMS=98; nPMS=9). All patients had undergone clinical and 3T MRI evaluations between 2015 and 2016 (baseline, BL) and clinical re-evaluations 2 years later (SD=1.0; follow-up, FU). Brain-volume, T2 lesion load, fractional anisotropy (FA) and resting-state functional connectivity (rsFC) of the default-mode (DMN) and sensorimotor network (SMN) at BL were correlated with the patients’ disease severity score progression (absolute Expanded Disability Status Scale (EDSS) score change from BL to FU).
Results
Across the entire cohort, median EDSS scores were significantly higher at FU (Med=1; IQR=2.5) than at BL (Med=1; IQR=2; p=0.04), with a low rate of disease severity score progression (assessed by EDSS BL – EDSS FU/ FU duration; Med = 0; IQR = 0.5). Neither normalized brain volume (NBV) nor T2 lesion load, extracted mean scores of whole brain FA or rsFC within DMN or SMN significantly correlated with disease severity score progression. Whole brain voxel-based analyses (controlled for age and disease duration) indicated trends for decreased FA within the corpus callosum (CC) and the corticospinal tract (CST) and decreased rsFC within the anterior cingulate cortex (ACC) and the hand motor area to be associated with disease progression. Subsequent ROI analyses revealed a significant decrease in mean FA in the CC genu (p=0.024), the CC forceps minor (p=0.020) and right CST (p=0.020) related to disease progression. Moreover, ROI analyses showed a decrease in mean rsFC in the left hand motor area (p=0.012) and the ACC (p=0.005) with increased disease progression.
Conclusions
Our results show that even within a relatively low rate of clinical disease progression over short term FU, subtle microstructural and functional changes may represent more sensitive predictors compared to gross morphological measures obtained from conventional MRI.