Isolated cognitive impairment in people with multiple sclerosis: frequency, MRI patterns and its development over time

OBJECTIVES

To study the frequency of isolated (i.e., single-domain) cognitive impairments, domain specific MRI correlates, and its longitudinal development in people with multiple sclerosis (PwMS).

METHODS

348 PwMS (mean age 48 ± 11 years, 67% female, 244RR/52SP/38PP) underwent neuropsychological testing (extended BRB-N) at baseline and at five-year follow-up. At baseline, structural MRI was acquired. Isolated cognitive impairment was defined as a Z-score of at least 1.5 SD below normative data in one domain only (processing speed, memory, executive functioning/working memory, and attention). Multi-domain cognitive impairment was defined as being affected in ≥ 2 domains, and cognitively preserved otherwise. For PwMS with isolated cognitive impairment, MRI correlates were explored using linear regression. Development of isolated cognitive impairment over time was evaluated based on reliable change index.

RESULTS

At baseline, 108 (31%) PwMS displayed isolated cognitive impairment, 148 (43%) PwMS displayed multi-domain cognitive impairment. Most PwMS with isolated cognitive impairment were impaired on executive functioning/working memory (EF/WM; N = 37), followed by processing speed (IPS; N = 25), memory (N = 23), and attention (N = 23). Isolated IPS impairment was explained by a model of cortical volume and fractional anisotropy (adj. R2 = 0.539, p < 0.001); memory by a model with cortical volume and hippocampal volume (adj. R2 = 0.493, p = 0.002); EF/WM and attention were not associated with any MRI measure. At follow-up, cognitive decline was present in 11/16 (69%) of PwMS with isolated IPS impairment at baseline. This percentage varied between 18 and 31% of PwMS with isolated cognitive impairment in domains other than IPS at baseline.

CONCLUSION

Isolated cognitive impairment is frequently present in PwMS and can serve as a proxy for further decline, particularly when it concerns processing speed. Cortical and deep grey matter atrophy seem to play a pivotal role in isolated cognitive impairment. Timely detection and patient-tailored intervention, predominantly for IPS, may help to postpone further cognitive decline.

Exploring the effects of extended interval dosing of natalizumab and drug concentrations on brain atrophy in multiple sclerosis

BACKGROUND

Extended interval dosing (EID) of natalizumab treatment is increasingly used in multiple sclerosis. Besides the clear anti-inflammatory effect, natalizumab is considered to have neuroprotective properties as well.

OBJECTIVES

This study aimed to study the longitudinal effects of EID compared to standard interval dosing (SID) and natalizumab drug concentrations on brain atrophy.

METHODS

Patients receiving EID or SID of natalizumab with a minimum radiological follow-up of 2 years were included. Changes in brain atrophy measures over time were derived from clinical routine 3D-Fluid Attenuated Inversion Recovery (FLAIR)-weighted magnetic resonance imaging (MRI) scans using SynthSeg.

RESULTS

We found no differences between EID (n = 32) and SID (n = 50) for whole brain (-0.21% vs -0.16%, p = 0.42), ventricular (1.84% vs 1.13%, p = 0.24), and thalamic (-0.32% vs -0.32%, p = 0.97) annualized volume change over a median follow-up of 3.2 years. No associations between natalizumab drug concentration and brain atrophy rate were found.

CONCLUSION

We found no clear evidence that EID compared to SID or lower natalizumab drug concentrations have a negative impact on the development of brain atrophy over time.

Feasibility of detecting atrophy relevant for disability and cognition in multiple sclerosis using 3D-FLAIR

BACKGROUND AND OBJECTIVES

Disability and cognitive impairment are known to be related to brain atrophy in multiple sclerosis (MS), but 3D-T1 imaging required for brain volumetrics is often unavailable in clinical protocols, unlike 3D-FLAIR. Here our aim was to investigate whether brain volumes derived from 3D-FLAIR images result in similar associations with disability and cognition in MS as do those derived from 3D-T1 images.

METHODS

3T-MRI scans of 329 MS patients and 76 healthy controls were included in this cross-sectional study. Brain volumes were derived using FreeSurfer on 3D-T1 and compared with brain volumes derived with SynthSeg and SAMSEG on 3D-FLAIR. Relative agreement was evaluated by calculating the intraclass correlation coefficient (ICC) of the 3D-T1 and 3D-FLAIR volumes. Consistency of relations with disability and average cognition was assessed using linear regression, while correcting for age and sex. The findings were corroborated in an independent validation cohort of 125 MS patients.

RESULTS

The ICC between volume measured with FreeSurfer and those measured on 3D-FLAIR for brain, ventricle, cortex, total deep gray matter and thalamus was above 0.74 for SAMSEG and above 0.91 for SynthSeg. Worse disability and lower average cognition were similarly associated with brain (adj. R2 = 0.24-0.27, p < 0.01; adj. R2 = 0.26-0.29, p < 0.001) ventricle (adj. R2 = 0.27-0.28, p < 0.001; adj. R2 = 0.19-0.20, p < 0.001) and deep gray matter volumes (adj. R2 = 0.24-0.28, p < 0.001; adj. R2 = 0.27-0.28, p < 0.001) determined with all methods, except for cortical volumes derived from 3D-FLAIR.

DISCUSSION

In this cross-sectional study, brain volumes derived from 3D-FLAIR and 3D-T1 show similar relationships to disability and cognitive dysfunction in MS, highlighting the potential of these techniques in clinical datasets.

Alterations in the inferior fronto-occipital fasciculus - a specific neural correlate of gender incongruence?

BACKGROUND

Increasing numbers of adolescents seek help for gender-identity questions. Consequently, requests for medical treatments, such as puberty suppression, are growing. However, studies investigating the neurobiological substrate of gender incongruence (when birth-assigned sex and gender identity do not align) are scarce, and knowledge about the effects of puberty suppression on the developing brain of transgender youth is limited.

METHODS

Here we cross-sectionally investigated sex and gender differences in regional fractional anisotropy (FA) as measured by diffusion MR imaging, and the impact of puberty on alterations in the white-matter organization of 35 treatment-naive prepubertal children and 41 adolescents with gender incongruence, receiving puberty suppression. The transgender groups were compared with 79 age-matched, treatment-naive cisgender (when sex and gender align) peers.

RESULTS

We found that transgender adolescents had lower FA in the bilateral inferior fronto-occipital fasciculus (IFOF), forceps major and corpus callosum than cisgender peers. In addition, average FA values of the right IFOF correlated negatively with adolescents' cumulative dosage of puberty suppressants received. Of note, prepubertal children also showed significant FA group differences in, again, the right IFOF and left cortico-spinal tract, but with the reverse pattern (transgender > cisgender) than was seen in adolescents.

CONCLUSIONS

Importantly, our results of lower FA (indexing less longitudinal organization, fiber coherence, and myelination) in the IFOF of gender-incongruent adolescents replicate prior findings in transgender adults, suggesting a salient neural correlate of gender incongruence. Findings highlight the complexity with which (pubertal) sex hormones impact white-matter development and add important insight into the neurobiological substrate associated with gender incongruence.

Multicenter Evaluation of AI-generated DIR and PSIR for Cortical and Juxtacortical Multiple Sclerosis Lesion Detection

Background Cortical multiple sclerosis lesions are clinically relevant but inconspicuous at conventional clinical MRI. Double inversion recovery (DIR) and phase-sensitive inversion recovery (PSIR) are more sensitive but often unavailable. In the past 2 years, artificial intelligence (AI) was used to generate DIR and PSIR from standard clinical sequences (eg, T1-weighted, T2-weighted, and fluid-attenuated inversion-recovery sequences), but multicenter validation is crucial for further implementation. Purpose To evaluate cortical and juxtacortical multiple sclerosis lesion detection for diagnostic and disease monitoring purposes on AI-generated DIR and PSIR images compared with MRI-acquired DIR and PSIR images in a multicenter setting. Materials and Methods Generative adversarial networks were used to generate AI-based DIR (n = 50) and PSIR (n = 43) images. The number of detected lesions between AI-generated images and MRI-acquired (reference) images was compared by randomized blinded scoring by seven readers (all with >10 years of experience in lesion assessment). Reliability was expressed as the intraclass correlation coefficient (ICC). Differences in lesion subtype were determined using Wilcoxon signed-rank tests. Results MRI scans of 202 patients with multiple sclerosis (mean age, 46 years ± 11 [SD]; 127 women) were retrospectively collected from seven centers (February 2020 to January 2021). In total, 1154 lesions were detected on AI-generated DIR images versus 855 on MRI-acquired DIR images (mean difference per reader, 35.0% ± 22.8; P < .001). On AI-generated PSIR images, 803 lesions were detected versus 814 on MRI-acquired PSIR images (98.9% ± 19.4; P = .87). Reliability was good for both DIR (ICC, 0.81) and PSIR (ICC, 0.75) across centers. Regionally, more juxtacortical lesions were detected on AI-generated DIR images than on MRI-acquired DIR images (495 [42.9%] vs 338 [39.5%]; P < .001). On AI-generated PSIR images, fewer juxtacortical lesions were detected than on MRI-acquired PSIR images (232 [28.9%] vs 282 [34.6%]; P = .02). Conclusion Artificial intelligence-generated double inversion-recovery and phase-sensitive inversion-recovery images performed well compared with their MRI-acquired counterparts and can be considered reliable in a multicenter setting, with good between-reader and between-center interpretative agreement. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Zivadinov and Dwyer in this issue.

Neurofilament-light and contactin-1 association with long-term brain atrophy in natalizumab-treated relapsing-remitting multiple sclerosis

BACKGROUND

Despite highly effective treatment strategies for patients with relapsing-remitting multiple sclerosis (RRMS), long-term neurodegeneration and disease progression are often considerable. Accurate blood-based biomarkers that predict long-term neurodegeneration are lacking.

OBJECTIVE

To assess the predictive value of serum neurofilament-light (sNfL) and serum contactin-1 (sCNTN1) for long-term magnetic resonance imaging (MRI)-derived neurodegeneration in natalizumab-treated patients with RRMS.

METHODS

sNfL and sCNTN1 were measured in an observational cohort of natalizumab-treated patients with RRMS at baseline (first dose) and at 3 months, Year 1, Year 2, and last follow-up (median = 5.2 years) of treatment. Disability progression was quantified using "EDSS-plus" criteria. Neurodegeneration was measured by calculating annualized percentage brain, ventricular, and thalamic volume change (PBVC, VVC, and TVC, respectively). Linear regression analysis was performed to identify longitudinal predictors of neurodegeneration.

RESULTS

In total, 88 patients (age = 37 ± 9 years, 75% female) were included, of whom 48% progressed. Year 1 sNfL level (not baseline or 3 months) was associated with PBVC (standardized (std.) β = -0.26, p = 0.013), VVC (standardized β = 0.36, p < 0.001), and TVC (standardized β = -0.24, p = 0.02). For sCNTN1, only 3-month level was associated with VVC (standardized β = -0.31, p = 0.002).

CONCLUSION

Year 1 (but not baseline) sNfL level was predictive for long-term brain atrophy in patients treated with natalizumab. sCNTN1 level did not show a clear predictive value.

A randomized trial predicting response to cognitive rehabilitation in multiple sclerosis: Is there a window of opportunity?

Background:

Cognitive training elicits mild-to-moderate improvements in cognitive functioning in people with multiple sclerosis (PwMS), although response heterogeneity limits overall effectiveness.

Objective:

To identify patient characteristics associated with response and non-response to cognitive training.

Methods:

Eighty-two PwMS were randomized into a 7-week attention training (n = 58, age = 48.4 ± 10.2 years) or a waiting-list control group (n = 24, age = 48.5 ± 9.4 years). Structural and functional magnetic resonance imaging (MRI) was obtained at baseline and post-intervention. Twenty-one healthy controls (HCs, age = 50.27 ± 10.15 years) were included at baseline. Responders were defined with a reliable change index of 1.64 on at least 2/6 cognitive domains. General linear models and logistic regression were applied.

Results:

Responders (n = 36) and non-responders (n = 22) did not differ on demographics, clinical variables and baseline cognition and structural MRI. However, non-responders exhibited a higher baseline functional connectivity (FC) between the default-mode network (DMN) and the ventral attention network (VAN), compared with responders (p = 0.018) and HCs (p = 0.001). Conversely, responders exhibited no significant baseline differences in FC compared with HCs. Response to cognitive training was predicted by lower DMN-VAN FC (p = 0.004) and DMN-frontoparietal FC (p = 0.029) (Nagelkerke R² = 0.25).

Conclusion:

An intact pre-intervention FC is associated with cognitive training responsivity in pwMS, suggesting a window of opportunity for successful cognitive interventions.

Artificial double inversion recovery images can substitute conventionally acquired images: an MRI-histology study

Cortical multiple sclerosis lesions are disease-specific, yet inconspicuous on magnetic resonance images (MRI). Double inversion recovery (DIR) images are sensitive, but often unavailable in clinical routine and clinical trials. Artificially generated images can mitigate this issue, but lack histopathological validation. In this work, artificial DIR images were generated from postmortem 3D-T1 and proton-density (PD)/T2 or 3D-T1 and 3D fluid-inversion recovery (FLAIR) images, using a generative adversarial network. All sequences were scored for cortical lesions, blinded to histopathology. Subsequently, tissue samples were stained for proteolipid protein (myelin) and scored for cortical lesions type I-IV (leukocortical, intracortical, subpial and cortex-spanning, respectively). Histopathological scorings were then (unblinded) compared to MRI using linear mixed models. Images from 38 patients (26 female, mean age 64.3 ± 10.7) were included. A total of 142 cortical lesions were detected, predominantly subpial. Histopathology-blinded/unblinded sensitivity was 13.4/35.2% for artificial DIR generated from T1-PD/T2, 14.1/41.5% for artificial DIR from T1-FLAIR, 17.6/49.3% for conventional DIR and 10.6/34.5% for 3D-T1. When blinded to histopathology, there were no differences; with histopathological feedback at hand, conventional DIR and artificial DIR from T1-FLAIR outperformed the other sequences. Differences between histopathology-blinded/unblinded sensitivity could be minified through adjustment of the scoring criteria. In conclusion, artificial DIR images, particularly generated from T1-FLAIR could potentially substitute conventional DIR images when these are unavailable.

Automatic segmentation of head and neck primary tumors on MRI using a multi-view CNN

Background 

Accurate segmentation of head and neck squamous cell cancer (HNSCC) is important for radiotherapy treatment planning. Manual segmentation of these tumors is time-consuming and vulnerable to inconsistencies between experts, especially in the complex head and neck region. The aim of this study is to introduce and evaluate an automatic segmentation pipeline for HNSCC using a multi-view CNN (MV-CNN).

Methods

The dataset included 220 patients with primary HNSCC and availability of T1-weighted, STIR and optionally contrast-enhanced T1-weighted MR images together with a manual reference segmentation of the primary tumor by an expert. A T1-weighted standard space of the head and neck region was created to register all MRI sequences to. An MV-CNN was trained with these three MRI sequences and evaluated in terms of volumetric and spatial performance in a cross-validation by measuring intra-class correlation (ICC) and dice similarity score (DSC), respectively.

Results

The average manual segmented primary tumor volume was 11.8±6.70 cm³ with a median [IQR] of 13.9 [3.22-15.9] cm³. The tumor volume measured by MV-CNN was 22.8±21.1 cm³ with a median [IQR] of 16.0 [8.24-31.1] cm³. Compared to the manual segmentations, the MV-CNN scored an average ICC of 0.64±0.06 and a DSC of 0.49±0.19. Improved segmentation performance was observed with increasing primary tumor volume: the smallest tumor volume group (<3 cm³) scored a DSC of 0.26±0.16 and the largest group (>15 cm³) a DSC of 0.63±0.11 (p<0.001). The automated segmentation tended to overestimate compared to the manual reference, both around the actual primary tumor and in false positively classified healthy structures and pathologically enlarged lymph nodes.

Conclusion

An automatic segmentation pipeline was evaluated for primary HNSCC on MRI. The MV-CNN produced reasonable segmentation results, especially on large tumors, but overestimation decreased overall performance. In further research, the focus should be on decreasing false positives and make it valuable in treatment planning.

Artificial double inversion recovery images for (juxta)cortical lesion visualization in multiple sclerosis

Background:

Cortical lesions are highly inconspicuous on magnetic resonance imaging (MRI). Double inversion recovery (DIR) has a higher sensitivity than conventional clinical sequences (i.e. T1, T2, FLAIR) but is difficult to acquire, leading to overseen cortical lesions in clinical care and clinical trials.

Objective:

To evaluate the usability of artificially generated DIR (aDIR) images for cortical lesion detection compared to conventionally acquired DIR (cDIR).

Methods:

The dataset consisted of 3D-T1 and 2D-proton density (PD) T2 images of 73 patients (49RR, 20SP, 4PP) at 1.5 T. Using a 4:1 train:test-ratio, a fully convolutional neural network was trained to predict 3D-aDIR from 3D-T1 and 2D-PD/T2 images. Randomized blind scoring of the test set was used to determine detection reliability, precision and recall.

Results:

A total of 626 vs 696 cortical lesions were detected on 15 aDIR vs cDIR images (intraclass correlation coefficient (ICC) = 0.92). Compared to cDIR, precision and recall were 0.84 ± 0.06 and 0.76 ± 0.09, respectively. The frontal and temporal lobes showed the largest differences in discernibility.

Conclusion:

Cortical lesions can be detected with good reliability on artificial DIR. The technique has potential to broaden the availability of DIR in clinical care and provides the opportunity of ex post facto implementation of cortical lesions imaging in existing clinical trial data.

Tissue Transglutaminase Expression Associates With Progression of Multiple Sclerosis

Objective

The clinical course of multiple sclerosis (MS) is variable and largely unpredictable pointing to an urgent need for markers to monitor disease activity and progression. Recent evidence revealed that tissue transglutaminase (TG2) is altered in patient-derived monocytes. We hypothesize that blood cell–derived TG2 messenger RNA (mRNA) can potentially be used as biomarker in patients with MS.

Methods

In peripheral blood mononuclear cells (PBMCs) from 151 healthy controls and 161 patients with MS, TG2 mRNA was measured and correlated with clinical and MRI parameters of disease activity (annualized relapse rate, gadolinium-enhanced lesions, and T2 lesion volume) and disease progression (Expanded Disability Status Scale [EDSS], normalized brain volume, and hypointense T1 lesion volume).

Results

PBMC-derived TG2 mRNA levels were significantly associated with disease progression, i.e., worsening of the EDSS over 2 years of follow-up, normalized brain volume, and normalized gray and white matter volume in the total MS patient group at baseline. Of these, in patients with relapsing-remitting MS, TG2 expression was significantly associated with worsening of the EDSS scores over 2 years of follow-up. In the patients with primary progressive (PP) MS, TG2 mRNA levels were significantly associated with EDSS, normalized brain volume, and normalized gray and white matter volume at baseline. In addition, TG2 mRNA associated with T1 hypointense lesion volume in the patients with PP MS at baseline.

Conclusion

PBMC-derived TG2 mRNA levels hold promise as biomarker for disease progression in patients with MS.

Classification of Evidence

This study provides Class II evidence that in patients with MS, PBMC-derived TG2 mRNA levels are associated with disease progression.

Histopathology-validated recommendations for cortical lesion imaging in multiple sclerosis

Cortical demyelinating lesions are clinically important in multiple sclerosis, but notoriously difficult to visualize with MRI. At clinical field strengths, double inversion recovery MRI is most sensitive, but still only detects 18% of all histopathologically validated cortical lesions. More recently, phase-sensitive inversion recovery was suggested to have a higher sensitivity than double inversion recovery, although this claim was not histopathologically validated. Therefore, this retrospective study aimed to provide clarity on this matter by identifying which MRI sequence best detects histopathologically-validated cortical lesions at clinical field strength, by comparing sensitivity and specificity of the thus far most commonly used MRI sequences, which are T₂, fluid-attenuated inversion recovery (FLAIR), double inversion recovery and phase-sensitive inversion recovery. Post-mortem MRI was performed on non-fixed coronal hemispheric brain slices of 23 patients with progressive multiple sclerosis directly after autopsy, at 3 T, using T₁ and proton-density/T₂-weighted, as well as FLAIR, double inversion recovery and phase-sensitive inversion recovery sequences. A total of 93 cortical tissue blocks were sampled from these slices. Blinded to histopathology, all MRI sequences were consensus scored for cortical lesions. Subsequently, tissue samples were stained for proteolipid protein (myelin) and scored for cortical lesion types I–IV (mixed grey matter/white matter, intracortical, subpial and cortex-spanning lesions, respectively). MRI scores were compared to histopathological scores to calculate sensitivity and specificity per sequence. Next, a retrospective (unblinded) scoring was performed to explore maximum scoring potential per sequence. Histopathologically, 224 cortical lesions were detected, of which the majority were subpial. In a mixed model, sensitivity of T₁, proton-density/T₂, FLAIR, double inversion recovery and phase-sensitive inversion recovery was 8.9%, 5.4%, 5.4%, 22.8% and 23.7%, respectively (20, 12, 12, 51 and 53 cortical lesions). Specificity of the prospective scoring was 80.0%, 75.0%, 80.0%, 91.1% and 88.3%. Sensitivity and specificity did not significantly differ between double inversion recovery and phase-sensitive inversion recovery, while phase-sensitive inversion recovery identified more lesions than double inversion recovery upon retrospective analysis (126 versus 95; P < 0.001). We conclude that, at 3 T, double inversion recovery and phase-sensitive inversion recovery sequences outperform conventional sequences T₁, proton-density/T₂ and FLAIR. While their overall sensitivity does not exceed 25%, double inversion recovery and phase-sensitive inversion recovery are highly pathologically specific when using existing scoring criteria and their use is recommended for optimal cortical lesion assessment in multiple sclerosis.

Long-range connections are more severely damaged and relevant for cognition in multiple sclerosis

An efficient network such as the human brain features a combination of global integration of information, driven by long-range connections, and local processing involving short-range connections. Whether these connections are equally damaged in multiple sclerosis is unknown, as is their relevance for cognitive impairment and brain function. Therefore, we cross-sectionally investigated the association between damage to short- and long-range connections with structural network efficiency, the functional connectome and cognition. From the Amsterdam multiple sclerosis cohort, 133 patients (age = 54.2 ± 9.6) with long-standing multiple sclerosis and 48 healthy controls (age = 50.8 ± 7.0) with neuropsychological testing and MRI were included. Structural connectivity was estimated from diffusion tensor images using probabilistic tractography (MRtrix 3.0) between pairs of brain regions. Structural connections were divided into short- (length < quartile 1) and long-range (length > quartile 3) connections, based on the mean distribution of tract lengths in healthy controls. To determine the severity of damage within these connections, (i) fractional anisotropy as a measure for integrity; (ii) total number of fibres; and (iii) percentage of tract affected by lesions were computed for each connecting tract and averaged for short- and long-range connections separately. To investigate the impact of damage in these connections for structural network efficiency, global efficiency was computed. Additionally, resting-state functional connectivity was computed between each pair of brain regions, after artefact removal with FMRIB’s ICA-based X-noiseifier. The functional connectivity similarity index was computed by correlating individual functional connectivity matrices with an average healthy control connectivity matrix. Our results showed that the structural network had a reduced efficiency and integrity in multiple sclerosis relative to healthy controls (both P < 0.05). The long-range connections showed the largest reduction in fractional anisotropy (z = −1.03, P < 0.001) and total number of fibres (z = −0.44, P < 0.01), whereas in the short-range connections only fractional anisotropy was affected (z = −0.34, P = 0.03). Long-range connections also demonstrated a higher percentage of tract affected by lesions than short-range connections, independent of tract length (P < 0.001). Damage to long-range connections was more strongly related to structural network efficiency and cognition (fractional anisotropy: r = 0.329 and r = 0.447. number of fibres r = 0.321 and r = 0.278. and percentage of lesions: r = −0.219; r = −0.426, respectively) than damage to short-range connections. Only damage to long-distance connections correlated with a more abnormal functional network (fractional anisotropy: r = 0.226). Our findings indicate that long-range connections are more severely affected by multiple sclerosis-specific damage than short-range connections. Moreover compared to short-range connections, damage to long-range connections better explains network efficiency and cognition.

Relationship between β-amyloid and structural network topology in decedents without dementia

OBJECTIVE

To investigate the association between β-amyloid (Aβ) load and postmortem structural network topology in decedents without dementia.

METHODS

Fourteen decedents (mean age at death 72.6 ± 7.2 years) without known clinical diagnosis of neurodegenerative disease and meeting pathology criteria only for no or low Alzheimer disease (AD) pathologic change were selected from the Normal Aging Brain Collection Amsterdam database. In situ brain MRI included 3D T1-weighted images for anatomical registration and diffusion tensor imaging for probabilistic tractography with subsequent structural network construction. Network topologic measures of centrality (degree), integration (global efficiency), and segregation (clustering and local efficiency) were calculated. Tissue sections from 12 cortical regions were sampled and immunostained for Aβ and hyperphosphorylated tau (p-tau), and histopathologic burden was determined. Linear mixed effect models were used to assess the relationship between Aβ and p-tau load and network topologic measures.

RESULTS

Aβ was present in 79% of cases and predominantly consisted of diffuse plaques; p-tau was sparsely present. Linear mixed effect models showed independent negative associations between Aβ load and global efficiency (β = -0.83 × 10^-3, p = 0.014), degree (β = -0.47, p = 0.034), and clustering (β = -0.55 × 10^-2, p = 0.043). A positive association was present between Aβ load and local efficiency (β = 3.16 × 10^-3, p = 0.035). Regionally, these results were significant in the posterior cingulate cortex (PCC) for degree (β = -2.22, p < 0.001) and local efficiency (β = 1.01 × 10^-2, p = 0.014) and precuneus for clustering (β = -0.91 × 10^-2, p = 0.017). There was no relationship between p-tau and network topology.

CONCLUSION

This study in deceased adults with AD-related pathologic change provides evidence for a relationship among early Aβ accumulation, predominantly of the diffuse type, and structural network topology, specifically of the PCC and precuneus.

Axonal degeneration as substrate of fractional anisotropy abnormalities in multiple sclerosis cortex

Cortical microstructural abnormalities are associated with clinical and cognitive deterioration in multiple sclerosis. Using diffusion tensor MRI, a higher fractional anisotropy has been found in cortical lesions versus normal-appearing cortex in multiple sclerosis. The pathological substrates of this finding have yet to be definitively elucidated. By performing a combined post-mortem diffusion tensor MRI and histopathology study, we aimed to define the histopathological substrates of diffusivity abnormalities in multiple sclerosis cortex. Sixteen subjects with multiple sclerosis and 10 age- and sex-matched non-neurological control donors underwent post-mortem in situ at 3 T MRI, followed by brain dissection. One hundred and ten paraffin-embedded tissue blocks (54 from multiple sclerosis patients, 56 from non-neurological controls) were matched to the diffusion tensor sequence to obtain regional diffusivity measures. Using immunohistochemistry and silver staining, cortical density of myelin, microglia, astrocytes and axons, and density and volume of neurons and glial cells were evaluated. Correlates of diffusivity abnormalities with histological markers were assessed through linear mixed-effects models. Cortical lesions (77% subpial) were found in 27/54 (50%) multiple sclerosis cortical regions. Multiple sclerosis normal-appearing cortex had a significantly lower fractional anisotropy compared to cortex from non-neurological controls (P = 0.047), whereas fractional anisotropy in demyelinated cortex was significantly higher than in multiple sclerosis normal-appearing cortex (P = 0.012) but not different from non-neurological control cortex (P = 0.420). Compared to non-neurological control cortex, both multiple sclerosis normal-appearing and demyelinated cortices showed a lower density of axons perpendicular to the cortical surface (P = 0.012 for both) and of total axons (parallel and perpendicular to cortical surface) (P = 0.028 and 0.012). In multiple sclerosis, demyelinated cortex had a lower density of myelin (P = 0.004), parallel (P = 0.018) and total axons (P = 0.029) versus normal-appearing cortex. Regarding the pathological substrate, in non-neurological controls, cortical fractional anisotropy was positively associated with density of perpendicular, parallel, and total axons (P = 0.031 for all). In multiple sclerosis, normal-appearing cortex fractional anisotropy was positively associated with perpendicular and total axon density (P = 0.031 for both), while associations with myelin, glial and total cells and parallel axons did not survive multiple comparison correction. Demyelinated cortex fractional anisotropy was positively associated with density of neurons, and total cells and negatively with microglia density, without surviving multiple comparison correction. Our results suggest that a reduction of perpendicular axons in normal-appearing cortex and of both perpendicular and parallel axons in demyelinated cortex may underlie the substrate influencing cortical microstructural coherence and being responsible for the different patterns of fractional anisotropy changes occurring in multiple sclerosis cortex.

Cortical axonal loss is associated with both gray matter demyelination and white matter tract pathology in progressive multiple sclerosis: Evidence from a combined MRI-histopathology study

Background:

Neuroaxonal degeneration is one of the hallmarks of clinical deterioration in progressive multiple sclerosis (PMS).

Objective:

To elucidate the association between neuroaxonal degeneration and both local cortical and connected white matter (WM) tract pathology in PMS.

Methods:

Post-mortem in situ 3T magnetic resonance imaging (MRI) and cortical tissue blocks were collected from 16 PMS donors and 10 controls. Cortical neuroaxonal, myelin, and microglia densities were quantified histopathologically. From diffusion tensor MRI, fractional anisotropy, axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) were quantified in normal-appearing white matter (NAWM) and white matter lesions (WML) of WM tracts connected to dissected cortical regions. Between-group differences and within-group associations were investigated through linear mixed models.

Results:

The PMS donors displayed significant axonal loss in both demyelinated and normal-appearing (NA) cortices (p < 0.001 and p = 0.02) compared with controls. In PMS, cortical axonal density was associated with WML MD and AD (p = 0.003; p = 0.02, respectively), and NAWM MD and AD (p = 0.04; p = 0.049, respectively). NAWM AD and WML AD explained 12.6% and 22.6%, respectively, of axonal density variance in NA cortex. Additional axonal loss in demyelinated cortex was associated with cortical demyelination severity (p = 0.002), explaining 34.4% of axonal loss variance.

Conclusion:

Reduced integrity of connected WM tracts and cortical demyelination both contribute to cortical axonal loss in PMS.

Can post-mortem MRI be used as a proxy for in vivo? A case study

Post-mortem in situ MRI has been used as an intermediate between brain histo(patho)logy and in vivo imaging. However, it is not known how comparable post-mortem in situ is to ante-mortem imaging. We report the unique situation of a patient with familial early-onset Alzheimer's disease due to a PSEN1 mutation, who underwent ante-mortem brain MRI and post-mortem in situ imaging only 4 days apart. T1-weighted and diffusion MRI was performed at 3-Tesla at both time points. Visual atrophy rating scales, brain volume, cortical thickness and diffusion measures were derived from both scans and compared. Post-mortem visual atrophy scores decreased 0.5-1 point compared with ante-mortem, indicating an increase in brain volume. This was confirmed by quantitative analysis; showing a 27% decrease of ventricular and 7% increase of whole-brain volume. This increase was more pronounced in the cerebellum and supratentorial white matter than in grey matter. Furthermore, axial and radial diffusivity decreased up to 60% post-mortem whereas average fractional anisotropy of white matter increased approximately 10%. This unique case study shows that the process of dying affects several imaging markers. These changes need to be taken into account when interpreting post-mortem MRI to make inferences on the in vivo situation.

Cortical atrophy accelerates as cognitive decline worsens in multiple sclerosis

Objective

To determine which pathologic process could be responsible for the acceleration of cognitive decline during the course of multiple sclerosis (MS), using longitudinal structural MRI, which was related to cognitive decline in relapsing-remitting MS (RRMS) and progressive MS (PMS).

Methods

A prospective cohort of 230 patients with MS (179 RRMS and 51 PMS) and 59 healthy controls was evaluated twice with 5-year (mean 4.9, SD 0.94) interval during which 22 patients with RRMS converted to PMS. Annual rates of cortical and deep gray matter atrophy as well as lesion volume increase were computed on longitudinal (3T) MRI data and correlated to the annual rate of cognitive decline as measured using an extensive cognitive evaluation at both time points.

Results

The deep gray matter atrophy rate did not differ between PMS and RRMS (−0.82%/year vs −0.71%/year, p = 0.11), while faster cortical atrophy was observed in PMS (−0.87%/year vs −0.48%/year, p < 0.01). Similarly, faster cognitive decline was observed in PMS compared to RRMS (p < 0.01). Annual cognitive decline was related to the rate of annual lesion volume increase in stable RRMS (r = −0.17, p = 0.03) to the rate of annual deep gray matter atrophy in converting RRMS (r = 0.50, p = 0.02) and annual cortical atrophy in PMS (r = 0.35, p = 0.01).

Conclusions

These results indicate that cortical atrophy and cognitive decline accelerate together during the course of MS. Substrates of cognitive decline shifted from worsening lesional pathology in stable RRMS to deep gray matter atrophy in converting RRMS and to accelerated cortical atrophy in PMS only.

Validation of mean upper cervical cord area (MUCCA) measurement techniques in multiple sclerosis (MS): High reproducibility and robustness to lesions, but large software and scanner effects

Introduction

Atrophy of the spinal cord is known to occur in multiple sclerosis (MS). The mean upper cervical cord area (MUCCA) can be used to measure this atrophy. Currently, several (semi-)automated methods for MUCCA measurement exist, but validation in clinical magnetic resonance (MR) images is lacking.

Methods

Five methods to measure MUCCA (SCT-PropSeg, SCT-DeepSeg, NeuroQLab, Xinapse JIM and ITK-SNAP) were investigated in a predefined upper cervical cord region. First, within-scanner reproducibility and between-scanner robustness were assessed using intra-class correlation coefficient (ICC) and Dice's similarity index (SI) in scan-rescan 3DT1-weighted images (brain, including cervical spine using a head coil) performed on three 3 T MR machines (GE MR750, Philips Ingenuity, Toshiba Vantage Titan) in 21 subjects with MS and 6 healthy controls (dataset A). Second, sensitivity of MUCCA measurement to lesions in the upper cervical cord was assessed with cervical 3D T1-weighted images (3 T GE HDxT using a head-neck-spine coil) in 7 subjects with MS without and 14 subjects with MS with cervical lesions (dataset B), using ICC and SI with manual reference segmentations.

Results

In dataset A, MUCCA differed between MR machines (p < 0.001) and methods (p < 0.001) used, but not between scan sessions. With respect to MUCCA values, Xinapse JIM showed the highest within-scanner reproducibility (ICC absolute agreement = 0.995) while Xinapse JIM and SCT-PropSeg showed the highest between-scanner robustness (ICC consistency = 0.981 and 0.976, respectively). Reproducibility of segmentations between scan sessions was highest in Xinapse JIM and SCT-PropSeg segmentations (median SI ≥ 0.921), with a significant main effect of method (p < 0.001), but not of MR machine or subject group. In dataset B, SI with manual outlines did not differ between patients with or without cervical lesions for any of the segmentation methods (p > 0.176). However, there was an effect of method for both volumetric and voxel wise agreement of the segmentations (both p < 0.001). Highest volumetric and voxel wise agreement was obtained with Xinapse JIM (ICC absolute agreement = 0.940 and median SI = 0.962).

Conclusion

Although MUCCA is highly reproducible within a scanner for each individual measurement method, MUCCA differs between scanners and between methods. Cervical cord lesions do not affect MUCCA measurement performance.

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Mean upper cervical cord area (MUCCA) was obtained with five different methods.

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MUCCA was determined in a unique scan-rescan multi-vendor MR study.

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Reproducibility: MUCCA did not differ between scan-rescan images for any method.

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Robustness: MUCCA differed between methods and between scanners.

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Performance of MUCCA methods was not affected by the presence of lesions.

Plasma proteome in multiple sclerosis disease progression

Background

The pathophysiology of multiple sclerosis disease progression remains undetermined. The aim of this study was to identify differences in plasma proteome during different stages of MS disease progression.

Methods

We used a multiplex aptamer proteomics platform (Somalogic) for sensitive detection of 1129 proteins in plasma. MS patients were selected and categorized based on baseline and a 4‐year follow‐up EDSS (delta EDSS) scores; relapse‐onset (RO) slow progression (n = 31), RO with rapid progression (n = 29), primary progressive (n = 30), and healthy controls (n = 20). The relation of baseline plasma protein levels with delta EDSS and different MRI progression parameters were assessed using linear regression models.

Results

Regression analyses of plasma proteins with delta EDSS showed six significant associations. Strong associations were found for the proteins LGLAS8 (P = 7.64 × 10⁻⁵, q = 0.06), CCL3 (P = 0.0001, q = 0.06), and RGMA (P = 0.0005, q = 0.09). In addition, associations of plasma proteins were found with percentage brain volume for C3 (P = 2,08 × 10⁻⁹, q = 1,70 × 10⁻⁶), FGF9 (P = 3,42 × 10⁻⁹, q = 1,70 × 10⁻⁶), and EHMT2 (P = 0.0007, q = 0.01). Most of the significant markers were associated with cell‐cell and cell‐extracellular matrix adhesion, immune system communication, immune system activation, and complement pathways.

Conclusions

Our results revealed eight novel biomarkers related to clinical and radiological progression in MS. These results indicate that changes in immune system, complement pathway and ECM remodeling proteins contribute to MS progression and may therefore be further explored for use in prognosis of MS.

A pilot study of the effects of running training on visuospatial memory in MS: A stronger functional embedding of the hippocampus in the default-mode network?

BACKGROUND/OBJECTIVE

Endurance exercise can improve memory function in persons with multiple sclerosis (pwMS), but the effects on hippocampal functioning are currently unknown. We investigated the effects of a running intervention on memory and hippocampal functional connectivity in pwMS.

METHODS/RESULTS

Memory and resting-state functional magnetic resonance imaging (fMRI) data were collected in a running intervention (n = 15) and waitlist group (n = 14). Visuospatial memory improvement was correlated to increased connectivity between the hippocampus and the default-mode network (DMN) in the intervention group only.

CONCLUSION

As a result of endurance exercise, improvements in visuospatial memory may be mediated by a stronger functional embedding of the hippocampus in the DMN.

Predicting cognitive decline in multiple sclerosis: a 5-year follow-up study

Cognitive decline is common in multiple sclerosis and strongly affects overall quality of life. Despite the identification of cross-sectional MRI correlates of cognitive impairment, predictors of future cognitive decline remain unclear. The objective of this study was to identify which MRI measures of structural damage, demographic and/or clinical measures at baseline best predict cognitive decline, during a 5-year follow-up period. A total of 234 patients with clinically definite multiple sclerosis and 60 healthy control subjects were examined twice, with a 5-year interval (mean = 4.9 years, standard deviation = 0.9). An extensive neuropsychological evaluation was performed at both time points and the reliable change index was computed to evaluate cognitive decline. Both whole-brain and regional MRI (3 T) measures were assessed at baseline, including white matter lesion volume, diffusion-based white matter integrity, cortical and deep grey matter volume. Logistic regression analyses were performed to determine which baseline measures best predicted cognitive decline in the entire sample as well as in early relapsing-remitting (symptom duration <10 years), late relapsing-remitting (symptom duration ≥10 years) and progressive phenotypes. At baseline, patients with multiple sclerosis had a mean disease duration of 14.8 (standard deviation = 8.4) years and 96/234 patients (41%) were classified as cognitively impaired. A total of 66/234 patients (28%) demonstrated cognitive decline during follow-up, with higher frequencies in progressive compared to relapsing-remitting patients: 18/33 secondary progressive patients (55%), 10/19 primary progressive patients (53%) and 38/182 relapsing-remitting patients (21%). A prediction model that included only whole-brain MRI measures (Nagelkerke R2 = 0.22, P < 0.001) showed cortical grey matter volume as the only significant MRI predictor of cognitive decline, while a prediction model that assessed regional MRI measures (Nagelkerke R2 = 0.35, P < 0.001) indicated integrity loss of the anterior thalamic radiation, lesions in the superior longitudinal fasciculus and temporal atrophy as significant MRI predictors for cognitive decline. Disease stage specific regressions showed that cognitive decline in early relapsing-remitting multiple sclerosis was predicted by white matter integrity damage, while cognitive decline in late relapsing-remitting and progressive multiple sclerosis was predicted by cortical atrophy. These results indicate that patients with more severe structural damage at baseline, and especially cortical atrophy, are more prone to suffer from cognitive decline. New studies now need to further elucidate the underlying mechanisms leading to cortical atrophy, evaluate the value of including cortical atrophy as a possible outcome marker in clinical trials as well as study its potential use in individual patient management.

Structural network topology relates to tissue properties in multiple sclerosis

OBJECTIVE

Abnormalities in segregative and integrative properties of brain networks have been observed in multiple sclerosis (MS) and are related to clinical functioning. This study aims to investigate the micro-scale correlates of macro-scale network measures of segregation and integration in MS.

METHODS

Eight MS patients underwent post-mortem in situ whole-brain diffusion tensor (DT) imaging and subsequent brain dissection. Macro-scale structural network topology was derived from DT data using graph theory. Clustering coefficient and mean white matter (WM) fiber length were measures of nodal segregation and integration. Thirty-three tissue blocks were collected from five cortical brain regions. Using immunohistochemistry micro-scale tissue properties were evaluated, including, neuronal size, neuronal density, axonal density and total cell density. Nodal network properties and tissue properties were correlated.

RESULTS

A negative correlation between clustering coefficient and WM fiber length was found. Higher clustering coefficient was associated with smaller neuronal size and lower axonal density, and vice versa for fiber length. Higher whole-brain WM lesion load was associated with higher whole-brain clustering, shorter whole-brain fiber length, lower neuronal size and axonal density.

CONCLUSION

Structural network properties on MRI associate with neuronal size and axonal density, suggesting that macro-scale network measures may grasp cortical neuroaxonal degeneration in MS.

In vivo assessment of neuroinflammation in progressive multiple sclerosis: a proof of concept study with [18F]DPA714 PET

Background

Over the past decades, positron emission tomography (PET) imaging has become an increasingly useful research modality in the field of multiple sclerosis (MS) research, as PET can visualise molecular processes, such as neuroinflammation, in vivo. The second generation PET radioligand [¹⁸F]DPA714 binds with high affinity to the 18-kDa translocator-protein (TSPO), which is mainly expressed on activated microglia. The aim of this proof of concept study was to evaluate this in vivo marker of neuroinflammation in primary and secondary progressive MS.

Methods

All subjects were genotyped for the rs6971 polymorphism within the TSPO gene, and low-affinity binders were excluded from participation in this study. Eight patients with progressive MS and seven age and genetic binding status matched healthy controls underwent a 60 min dynamic PET scan using [¹⁸F]DPA714, including both continuous on-line and manual arterial blood sampling to obtain metabolite-corrected arterial plasma input functions.

Results

The optimal model for quantification of [¹⁸F]DPA714 kinetics was a reversible two-tissue compartment model with additional blood volume parameter. For genetic high-affinity binders, a clear increase in binding potential was observed in patients with MS compared with age-matched controls. For both high and medium affinity binders, a further increase in binding potential was observed in T2 white matter lesions compared with non-lesional white matter. Volume of distribution, however, did not differentiate patients from healthy controls, as the large non-displaceable compartment of [¹⁸F]DPA714 masks its relatively small specific signal.

Conclusion

The TSPO radioligand [¹⁸F]DPA714 can reliably identify increased focal and diffuse neuroinflammation in progressive MS when using plasma input-derived binding potential, but observed differences were predominantly visible in high-affinity binders.

Electronic supplementary material

The online version of this article (10.1186/s12974-018-1352-9) contains supplementary material, which is available to authorized users.

Accelerated executive functions decline and gray matter structural changes in middle-aged type 1 diabetes mellitus patients with proliferative retinopathy

BACKGROUND

The aim of the present study was to determine trajectories of cognitive and cortical changes over time in middle-aged patients with type 1 diabetes mellitus (T1DM) and proliferative retinopathy.

METHODS

Twenty-five patients and 25 controls underwent neuropsychological assessment and neuroimaging twice in a mean (±SD) of 3.56 ± 0.65 and 3.94 ± 0.91 years, respectively (P = 0.098). Cognitive assessment included the domains of general cognitive ability, memory, information processing speed, executive functions, attention, and motor and psychomotor speed. Symmetrized percentage change in local cortical thickness, surface area, and volume was determined using the FreeSurfer 6 vertex-wise general linear model method. Analyses were performed uncorrected and corrected for baseline systolic blood pressure and depressive symptoms.

RESULTS

In patients versus controls, accelerated executive function decline was accompanied by, but not related to, lower left frontal and temporal surface area, left parietal and right frontal thickness, and bilateral frontal and right posterior cingulate volume (family-wise error [FWE]-corrected P < 0.05 for all). In patients, lower executive performance was related to loss of right precuneus surface area (P_FWE  = 0.005). Higher HbA1c during follow-up was related to executive function decline (r = -0.509, P = 0.016) and loss of left hemisphere surface area (r_{corrected analysis}  = -0.555, P = 0.007).

CONCLUSIONS

After 3.5 years of follow-up, middle-aged T1DM patients with proliferative retinopathy, mild focal changes in executive functions, and cortical structure were found, which may indicate accelerated aging.

Information processing speed in multiple sclerosis: Relevance of default mode network dynamics

Objective

To explore the added value of dynamic functional connectivity (dFC) of the default mode network (DMN) during resting-state (RS), during an information processing speed (IPS) task, and the within-subject difference between these conditions, on top of conventional brain measures in explaining IPS in people with multiple sclerosis (pwMS).

Methods

In 29 pwMS and 18 healthy controls, IPS was assessed with the Letter Digit Substitution Test and Stroop Card I and combined into an IPS-composite score. White matter (WM), grey matter (GM) and lesion volume were measured using 3 T MRI. WM integrity was assessed with diffusion tensor imaging. During RS and task-state fMRI (i.e. symbol digit modalities task, IPS), stationary functional connectivity (sFC; average connectivity over the entire time series) and dFC (variation in connectivity using a sliding window approach) of the DMN was calculated, as well as the difference between both conditions (i.e. task-state minus RS; ΔsFC-DMN and ΔdFC-DMN). Regression analysis was performed to determine the most important predictors for IPS.

Results

Compared to controls, pwMS performed worse on IPS-composite (p = 0.022), had lower GM volume (p < 0.05) and WM integrity (p < 0.001), but no alterations in sFC and dFC at the group level. In pwMS, 52% of variance in IPS-composite could be predicted by cortical volume (β = 0.49, p = 0.01) and ΔdFC-DMN (β = 0.52, p < 0.01). After adding dFC of the DMN to the model, the explained variance in IPS increased with 26% (p < 0.01).

Conclusion

On top of conventional brain measures, dFC from RS to task-state explains additional variance in IPS. This highlights the potential importance of the DMN to adapt upon cognitive demands to maintain intact IPS in pwMS.

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Problems with information processing speed occur often in multiple sclerosis (MS)

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Dynamics in brain communication can reflect information transfer within the brain

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With fMRI, dynamic communication can be measured, which increases upon task demands

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This increase in dynamics explains information processing speed in MS

Fronto-limbic disconnection in patients with multiple sclerosis and depression

Background:

The biological mechanism of depression in multiple sclerosis (MS) is not well understood. Based on work in major depressive disorder, fronto-limbic disconnection might be important.

Objective:

To investigate structural and functional fronto-limbic changes in depressed MS (DMS) and non-depressed MS (nDMS) patients.

Methods:

In this retrospective study, 22 moderate-to-severe DMS patients (disease duration 8.2 ± 7.7 years), 21 nDMS patients (disease duration 15.3 ± 8.3 years), and 12 healthy controls underwent neuropsychological testing and magnetic resonance imaging (MRI; 1.5 T). Brain volumes (white matter (WM), gray matter, amygdala, hippocampus, thalamus), lesion load, fractional anisotropy (FA) of fronto-limbic tracts, and resting-state functional connectivity (FC) between limbic and frontal areas were measured and compared between groups. Regression analysis was performed to relate MRI measures to the severity of depression.

Results:

Compared to nDMS patients, DMS patients (shorter disease duration) had lower WM volume (p < 0.01), decreased FA of the uncinate fasciculus (p < 0.05), and lower FC between the amygdala and frontal regions (p < 0.05). Disease duration, FA of the uncinate fasciculus, and FC of the amygdala could explain 48% of variance in the severity of depression. No differences in cognition were found.

Conclusion:

DMS patients showed more pronounced (MS) damage, that is, structural and functional changes in temporo-frontal regions, compared to nDMS patients, suggestive of fronto-limbic disconnection.

Explaining the heterogeneity of functional connectivity findings in multiple sclerosis: An empirically informed modeling study

To understand the heterogeneity of functional connectivity results reported in the literature, we analyzed the separate effects of grey and white matter damage on functional connectivity and networks in multiple sclerosis. For this, we employed a biophysical thalamo‐cortical model consisting of interconnected cortical and thalamic neuronal populations, informed and amended by empirical diffusion MRI tractography data, to simulate functional data that mimic neurophysiological signals. Grey matter degeneration was simulated by decreasing within population connections and white matter degeneration by lowering between population connections, based on lesion predilection sites in multiple sclerosis. For all simulations, functional connectivity and functional network organization are quantified by phase synchronization and network integration, respectively. Modeling results showed that both cortical and thalamic grey matter damage induced a global increase in functional connectivity, whereas white matter damage induced an initially increased connectivity followed by a global decrease. Both white and especially grey matter damage, however, induced a decrease in network integration. These empirically informed simulations show that specific topology and timing of structural damage are nontrivial aspects in explaining functional abnormalities in MS. Insufficient attention to these aspects likely explains contradictory findings in multiple sclerosis functional imaging studies so far.

Gray matter networks and cognitive impairment in multiple sclerosis

BACKGROUND

Coordinated patterns of gray matter morphology can be represented as networks, and network disruptions may explain cognitive dysfunction related to multiple sclerosis (MS).

OBJECTIVE

To investigate whether single-subject gray matter network properties are related to impaired cognition in MS.

METHODS

We studied 148 MS patients (99 female) and 33 healthy controls (HC, 21 female). Seven network parameters were computed and compared within MS between cognitively normal and impaired subjects, and associated with performance on neuropsychological tests in six cognitive domains with regression models. Analyses were controlled for age, gender, whole-brain gray matter volumes, and education level.

RESULTS

Compared to MS subjects with normal cognition, MS subjects with cognitive impairment showed a more random network organization as indicated by lower lambda values (all p < 0.05). Worse average cognition and executive function were associated with lower lambda values. Impaired information processing speed, working memory, and attention were associated with lower clustering values.

CONCLUSION

Our findings indicate that MS subjects with a more randomly organized gray matter network show worse cognitive functioning, suggesting that single-subject gray matter graphs may capture neurological dysfunction due to MS.

Reproducibility of Deep Gray Matter Atrophy Rate Measurement in a Large Multicenter Dataset

BACKGROUND AND PURPOSE

Precise in vivo measurement of deep GM volume change is a highly demanded prerequisite for an adequate evaluation of disease progression and new treatments. However, quantitative data on the reproducibility of deep GM structure volumetry are not yet available. In this paper we aim to investigate this reproducibility using a large multicenter dataset.

MATERIALS AND METHODS

We have assessed the reproducibility of 2 automated segmentation software packages (FreeSurfer and the FMRIB Integrated Registration and Segmentation Tool) by quantifying the volume changes of deep GM structures by using back-to-back MR imaging scans from the Alzheimer Disease Neuroimaging Initiative's multicenter dataset. Five hundred sixty-two subjects with scans at baseline and 1 year were included. Reproducibility was investigated in the bilateral caudate nucleus, putamen, amygdala, globus pallidus, and thalamus by carrying out descriptives as well as multilevel and variance component analysis.

RESULTS

Median absolute back-to-back differences varied between GM structures, ranging from 59.6-156.4 μL for volume change, and 1.26%-8.63% for percentage volume change. FreeSurfer had a better performance for the outcome of longitudinal volume change for the bilateral amygdala, putamen, left caudate nucleus (P < .005), and right thalamus (P < .001). For longitudinal percentage volume change, Freesurfer performed better for the left amygdala, bilateral caudate nucleus, and left putamen (P < .001). Smaller limits of agreement were found for FreeSurfer for both outcomes for all GM structures except the globus pallidus. Our results showed that back-to-back differences in 1-year percentage volume change were approximately 1.5-3.5 times larger than the mean measured 1-year volume change of those structures.

CONCLUSIONS

Longitudinal deep GM atrophy measures should be interpreted with caution. Furthermore, deep GM atrophy measurement techniques require substantially improved reproducibility, specifically when aiming for personalized medicine.

Performance of five research-domain automated WM lesion segmentation methods in a multi-center MS study

BACKGROUND AND PURPOSE

In vivoidentification of white matter lesions plays a key-role in evaluation of patients with multiple sclerosis (MS). Automated lesion segmentation methods have been developed to substitute manual outlining, but evidence of their performance in multi-center investigations is lacking. In this work, five research-domain automated segmentation methods were evaluated using a multi-center MS dataset.

METHODS

70 MS patients (median EDSS of 2.0 [range 0.0-6.5]) were included from a six-center dataset of the MAGNIMS Study Group (www.magnims.eu) which included 2D FLAIR and 3D T1 images with manual lesion segmentation as a reference. Automated lesion segmentations were produced using five algorithms: Cascade; Lesion Segmentation Toolbox (LST) with both the Lesion growth algorithm (LGA) and the Lesion prediction algorithm (LPA); Lesion-Topology preserving Anatomical Segmentation (Lesion-TOADS); and k-Nearest Neighbor with Tissue Type Priors (kNN-TTP). Main software parameters were optimized using a training set (N = 18), and formal testing was performed on the remaining patients (N = 52). To evaluate volumetric agreement with the reference segmentations, intraclass correlation coefficient (ICC) as well as mean difference in lesion volumes between the automated and reference segmentations were calculated. The Similarity Index (SI), False Positive (FP) volumes and False Negative (FN) volumes were used to examine spatial agreement. All analyses were repeated using a leave-one-center-out design to exclude the center of interest from the training phase to evaluate the performance of the method on 'unseen' center.

RESULTS

Compared to the reference mean lesion volume (4.85 ± 7.29 mL), the methods displayed a mean difference of 1.60 ± 4.83 (Cascade), 2.31 ± 7.66 (LGA), 0.44 ± 4.68 (LPA), 1.76 ± 4.17 (Lesion-TOADS) and -1.39 ± 4.10 mL (kNN-TTP). The ICCs were 0.755, 0.713, 0.851, 0.806 and 0.723, respectively. Spatial agreement with reference segmentations was higher for LPA (SI = 0.37 ± 0.23), Lesion-TOADS (SI = 0.35 ± 0.18) and kNN-TTP (SI = 0.44 ± 0.14) than for Cascade (SI = 0.26 ± 0.17) or LGA (SI = 0.31 ± 0.23). All methods showed highly similar results when used on data from a center not used in software parameter optimization.

CONCLUSION

The performance of the methods in this multi-center MS dataset was moderate, but appeared to be robust even with new datasets from centers not included in training the automated methods.

Structure-function relationships in the visual system in multiple sclerosis: an MEG and OCT study

BACKGROUND

We conducted a multi-modal optical coherence tomography (OCT) and magnetoencephalography (MEG) study to test whether there is a relationship between retinal layer integrity and electrophysiological activity and connectivity (FC) in the visual network influenced by optic neuritis (ON) in patients with multiple sclerosis (MS).

METHODS

One hundred and two MS patients were included in this MEG/OCT study. Retinal OCT data were collected from the optic discs, macular region, and segmented. Neuronal activity and FC in the visual cortex was estimated from source-reconstructed resting-state MEG data by computing relative power and the phase lag index (PLI). Generalized estimating equations (GEE) were used to account for intereye within-patient dependencies.

RESULTS

There was a significant relationship for both relative power and FC in the visual cortex with retinal layer thicknesses. The findings were influenced by the presence of MSON, particularly for connectivity in the alpha bands and the outer macular layers. In the absence of MSON, this relationship was dominated by the lower frequency bands (theta, delta) and inner and outer retinal layers.

CONCLUSION

These results suggest that visual cortex FC more than activity alters in the presence of MSON, which may guide the understanding of FC plasticity effects following MSON.

Agreement of MSmetrix with established methods for measuring cross-sectional and longitudinal brain atrophy

INTRODUCTION

Despite the recognized importance of atrophy in multiple sclerosis (MS), methods for its quantification have been mostly restricted to the research domain. Recently, a CE labelled and FDA approved MS-specific atrophy quantification method, MSmetrix, has become commercially available. Here we perform a validation of MSmetrix against established methods in simulated and in vivo MRI data.

METHODS

Whole-brain and gray matter (GM) volume were measured with the cross-sectional pipeline of MSmetrix and compared to the outcomes of FreeSurfer (cross-sectional pipeline), SIENAX and SPM. For this comparison we investigated 20 simulated brain images, as well as in vivo data from 100 MS patients and 20 matched healthy controls. In fifty of the MS patients a second time point was available. In this subgroup, we additionally analyzed the whole-brain and GM volume change using the longitudinal pipeline of MSmetrix and compared the results with those of FreeSurfer (longitudinal pipeline) and SIENA.

RESULTS

In the simulated data, SIENAX displayed the smallest average deviation compared with the reference whole-brain volume (+ 19.56 ± 10.34 mL), followed by MSmetrix (- 38.15 ± 17.77 mL), SPM (- 42.99 ± 17.12 mL) and FreeSurfer (- 78.51 ± 12.68 mL). A similar pattern was seen in vivo. Among the cross-sectional methods, Deming regression analyses revealed proportional errors particularly in MSmetrix and SPM. The mean difference percentage brain volume change (PBVC) was lowest between longitudinal MSmetrix and SIENA (+ 0.16 ± 0.91%). A strong proportional error was present between longitudinal percentage gray matter volume change (PGVC) measures of MSmetrix and FreeSurfer (slope = 2.48). All longitudinal methods were sensitive to the MRI hardware upgrade that occurred during the time of the study.

CONCLUSION

MSmetrix, FreeSurfer, FSL and SPM show differences in atrophy measurements, even at the whole-brain level, that are large compared to typical atrophy rates observed in MS. Especially striking are the proportional errors between methods. Cross-sectional MSmetrix behaved similarly to SPM, both in terms of mean volume difference as well as proportional error. Longitudinal MSmetrix behaved most similar to SIENA. Our results indicate that brain volume measurement and normalization from T1-weighted images remains an unsolved problem that requires much more attention.

Cerebrospinal fluid mtDNA concentration is elevated in multiple sclerosis disease and responds to treatment

BACKGROUND

Mitochondrial dysfunction is increasingly recognized as an important feature of multiple sclerosis (MS) pathology and may be relevant for clinical disease progression. However, it is unknown whether mitochondrial DNA (mtDNA) levels in the cerebrospinal fluid (CSF) associate with disease progression and therapeutic response.

OBJECTIVES

To evaluate whether CSF concentrations of mtDNA in MS patients can serve as a marker of ongoing neuropathology and may be helpful to differentiate between MS disease subtypes. To explore the effect of disease-modifying therapies on mtDNA levels in the CSF.

METHODS

CSF mtDNA was measured using a digital polymerase chain reaction (PCR) CSF mtDNA in two independent MS cohorts. The cohorts included 92 relapsing-remitting multiple sclerosis (RRMS) patients, 40 progressive multiple sclerosis (PMS) patients (27 secondary progressive and 13 primary progressive), 50 various neurologic disease controls, and 5 healthy controls.

RESULTS

Patients with PMS showed a significant increase in CSF mtDNA compared to non-inflammatory neurologic disease controls. Patients with higher T2 lesion volumes and lower normalized brain volumes showed increased concentration of mtDNA. Patients treated with fingolimod had significantly lower mtDNA copy levels at follow-up compared to baseline.

CONCLUSION

Our results showed a non-specific elevation of concentration of mtDNA in PMS patients. mtDNA concentrations respond to fingolimod and may be used to monitor biological effect of this treatment.

Increased default-mode network centrality in cognitively impaired multiple sclerosis patients

OBJECTIVE

To investigate how changes in functional network hierarchy determine cognitive impairment in multiple sclerosis (MS).

METHODS

A cohort consisting of 332 patients with MS (age 48.1 ± 11.0 years, symptom duration 14.6 ± 8.4 years) and 96 healthy controls (HCs; age 45.9 ± 10.4 years) underwent structural MRI, fMRI, and extensive neuropsychological testing. Patients were divided into 3 groups: cognitively impaired (CI; n = 87), mildly cognitively impaired (MCI; n = 65), and cognitively preserved (CP; n = 180). The functional importance of brain regions was quantified with degree centrality, the average strength of the functional connections of a brain region with the rest of the brain, and eigenvector centrality, which adds to this concept by adding additional weight to connections with brain hubs because these are known to be especially important. Centrality values were calculated for each gray matter voxel based on resting-state fMRI data, registered to standard space. Group differences were assessed with a cluster-wise permutation-based method corrected for age, sex, and education.

RESULTS

CI patients demonstrated widespread centrality increases compared to both HCs and CP patients, mainly in regions making up the default-mode network. Centrality decreases were similar in all patient groups compared to HCs, mainly in occipital and sensorimotor areas. Results were robust across centrality measures.

CONCLUSIONS

Patients with MS with cognitive impairment show hallmark alterations in functional network hierarchy with increased relative importance (centrality) of the default-mode network.

High-resolution T1-relaxation time mapping displays subtle, clinically relevant, gray matter damage in long-standing multiple sclerosis

Background:

Gray matter (GM) pathology has high clinical relevance in multiple sclerosis (MS), but conventional magnetic resonance imaging (MRI) is insufficiently sensitive to visualize the rather subtle damage.

Objective:

To investigate whether high spatial resolution T1-relaxation time (T1-RT) measurements can detect changes in the normal-appearing GM of patients with long-standing MS and whether these changes are associated with physical and cognitive impairment.

Methods:

High spatial resolution (1.05 × 1.05 × 1.2 mm3) T1-RT measurements were performed at 3 T in 156 long-standing MS patients and 54 healthy controls. T1-RT histogram parameters in several regions were analyzed to investigate group differences. Stepwise linear regression analyses were used to assess the relation of T1-RT with physical and cognitive impairment.

Results:

In both thalamus and cortex, T1-RT histogram skewness was higher in patients than controls. In the cortex, this was driven by the frontal and temporal lobes. No differences were found in other GM histogram parameters. Cortical skewness, thalamus volume, and average white matter (WM) lesion T1-RT emerged as the strongest predictors for cognitive performance (adjusted R2 = 0.39).

Conclusion:

Subtle GM damage was present in the cortex and thalamus of MS patients, as indicated by increased T1-RT skewness. Increased cortical skewness emerged as an independent predictor of cognitive dysfunction.

Elevated CSF neurofilament proteins predict brain atrophy: A 15-year follow-up study

Background:

Body fluid and structural imaging biomarkers give information on neurodegeneration. The relationship over time is not known in multiple sclerosis.

Objective:

To investigate the temporal relationship of elevated cerebrospinal fluid (CSF) neurofilament (Nf) protein levels, a biomarker for axonal loss, with magnetic resonance imaging (MRI) atrophy measures.

Methods:

In patients with multiple sclerosis, CSF Nf heavy chain (NfH) phosphoform levels were quantified at baseline and dichotomised into ‘normal’ and ‘high’. Atrophy was assessed by MRI at baseline and 15-year follow-up using SIENAX and FreeSurfer software.

Results:

High baseline CSF NfH SMI35 levels predicted pronounced atrophy at 15-year follow-up (odds ratio (OR): 36, p < 0.01), in the absence of baseline brain atrophy (OR: 28, p < 0.05), for the averaged MRI normalised brain volume (1.44 L vs 1.33 L, p < 0.05), normalised grey matter volume (0.77 L vs 0.69 L, p < 0.01) and putamen (12.7 mL vs 10.7 mL, p < 0.05). Region-specific calculations including the spinal cord showed that a power of >80% is reached with 14–50 patients.

Conclusion:

These data suggest that high CSF NfH levels are an early predictor of later brain and spinal cord atrophy using structural imaging biomarkers and can be investigated in reasonably sized patient cohorts.

White Matter Hyperintensity Volume and Cerebral Perfusion in Older Individuals with Hypertension Using Arterial Spin-Labeling

BACKGROUND AND PURPOSE

White matter hyperintensities of presumed vascular origin in elderly patients with hypertension may be part of a general cerebral perfusion deficit, involving not only the white matter hyperintensities but also the surrounding normal-appearing white matter and gray matter. We aimed to study the relation between white matter hyperintensity volume and CBF and assess whether white matter hyperintensities are related to a general perfusion deficit.

MATERIALS AND METHODS

In 185 participants of the Prevention of Dementia by Intensive Vascular Care trial between 72 and 80 years of age with systolic hypertension, white matter hyperintensity volume and CBF were derived from 3D FLAIR and arterial spin-labeling MR imaging, respectively. We compared white matter hyperintensity CBF, normal-appearing white matter CBF, and GM CBF across quartiles of white matter hyperintensity volume and assessed the continuous relation between these CBF estimates and white matter hyperintensity volume by using linear regression.

RESULTS

Mean white matter hyperintensity CBF was markedly lower in higher quartiles of white matter hyperintensity volume, and white matter hyperintensity volume and white matter hyperintensity CBF were negatively related (standardized β = -0.248, P = .001) in linear regression. We found no difference in normal-appearing white matter or GM CBF across quartiles of white matter hyperintensity volume or any relation between white matter hyperintensity volume and normal-appearing white matter CBF (standardized β = -0.065, P = .643) or GM CBF (standardized β = -0.035, P = .382) in linear regression.

CONCLUSIONS

Higher white matter hyperintensity volume in elderly individuals with hypertension was associated with lower perfusion within white matter hyperintensities, but not with lower perfusion in the surrounding normal-appearing white matter or GM. These findings suggest that white matter hyperintensities in elderly individuals with hypertension relate to local microvascular alterations rather than a general cerebral perfusion deficit.

White Matter Diffusion Changes during the First Year of Natalizumab Treatment in Relapsing-Remitting Multiple Sclerosis

BACKGROUND AND PURPOSE

Natalizumab treatment strongly affects relapsing-remitting multiple sclerosis, possibly by restraining white matter damage. This study investigated changes in white matter diffusivity in patients with relapsing-remitting multiple sclerosis during their first year of natalizumab treatment by using diffusion tensor imaging.

MATERIALS AND METHODS

The study included patients with relapsing-remitting multiple sclerosis initiating natalizumab at baseline (n = 22), patients with relapsing-remitting multiple sclerosis continuing interferon-β or glatiramer acetate (n = 17), and healthy controls (n = 12). Diffusion tensor imaging parameters were analyzed at baseline and month 12. We measured the extent and severity of white matter damage with diffusion tensor imaging parameters such as fractional anisotropy, comparing the patient groups with healthy controls at both time points.

RESULTS

The extent and severity of white matter damage were reduced significantly in the natalizumab group with time (fractional anisotropy-based extent, 56.8% to 47.2%; severity, z = -0.67 to -0.59; P = .02); this reduction was not observed in the interferon-β/glatiramer acetate group (extent, 41.4% to 39.1%, and severity, z = -0.64 to -0.67; P = .94). Cognitive performance did not change with time in the patient groups but did correlate with the severity of damage (r = 0.53, P = < .001).

CONCLUSIONS

In patients with relapsing-remitting multiple sclerosis starting natalizumab treatment, the extent and severity of white matter damage were reduced significantly in the first year of treatment. These findings may aid in explaining the large observed clinical effect of natalizumab in relapsing-remitting multiple sclerosis.

Causes, effects and connectivity changes in MS-related cognitive decline

Cognitive decline is a frequent but undervalued aspect of multiple sclerosis (MS). Currently, it remains unclear what the strongest determinants of cognitive dysfunction are, with grey matter damage most directly related to cognitive impairment. Multi-parametric studies seem to indicate that individual factors of MS-pathology are highly interdependent causes of grey matter atrophy and permanent brain damage. They are associated with intermediate functional effects (e.g. in functional MRI) representing a balance between disconnection and (mal) adaptive connectivity changes. Therefore, a more comprehensive MRI approach is warranted, aiming to link structural changes with functional brain organization. To better understand the disconnection syndromes and cognitive decline in MS, this paper reviews the associations between MRI metrics and cognitive performance, by discussing the interactions between multiple facets of MS pathology as determinants of brain damage and how they affect network efficiency.

Ultra-high field MTR and qR2* differentiates subpial cortical lesions from normal-appearing gray matter in multiple sclerosis

BACKGROUND

Cortical gray matter (GM) demyelination is frequent and clinically relevant in multiple sclerosis (MS). Quantitative magnetic resonance imaging (qMRI) sequences such as magnetization transfer ratio (MTR) and quantitative R2* (qR2*) can capture pathological subtleties missed by conventional magnetic resonance imaging (MRI) sequences. Although differences in MTR and qR2* have been reported between lesional and non-lesional tissue, differences between lesion types or lesion types and myelin density matched normal-appearing gray matter (NAGM) have not been found or investigated.

OBJECTIVE

Identify quantitative differences in histopathologically verified GM lesion types and matched NAGM at ultra-high field strength.

METHODS

Using 7T post-mortem MRI, MRI lesions were marked on T2 images and co-registered to the calculated MTR and qR2* maps for further evaluation. In all, 15 brain slices were collected, containing a total of 74 cortical GM lesions and 45 areas of NAGM.

RESULTS

Intracortical lesions had lower MTR and qR2* values compared to NAGM. Type I lesions showed lower MTR than type III lesions. Type III lesions showed lower MTR than matched NAGM, and type I and IV lesions showed lower qR2* than matched NAGM.

CONCLUSION

qMRI at 7T can provide additional information on extent of cortical pathology, especially concerning subpial lesions. This may be relevant for monitoring disease progression and potential treatment effects.

Multicenter Validation of Mean Upper Cervical Cord Area Measurements from Head 3D T1-Weighted MR Imaging in Patients with Multiple Sclerosis

BACKGROUND AND PURPOSE

Spinal cord atrophy is a common and clinically relevant characteristic in multiple sclerosis. We aimed to perform a multicenter validation study of mean upper cervical cord area measurements in patients with multiple sclerosis and healthy controls from head MR images and to explore the effect of gadolinium administration on mean upper cervical cord area measurements.

MATERIALS AND METHODS

We recruited 97 subjects from 3 centers, including 60 patients with multiple sclerosis of different disease types and 37 healthy controls. Both cervical cord and head 3D T1-weighted images were acquired. In 11 additional patients from 1 center, head images before and after gadolinium administration and cervical cord images after gadolinium administration were acquired. The mean upper cervical cord area was compared between cervical cord and head images by using intraclass correlation coefficients (ICC) for both consistency (ICCconsist) and absolute (ICCabs) agreement.

RESULTS

There was excellent agreement of mean upper cervical cord area measurements from head and cervical cord images in the entire group (ICCabs = 0.987) and across centers and disease subtypes. The mean absolute difference between the mean upper cervical cord area measured from head and cervical cord images was 2 mm(2) (2.3%). Additionally, excellent agreement was found between the mean upper cervical cord area measured from head images with and without gadolinium administration (ICCabs = 0.991) and between the cervical cord and head images with gadolinium administration (ICCabs = 0.992).

CONCLUSIONS

Excellent agreement between mean upper cervical cord area measurements on head and cervical cord images was observed in this multicenter study, implying that upper cervical cord atrophy can be reliably measured from head images. Postgadolinium head or cervical cord images may also be suitable for measuring mean upper cervical cord area.