A systematic review of microstructural abnormalities in multiple sclerosis detected with NODDI and DTI models of diffusion-weighted magnetic resonance imaging

White Matter Tract Degeneration in Multiple Sclerosis Patients With Progression Independent of Relapse Activity

BACKGROUND AND OBJECTIVES

Progression independent of relapse activity (PIRA) is associated with worse outcomes in people with multiple sclerosis (pwMS). Although previous research has linked PIRA to accelerated brain and spinal cord atrophy and compartmentalized chronic inflammation, the role of white matter (WM) tract degeneration remains unclear. This study aimed to explore the relationship between PIRA and the integrity of major WM tracts using diffusion tensor imaging (DTI).

METHODS

A cohort of 258 pwMS was stratified based on the presence or absence of PIRA over a 4-year follow-up period. At the end of follow-up, DTI metrics were compared between groups using propensity score-weighted linear regression models to account for potential confounders.

RESULTS

PwMS with ≥1 PIRA event (n = 39) exhibited significant reductions in fractional anisotropy and increases in radial, axial, and mean diffusivity within the corpus callosum and motor tracts (false discovery rate-adjusted p ≤ 0.04) compared with those without PIRA, indicating more pronounced WM damage.

DISCUSSION

Our findings highlight an association between PIRA and microstructural damage in key WM tracts. The observed DTI changes likely reflect processes such as Wallerian degeneration and contribute to the growing evidence linking PIRA to neurodegeneration.

Microglia positron emission tomography and progression in multiple sclerosis: thalamus on fire

Increased innate immune activity promotes neurodegeneration and contributes to progression in multiple sclerosis. This prospective case-control study aims to investigate thalamic microglia density on 18kDa translocator protein PET in patients with multiple sclerosis using a third-generation radioligand, 11C-ER176, and investigate the associations of 11C-ER176 PET uptake with imaging and clinical measures of progression in multiple sclerosis. Patients with multiple sclerosis (n = 50) and controls (n = 55) were prospectively enrolled and they underwent 11C-ER176 PET and MRI including diffusion MRI with neurite orientation dispersion and density imaging. Disease characteristics, expanded disability status scale and multiple sclerosis functional composite scores were obtained in patients with multiple sclerosis. Age at imaging (mean ± standard deviation: patients = 49.6 ± 12.9 years, controls = 48.2 ± 15.4 years, P = 0.63) and sex (female ratio; patients = 72%, controls = 65%, P = 0.47) were not different between the groups. Thalamus 11C-ER176 PET uptake was highest in patients with progressive multiple sclerosis (1.272 ± 0.072 standardized uptake value ratio), followed by patients with relapsing multiple sclerosis (1.209 ± 0.074 standardized uptake value ratio) and lowest in controls (1.162 ± 0.067 standardized uptake value ratio, P < 0.001). Patients with thalamic lesions had higher thalamus 11C-ER176 PET uptake than those without thalamic lesions in both relapsing multiple sclerosis and progressive multiple sclerosis (P < 0.001). In patients with multiple sclerosis, higher thalamus 11C-ER176 PET uptake correlated with lower thalamic volume (r = -0.45, P = 0.001), higher mean diffusivity (r = 0.56, P < 0.001), lower neurite density index (r = -0.43, P = 0.002), lower orientation dispersion index (r = -0.40, P = 0.005) and higher free water fraction (r = 0.42, P = 0.003) in the thalamus. In patients with multiple sclerosis, higher thalamus 11C-ER176 PET uptake also correlated with higher mean diffusivity (r = 0.47, P < 0.001) and lower neurite density index (r = -0.36, P = 0.012) in the corpus callosum. In patients with multiple sclerosis, higher thalamus 11C-ER176 PET uptake correlated with worse expanded disability status scale scores (r = 0.33, P = 0.02), paced auditory serial addition test scores (r = -0.43, P = 0.003) and multiple sclerosis functional composite z-scores (r = -0.46, P = 0.001). Microglia density in the thalamus is highest in patients with progressive multiple sclerosis and is associated with imaging biomarkers of neurodegeneration and clinical disease severity. As a signature imaging biomarker of progression in multiple sclerosis, effectively reflecting the global disease burden, 11C-ER176 PET may aid development and efficacy evaluation of therapeutics targeting microglia.

Soma and neurite density imaging detects brain microstructural impairments in amyotrophic lateral sclerosis

OBJECTIVE

To investigate whole-brain microstructural changes in amyotrophic lateral sclerosis (ALS) using soma and neurite density imaging (SANDI), a novel multicompartment model of diffusion-weighted imaging that estimates apparent soma and neurite density.

METHODS

This study consists of 41 healthy controls and 43 patients with ALS, whose diffusion-weighted data were acquired. The SANDI-derived (including signal fractions of soma (fsoma), neurite (fneurite), and extra-cellular space (fextra)) and diffusion tensor imaging (DTI)-derived metrics were obtained. Voxel-based analyses were performed to evaluate intergroup differences and the correlation of SANDI and DTI metrics with clinical parameters.

RESULTS

In ALS patients, fneurite reduction involved both gray matter (primarily the bilateral precentral gyri, supplementary motor area, medial frontal gyrus, anterior cingulate cortex, inferior frontal gyrus, orbital gyrus, paracentral lobule, postcentral gyrus, middle cingulate cortex, hippocampus and parahippocampal gyrus, and insula, and left anterior parts of the temporal lobe) and white matter (primarily the bilateral corticospinal tract, body of corpus callosum, and brainstem) (P <0.05 after false discovery rate correction). The fextra increment showed a similar spatial distribution in ALS patients. Interestingly, the decreased fsoma in ALS primarily located in gray matter; while, the increased fsoma primarily involved white matter. The spatial distribution of fneurite/fextra/fsoma changes was larger than that detected by conventional DTI metrics, and the fneurite/fextra/fsoma were correlated with disease severity.

CONCLUSIONS

SANDI may serve as a clinically relevant model, superior to conventional DTI, for characterizing microstructural impairments such as neurite degeneration and soma alteration in ALS.

Structural and functional changes of Post-Stroke Depression: A multimodal magnetic resonance imaging study

This study investigated changes in gray matter volume (GMV), white matter microstructure, and spontaneous brain activity in post-stroke depression (PSD) using multiple MRI techniques, including neurite orientation dispersion and density imaging (NODDI). Changes in GMV, neurite density index (NDI), orientation dispersion index (ODI), fraction of isotropic water (ISO), diffusion tensor imaging (DTI) parameters, and the amplitude of frequency fluctuations (ALFF) were assessed between PSD (n = 20), post-stroke without depression (n = 20), and normal control (n = 20) groups. Receiver operating characteristic (ROC) curve analysis was performed to test the classification performance of the variant parameters of each MRI modality, each single MRI modality and multiple MRI modality. Compared to patients with post-stroke without depression (non-PSD), those with PSD showed increased ODI and ISO in the widespread white matter, as well as increased ALFF in the left pallidum. No significant differences in the GMV or DTI parameters were observed between the two groups. Furthermore, the ODI of the right superior longitudinal fasciculus and NODDI showed the best classification performance for PSD at their respective comparison level (the areas under the ROC curves (AUC) = 0.917(0.000), 0.933(0.000)). The model of NODDI-derived parameters combined with non-diffusion MRI modality parameters (i.e., GMV and ALFF) showed better diagnostic performance than that of DTI-derived parameters. These findings suggest that PSD is associated with structural and functional abnormalities that may contribute to depressive symptoms. Additionally, NODDI showed its advantages in the description of structural alterations in emotion-related white matter pathways and classification performance in PSD.

Imaging neuroglia

Imaging can help us understand the role neuroglia plays in health and during the course of neurologic disorders. In vivo microscopy has had a great impact on our understanding of how neuroglia behaves during health and disease. While initially the technique was hindered by the limited penetration depth in brain tissue, recent advancements lead to increasing possibilities for imaging of deeper brain structures, even at super-resolution. Unfortunately, in vivo microscopy cannot be applied in a clinical setting and thus cannot be used to study neuroglia in patient populations. However, noninvasive imaging techniques like positron emission tomography (PET) and magnetic resonance imaging (MRI) can. PET has provided valuable information on the involvement of neuroglia in neurologic disorders. To more specifically image microglia and astrocytes, many new PET biomarkers have been defined for which PET tracers are continuously developed, evaluated, and improved. A cell-type specific PET tracer with favorable imaging characteristics can have a huge impact on neuroglia research. While being less sensitive than PET, MRI is a more accessible imaging technique. Initially, only general neuroinflammation processes could be imaged with MRI, but newly developed methods and sequences allow for increasing cell-type specificity. Overall, while each imaging method comes with limitations, improvements are continuously made, all with the aim to truly understand the role that neuroglia play in health and disease.

Genetic Associations Among Inflammation, White Matter Architecture, and Extracellular Free Water

Phenotypic and genetic relationships between white matter microstructure (i.e., fractional anisotropy [FA]) and peripheral inflammatory responses (i.e., circulating cytokines) have important implications for health and disease. However, it is unclear whether previously discovered genetic correlations between the two traits are due to tissue-specific white matter architecture or increased free water in the extracellular space. We applied a two-compartment model to diffusion tensor imaging (DTI) data and estimated tissue-specific white matter microstructure (FAT) and free water volume (FW). We then quantified their heritability and their genetic correlations with two peripherally circulating proinflammatory cytokines (IL-8 and TNFα), and compared these correlations to those obtained using traditional FA measures from one-compartment DTI models. All DTI and cytokine measures were significantly moderately heritable. We confirmed phenotypic and genetic correlations between circulating cytokine levels and single-compartment FA across the brain (IL-8: ρp = -0.16, FDRp = 4.8 × 10-07; ρg = -0.37 (0.12), FDRp = 0.01; TNFα: ρp = -0.15, FDRp = 2.4 × 10-07; ρg = -0.34 (0.12), p = 0.01). However, this relationship no longer reached significance when FA measures were derived using the two-compartment DTI model (IL-8: ρp = -0.04, FDRp = 0.17; ρg = -0.14 (0.13), FDRp = 0.29; TNFα: ρp = -0.05, FDRp = 0.10; ρg = -0.22 (0.13), FDRp = 0.10). There were significant phenotypic and genetic correlations between FW and both IL-8 (ρp = 0.19, FDRp = 2.1 × 10-10; ρg = 0.34 (0.11), FDRp = 0.01) and TNFα (ρp = 0.16, FDRp = 1.89 × 10-07; ρg = 0.30 (0.12), FDRp = 0.02). These results have important implications for understanding the mechanisms linking the two phenomena, but they also serve as a cautionary note for those examining associations between white matter integrity using single-compartment models and inflammatory processes.

Longitudinal Identification of Pre-Lesional Tissue in Multiple Sclerosis With Advanced Diffusion MRI

BACKGROUND AND PURPOSE

Structural MRI (sMRI) is used in monitoring multiple sclerosis (MS) but lacks sensitivity in detecting clinically relevant damage to normal-appearing white matter (NAWM), that is, pre-lesional tissue, and specificity for identifying the underlying substrate of injury. In this longitudinal study, we identified pre-lesional tissue in MS patients and investigated its microstructure by modeling diffusion-weighted imaging (DWI) data using diffusion tensor imaging and neurite orientation dispersion and density imaging (NODDI).

METHODS

We enrolled 18 patients with relapsing-remitting MS (10 females, 31.92 ± 8.09 years, disease duration 0.91 ± 1.81 years) and 18 healthy controls (10 females, 31.89 ± 8.15 years). Participants underwent two sMRI and DWI sessions (baseline and follow-up) with the same protocols. Average apparent diffusion coefficient (ADC), fractional anisotropy (FA), orientation dispersion index (ODI), and neurite density index (NDI) were estimated in data-driven regions of interest: nonpersistent lesional tissue (lesional tissue at baseline, resolved at follow-up), lesions that only existed at follow-up (pre-lesional tissue at baseline, lesions at follow-up), persistent lesional tissue (lesions at baseline and follow-up), and NAWM.

RESULTS

Compared to NAWM, pre-lesional tissue showed lower ODI, and resolved lesional tissue showed higher FA and ADC and lower ODI and NDI. Over time, persistent lesional tissue showed a decrease in FA and ODI and an increase in NDI. Compared to nonpersistent lesional tissue, persistent lesional tissue showed higher ADC and lower NDI.

CONCLUSIONS

DWI and, more particularly, NODDI, can reveal the unique microstructure of persistent, resolved, and pre-lesional tissue in MS.

White Matter Magnetic Resonance Diffusion Measures in Multiple Sclerosis with Overactive Bladder

BACKGROUND

Lower urinary tract (LUT) symptoms are reported in more than 80% of patients with multiple sclerosis (MS), most commonly an overactive bladder (OAB). The relationship between brain white matter (WM) changes in MS and OAB symptoms is poorly understood.

OBJECTIVES

We aim to evaluate (i) microstructural WM differences across MS patients (pwMS) with OAB symptoms, patients without LUT symptoms, and healthy subjects using diffusion tensor imaging (DTI), and (ii) associations between clinical OAB symptom scores and DTI indices.

METHODS

Twenty-nine female pwMS [mean age (SD) 43.3 years (9.4)], including seventeen with OAB [mean age (SD) 46.1 years (8.6)] and nine without LUT symptoms [mean age (SD) 37.5 years (8.9)], and fourteen healthy controls (HCs) [mean age (SD) 48.5 years (20)] were scanned in a 3T MRI with a DTI protocol. Additionally, clinical scans were performed for WM lesion segmentation. Group differences in fractional anisotropy (FA) were evaluated using tract-based spatial statistics. The Urinary Symptom Profile questionnaire assessed OAB severity.

RESULTS

A statistically significant reduction in FA (p = 0.004) was identified in microstructural WM in pwMS, compared with HCs. An inverse correlation was found between FA in frontal and parietal WM lobes and OAB scores (p = 0.021) in pwMS. Areas of lower FA, although this did not reach statistical significance, were found in both frontal lobes and the rest of the non-dominant hemisphere in pwMS with OAB compared with pwMS without LUT symptoms (p = 0.072).

CONCLUSIONS

This study identified that lesions affecting different WM tracts in MS can result in OAB symptoms and demonstrated the role of the WM in the neural control of LUT functions. By using DTI, the association between OAB symptom severity and WM changes were identified, adding knowledge to the current LUT working model. As MS is predominantly a WM disease, these findings suggest that regional WM involvement, including of the anterior corona radiata, anterior thalamic radiation, superior longitudinal fasciculus, and superior frontal-occipital fasciculus and a non-dominant prevalence in WM, can result in OAB symptoms. OAB symptoms in MS correlate with anisotropy changes in different white matter tracts as demonstrated by DTI. Structural impairment in WM tracts plays an important role in LUT symptoms in MS.

The Role of Advanced Magnetic Resonance Imaging Sequences in Multiple Sclerosis

Background The neurological condition known as multiple sclerosis (MS) is crippling and has a complicated pathogenesis as well as a wide range of clinical symptoms, including fatigue, difficulty walking, numbness or tingling, muscle spasms and spasticity, weakness, vision problems, dizziness and vertigo, bladder and bowel dysfunction, cognitive impairment, and emotional changes. The complete scope of MS pathology cannot be fully captured by conventional magnetic resonance imaging (MRI) sequences, which has led to the investigation of sophisticated MRI methods for better diagnosis and treatment. Objective This study aims to evaluate the clinical relevance of advanced MRI sequences in multiple sclerosis. Methodology A retrospective cohort study was conducted across multiple specialized medical centers renowned for treating neurological disorders, particularly multiple sclerosis, and involved 310 patients with diverse geography seeking treatment throughout 2022. Records were searched to obtain patient information, demographics, and treatment history. Descriptive statistics and t-tests were among the statistical studies that investigated relationships between MRI biomarkers and clinical factors to help with the diagnosis and treatment of MS. A p-value of <0.05 was significant. Results The research group consisted of 310 MS patients, the majority of whom were female (67.42%) and had a mean age of 34.7 years. With hypertension (14.52%) and hyperlipidemia (19.35%) as prevalent comorbidities, the majority of patients (72.26%) were on disease-modifying treatments. The results of advanced MRI showed that lesions with white matter had higher mean diffusivity (1.25 ± 0.15 mm²/s) on DWI, lesions with reduced magnetization transfer ratio (MTR) (0.15 ± 0.03) on MTI, and lesions with reduced fractional anisotropy (FA) (0.40 ± 0.08) on diffusion tensor imaging (DTI). Additionally, the blood oxygen level-dependent (BOLD) signals in cognitive processing regions (0.75 ± 0.10) on functional MRI were different from those with normal-appearing white matter (0.40 ± 0.08). Conclusion Advanced MRI sequences are essential for bettering MS diagnosis, prognosis, and treatment because they link imaging biomarkers to important clinical parameters, which improves patient care and quality of life.

An update on the role of magnetic resonance imaging in predicting and monitoring multiple sclerosis progression

INTRODUCTION

While magnetic resonance imaging (MRI) is established in diagnosing and monitoring disease activity in multiple sclerosis (MS), its utility in predicting and monitoring disease progression is less clear.

AREAS COVERED

The authors consider changing concepts in the phenotypic classification of MS, including progression independent of relapses; pathological processes underpinning progression; advances in MRI measures to assess them; how well MRI features explain and predict clinical outcomes, including models that assess disease effects on neural networks, and the potential role for machine learning.

EXPERT OPINION

Relapsing-remitting and progressive MS have evolved from being viewed as mutually exclusive to having considerable overlap. Progression is likely the consequence of several pathological elements, each important in building more holistic prognostic models beyond conventional phenotypes. MRI is well placed to assess pathogenic processes underpinning progression, but we need to bridge the gap between MRI measures and clinical outcomes. Mapping pathological effects on specific neural networks may help and machine learning methods may be able to optimize predictive markers while identifying new, or previously overlooked, clinically relevant features. The ever-increasing ability to measure features on MRI raises the dilemma of what to measure and when, and the challenge of translating research methods into clinically useable tools.