Impact of Cerebral Microbleeds in Stroke Patients with Atrial Fibrillation.

OBJECTIVES: Cerebral microbleeds are associated with the risks of ischemic stroke and intracranial hemorrhage, causing clinical dilemmas for antithrombotic treatment decisions. We aimed to evaluate the risks of intracranial hemorrhage and ischemic stroke associated with microbleeds in patients with atrial fibrillation treated with vitamin K antagonists, direct oral anticoagulants, antiplatelets, and combination therapy (i.e. concurrent oral anticoagulant and antiplatelet). METHODS: We included patients with documented atrial fibrillation from the pooled individual patient data analysis by the Microbleeds International Collaborative Network. Risks of subsequent intracranial hemorrhage and ischemic stroke were compared between patients with and without microbleeds, stratified by antithrombotic use. RESULTS: A total of 7,839 patients were included. The presence of microbleeds was associated with an increased relative risk of intracranial hemorrhage (adjusted hazard ratio [aHR] = 2.74, 95% confidence interval = 1.76-4.26) and ischemic stroke (aHR = 1.29, 95% confidence interval = 1.04-1.59). For the entire cohort, the absolute incidence of ischemic stroke was higher than intracranial hemorrhage regardless of microbleed burden. However, for the subgroup of patients taking combination of anticoagulant and antiplatelet therapy, the absolute risk of intracranial hemorrhage exceeded that of ischemic stroke in those with 2 to 4 microbleeds (25 vs 12 per 1,000 patient-years) and ≥ 11 microbleeds (94 vs 48 per 1,000 patient-years). INTERPRETATION: Patients with atrial fibrillation and high burden of microbleeds receiving combination therapy have a tendency of higher rate of intracranial hemorrhage than ischemic stroke, with potential for net harm. Further studies are needed to help optimize stroke preventive strategies in this high-risk group. ANN NEUROL 2023;94:61-74.

Deep-Learning-Based MRI Microbleeds Detection for Cerebral Small Vessel Disease on Quantitative Susceptibility Mapping.

BACKGROUND: Cerebral microbleeds (CMB) are indicators of severe cerebral small vessel disease (CSVD) that can be identified through hemosiderin-sensitive sequences in MRI. Specifically, quantitative susceptibility mapping (QSM) and deep learning were applied to detect CMBs in MRI. PURPOSE: To automatically detect CMB on QSM, we proposed a two-stage deep learning pipeline. STUDY TYPE: Retrospective. SUBJECTS: A total number of 1843 CMBs from 393 patients (69 ± 12) with cerebral small vessel disease were included in this study. Seventy-eight subjects (70 ± 13) were used as external testing. FIELD STRENGTH/SEQUENCE: 3 T/QSM. ASSESSMENT: The proposed pipeline consisted of two stages. In stage I, 2.5D fast radial symmetry transform (FRST) algorithm along with a one-layer convolutional network was used to identify CMB candidate regions in QSM images. In stage II, the V-Net was utilized to reduce false positives. The V-Net was trained using CMB and non CMB labels, which allowed for high-level feature extraction and differentiation between CMBs and CMB mimics like vessels. The location of CMB was assessed according to the microbleeds anatomical rating scale (MARS) system. STATISTICAL TESTS: The sensitivity and positive predicative value (PPV) were reported to evaluate the performance of the model. The number of false positive per subject was presented. RESULTS: Our pipeline demonstrated high sensitivities of up to 94.9% at stage I and 93.5% at stage II. The overall sensitivity was 88.9%, and the false positive rate per subject was 2.87. With respect to MARS, sensitivities of above 85% were observed for nine different brain regions. DATA CONCLUSION: We have presented a deep learning pipeline for detecting CMB in the CSVD cohort, along with a semi-automated MARS scoring system using the proposed method. Our results demonstrated the successful application of deep learning for CMB detection on QSM and outperformed previous handcrafted methods. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

A scoping review of resting-state brain functional alterations in Type 2 diabetes.

Resting-state functional magnetic resonance imaging (rs-fMRI) has been actively used in the last decade to investigate brain functional connectivity alterations in Type 2 Diabetes Mellitus (T2DM) to understand the neuropathophysiology of T2DM in cognitive degeneration. Given the emergence of new analysis techniques, this scoping review aims to map the rs-fMRI analysis techniques that have been applied in the literature and reports the latest rs-fMRI findings that have not been covered in previous reviews. Graph theory, the contemporary rs-fMRI analysis, has been used to demonstrate altered brain topological organisations in people with T2DM, which included altered degree centrality, functional connectivity strength, the small-world architecture and network-based statistics. These alterations were correlated with T2DM patients' cognitive performances. Graph theory also contributes to identify unbiased seeds for seed-based analysis. The expanding rs-fMRI analytical approaches continue to provide new evidence that helps to understand the mechanisms of T2DM-related cognitive degeneration.

Semisupervised white matter hyperintensities segmentation on MRI.

This study proposed a semisupervised loss function named level-set loss (LSLoss) for cerebral white matter hyperintensities (WMHs) segmentation on fluid-attenuated inversion recovery images. The training procedure did not require manually labeled WMH masks. Our image preprocessing steps included biased field correction, skull stripping, and white matter segmentation. With the proposed LSLoss, we trained a V-Net using the MRI images from both local and public databases. Local databases were the small vessel disease cohort (HKU-SVD, n = 360) and the multiple sclerosis cohort (HKU-MS, n = 20) from our institutional imaging center. Public databases were the Medical Image Computing Computer-assisted Intervention (MICCAI) WMH challenge database (MICCAI-WMH, n = 60) and the normal control cohort of the Alzheimer's Disease Neuroimaging Initiative database (ADNI-CN, n = 15). We achieved an overall dice similarity coefficient (DSC) of 0.81 on the HKU-SVD testing set (n = 20), DSC = 0.77 on the HKU-MS testing set (n = 5), and DSC = 0.78 on MICCAI-WMH testing set (n = 30). The segmentation results obtained by our semisupervised V-Net were comparable with the supervised methods and outperformed the unsupervised methods in the literature.

Deep learning-regularized, single-step quantitative susceptibility mapping quantification.

The purpose of the current study was to develop deep learning-regularized, single-step quantitative susceptibility mapping (QSM) quantification, directly generating QSM from the total phase map. A deep learning-regularized, single-step QSM quantification model, named SS-POCSnet, was trained with datasets created using the QSM synthesis approach in QSM reconstruction challenge 2.0. In SS-POCSnet, a data fidelity term based on a single-step model was iteratively applied that combined the spherical mean value kernel and dipole model. Meanwhile, SS-POCSnet regularized susceptibility maps, avoiding underestimating susceptibility values. We evaluated the SS-POCSnet on 10 synthetic datasets, 24 clinical datasets with lesions of cerebral microbleed (CMB) and calcification, and 10 datasets with multiple sclerosis (MS).On synthetic datasets, SS-POCSnet showed the best performance among the methods evaluated, with a normalized root mean squared error of 37.3% ± 4.2%, susceptibility-tuned structured similarity index measure of 0.823 ± 0.02, high-frequency error norm of 37.0 ± 5.7, and peak signal-to-noise ratio of 42.8 ± 1.1. SS-POCSnet also reduced the underestimations of susceptibility values in deep brain nuclei compared with those from the other models evaluated. Furthermore, SS-POCSnet was sensitive to CMB/calcification and MS lesions, demonstrating its clinical applicability. Our method also supported variable imaging parameters, including matrix size and resolution. It was concluded that deep learning-regularized, single-step QSM quantification can mitigate underestimating susceptibility values in deep brain nuclei.

Prevalence of mild behavioural impairment domains: a meta-analysis.

BACKGROUND: Mild behavioural impairment (MBI) is a neurobehavioural syndrome characterised by later life emergence of persistent neuropsychiatric symptoms. Our previous meta-analysis showed that MBI is prevalent among cognitively normal (CN), subjective cognitive impairment (SCI) and mild cognitive impairment (MCI) subjects. This study is to calculate the pooled prevalence of MBI domains among CN, SCI, and MCI subjects. METHODS: A search of relevant literature published between 1 January 2003 and 6 August 2021 was conducted. Meta-analysis using a random effects model and meta-regression was performed. RESULTS: Ten studies conducted among 12 067 subjects (9758 CN, 1057 SCI and 1252 MCI) with retrievable MBI domains data underwent meta-analysis, revealing pooled prevalence of affective dysregulation (AFD), impulse dyscontrol (IDS), decreased motivation (DMT), social inappropriateness (SIP) and abnormal perception/thought (APT) of 32.84% (95% CI 24.44-42.5%), 26.67% (95% CI 18.24-37.23%), 12.58% (95% CI 6.93-21.75%), 6.05% (95% CI 3.44-10.42%), and 2.81% (95% CI 1.67-4.69%) respectively. AFD and APT domains demonstrated ordinal increase in pooled prevalence from CN, SCI and MCI subgroups, but meta-regression demonstrated no significant difference in MBI domains prevalence among cognitive subgroups (in contrast to the significant increase in MBI prevalence from CN to SCI to MCI). The pooled prevalence of AFD and IDS are greater than that of DMT, SIP and APT among all cognitive subgroups. Several variables were found to explain the high heterogeneity. CONCLUSIONS: AFD and IDS are the two most prevalent MBI domains and remain the same with cognitive deterioration. This finding is potentially relevant to clinical practice.

Asymmetric left-right hippocampal glutamatergic modulation of cognitive control in ApoE-isoform subjects is unrelated to neuroinflammation.

The glutamatergic cycle is essential in modulating memory processing by the hippocampal circuitry. Our combined proton magnetic resonance spectroscopy (1 H-MRS) and task-based functional magnetic resonance imaging (fMRI) study (using face-name paired-associates encoding and retrieval task) of a cognitively normal cohort of 67 healthy adults (18 ApoE4 carriers and 49 non-ApoE4 carriers) found altered patterns of relationships between glutamatergic-modulated synaptic signalling and neuronal activity or functional hyperaemia in the ApoE4 isoforms. Our study highlighted the asymmetric left-right hippocampal glutamatergic system in modulating neuronal activities in ApoE4 carriers versus non-carriers. Such brain differentiation might be developmental cognitive advantages or compensatory due to impaired synaptic integrity and plasticity in ApoE4 carriers. As there was no difference in myoinositol levels measured by MRS between the ApoE4 and non-ApoE4 subgroups, the mechanism is unlikely to be a response to neuroinflammation.

Small-World Networks and Their Relationship With Hippocampal Glutamine/Glutamate Concentration in Healthy Adults With Varying Genetic Risk for Alzheimer's Disease.

BACKGROUND: Apolipoprotein E ɛ4 allele (ApoE4) is the most common gene polymorphism related to Alzheimer's disease (AD). Impaired synaptic dysfunction occurs in ApoE4 carriers before any clinical symptoms. It remains unknown whether ApoE4 status affects the hippocampal neuromodulation, which further influences brain network topology. PURPOSE: To study the relationship of regional and global network properties by using graph theory analysis and glutamatergic (Glx) neuromodulation in the ApoE isoforms. STUDY TYPE: Prospective. SUBJECTS: Eighty-four cognitively normal adults (26 ApoE4 and 58 non-ApoE4 carriers). FIELD STRENGTH/SEQUENCE: Gradient-echo echo-planar and point resolved spectroscopy sequence at 3 T. ASSESSMENT: Glx concentration in bilateral hippocampi were processed with jMRUI (4.0), and graph theory metrics (global: γ, λ, small-worldness in whole brain; regional: nodal clustering coefficient (Ci ) and nodal characteristic path length (Li )) in top 20% highly connected hubs of subgroups (low-risk: non-ApoE4; high-risk: APOE4) were calculated and compared. STATISTICAL TESTS: Two-sample t test was used to compare metrics between subgroups. Correlations between regional properties and Glx by Pearson's partial correlation with false discovery rate correction. RESULTS: Significant differences (P < 0.05) in Ci between subgroups were found in hubs of left inferior frontal, bilateral inferior temporal, and bilateral precentral gyri, right parahippocampus, and bilateral precuneus. In addition, there was a significant correlation between Glx in the left hippocampus and Ci in inferior frontal gyrus (r = -0.537, P = 0.024), right inferior temporal (r = -0.478, P = 0.043), right parahippocampus (r = -0.629, P = 0.016), left precentral (r = -0.581, P = 0.022), right precentral (r = -0.651, P = 0.003), left precuneus (r = -0.545, P = 0.024), and right precuneus (r = -0.567, P = 0.022); and Li in left precuneus (r = 0.575, P = 0.032) and right precuneus (r = 0.586, P = 0.032) in the high-risk group, but not in the low-risk group. DATA CONCLUSION: Our results suggested that healthy ApoE4 carriers exhibit poorer local interconnectivity. Moreover, the close relationship between glutamate and small-world network properties in ApoE4 carriers might reflect a compensatory response to the impaired network efficiency. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 3.

A systematic review of atypical Alzheimer's disease including behavioural and psychological symptoms.

Alzheimer's disease (AD) is the commonest cause of dementia, characterized by the clinical presentation of progressive anterograde episodic memory impairment. However, atypical presentation of patients is increasingly recognized. These atypical AD include logopenic aphasia, behavioural variant AD, posterior cortical atrophy, and corticobasal syndrome. These atypical AD are more common in patients with young onset AD before the age of 65 years old. Since medical needs (including the behavioural and psychological symptoms of dementia) of atypical AD patients could be different from typical AD patients, it is important for clinicians to be aware of these atypical forms of AD. In addition, disease modifying treatment may be available in the future. This review aims at providing an update on various important subtypes of atypical AD including behavioural and psychological symptoms.

Prevalence of mild behavioural impairment: a systematic review and meta-analysis.

AIM: Mild behavioural impairment (MBI) is a neurobehavioural syndrome characterized by emergent neuropsychiatric symptoms in later life. There has been no systematic review or meta-analysis on the prevalence of MBI. The main aim of the study is to calculate the pooled prevalence of MBI. METHODS: A search of the literature on MBI in mild cognitive impairment (MCI), cognitively normal (CN), and subjective cognitive impairment (SCI) and CN but at risk (CN-AR) subjects published between 1 January 2003 and 28 September 2020 was conducted. Meta-analysis using a random effects model was performed to determine the pooled estimate of the prevalence of MBI. Meta-regression was performed to identify factors contributing to the variance of prevalence rate. A systematic review was also performed to study the impact of MBI in cognitive outcomes and its correlation to the pathology and genetics of Alzheimer's disease. RESULTS: Eleven studies conducted among 15 689 subjects underwent meta-analysis, revealing the pooled prevalence of MBI to be 33.5% (95% confidence interval (CI): 22.6%-46.6%). Seven studies conducted among 1358 MCI subjects underwent meta-analysis, revealing the pooled prevalence to be 45.5% (95%CI: 36.1%-55.3%). Four studies conducted among 13 153 CN subjects underwent meta-analysis, revealing the pooled prevalence to be 17.0% (95%CI: 7.2%-34.9%). Five studies conducted among 1158 SCI or CN-AR subjects underwent meta-analysis, revealing the pooled prevalence to be 35.8% (95%CI: 21.4%-53.2%). A systematic review of 13 studies showed that MBI has a significant impact on cognitive deterioration and is associated with the pathology and genetics of Alzheimer's disease. CONCLUSIONS: In MCI, CN, and SCI and CN-AR subjects, MBI is common. Our finding is potentially useful in planning future clinical trials.

Age-Specific Associations of Renal Impairment and Cerebral Small Vessel Disease Burden in Chinese with Ischaemic Stroke.

BACKGROUND: Recent studies in Caucasians with transient ischaemic attack or ischaemic stroke have demonstrated significant age-specific associations between cerebral small vessel disease (SVD) burden on magnetic resonance imaging and renal impairment. We aimed to validate these findings in a large cohort of Chinese with ischaemic stroke. METHODS: In 959 Chinese with ischaemic stroke who received a brain magnetic resonance imaging at the University of Hong Kong, we determined the age-specific associations of renal impairment (glomerular filtration rate < 60 mL/min/1.73 m2) with neuroimaging markers of SVD as well as with the SVD score. RESULTS: Although renal impairment was associated with the SVD score in univariate analysis in all patients (odds ratio 1.61, 95% confidence interval 1.24-2.09, P < .0001), these associations were attenuated after adjusting for age and sex (P = .38). Similar findings were noted in patients with ischaemic stroke due to SVD and non-SVD subtypes. However, in 222 of 959 patients aged <60, renal impairment was independently associated with an increasing microbleed (adjusted odds ratio 6.82, 2.26-20.59), subcortical (4.97, 1.62-15.24) periventricular white matter hyperintensity (3.96, 1.08-14.51) and global SVD burden (3.41, 1.16-10.04; all P < .05) even after adjusting for age, sex, and vascular risk factors. Nevertheless, there were no associations between renal impairment and individual neuroimaging markers of SVD nor with the SVD score in patients aged ≥60 after adjusting for age and sex (all P > .05). CONCLUSIONS: In Chinese with ischaemic stroke, renal impairment was independently associated with microbleed, white matter hyperintensity and global SVD burden in individuals aged <60, but not in those aged ≥60, suggesting that there may be shared susceptibilities to premature systemic disease.

Antiplatelet Treatment After Transient Ischemic Attack and Ischemic Stroke in Patients With Cerebral Microbleeds in 2 Large Cohorts and an Updated Systematic Review.

BACKGROUND AND PURPOSE: In patients with transient ischemic attack/ischemic stroke, microbleed burden predicts intracerebral hemorrhage (ICH), and ischemic stroke, but implications for antiplatelet treatment are uncertain. Previous cohort studies have had insufficient follow-up to assess the time course of risks, have not stratified risks by antithrombotic use, and have not reported extracranial bleeds or functional outcome of ICH versus ischemic stroke. METHODS: In 2 independent prospective cohorts with transient ischemic attack/ischemic stroke (Oxford Vascular Study/mainly white; University of Hong Kong/mainly Chinese), antiplatelet treatment was started routinely irrespective of microbleed burden. Risks, time course and outcome of ICH, extracranial bleeds, and recurrent ischemic events were determined and stratified by microbleed burden (0 versus 1, 2-4, and ≥5), adjusting for age, sex, and vascular risk factors. RESULTS: Microbleeds were more frequent in the Chinese cohort (450 of 1003 versus 165 of 1080; P<0.0001), but risk associations were similar during 7433 patient-years of follow-up. Among 1811 patients on antiplatelet drugs, risk of major extracranial bleeds was unrelated to microbleed burden (Ptrend=0.87), but the 5-year risk of ICH was steeply related (Ptrend<0.0001), with 11 of 15 (73%) of ICH in 140 of 1811 (7.7%) patients with ≥5 microbleeds. However, risk of ischemic stroke also increased with microbleed burden (Ptrend=0.013), such that risk of ischemic stroke and coronary events exceeded ICH and major extracranial bleeds during the first year, even among patients with ≥5 microbleeds (11.6% versus 3.9%). However, this ratio changed over time, with risk of hemorrhage (11.2%) matching that of ischemic events (12.0%) after 1 year. Moreover, whereas the association between microbleed burden and risk of ischemic stroke was due mainly to nondisabling events (Ptrend=0.007), the association with ICH was accounted for (Ptrend<0.0001) by disabling/fatal events (≥5 microbleeds: 82% disabling/fatal ICH versus 40% disabling/fatal ischemic stroke; P=0.035). CONCLUSIONS: In white and Chinese patients with ≥5 microbleeds, withholding antiplatelet drugs during the first year after transient ischemic attack/ischemic stroke may be inappropriate. However, the risk of ICH may outweigh any benefit thereafter.

Differential brainstem atrophy patterns in multiple sclerosis and neuromyelitis optica spectrum disorders.

BACKGROUND: Multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD) are central nervous system (CNS) inflammatory demyelinating disorders. It is clinically important to distinguish MS from NMOSD, as treatment and prognosis differ. Brainstem involvement is common in both disorders. PURPOSE: To investigate whether the patterns of brainstem atrophy on volumetric analysis in MS and NMOSD were different and correlated with clinical disability. STUDY TYPE: Case-control cross-sectional study. SUBJECTS: In all, 17 MS, 13 NMOSD, and 18 healthy control (HC) subjects were studied. FIELD STRENGTH/SEQUENCE: T1 -weighted and T2 w spin-echo images were acquired with a 3T scanner. ASSESSMENT: Semiautomated segmentation and volumetric measurement of brainstem regions were performed. Anatomical information was obtained from whole brain T1 w images using a 3D magnetization-prepared rapid gradient-echo (MPRAGE) imaging sequence (TR/TE/T: 7.0/3.2/800 msec, voxel size: 1 × 1 × 1 mm3 , scan time: 10 min 41 sec). STATISTICAL TESTS: Independent samples t-test, Mann-Whitney U-test, partial correlation, and multiple regression analysis. RESULTS: Baseline characteristics were similar across the three groups, without significant difference in disease duration (P = 0.354) and EDSS score (P = 0.159) between MS and NMOSD subjects. Compared to HC, MS subjects had significantly smaller normalized whole brainstem (-5.2%, P = 0.027), midbrain (-8.3%, P = 0.0001), and pons volumes (-5.9%, P = 0.048), while only the normalized medulla volume was significantly smaller in NMOSD subjects compared to HC (-8.5% vs. HC, P = 0.024). Normalized midbrain volume was significantly smaller in MS compared to NMOSD subjects (-5.0%, P = 0.014), whereas normalized medulla volume was significantly smaller in NMOSD compared to MS subjects (-8.1%, P = 0.032). Partial correlations and multiple regression analysis revealed that smaller normalized whole brainstem, pons, and medulla oblongata volumes were associated with greater disability on the Expanded Disability Status Scale (EDSS), Functional System Score (FSS)-brainstem and FSS-cerebellar in NMOSD subjects. DATA CONCLUSION: Differential patterns of brainstem atrophy were observed, with the midbrain being most severely affected followed by pons in MS, whereas only the medulla oblongata was affected in NMOSD. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1601-1609.

Clinical Correlates, Ethnic Differences, and Prognostic Implications of Perivascular Spaces in Transient Ischemic Attack and Ischemic Stroke.

BACKGROUND AND PURPOSE: Perivascular spaces (PVSs) are considered markers of small vessel disease. However, their long-term prognostic implications in transient ischemic attack/ischemic stroke patients are unknown. Ethnic differences in PVS prevalence are also unknown. METHODS: Two independent prospective studies were conducted, 1 comprising predominantly whites with transient ischemic attack/ischemic stroke (OXVASC [Oxford Vascular] study) and 1 comprising predominantly Chinese with ischemic stroke (University of Hong Kong). Clinical and imaging correlates, prognostic implications for stroke and death, and ethnic differences in basal ganglia (BG) and centrum semiovale (CS) PVSs were studied with adjustment for age, sex, vascular risk factors, and scanner strength. RESULTS: Whites with transient ischemic attack/ischemic stroke (n=1028) had a higher prevalence of both BG and CS-PVSs compared with Chinese (n=974; >20 BG-PVSs: 22.4% versus 7.1%; >20 CS-PVSs: 45.8% versus 10.4%; P<0.0001). More than 20 BG or CS-PVSs were both associated with increasing age and white matter hyperintensity, although associations with BG-PVSs were stronger (all P<0.0001). During 6924 patient-years of follow-up, BG-PVSs were also independently associated with an increased risk of recurrent ischemic stroke (adjusted hazard ratio compared with <11 PVSs, 11-20 PVSs: HR, 1.15; 95% confidence interval, 0.78-1.68; >20 PVSs: HR, 1.82; 1.18-2.80; P=0.011) but not intracerebral hemorrhage (P=0.10) or all-cause mortality (P=0.16). CS-PVSs were not associated with recurrent stroke (P=0.57) or mortality (P=0.072). Prognostic associations were similar in both cohorts. CONCLUSIONS: Over and above ethnic differences in frequency of PVSs in transient ischemic attack/ischemic stroke patients, BG and CS-PVSs had similar risk factors, but although >20 BG-PVSs were associated with an increased risk of recurrent ischemic stroke, CS-PVSs were not.

Application of diffusional kurtosis imaging to detect occult brain damage in multiple sclerosis and neuromyelitis optica.

Multiple sclerosis (MS) and neuromyelitis optica (NMO) are two common types of inflammatory demyelinating disease of the central nervous system. Early distinction of NMO from MS is crucial but quite challenging. In this study, 13 NMO spectrum disorder patients (Expanded Disability Status Scale (EDSS) of 3.0 ± 1.7, ranging from 2 to 6.5; disease duration of 5.3 ± 4.7 years), 17 relapsing-remitting MS patients (EDSS of 2.6 ± 1.4, ranging from 1 to 5.5; disease duration of 7.9 ± 7.8 years) and 18 healthy volunteers were recruited. Diffusional kurtosis imaging was employed to discriminate NMO and MS patients at the early or stable stage from each other, and from healthy volunteers. The presence of alterations in diffusion and diffusional kurtosis metrics in normal-appearing white matter (NAWM) and diffusely increased mean diffusivity (MD) in the cortical normal-appearing gray matter (NAGM) favors the diagnosis of MS rather than NMO. Meanwhile, normal diffusivities and kurtosis metrics in all NAWM as well as increases in MD in the frontal and temporal NAGM suggest NMO. Our results suggest that diffusion and diffusional kurtosis metrics may well aid in discriminating the two diseases.

Effective time window in reducing pituitary adenoma size by gamma knife radiosurgery.

OBJECTIVES: Although the effectiveness of gamma knife radiosurgery (GKRS) in controlling the size of pituitary adenomas has been well demonstrated in many studies, the time period in which significant changes in tumor size occurs has been investigated in a limited fashion. It is important to determine the therapeutic window of GKRS in treating pituitary adenomas, i.e., the effective timeframe during which significant size reduction of these tumors occurs, so that alternative treatments such as further GKRS or microsurgery might be prescribed in a timely manner if clinically indicated. METHODS: This was a nested sample of an ongoing local cohort study on GKRS for pituitary adenomas at the University of Virginia. Magnetic resonance imaging (MRI) using dedicated sequences was employed. Only patients with a baseline MRI (TP0) and at least 1 follow-up study performed in the University Hospital after GKRS were included. The follow-up scans were performed at five time-points (TP1-TP5) which were 6, 12, 24, 36 and 48 months after GKRS. The dimensional indices of the tumors were measured in three orthogonal planes, i.e., transverse (TR), antero-posterior (AP) and cranio-caudal (CC). The volumes of the tumors were estimated by using the following formula: [Formula: see text]. Tumor volume decrease by more than 25% from baseline was considered as 'shrinkage', <25% tumor size increase or decrease was considered 'static', and more than 25% increase as 'increment'. Our cohort consisted of 21 patients, with functioning adenomas in 13 subjects i.e. six adrenocorticotrophic hormone (ACTH)-secreting and seven growth hormone (GH)-secreting, and non-functioning (NF) adenomas in eight subjects. RESULTS: In 26 adenomas (8 ACTH, 9 GH and 9 NF), tumor control (tumor shrinkage or static) were achieved in 21 tumors (80.8%); 89, 75, and 78% for GH-secreting, ACTH-secreting and NF adenomas respectively, at the end of the 4-year follow-up period. Analysis of variance showed significant differences of GKRS margin dose among different types of tumors (p = 0.013), but not of baseline tumor volumes (p = 0.240). Logistic regression analysis showed no significant association of margin dose, baseline volume or tumor type with the tumor control outcome. Comparison of tumor change using dimensional indices relative to the base time point (TP0) showed that in the sample there was an average reduction of 1.290 mm at TP1 (6 months) with p values 0.155 (parametric t test) and 0.098 (non-parametric Wilcoxon signed-ranked test) respectively, showing a moderate reduction in tumor dimensional indices. The change in dimensional indices at later time points (TP2-TP5) showed an average reduction ranging from 1.930 to 2.471 mm. Significant reduction in the mean dimensional indices was firstly observed at TP2 (1 year) with p values 0.013 (t test) and 0.018 (Wilcoxon signed-rank test). Such scale of reduction in the dimensional indices appeared to be maintained along the time axis (from TP2 to TP5). CONCLUSIONS: Significant decrease in tumor dimensional indices tended to occur at 1 year post-GKRS. Although to a lesser extent, such decrease in dimensional indices continued up to the end of our follow-up period.

The default mode network is disrupted in Parkinson's disease with visual hallucinations.

BACKGROUND: Visual hallucinations (VH) are one of the most striking nonmotor symptoms in Parkinson's disease (PD), and predict dementia and mortality. Aberrant default mode network (DMN) is associated with other psychoses. Here, we tested the hypothesis that DMN dysfunction contributes to VH in PD. METHODS: Resting state functional data was acquired from individuals with PD with VH (PDVH) and without VH (PDnonVH), matched for levodopa drug equivalent dose, and a healthy control group (HC). Independent component analysis was used to investigate group differences in functional connectivity within the DMN. In addition, we investigated whether the functional changes associated with hallucinations were accompanied by differences in cortical thickness. RESULTS: There were no group differences in cortical thickness but functional coactivation within components of the DMN was significantly lower in both PDVH and PDnonVH groups compared to HC. Functional coactivation within the DMN was found to be greater in PDVH group relative to PDnonVH group. CONCLUSION: Our study demonstrates, for the first time that, within a functionally abnormal DMN in PD, relatively higher "connectivity" is associated with VH. We postulate that aberrant connectivity in a large scale network affects sensory information processing and perception, and contributes to "positive" symptom generation in PD.

The structural-functional-connectivity coupling of the aging brain.

Aging primarily affects memory and executive functions, a relationship that may be underpinned by the fact that almost all adults over 60 years old develop small vessel disease (SVD). The fact that a wide range of neuropathologies could only explain up to 43% of the variation in age-related cognitive impairment suggests that other factors, such as cognitive reserve, may play a role in the brain's resilience against aging-related cognitive decline. This study aims to examine the relationship between structural-functional-connectivity coupling (SFC), and aging, cognitive abilities and reserve, and SVD-related neuropathologies using a cohort of n = 176 healthy elders from the Harvard Aging Brain Study. The SFC is a recently proposed biomarker that reflects the extent to which anatomical brain connections can predict coordinated neural activity. After controlling for the effect of age, sex, and years of education, global SFC, as well as the intra-network SFC of the dorsolateral somatomotor and dorsal attention networks, and the inter-network SFC between dorsolateral somatomotor and frontoparietal networks decreased with age. The global SFC decreased with total cognitive score. There were significant interaction effects between years of education versus white matter hyperintensities and between years of education versus cerebral microbleeds on inter-network SFC. Enlarged perivascular space in basal ganglia was associated with higher inter-network SFC. Our results suggest that cognitive ability is associated with brain coupling at the global level and cognitive reserve with brain coupling at the inter-functional-brain-cluster level with interaction effect from white matter hyperintensities and cerebral microbleed in a cohort of healthy elderlies.

Integrating Demographics and Imaging Features for Various Stages of Dementia Classification: Feed Forward Neural Network Multi-Class Approach.

BACKGROUND: MRI magnetization-prepared rapid acquisition (MPRAGE) is an easily available imaging modality for dementia diagnosis. Previous studies suggested that volumetric analysis plays a crucial role in various stages of dementia classification. In this study, volumetry, radiomics and demographics were integrated as inputs to develop an artificial intelligence model for various stages, including Alzheimer's disease (AD), mild cognitive decline (MCI) and cognitive normal (CN) dementia classifications. METHOD: The Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset was separated into training and testing groups, and the Open Access Series of Imaging Studies (OASIS) dataset was used as the second testing group. The MRI MPRAGE image was reoriented via statistical parametric mapping (SPM12). Freesurfer was employed for brain segmentation, and 45 regional brain volumes were retrieved. The 3D Slicer software was employed for 107 radiomics feature extractions from within the whole brain. Data on patient demographics were collected from the datasets. The feed-forward neural network (FFNN) and the other most common artificial intelligence algorithms, including support vector machine (SVM), ensemble classifier (EC) and decision tree (DT), were used to build the models using various features. RESULTS: The integration of brain regional volumes, radiomics and patient demographics attained the highest overall accuracy at 76.57% and 73.14% in ADNI and OASIS testing, respectively. The subclass accuracies in MCI, AD and CN were 78.29%, 89.71% and 85.14%, respectively, in ADNI testing, as well as 74.86%, 88% and 83.43% in OASIS testing. Balanced sensitivity and specificity were obtained for all subclass classifications in MCI, AD and CN. CONCLUSION: The FFNN yielded good overall accuracy for MCI, AD and CN categorization, with balanced subclass accuracy, sensitivity and specificity. The proposed FFNN model is simple, and it may support the triage of patients for further confirmation of the diagnosis.

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

BACKGROUND: 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. PURPOSE: 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. METHODS: 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 6 min 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. RESULTS: 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. CONCLUSION: 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.