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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.

BACKGROUND AND PURPOSE: Biomechanical changes in the brain have not been fully elucidated in Alzheimer’s disease (AD). We aimed to investigate the effect of β-amyloid accumulation on mouse brain viscoelasticity. METHODS: Magnetic Resonance Elastography was used to calculate magnitude of the viscoelastic modulus (|G*|), elasticity (G(d)), and viscosity (G(l)) in the whole brain parenchyma (WB) and bilateral hippocampi of 9 transgenic J20 (AD) mice (5 males/4 females) and 10 wild-type (WT) C57BL/6 mice (5 males/5 females) at 11 and 14 months of age. RESULTS: Cross-sectional analyses showed no significant difference between AD and WT mice at either time-points. No sex-specific differences were observed at 11 months of age, but AD females showed significantly higher hippocampal |G*| and G(l) and WB |G*|, G(d) and G(l) compared to both AD and WT males at 14 months of age. Similar trending differences were found between female AD and female WT animals but did not reach significance. Longitudinal analyses showed significant increases in hippocampal |G*|, G(d), and G(l), and significant decreases in WB |G*|, G(d), and G(l) between 11 and 14 months in both AD and WT mice. Each subgroup showed significant increases in all hippocampal and significant decreases in all WB measures, with the exception of AD females, which showed no significant changes in WB |G*|, G(d), or G(l). CONCLUSION: Aging had region-specific effects on cerebral viscoelasticity, namely WB softening and hippocampal stiffening. Amyloid plaque deposition may have sex-specific effects, which require further scrutiny.

Multiple sclerosis is a heterogeneous disease with an unpredictable course. We applied machine learning to generate individualised risk scores of disability worsening and stratify patients into subgroups with different prognosis.Clinical data and MRI scans from published randomised clinical trials in patients with relapsing-remitting and progressive MS were divided into training (n=5,483) and external validation data sets (n=2,668). We processed brain MRI scans to obtain 18 measures for lobar grey matter, deep grey matter and lesion volumes, and T1-/T2-weighted ratio of the normal-appearing white matter regions. We developed a machine learning model, called subpopulation risk stratification (SunRiSe), that combines multi-parametric clinical and MRI data to estimate individualised risk scores and stratify patients into subgroups on the basis of this risk; in particular, we entered MRI measures, the Expanded Disability Status Scale, age and gender to generate risk scores of disability worsening (i.e., the time to confirmed disability worsening). Based on SunRiSe risk scores, high-, medium-, and low-risk subpopulations were defined at study entry. We assessed whether selecting patients at high risk of disability worsening reduces sample size compared to when all risk groups were sampled together.In both the training and external validation data sets, SunRiSe-stratified patients in three groups associated with different levels of risk of disability worsening. In the external validation data set, patients at high risk were mainly progressive MS and had more disability events compared to those at medium-risk (hazard ratio [HR]=1.34, pThe inclusion of patients predicted to be at high risk, reduced (i) duration of an event-driven trial by an average of 4.5 months (±2.1 months); (ii) the number of participants in a randomised trial by approximately 200, with 80% statistical power to detect a 30% treatment effect.Machine learning provides a personalised risk score that can identify patients who have the greatest risk of disability worsening and therefore should be treated with the most effective medications and monitored more closely. Risk stratification allows the enrichment of clinical trials with patients more likely to worsen, and thereby reduces trial duration and sample size.

Experimental autoimmune encephalomyelitis (EAE) is a model of multiple sclerosis (MS). EAE reflects important histopathological hallmarks, dissemination, and diversity of the disease, but has only moderate reproducibility of clinical and histopathological features. Focal lesions are less frequently observed in EAE than in MS, and can neither be constrained to specific locations nor timed to occur at a pre-specified moment. This renders difficult any experimental assessment of the pathogenesis of lesion evolution, including its inflammatory, degenerative (demyelination and axonal degeneration), and reparatory (remyelination, axonal sprouting, gliosis) component processes. We sought to develop a controlled model of inflammatory, focal brain lesions in EAE using focused ultrasound (FUS). We hypothesized that FUS induced focal blood brain barrier disruption (BBBD) will increase the likelihood of transmigration of effector cells and subsequent lesion occurrence at the sonicated location. Lesion development was monitored with conventional magnetic resonance imaging (MRI) as well as with magnetic resonance elastography (MRE) and further analyzed by histopathological means. EAE was induced in 12 6–8 weeks old female C57BL/6 mice using myelin oligodendrocyte glycoprotein (MOG) peptide. FUS-induced BBBD was performed 6, 7, and 9 days after immunization in subgroups of four animals and in an additional control group. MRI and MRE were performed on a 7T horizontal bore small animal MRI scanner. Imaging was conducted longitudinally 2 and 3 weeks after disease induction and 1 week after sonication in control animals, respectively. The scan protocol comprised contrast-enhanced T1-weighted and T2-weighted sequences as well as MRE with a vibration frequency of 1 kHz. Animals were sacrificed for histopathology after the last imaging time point. The overall clinical course of EAE was mild. A total of seven EAE animals presented with focal T2w hyperintense signal alterations in the sonicated hemisphere. These were most frequent in the group of animals sonicated 9 days after immunization. Histopathology revealed foci of activated microglia/macrophages in the sonicated right hemisphere of seven EAE animals. Larger cellular infiltrates or apparent demyelination were not seen. Control animals showed no abnormalities on MRI and did not have clusters of activated microglia/macrophages at the sites targeted with FUS. None of the animals had hemorrhages or gross tissue damage as potential side effects of FUS. EAE-animals tended to have lower values of viscoelasticity and elasticity in the sonicated compared to the contralateral parenchyma. This trend was significant when comparing the right sonicated to the left normal hemisphere and specifically the right sonicated compared to the left normal cortex in animals that underwent FUS-BBBD 9 days after immunization (right vs. left hemisphere: mean viscoelasticity 6.1 vs. 7.2 kPa; p = 0.003 and mean elasticity 4.9 vs. 5.7 kPa, p = 0.024; right vs. left cortex: mean viscoelasticity 5.8 vs. 7.5 kPa; p = 0.004 and mean elasticity 5 vs. 6.5 kPa; p = 0.008). A direct comparison of the biomechanical properties of focal T2w hyperintensities with normal appearing brain tissue did not yield significant results. Control animals showed no differences in viscoelasticity between sonicated and contralateral brain parenchyma. We here provide first evidence for a controlled lesion induction model in EAE using FUS-induced BBBD. The observed lesions in EAE are consistent with foci of activated microglia that may be interpreted as targeted initial inflammatory activity and which have been described as pre-active lesions in MS. Such foci can be identified and monitored with MRI. Moreover, the increased inflammatory activity in the sonicated brain parenchyma seems to have an effect on overall tissue matrix structure as reflected by changes of biomechanical parameters.

Most neurological disorders seemingly have heterogenous pathogenesis, with overlapping contribution of neuronal, immune and vascular mechanisms of brain damage. The perivascular space (PVS) in the brain represents a crossroad where those mechanisms interact, as well as a key anatomical component of the recently discovered glymphatic pathway, which is considered to play a crucial role in the clearance of brain waste linked to neurodegenerative diseases. The pathological interplay between neuronal, immune and vascular factors can create an environment that promotes self-perpetration of mechanisms of brain damage across different neurological diseases, including those that are primarily thought of as neurodegenerative, neuroinflammatory or cerebrovascular. PVS changes can be monitored in humans in vivo using magnetic resonance imaging (MRI). In the context of glymphatic clearance, MRI-visible enlarged perivascular spaces (EPVS) are considered to reflect glymphatic stasis secondary to the perivascular accumulation of brain debris, although they may also represent an adaptive mechanism of the glymphatic system to clear them. EPVS are also established correlates of dementia and cerebral small vessel disease (SVD) and are considered to reflect brain inflammatory activity. In this review, we describe the “perivascular unit” as a key anatomical substrate for the interaction between neuronal, immune and vascular mechanisms of brain damage, which are shared across different neurological diseases, including those that are considered primarily neurodegenerative, neuroinflammatory or cerebrovascular. We will describe the main anatomical, physiological and pathological features of the perivascular unit, highlight potential substrates for the interplay between different noxae and summarize MRI studies of EPVS in cerebrovascular, neuroinflammatory and neurodegenerative disorders.

To investigate the effect of vaccinations and boosters on the severity of COVID-19 pneumonia on CT scans during the period of Delta and Omicron variants.Retrospectively studied were 303 patients diagnosed with COVID-19 between July 2021 and February 2022, who had obtained at least one CT scan within 6 weeks around the COVID-19 diagnosis (-2 to +4 weeks). The severity of pneumonia was evaluated with a 6-point scale Pneumonia Score. The association between demographic and clinical data and vaccination status (booster/additional vaccination, complete vaccination and un-vaccination) and the difference between Pneumonia Scores by vaccination status were investigated.Of 303 patients (59.4 ± 16.3 years; 178 females), 62 (20 %) were in the booster/additional vaccination group, 117 (39 %) in the complete vaccination group, and 124 (41 %) in the unvaccinated group. Interobserver agreement of the Pneumonia Score was high (weighted kappa score = 0.875). Patients in the booster/additionally vaccinated group tended to be older (P = 0.0085) and have more underlying comorbidities (P 0.0001), and the Pneumonia Scores were lower in the booster/additionally vaccinated [median 2 (IQR 0-4)] and completely vaccinated groups [median 3 (IQR 1-4)] than those in the unvaccinated group [median 4 (IQR 2-4)], respectively (P 0.0001 and P 0.0001, respectively). A multivariable linear analysis adjusted for confounding factors confirmed the difference.Vaccinated patients, with or without booster/additional vaccination, had milder COVID-19 pneumonia on CT scans than unvaccinated patients during the period of Delta and Omicron variants. This study supports the efficacy of the vaccine against COVID-19 from a radiological perspective.

BACKGROUND AND PURPOSE A pipeline for fully automated segmentation of 3T brain MRI scans in multiple sclerosis (MS) is presented. This 3T morphometry (3TM) pipeline provides indicators of MS disease progression from multichannel datasets with high‐resolution 3‐dimensional T1‐weighted, T2‐weighted, and fluid‐attenuated inversion‐recovery (FLAIR) contrast. 3TM segments white (WM) and gray matter (GM) and cerebrospinal fluid (CSF) to assess atrophy and provides WM lesion (WML) volume. METHODS To address nonuniform distribution of noise/contrast (eg, posterior fossa in 3D‐FLAIR) of 3T magnetic resonance imaging, the method employs dual sensitivity (different sensitivities for lesion detection in predefined regions). We tested this approach by assigning different sensitivities to supratentorial and infratentorial regions, and validated the segmentation for accuracy against manual delineation, and for precision in scan‐rescans. RESULTS Intraclass correlation coefficients of .95, .91, and .86 were observed for WML and CSF segmentation accuracy and brain parenchymal fraction (BPF). Dual sensitivity significantly reduced infratentorial false‐positive WMLs, affording increases in global sensitivity without decreasing specificity. Scan‐rescan yielded coefficients of variation (COVs) of 8% and .4% for WMLs and BPF and COVs of .8%, 1%, and 2% for GM, WM, and CSF volumes. WML volume difference/precision was .49 ± .72 mL over a range of 0–24 mL. Correlation between BPF and age was r = .62 (P = .0004), and effect size for detecting brain atrophy was Cohen's d = 1.26 (standardized mean difference vs. healthy controls). CONCLUSIONS This pipeline produces probability maps for brain lesions and tissue classes, facilitating expert review/correction and may provide high throughput, efficient characterization of MS in large datasets.

Erythropoietin (EPO) has received growing attention because of its neuroregenerative properties. Preclinical and clinical evidence supports its therapeutic potential in brain conditions like stroke, multiple sclerosis, and schizophrenia. Also, in Friedreich ataxia, clinical improvement after EPO therapy was shown. The aim of this study was to assess possible therapy-associated brain white matter changes in these patients.Nine patients with Friedreich ataxia underwent Diffusion Tensor Imaging (DTI) before and after EPO treatment. Tract-based spatial statistics was used for longitudinal comparison.We detected widespread longitudinal increase in fractional anisotropy and axial diffusivity (D||) in cerebral hemispheres bilaterally (P.05, corrected), while no changes were observed within the cerebellum, medulla oblongata, and pons.To the best of our knowledge, this is the first DTI study to investigate the effects of EPO in a neurodegenerative disease. Anatomically, the diffusivity changes appear disease unspecific, and their biological underpinnings deserve further study.

Approved symptomatic therapies for Alzheimer's disease (AD) provide modest relief. In the future, it is likely that symptomatic treatments will be utilized with AD modifying therapies, the development of which are currently a primary focus of research. The nicotinic α7 receptor agonist may be an attractive drug candidate to potentially improve cognition in Alzheimer's disease patients either as a stand-alone therapy or in combination with other symptomatic treatments. EVP-6124 is a novel, potent, and selective α7 nicotinic receptor agonist. EVP-6124 has an excellent brain to plasma exposure ratio and has shown excellent efficacy and potency in a number of animal models of cognition. Four clinical studies in >125 healthy normal human subjects have been completed with EVP-6124, including a single-ascending-dose study, a 14-day multiple-ascending-dose study, a 21-day multiple-dose study, and a single-dose relative bioavailability, food, and gender effect study. EVP-6124 exhibited linear kinetics over the range of 1 to 180 mg and demonstrated a half-life suitable for once daily dosing. EVP-6124 appears to be safe and well tolerated for up to 21 days as measured by adverse events, vital signs, continuous cardiac monitoring, physical examination, and clinical laboratory evaluations. In addition, in normal volunteers, EVP-6124 demonstrated pro-cognitive effects (CogState testing) in various cognitive domains including executive function. These data suggest that EVP-6124 administered to AD subjects on stable cholinesterase inhibitor therapies may have potential benefit and that further study in this patient population is indicated. Larger phase II studies are currently being initiated in both Alzheimer's disease and schizophrenia.

To compare long-interval T2-weighted subtraction (T2w-Sub) imaging with monthly gadolinium-enhanced T1-weighted (Gd-T1w) imaging for (1) detection of active lesions, (2) assessment of treatment efficacy, and (3) statistical power, in a multiple sclerosis (MS), phase 2, clinical trial setting.Magnetic resonance imaging (MRI) data over 9 months from 120 patients (61 treatment, 59 placebo) from the oral temsirolimus trial were used. T2w-Sub images were scored for active lesions, independent of the original reading of the monthly Gd-T1w images. Treatment efficacy was evaluated using the nonparametric Mann-Whitney U test, and parametric negative binomial (NB)-regression and power calculations were conducted.Datasets from 116 patients (58 treatment, 58 placebo) were evaluated. The mean number of T2w-Sub lesions in the treatment group was 3.0 (+/-4.6) versus 5.9 (+/-8.8) for placebo; the mean cumulative number of new Gd-T1w lesions in the treatment group was 5.5(+/-9.1) versus 9.1(+/-17.2) for placebo. T2w-Sub imaging showed increased power to assess treatment efficacy compared with Gd-T1w imaging, when evaluated by Mann-Whitney U test (p = 0.017 vs p = 0.177), or NB-regression without (p = 0.011 vs p = 0.092) or with baseline adjustment (p0.001 vs p = 0.002). Depending on the magnitude of the simulated treatment effect, sample size calculations showed reductions of 22 to 34% in the number of patients (translating into reductions of 81-83% in the number of MRI scans) needed to detect a significant treatment effect in favor of T2w-Sub imaging.Compared with monthly Gd-T1w imaging, long-interval T2w-Sub MRI exhibited increased power to assess treatment efficacy, and could greatly increase the cost-effectiveness of phase 2 MS trials by limiting the number of patients, contrast injections, and MRI scans needed.

Computation of B1 fields is a key issue for determination and correction of intensity nonuniformity in magnetic resonance images. This paper presents a new method for computing transmitted and received B1 fields. Our method combines a modified MRI acquisition protocol and an estimation technique based on the Levenberg-Marquardt algorithm and spatial filtering. It enables accurate estimation of transmitted and received B1 fields for both homogeneous and heterogeneous objects. The method is validated using numerical simulations and experimental data from phantom and human scans. The experimental results are in agreement with theoretical expectations.