Idiopathic inflammatory-demyelinating diseases (IIDDs) include a broad spectrum of central nervous system disorders that can usually be differentiated on the basis of clinical, imaging, laboratory ...and pathological findings. However, there can be a considerable overlap between at least some of these disorders, leading to misdiagnoses or diagnostic uncertainty. The relapsing-remitting and secondary progressive forms of multiple sclerosis (MS) are the most common IIDDs. Other MS phenotypes include those with a progressive course from onset (primary progressive and progressive relapsing) or with a benign course continuing for years after onset (benign MS). Uncommon forms of IIDDs can be classified clinically into: (1) fulminant or acute IIDDs, such as the Marburg variant of MS, Baló's concentric sclerosis, Schilder's disease, and acute disseminated encephalomyelitis; (2) monosymptomatic IIDDs, such as those involving the spinal cord (transverse myelitis), optic nerve (optic neuritis) or brainstem and cerebellum; and (3) IIDDs with a restricted topographical distribution, including Devic's neuromyelitis optica, recurrent optic neuritis and relapsing transverse myelitis. Other forms of IIDD, which are classified clinically and radiologically as pseudotumoral, can have different forms of presentation and clinical courses. Although some of these uncommon IIDDs are variants of MS, others probably correspond to different entities. MR imaging of the brain and spine is the imaging technique of choice for diagnosing these disorders, and together with the clinical and laboratory findings can accurately classify them. Precise classification of these disorders may have relevant prognostic and treatment implications, and might be helpful in distinguishing them from tumoral or infectious lesions, avoiding unnecessary aggressive diagnostic or therapeutic procedures.
Previous studies have suggested that the central vein sign and iron rims are specific features of MS lesions. Using 3T SWI, we aimed to compare the frequency of lesions with central veins and iron ...rims in patients with clinically isolated syndrome and MS-mimicking disorders and test their diagnostic value in predicting conversion from clinically isolated syndrome to MS.
For each patient, we calculated the number of brain lesions with central veins and iron rims. We then identified a simple rule involving an absolute number of lesions with central veins and iron rims to predict conversion from clinically isolated syndrome to MS. Additionally, we tested the diagnostic performance of central veins and iron rims when combined with evidence of dissemination in space.
We included 112 patients with clinically isolated syndrome and 35 patients with MS-mimicking conditions. At follow-up, 94 patients with clinically isolated syndrome developed MS according to the 2017 McDonald criteria. Patients with clinically isolated syndrome had a median of 2 central veins (range, 0-19), while the non-MS group had a median of 1 central vein (range, 0-6). Fifty-six percent of patients who developed MS had ≥1 iron rim, and none of the patients without MS had iron rims. The sensitivity and specificity of finding ≥3 central veins and/or ≥1 iron rim were 70% and 86%, respectively. In combination with evidence of dissemination in space, the 2 imaging markers had higher specificity than dissemination in space and positive findings of oligoclonal bands currently used to support the diagnosis of MS.
A single 3T SWI scan offers valuable diagnostic information, which has the potential to prevent MS misdiagnosis.
Background
Recent studies have created awareness that facial features can be reconstructed from high-resolution MRI. Therefore, data sharing in neuroimaging requires special attention to protect ...participants’ privacy. Facial features removal (FFR) could alleviate these concerns. We assessed the impact of three FFR methods on subsequent automated image analysis to obtain clinically relevant outcome measurements in three clinical groups.
Methods
FFR was performed using QuickShear, FaceMasking, and Defacing. In 110 subjects of Alzheimer’s Disease Neuroimaging Initiative, normalized brain volumes (NBV) were measured by SIENAX. In 70 multiple sclerosis patients of the MAGNIMS Study Group, lesion volumes (WMLV) were measured by lesion prediction algorithm in lesion segmentation toolbox. In 84 glioblastoma patients of the PICTURE Study Group, tumor volumes (GBV) were measured by BraTumIA. Failed analyses on FFR-processed images were recorded. Only cases in which all image analyses completed successfully were analyzed. Differences between outcomes obtained from FFR-processed and full images were assessed, by quantifying the intra-class correlation coefficient (ICC) for absolute agreement and by testing for systematic differences using paired
t
tests.
Results
Automated analysis methods failed in 0–19% of cases in FFR-processed images versus 0–2% of cases in full images. ICC for absolute agreement ranged from 0.312 (GBV after FaceMasking) to 0.998 (WMLV after Defacing). FaceMasking yielded higher NBV (
p
= 0.003) and WMLV (
p
≤ 0.001). GBV was lower after QuickShear and Defacing (both
p
< 0.001).
Conclusions
All three outcome measures were affected differently by FFR, including failure of analysis methods and both “random” variation and systematic differences. Further study is warranted to ensure high-quality neuroimaging research while protecting participants’ privacy.
Key Points
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Protecting participants’ privacy when sharing MRI data is important
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Impact of three facial features removal methods on subsequent analysis was assessed in three clinical groups
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Removing facial features degrades performance of image analysis methods
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MR imaging is the preferred technique for the diagnosis, treatment planning, and monitoring of patients with neoplastic CNS lesions. Conventional MR imaging, with gadolinium-based contrast ...enhancement, is increasingly combined with advanced, functional MR imaging techniques to offer morphologic, metabolic, and physiologic information. This article provides updated recommendations to neuroradiologists, neuro-oncologists, neurosurgeons, and radiation oncologists on the practical applications of MR imaging of neoplastic CNS lesions in adults, with particular focus on gliomas, based on a review of the clinical trial evidence and personal experiences shared at a recent international meeting of experts in neuroradiology, neuro-oncology, neurosurgery, and radio-oncology.
The term hepatic encephalopathy (HE) includes a spectrum of neuropsychiatric abnormalities occurring in patients with liver dysfunction. Most cases are associated with cirrhosis and portal ...hypertension or portal-systemic shunts, but the condition can also be seen in patients with acute liver failure and, rarely, with portal-systemic bypass and no associated intrinsic hepatocellular disease. Although HE is a clinical condition, several neuroimaging techniques, particularly MR imaging, may eventually be useful for the diagnosis because they can identify and measure the consequences of central nervous system (CNS) increase in substances that under normal circumstances, are efficiently metabolized by the liver. Classic MR imaging abnormalities include high signal intensity in the globus pallidum on T1-weighted images, likely a reflection of increased tissue concentrations of manganese, and an elevated glutamine/glutamate peak coupled with decreased myo-inositol and choline signals on proton MR spectroscopy, representing disturbances in cell-volume homeostasis secondary to brain hyperammonemia. Recent data have shown that white matter abnormalities, also related to increased CNS ammonia concentration, can also be detected with several MR imaging techniques such as magnetization transfer ratio measurements, fast fluid-attenuated inversion recovery sequences, and diffusion-weighted images. All these MR imaging abnormalities, which return to normal with restoration of liver function, probably reflect the presence of mild diffuse brain edema, which seems to play an essential role in the pathogenesis of HE. It is likely that MR imaging will be increasingly used to evaluate the mechanisms involved in the pathogenesis of HE and to assess the effects of therapeutic measures focused on correcting brain edema in these patients.
MRI studies have provided valuable insights into the structure and function of neural networks, particularly in health and in classical neurodegenerative conditions such as Alzheimer disease. ...However, such work is also highly relevant in other diseases of the CNS, including multiple sclerosis (MS). In this Review, we consider the effects of MS pathology on brain networks, as assessed using MRI, and how these changes to brain networks translate into clinical impairments. We also discuss how this knowledge can inform the targeting of MS treatments and the potential future directions for research in this area. Studying MS is challenging as its pathology involves neurodegenerative and focal inflammatory elements, both of which could disrupt neural networks. The disruption of white matter tracts in MS is reflected in changes in network efficiency, an increasingly random grey matter network topology, relative cortical disconnection, and both increases and decreases in connectivity centred around hubs such as the thalamus and the default mode network. The results of initial longitudinal studies suggest that these changes evolve rather than simply increase over time and are linked with clinical features. Studies have also identified a potential role for treatments that functionally modify neural networks as opposed to altering their structure.
•A method has been developed to estimate the density of veins from susceptibility-weighted magnetic resonance.•The method uses Mamdani Fuzzy logic.•The density of veins has been assessed in healthy ...subjects and people with migraine.•Results suggest an increase in the density in people with migrane compared to healthy subjects.
An impaired neurovascular coupling has been described as a possible player in neurodegeneration and cognitive decline. Migraine is a recurrent and incapacitating disorder that starts early in life and has shown neurovascular coupling abnormalities. Despite its high prevalence, the physiology and underlying mechanisms are poorly understood. In this context, new biomarkers from magnetic resonance imaging (MRI) are needed to bring new knowledge into the field. The aim of this study was to determine the vein density from Susceptibility-Weighted Imaging (SWI) MRI, in subjects with migraine and healthy controls; and to assess whether it relates to Resting-State functional MRI (RS-fMRI).
The cohort included 30 healthy controls and 70 subjects with migraine (26 episodic, 44 chronic) who underwent a brain 3.0 T MRI. Clinical characteristics were also collected. Maps of density of veins were generated based on a Mamdani Fuzzy-Type Rule-Based System from the SWI MRI. Mean values of vein density were obtained in grey (GM) and white matter (WM) Freesurfer lobar parcellations. The Amplitude of Low-Frequency Fluctuations (ALFF) image was calculated for the RS-fMRI, and the mean values over the parcellated GM lobes were estimated. Differences between groups were assessed through and analysis of variance (age, sex, education and anxiety as covariates; p < 0.05), followed by post-hoc comparisons. Associations were run between clinical and MRI-derived variables.
When comparing the density of veins in GM, no differences between groups were found, neither associations with clinical variables. The density of veins was significantly higher in the WM of the occipital lobe for subjects with chronic migraine compared to controls (30%, p < 0.05). WM vein density in either frontal, temporal or cingulate regions was associated with clinical variables such as headache days, disability scores, and cognitive impairment (r between 0.25 and 0.41; p < 0.05). Mean values of ALFF did not differ significantly between controls and subjects with migraine. Strong significant associations between vein density and ALFF measures were obtained in most GM lobes for healthy subjects (r between 0.50 and 0.67; p < 0.05), instead, vein density in WM was significantly associated with ALFF for subjects with migraine (r between 0.32 and 0.58; p < 0.05).
Results point towards an increase in vein density in subjects with migraine, when compared to healthy controls. In addition, the association between GM vein density and ALFF found in healthy subjects was lost in migraine. Taken together, these results support the idea of abnormalities in the neurovascular coupling in migraine. Quantitative SWI MRI indicators in migraine might be an interesting target that may contribute to its comprehension.
The structural MR imaging correlates of cognitive impairment in multiple sclerosis are still debated. This study assessed lesional and atrophy measures of white matter and gray matter involvement in ...patients with MS acquired in 7 European sites to identify the MR imaging variables most closely associated with cognitive dysfunction.
Brain dual-echo, 3D T1-weighted, and double inversion recovery scans were acquired at 3T from 62 patients with relapsing-remitting MS and 65 controls. Patients with at least 2 neuropsychological tests with abnormal findings were considered cognitively impaired. Focal WM and cortical lesions were identified, and volumetric measures from WM, cortical GM, the hippocampus, and deep GM nuclei were obtained. Age- and site-adjusted models were used to compare lesion and volumetric MR imaging variables between patients with MS who were cognitively impaired and cognitively preserved. A multivariate analysis identified MR imaging variables associated with cognitive scores and disability.
Twenty-three patients (38%) were cognitively impaired. Compared with those with who were cognitively preserved, patients with MS with cognitive impairment had higher T2 and T1 lesion volumes and a trend toward a higher number of cortical lesions. Significant brain, cortical GM, hippocampal, deep GM nuclei, and WM atrophy was found in patients with MS with cognitive impairment versus those who were cognitively preserved. Hippocampal and deep GM nuclei atrophy were the best predictors of cognitive impairment, while WM atrophy was the best predictor of disability.
Hippocampal and deep GM nuclei atrophy are key factors associated with cognitive impairment in MS. These MR imaging measures could be applied in a multicenter context, with cognition as clinical outcome.
To assess the time course of brain atrophy and the difference across clinical subtypes in multiple sclerosis (MS).
The percent brain volume change (PBVC) was computed on existing longitudinal (2 time ...points) T1-weighted MRI from untreated (trial and nontrial) patients with MS. Patients (n = 963) were classified as clinically isolated syndromes suggestive of MS (CIS, 16%), relapsing-remitting (RR, 60%), secondary progressive (SP, 15%), and primary progressive (9%) MS. The median length of follow-up was 14 months (range 12-68).
There was marked heterogeneity of the annualized PBVC (PBVC/y) across MS subtypes (p = 0.003), with higher PBVC/y in SP than in CIS (p = 0.003). However, this heterogeneity disappeared when data were corrected for the baseline normalized brain volume. When the MS population was divided into trial and nontrial subjects, the heterogeneity of PBVC/y across MS subtypes was present only in the second group, due to the higher PBVC/y values found in trial data in CIS (p = 0.01) and RR (p < 0.001). The estimation of the sample sizes required for demonstrating a reduction of brain atrophy in patients in a placebo-controlled trial showed that this was larger in patients with early MS than in those with the progressive forms of the disease.
This first large study in untreated patients with multiple sclerosis (MS) with different disease subtypes shows that brain atrophy proceeds relentlessly throughout the course of MS, with a rate that seems largely independent of the MS subtype, when adjusting for baseline brain volume.
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