Normal-appearing White Matter Research Articles

Diffuse white matter pathology in multiple sclerosis during treatment with dimethyl fumarate-An observational study of changes in normal-appearing white matter using proton magnetic resonance spectroscopy.

Multiple sclerosis (MS) is an inflammatory demyelinating disease with neurodegenerative features causing risk for neurologic irreversible disability over time. Examination of normal-appearing white matter (NAWM) changes in MS by proton magnetic resonance spectroscopy (1H-MRS), may detect diffuse white matter pathology that is associated with neurodegeneration. In this observational study of in total twenty-six patients with MS, starting treatment with dimethyl fumarate (DMF), we measured the absolute concentration of metabolites in periventricular NAWM using 1H-MRS at baseline and after one and three years of treatment. Metabolite concentrations were analyzed both cross-sectionally, in relation to 10 controls and longitudinally in relation to disease activity. Patients with MS had higher concentrations of myo-inositol (mIns) in NAWM at baseline compared with controls (mean 5.98 ± 1.37 (SD) and 4.32 ± 1.16 (SD), p<0.01, independent samples t-test). The disease duration was inversely correlated with concentrations of total N-acetylaspartate and N-acetylaspartylglutamate (tNA) (r = -0.62, p<0.01) in NAWM as well as positively to the ratio of mIns and tNA (r = 0.51, p = 0.03). Metabolite concentrations during one-year (n = 19) and three-years (n = 11) follow-up were generally stable. The dropouts were caused by treatment switch after one year, mainly due to new MRI activity. Cross-sectional analyses showed that there was an inverse correlation between concentrations of tNA and mIns at both baseline and at 1 and 3-years follow-up (r = -0.44 to -0.65, p = 0.04 to 0.004). Metabolite concentrations were stable during 1-year follow-up independently of disease activity. Higher concentrations of the astrogliosis marker mIns in MS compared to controls, the inverse relation between MS disease duration and the neuroaxonal integrity marker tNA, as well as the consistent inverse relation between these two metabolites during follow-up, showed that non-lesional white matter pathology is present in this cohort of MS patients in early disease stages. However, metabolite concentrations during follow-up were generally stable and did not reflect differences in disease activity among patients.

Volume and Permeability of White Matter Hyperintensity on Cognition: A DCE Imaging Study of an Older Cohort With and Without Cognitive Impairment.

The impact of blood-brain barrier (BBB) leakage on white matter hyperintensity (WMH) subtypes (location) and its association with clinical factors and cognition remains unclear. To investigate the relationship between WMH volume, permeability, clinical factors, and cognition in older individuals across the cognitive spectrum. Prospective, cross-sectional. A total of 193 older adults with/without cognitive impairment; 128 females; mean age 70.1 years (standard deviation 6.8). 3 T, GE Dynamic contrast-enhanced, three-dimensional (3D) Magnetization-prepared rapid gradient-echo (MPRAGE T1WI), 3D fluid-attenuated inversion recovery (FLAIR). Periventricular WMH (PWMH), deep WMH (DWMH), and normal-appearing white matter (NAWM) were segmented using FMRIB automatic segmentation tool algorithms on 3D FLAIR. Hippocampal volume and cortex volume were segmented on 3D T1WI. BBB permeability (Ktrans) and blood plasma volume (Vp) were determined using the Patlak model. Vascular risk factors and cognition were assessed. Univariate and multivariate analyses were performed to identify factors associated with WMH permeability. Logistic regression analysis assessed the association between WMH imaging features and cognition, adjusting for age, sex, apolipoprotein E4 status, education, and brain volumes. A P-value <0.05 was considered significant. PWMH exhibited higher Ktrans (0.598 ± 0.509 × 10-3 minute-1) compared to DWMH (0.496 ± 0.478 × 10-3 minute-1) and NAWM (0.476 ± 0.398 × 10-3 minute-1). Smaller PWMH volume and cardiovascular disease (CVD) history were significantly associated with higher Ktrans in PWMH. In DWMH, higher Ktrans were associated with CVD history and cortical volume. In NAWM, it was linked to CVD history and dyslipidemia. Larger PWMH volume (odds ratio [OR] 1.106, confidence interval [CI]: 1.021-1.197) and smaller hippocampal volume (OR 0.069; CI: 0.019-0.253) were independently linked to worse global cognition after covariate adjustment. Elevated BBB leakage in PWMH was associated with lower PWMH volume and prior CVD history. Notably, PWMH volume, rather than permeability, was correlated with cognitive decline, suggesting that BBB leakage in WMH may be a consequence of CVD rather than indicate disease progression. 2 TECHNICAL EFFICACY: Stage 3.

Multi-Site Benchmark Study for Standardized Relative Cerebral Blood Volume in Untreated Brain Metastases Using the DSC-MRI Consensus Acquisition Protocol.

A national consensus recommendation for the collection of DSC (dynamic susceptibility contrast) MRI perfusion data, used to create maps of relative cerebral blood volume (rCBV), has been recently established for primary and metastatic brain tumors. The goal was to reduce inter-site variability and improve ease of comparison across time and sites, fostering widespread use of this informative measure. To translate this goal into practice the prospective collection of consensus DSC-MRI data and characterization of derived rCBV maps in brain metastases is needed. The purpose of this multi-site study was to determine rCBV in untreated brain metastases in comparison to glioblastoma and normal appearing brain using the national consensus protocol. Subjects from three sites with untreated enhancing brain metastases underwent DSC-MRI according to a recommended option that uses a mid-range flip angle, GRE-EPI acquisition and the administration of both a pre-load and 2nd DSC-MRI dose of 0.1 mmol/kg GBCA. Quantitative maps of standardized rCBV (sRCBV) were generated and enhancing lesion ROIs determined from post-contrast T1-weighted images alone or calibrated difference maps, termed delta T1 (dT1) maps. Mean sRCBV for metastases were compared to normal appearing white matter (NAWM) and glioblastoma (GBM) from a previous study. Comparisons were performed using either the Wilcoxon signed-rank test for paired comparisons or the Mann-Whitney nonparametric test for unpaired comparisons. 49 patients with a primary histology of lung (n=25), breast (n=6), squamous cell carcinoma (SCC) (n=1), melanoma (n=5), gastrointestinal (GI) (n=3) and genitourinary (GU) (n=9) were included in comparison to GBM (n=31). The mean sRCBV of all metastases (1.83+/-1.05) were significantly lower (p=0.0009) than mean sRCBV for GBM (2.67±1.34) with both statistically greater (p<0.0001) than NAWM (0.68 +/- 0.18). Histologically distinct metastases are each statistically greater than NAWM (p<0.0001) with lung (p=0.0002) and GU (p=.02) sRCBV being significantly different than GBM sRCBV. 49 patients with a primary histology of lung (n=25), breast (n=6), squamous cell carcinoma (SCC) (n=1), melanoma (n=5), gastrointestinal (GI) (n=3) and genitourinary (GU) (n=9) were included in comparison to GBM (n=31). The mean sRCBV of all metastases (1.83+/-1.05) were significantly lower (p=0.0009) than mean sRCBV for GBM (2.67+1.34) with both statistically greater (p<0.0001) than NAWM (0.68 +/- 0.18). Histologically distinct metastases are each statistically greater than NAWM (p<0.0001) with lung (p=0.0002) and GU (p=.02) sRCBV being significantly different than GBM sRCBV. dT1=delta T1; GBCA=gadolinium-based contrast agent; NAWM=normal appearing white matter; normalized relative cerebral blood volume=nRCBV; relative cerebral blood volume=rCBV; standardized relative cerebral blood volume=sRCBV.

Quantitative myelin water assessment for multiple sclerosis using multi-inversion magnetic resonance fingerprinting.

Multiple sclerosis (MS) is a demyelination disease. Myelin water is a biomarker of myelin and thus myelin water imaging is a vital tool to provide insight into the demyelination process. This study aimed to characterize the multiple compartments including myelin water fraction (MWF), gray matter (GM) cellular water, white matter (WM) cellular water, and cerebrospinal fluid (CSF) using multiple inversion recovery (mIR) magnetic resonance fingerprinting (MRF) on a clinical MS cohort. The Phantom experiment was conducted with tubes containing different WM and GM concentrations extracted from pig brains. For the in-vivo experiment, 23 healthy control (HC) volunteers and 18 MS patients were recruited for this study. The experiments were performed using a clinical 3T MRI. A multi-slice, fast imaging with a steady-state precession (FISP) based mIR MRF protocol was used to obtain the MWF measurements, with 6min of scan time for each volunteer. The quantification was based on the iterative non-negative least squares (NNLS) with reweighting. The brain compartments quantified were myelin water, WM cellular water, GM cellular water, and CSF. A radiologist with 6 years of experience labeled the MS lesions on FLAIR, MPRAGE, and MWF. Statistical analysis was performed by applying unpaired and paired student's t-tests to compare the MWF results in different groups and in normal-appearing white matter (NAWM) and MS lesions. The phantom result demonstrated the ability to detect MWF with various myelin concentrations. The maps derived from mIR MRF, including MWF, WM cellular water, GM cellular water, and CSF were consistent with the anatomical structures observed in FLAIR and MPRAGE. The MWF values in the NAWM of MS patients were significantly different from those in HC, with values of 0.32±0.025 and 0.25±0.036, respectively. Additionally, the MWF values in WM lesions were significantly smaller than in NAWM at 0.034±0.036. The mIR-MRF technique, using multi-compartment analysis, can simultaneously generate maps of MWF, WM cellular water, GM cellular water, and CSF with sufficient brain coverage and in a reasonably short scan time. The MWF map might provide insights into the demyelination associated with MS.

Quantifying Remyelination Using χ-Separation in White Matter and Cortical Multiple Sclerosis Lesions.

Myelin and iron play essential roles in remyelination processes of multiple sclerosis (MS) lesions. χ-separation, a novel biophysical model applied to multiecho T2*-data and T2-data, estimates the contribution of myelin and iron to the obtained susceptibility signal. We used this method to investigate myelin and iron levels in lesion and nonlesion brain areas in patients with MS and healthy individuals. This prospective MS cohort study included patients with MS fulfilling the McDonald Criteria 2017 and healthy individuals, aged 18 years or older, with no other neurologic comorbidities. Participants underwent MRI at baseline and after 2 years, including multiecho GRE-(T2*) and FAST-(T2) sequences. Using χ-separation, we generated myelin-sensitive and iron-sensitive susceptibility maps. White matter lesions (WMLs), cortical lesions (CLs), surrounding normal-appearing white matter (NAWM), and normal-appearing gray matter were segmented on fluid-attenuated inversion recovery and magnetization-prepared 2 rapid gradient echo images, respectively. Cross-sectional group comparisons used Wilcoxon rank-sum tests, longitudinal analyses applied Wilcoxon signed-rank tests. Associations with clinical outcomes (disease phenotype, age, sex, disease duration, disability measured by Expanded Disability Status Scale [EDSS], neurofilament light chain levels, and T2-lesion number and volume) were assessed using linear regression models. Of 168 patients with MS (median [interquartile range (IQR)] age 47.0 [21.7] years; 101 women; 6,898 WMLs, 775 CLs) and 103 healthy individuals (age 33.0 [10.5] years, 57 women), 108 and 62 were followed for a median of 2 years, respectively (IQR 0.1; 5,030 WMLs, 485 CLs). At baseline, WMLs had lower myelin (median 0.025 [IQR 0.015] parts per million [ppm]) and iron (0.017 [0.015] ppm) than the corresponding NAWM (myelin 0.030 [0.012]; iron 0.019 [0.011] ppm; both p < 0.001). After 2 years, both myelin (0.027 [0.014] ppm) and iron had increased (0.018 [0.015] ppm; both p < 0.001). Younger age (p < 0.001, b = -5.111 × 10-5), lower disability (p = 0.04, b = -2.352 × 10-5), and relapsing-remitting phenotype (RRMS, 0.003 [0.01] vs primary progressive 0.002 [IQR 0.01], p < 0.001; vs secondary progressive 0.0004 [IQR 0.01], p < 0.001) at baseline were associated with remyelination. Increment of myelin correlated with clinical improvement measured by EDSS (p = 0.015, b = -6.686 × 10-4). χ-separation, a novel mathematical model applied to multiecho T2*-images and T2-images shows that young RRMS patients with low disability exhibit higher remyelination capacity, which correlated with clinical disability over a 2-year follow-up.

CNS Embryonal Tumor with PLAGL Amplification, a New Tumor Type in Children and Adolescents: Insights from a Comprehensive MRI Analysis.

CNS embryonal tumor with PLAGL1/PLAGL2 amplification (ET, PLAGL) is a newly identified, highly malignant pediatric tumor. Systematic MRI descriptions of ET, PLAGL are currently lacking. MRI data from 19 treatment-naïve patients with confirmed ET, PLAGL were analyzed. Evaluation focused on anatomical involvement, tumor localization, MRI signal characteristics, DWI behavior, and the presence of necrosis and hemorrhage. Descriptive statistics (median, interquartile range, percentage) were assessed. Ten patients had PLAGL1 and nine PLAGL2 amplifications. The solid components of the tumors were often multinodular with heterogeneous enhancement (mild to intermediate in 47% and intermediate to strong in 47% of cases). Non-solid components included cysts in 47% and necrosis in 84% of the cases. The tumors showed heterogeneous T2WI hyper-and isointensity (74%), relatively little diffusion restriction (ADC values < contralateral normal-appearing WM in 36% of cases with available DWI), and tendencies towards hemorrhage/calcification (42%). No reliable distinction was found between PLAGL1-and PLAGL2-amplified tumors or compared to other embryonal CNS tumors. The study contributes to understanding the imaging characteristics of ET, PLAGL. It underscores the need for collaboration in studying rare pediatric tumors and advocates for the use of harmonized imaging protocols for better characterization. ATRT= atypical teratoid/rhabdoid tumor; ETMR= embryonal tumor with multilayered rosettes; ET, PLAGL= CNS embryonal tumor with PLAGL amplification; EVD= external ventricular drain; IQR: interquartile range; PLAGL1= pleomorphic adenoma gene-like 1; PLAGL2= pleomorphic adenoma gene-like 2; WHO= World Health Organization.

Predicting white-matter hyperintensity progression and cognitive decline in patients with cerebral small-vessel disease: a magnetic resonance-based habitat analysis.

White-matter hyperintensity (WMH) is the key magnetic resonance imaging (MRI) marker of cerebral small-vessel disease (CSVD). This study aimed to investigate whether habitat analysis based on physiologic MRI parameters can predict the progression of WMH and cognitive decline in CSVD. Diffusion- and perfusion-weighted imaging data were obtained from 69 patients with CSVD at baseline and at 1-year of follow-up. The white-matter region was classified into constant WMH, growing WMH, shrinking WMH, and normal-appearing white matter (NAWM) according to the T2-fluid-attenuated inversion recovery (FLAIR) sequences images at the baseline and follow-up. We employed k-means clustering on a voxel-wise basis to delineate WMH habitats, integrating multiple diffusion metrics and cerebral blood flow (CBF) values derived from perfusion data. The WMH at the baseline and the predicted WMH from the habitat analysis were used as regions of avoidance (ROAs). The decreased rate of global efficiency for the whole brain structural connectivity was calculated after removal of the ROA. The association between the decreased rate of global efficiency and Montreal Cognitive Assessment (MoCA) and mini-mental state examination (MMSE) scores was evaluated using Pearson correlation coefficients. We found that the physiologic MRI habitats with lower fractional anisotropy and CBF values and higher mean diffusivity, axial diffusivity, and radial diffusivity values overlapped considerably with the new WMH (growing WMH of baseline) after a 1-year follow-up; the accuracy of distinguishing growing WMH from NAWM was 88.9%±12.7% at baseline. Similar results were also found for the prediction of shrinking WMH. Moreover, after the removal of the predicted WMH, a decreased rate of global efficiency had a significantly negative correlation with the MoCA and MMSE scores at follow-up. This study revealed that a habitat analysis combining perfusion with diffusion parameters could predict the progression of WMH and related cognitive decline in patients with CSVD.

Accurate low and high grade glioma classification using free water eliminated diffusion tensor metrics and ensemble machine learning

Glioma, a predominant type of brain tumor, can be fatal. This necessitates an early diagnosis and effective treatment strategies. Current diagnosis is based on biopsy, prompting the need for non invasive neuroimaging alternatives. Diffusion tensor imaging (DTI) is a promising method for studying the pathophysiological impact of tumors on white matter (WM) tissue. Single-shell DTI studies in brain glioma patients have not accounted for free water (FW) contamination due to tumors. This study aimed to (a) assess the efficacy of a two-compartment DTI model that accounts for FW contamination and (b) identify DTI-based biomarkers to classify low-grade glioma (LGG) and high-grade glioma (HGG) patients. DTI data from 86 patients (LGG n = 39, HGG n = 47) were obtained using a routine clinical imaging protocol. DTI metrics of tumorous regions and normal-appearing white matter (NAWM) were evaluated. Advanced stacked-based ensemble learning was employed to classify LGG and HGG patients using both single- and two-compartment DTI model measures. The DTI metrics of the two-compartment model outperformed those of the standard single-compartment DTI model in terms of sensitivity, specificity, and area under the curve of receiver operating characteristic (AUC-ROC) score in classifying LGG and HGG patients. Four features (out of 16 features), namely fractional anisotropy (FA) of the edema and core region and FA and mean diffusivity of the NAWM region, showed superior performance (sensitivity = 92%, specificity = 90%, and AUC-ROC = 90%) in classifying LGG and HGG. This demonstrates that both tumorous and NAWM regions may be differentially affected in LGG and HGG patients. Our results demonstrate the significance of using a two-compartment DTI model that accounts for FW contamination by improving diagnostic accuracy. This improvement may eventually aid in planning treatment strategies for glioma patients.

Deep learning-based segmentation in MRI-(immuno)histological examination of myelin and axonal damage in normal-appearing white matter and white matter hyperintensities.

The major vascular cause of dementia is cerebral small vessel disease (SVD). Its diagnosis relies on imaging hallmarks, such as white matter hyperintensities (WMH). WMH present a heterogenous pathology, including myelin and axonal loss. Yet, these might be only the "tip of the iceberg." Imaging modalities imply that microstructural alterations underlie still normal-appearing white matter (NAWM), preceding the conversion to WMH. Unfortunately, direct pathological characterization of these microstructural alterations affecting myelinated axonal fibers in WMH, and especially NAWM, is still missing. Given that there are no treatments to significantly reduce WMH progression, it is important to extend our knowledge on pathological processes that might already be occurring within NAWM. Staining of myelin with Luxol Fast Blue, while valuable, fails to assess subtle alterations in white matter microstructure. Therefore, we aimed to quantify myelin surrounding axonal fibers and axonal- and microstructural damage in detail by combining (immuno)histochemistry with polarized light imaging (PLI). To study the extent (of early) microstructural damage from periventricular NAWM to the center of WMH, we refined current analysis techniques by using deep learning to define smaller segments of white matter, capturing increasing fluid-attenuated inversion recovery signal. Integration of (immuno)histochemistry and PLI with post-mortem imaging of the brains of individuals with hypertension and normotensive controls enables voxel-wise assessment of the pathology throughout periventricular WMH and NAWM. Myelin loss, axonal integrity, and white matter microstructural damage are not limited to WMH but already occur within NAWM. Notably, we found that axonal damage is higher in individuals with hypertension, particularly in NAWM. These findings highlight the added value of advanced segmentation techniques to visualize subtle changes occurring already in NAWM preceding WMH. By using quantitative MRI and advanced diffusion MRI, future studies may elucidate these very early mechanisms leading to neurodegeneration, which ultimately contribute to the conversion of NAWM to WMH.

Serum glial fibrillary acidic protein as a marker of brain MRI metrics in multiple sclerosis: A scoping review.

Magnetic resonance imaging (MRI) is heavily relied upon for the diagnosis and monitoring of multiple sclerosis (MS), a chronic, demyelinating disease of the central nervous system. Serum biomarkers may serve as an accessible tool for increasing sensitivity, improving accessibility, corroborating symptoms, and providing additional data to guide clinical management. This scoping review investigates the current understanding of how the serum biomarker glial fibrillary acidic protein (sGFAP) relates to brain MRI metrics. We adhered to the Joanna Briggs Institute methodology for scoping reviews and the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines. The databases Medline (Ovid), Embase (Ovid), CINAHL (Ebsco), and Web of Science (University of British Columbia institutional access) were searched on August 24, 2023 using a combination of medical subject headings and keyword terms for the topic of serum biomarkers in MS. A total of 9880 articles were retrieved in total of which 6271 unique titles and abstracts were screened. Twelve of the 259 resultant papers contained sGFAP data and proceeded to extraction. It was found that lesion MRI metrics generally had a positive relationship with sGFAP, while gray matter and white matter metrics, including normal-appearing white matter, were related negatively or not at all. These results highlight that while sGFAP may not be specific for MS, it may have utility for increasing sensitivity in postdiagnosis monitoring of MS progression.

Assessment the Impact of IDH Mutation Status on MRI Assessments of White Matter Integrity in Glioma Patients: Insights From Peak Width of Skeletonized Mean Diffusivity and Free Water Metrics.

Gliomas are highly invasive brain tumors that evade accurate geographic assessment by conventional MRI due to microscopic invasion along white matter (WM) tracts. Advanced diffusion MRI techniques are needed to assess occult WM involvement. To evaluate peak width of skeletonized mean diffusivity (PSMD) and peak width of skeletonized free water (PSFW), and axonal water fraction (AWF) for assessing glioma-induced alterations in normal-appearing WM and their relationship with isocitrate dehydrogenase 1 (IDH1) mutation. Retrospective. One hundred five glioma patients (46 ± 13 years), 53 healthy controls (HCs) (46 ± 9 years). 3.0 T, T1WI, T1-CE, T2WI, T2FLAIR, and DKI. PSMD and PSFW were compared between lesion and contralateral sides in glioma patients and between patients and HCs. The associations between these metrics and clinical variables, including IDH1 mutation, was assessed. Corpus callosum (CC) injury, quantified by the AWF, was evaluated for its mediated effect of IDH1 mutation on contralesional PSMD and PSFW. Paired-t tests, ANCOVA, univariate and multivariate linear regression, and mediation analysis with significance set at P < 0.05. Contralateral PSMD and PSFW were significantly higher in left-sided gliomas (PSMD: 0.206 ± 0.027 vs. 0.193 ± 0.023; PSFW: 0.119 ± 0.019 vs. 0.106 ± 0.020) than in HCs, with similar increases in right-sided gliomas (PSMD: 0.219 ± 0.036 vs. 0.195 ± 0.023; PSFW: 0.129 ± 0.031 vs. 0.109 ± 0.020). IDH1 wild-type gliomas were associated with higher contralateral PSMD and PSFW (β = -0.302 and -0.412). AWF of CC mediated the impact of IDH1 mutations on contralesional PSMD and PSFW (mediated proportion: 42.7% and 53.7%). PSMD and PSFW are effective biomarkers for assessing WM integrity in gliomas, significantly associated with IDH1 mutation status. AWF of CC mediates the relationship between IDH1 mutation and contralesional PSMD and PSFW. 4 TECHNICAL EFFICACY: Stage 2.

Multicompartment imaging of the brain using a comprehensive MR imaging protocol

In this study, we describe a comprehensive 3D magnetic resonance imaging (MRI) protocol designed to assess major tissue and fluid components in the brain. The protocol comprises four different sequences: 1) magnetization transfer prepared Cones (MT-Cones) for two-pool MT modeling to quantify macromolecular content; 2) short-TR adiabatic inversion-recovery prepared Cones (STAIR-Cones) for myelin water imaging; 3) proton-density weighted Cones (PDw-Cones) for total water imaging; and 4) highly T2 weighted Cones (T2w-Cones) for free water imaging. By integrating these techniques, we successfully mapped key brain components—namely macromolecules, myelin water, intra/extracellular water, and free water—in ten healthy volunteers and five patients with multiple sclerosis (MS) using a 3T clinical scanner. Brain macromolecular proton fraction (MMPF), myelin water proton fraction (MWPF), intra/extracellular water proton fraction (IEWPF), and free water proton fraction (FWPF) values were generated in white matter (WM), grey matter (GM), and MS lesions. Excellent repeatability of the protocol was demonstrated with high intra-class correlation coefficient (ICC) values. In MS patients, the MMPF and MWPF values of the lesions and normal-appearing WM (NAWM) were significantly lower than those in normal WM (NWM) in healthy volunteers. Moreover, we observed significantly higher FWPF values in MS lesions compared to those in NWM and NAWM regions. This study demonstrates the capability of our technique to volumetrically map major brain components. The technique may have particular value in providing a comprehensive assessment of neuroinflammatory and neurodegenerative diseases of the brain.

Differential Expression of PACAP/VIP Receptors in the Post-Mortem CNS White Matter of Multiple Sclerosis Donors.

Pituitary adenylate cyclase-activating polypeptide (PACAP) and vasoactive intestinal peptide (VIP) are two neuroprotective and anti-inflammatory molecules of the central nervous system (CNS). Both bind to three G protein-coupled receptors, namely PAC1, VPAC1 and VPAC2, to elicit their beneficial effects in various CNS diseases, including multiple sclerosis (MS). In this study, we assessed the expression and distribution of PACAP/VIP receptors in the normal-appearing white matter (NAWM) of MS donors with a clinical history of either relapsing-remitting MS (RRMS), primary MS (PPMS), secondary progressive MS (SPMS) or in aged-matched non-MS controls. Gene expression studies revealed MS-subtype specific changes in PACAP and VIP and in the receptors' levels in the NAWM, which were partly corroborated by immunohistochemical analyses. Most PAC1 immunoreactivity was restricted to myelin-producing cells, whereas VPAC1 reactivity was diffused within the neuropil and in axonal bundles, and VPAC2 in small vessel walls. Within and around lesioned areas, glial cells were the predominant populations showing reactivity for the different PACAP/VIP receptors, with distinctive patterns across MS subtypes. Together, these data identify the differential expression patterns of PACAP/VIP receptors among the different MS clinical entities. These results may offer opportunities for the development of personalized therapeutic approaches to treating MS and/or other demyelinating disorders.

Exploring cognitive related microstructural alterations in normal appearing white matter and deep grey matter for small vessel disease: A quantitative susceptibility mapping study

Brain microstructural alterations possibly occur in the normal-appearing white matter (NAWM) and grey matter of small vessel disease (SVD) patients, and may contribute to cognitive impairment. The aim of this study was to explore cognitive related microstructural alterations in white matter and deep grey matter nuclei in SVD patients using magnetic resonance (MR) quantitative susceptibility mapping (QSM). 170 SVD patients, including 103 vascular mild cognitive impairment (VaMCI) and 67 no cognitive impairment (NCI), and 21 healthy control (HC) subjects were included, all underwent a whole-brain QSM scanning. Using a white matter and a deep grey matter atlas, subregion-based QSM analysis was conducted to identify and characterize microstructural alterations occurring within white matter and subcortical nuclei. Significantly different susceptibility values were revealed in NAWM and in several specific white matter tracts including anterior limb of internal capsule, corticospinal tract, medial lemniscus, middle frontal blade, superior corona radiata and tapetum among VaMCI, NCI and HC groups. However, no difference was found in white matter hyperintensities between VaMCI and NCI. A trend toward higher susceptibility in the caudate nucleus and globus pallidus of VaMCI patients compared to HC, indicating elevated iron deposition in these areas. Interestingly, some of these QSM parameters were closely correlated with both global and specific cognitive function scores, controlling age, gender and education level. Our study suggested that QSM may serve as a useful imaging tool for monitoring cognitive related microstructural alterations in brain. This is especially meaningful for white matter which previously lacks of attention.

Cortical CD200-CD200R and CD47-SIRPα expression is associated with multiple sclerosis pathology.

Control of microglia activity through CD200-CD200R and CD47-SIRPα interactions has been implicated in brain homeostasis. Here, we assessed CD200, CD47, CD200R and SIRPα expression with qPCR and immunohistochemistry in multiple sclerosis (MS) normal-appearing cortical grey matter (NAGM), normal-appearing white matter (NAWM), cortical grey matter (GM) lesions and perilesional GM, and compared this to control GM and white matter (WM), to investigate possible altered control of microglia in MS. In MS NAGM, CD200 expression is lower compared with control GM, specifically in cortical layers 1 and 2, and CD200 expression in NAGM negatively correlates with the cortical lesion rate. Interestingly, NAGM and NAWM CD200 expression is positively correlated, and NAGM CD200 expression negatively correlates with the proportion of active and mixed WM lesions. In GM lesions, CD200 and CD47 expressions are lower compared with NAGM and perilesional GM. CD200R expression is lower in MS NAGM, whereas SIRPα was increased in and around GM lesions. Taken together, our data indicate that CD200 and CD47 play a role in GM MS lesion formation and progression, respectively, and that targeting CD200 pathways may offer therapeutic avenues to mitigate MS pathology in both WM and GM.

Spin-lock based fast whole-brain 3D macromolecular proton fraction mapping of relapsing–remitting multiple sclerosis

A sensitive and efficient imaging technique is required to assess the subtle abnormalities occurring in the normal-appearing white matter (NAWM) and normal-appearing grey matter (NAGM) in patients with relapsing–remitting multiple sclerosis (RRMS). In this study, a fast 3D macromolecular proton fraction (MPF) quantification based on spin-lock (fast MPF-SL) sequence was proposed for brain MPF mapping. Thirty-four participants, including 17 healthy controls and 17 RRMS patients were prospectively recruited. We conducted group comparison and correlation between conventional MPF-SL, fast MPF-SL, and DWI, and compared differences in quantified parameters within MS lesions and the regional NAWM, NAGM, and normal-appearing deep grey matter (NADGN). MPF of MS lesions was significantly reduced (7.17% ± 1.15%, P\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$P$$\\end{document} < 0.01) compared to all corresponding normal-appearing regions. MS patients also showed significantly reduced mean MPF values compared with controls in NAGM (4.87% ± 0.38% vs 5.21% ± 0.32%, P\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$P$$\\end{document} = 0.01), NAWM (9.49% ± 0.69% vs 10.32% ± 0.59%, P\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$P$$\\end{document} < 0.01) and NADGM (thalamus 5.59% ± 0.67% vs 6.00% ± 0.41%, P\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$P$$\\end{document} = 0.04; caudate 5.10% ± 0.55% vs 5.53% ± 0.58%, P\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$P$$\\end{document} = 0.03). MPF and ADC showed abnormalities in otherwise normal appearing close to lesion areas (P < 0.01). In conclusion, time-efficient MPF mapping of the whole brain can be acquired efficiently (< 3 min) using fast MPF-SL. It offers a promising alternative way to detect white matter abnormalities in MS.

Improved myelin water imaging using B1+ correction and data-driven global feature extraction: Application on people with MS

Abstract The predominant technique for quantifying myelin content in the white matter is multicompartment analysis of MRI’s T2 relaxation times (mcT2 analysis). The process of resolving the T2 spectrum at each voxel, however, is highly ill-posed and remarkably susceptible to noise and to inhomogeneities of the transmit field (B1+). To address these challenges, we employ a preprocessing stage wherein a spatially global data-driven analysis of the tissue is performed to identify a set of mcT2 configurations (motifs) that best describe the tissue under investigation, followed by using this basis set to analyze the signal in each voxel. This procedure is complemented by a new algorithm for correcting B1+ inhomogeneities, lending the overall fitting process with improved robustness and reproducibility. Successful validations are presented using numerical and physical phantoms vs. ground truth, showcasing superior fitting accuracy and precision compared with conventional (non-data-driven) fitting. In vivo application of the technique is presented on 26 healthy subjects and 29 people living with multiple sclerosis (MS), revealing substantial reduction in myelin content within normal-appearing white matter regions of people with MS (i.e., outside obvious lesions), and confirming the potential of data-driven myelin values as a radiological biomarker for MS.

Diffusion decrease in normal-appearing white matter structures following photon or proton irradiation indicates differences in regional radiosensitivity

PurposeRadio(chemo)therapy (RCT) as part of the standard treatment of glioma patients, inevitably leads to radiation exposure of the tumor-surrounding normal-appearing (NA) tissues. The effect of radiotherapy on the brain microstructure can be assessed by magnetic resonance imaging (MRI) using diffusion tensor imaging (DTI). The aim of this study was to analyze regional DTI changes of white matter (WM) structures and to determine their dose- and time-dependency. MethodsAs part of a longitudinal prospective clinical study (NCT02824731), MRI data of 23 glioma patients treated with proton or photon beam therapy were acquired at three-monthly intervals until 36 months following irradiation. Mean, radial and axial diffusivity (MD, RD, AD) as well as fractional anisotropy (FA) were investigated in the NA tissue of 15 WM structures and their dependence on radiation dose, follow-up time and distance to the clinical target volume (CTV) was analyzed in a multivariate linear regression model. Due to the small and non-comparable patient numbers for proton and photon beam irradiation, a separate assessment of the findings per treatment modality was not performed. ResultsFour WM structures (i.e., internal capsule, corona radiata, posterior thalamic radiation, and superior longitudinal fasciculus) showed statistically significantly decreased RD and MD after RT, whereas AD decrease and FA increase occurred less frequently. The posterior thalamic radiation showed the most pronounced changes after RCT [i.e., ΔRD = −8.51 % (p = 0.012), ΔMD = −6.14 % (p = 0.012)]. The DTI changes depended significantly on mean dose and time. ConclusionSignificant changes in DTI for WM substructures were found even at low radiation doses. These findings may prompt new radiation dose constraints sparing the vulnerable structures from damage and subsequent side-effects.

Glioma Type Prediction with Dynamic Contrast-Enhanced MR Imaging and Diffusion Kurtosis Imaging-A Standardized Multicenter Study.

The aim was to explore the performance of dynamic contrast-enhanced (DCE) MRI and diffusion kurtosis imaging (DKI) in differentiating the molecular subtypes of adult-type gliomas. A multicenter MRI study with standardized imaging protocols, including DCE-MRI and DKI data of 81 patients with WHO grade 2-4 gliomas, was performed at six centers. The DCE-MRI and DKI parameter values were quantitatively evaluated in ROIs in tumor tissue and contralateral normal-appearing white matter. Binary logistic regression analyses were performed to differentiate between high-grade (HGG) vs. low-grade gliomas (LGG), IDH1/2 wildtype vs. mutated gliomas, and high-grade astrocytic tumors vs. high-grade oligodendrogliomas. Receiver operating characteristic (ROC) curves were generated for each parameter and for the regression models to determine the area under the curve (AUC), sensitivity, and specificity. Significant differences between tumor groups were found in the DCE-MRI and DKI parameters. A combination of DCE-MRI and DKI parameters revealed the best prediction of HGG vs. LGG (AUC = 0.954 (0.900-1.000)), IDH1/2 wildtype vs. mutated gliomas (AUC = 0.802 (0.702-0.903)), and astrocytomas/glioblastomas vs. oligodendrogliomas (AUC = 0.806 (0.700-0.912)) with the lowest Akaike information criterion. The combination of DCE-MRI and DKI seems helpful in predicting glioma types according to the 2021 World Health Organization's (WHO) classification.

Changes of brain parenchyma free water fraction reflect tissue damage and impaired processing speed in multiple sclerosis.

Free water fraction (FWF) represents the amount of water per unit volume of brain parenchyma, which is not bound to macromolecules. Its excess in multiple sclerosis (MS) is related to increased tissue loss. The use of mcDESPOT (multicomponent driven single pulse observation of T1 and T2), a 3D imaging method which exploits both the T1 and T2 contrasts, allows FWF to be derived in clinically feasible times. However, this method has not been used to quantify changes of FWF and their potential clinical impact in MS. The aim of this study is to investigate the changes in FWF in MS patients and their relationship with tissue damage and cognition, under the hypothesis that FWF is a proxy of clinically meaningful tissue loss. To this aim, we tested the relationship between FWF, MS lesion burden and information processing speed, evaluated via the Symbol Digit Modalities Test (SDMT). In addition to standard sequences, used for T1- and T2-weighted lesion delineation, the mcDESPOT sequence with 1.7 mm isotropic resolution and a diffusion weighted imaging protocol (b = 0, 1200 s/mm2, 40 diffusion directions) were employed at 3 T. The fractional anisotropy map derived from diffusion data was used to define a subject-specific white matter (WM) atlas. Brain parenchyma segmentation returned masks of gray matter (GM) and WM, and normal-appearing WM (NAWM), in addition to the T1 and T2 lesion masks (T1L and T2L, respectively). Ninety-nine relapsing-remitting MS patients (age = 43.3 ± 9.9 years, disease duration 12.3 ± 7.7 years) were studied, together with twenty-five healthy controls (HC, age = 38.8 ± 11.0 years). FWF was higher in GM and NAWM of MS patients, compared to GM and WM of HC (both p < .001). In MS patients, FWF was the highest in the T1L and GM, followed by T2L and NAWM, respectively. FWF increased significantly with T1L and T2L volume (ρ ranging from 0.40 to 0.58, p < .001). FWF in T2L was strongly related to both T1L volume and the volume ratio T1L/T2L (ρ = 0.73, p < .001). MS patients performed worse than HC in the processing speed test (mean ± SD: 54.1 ± 10.3 for MS, 63.8 ± 10.8 for HC). FWF in GM, T2L, perilesional tissue and NAWM increased with SDMT score reduction (ρ = -0.30, -0.29, -0.33 respectively and r = -.30 for T2L, all with p < .005). A regional analysis, conducted to determine which NAWM regions were of particular importance to explain the relationship between FWF and cognitive impairment, revealed that FWF spatial variance was negatively related to SDMT score in the corpus callosum and the superior longitudinal fasciculus, WM structures known to be associated with cognitive impairment, in addition to the left corticospinal tract, the sagittal stratum, the right anterior limb of internal capsule. In conclusion, we found excess free water in brain parenchyma of MS patients, an alteration that involved not only MS lesions, but also the GM and NAWM, impinging on brain function and negatively associated with cognitive processing speed. We suggest that the FWF metric, derived from noninvasive, rapid MRI acquisitions and bearing good biological interpretability, may prove valuable as an MRI biomarker of tissue damage and associated cognitive impairment in MS.