Dynamic Changes in Long-Standing Multiple Sclerosis Revealed by Longitudinal Structural Network Analysis Using Diffusion Tensor Imaging.

BACKGROUND AND PURPOSE: DTI can be used to derive conventional diffusion measurements, which can measure WM abnormalities in multiple sclerosis. DTI can also be used to construct structural brain networks and derive network measurements. However, few studies have compared their sensitivity in detecting brain alterations, especially in longitudinal studies. Therefore, in this study, we aimed to determine which type of measurement is more sensitive in tracking the dynamic changes over time in MS. MATERIALS AND METHODS: Eighteen patients with MS were recruited at baseline and followed up at 6 and 12 months. All patients underwent MR imaging and clinical evaluation at 3 time points. Diffusion and network measurements were derived, and their brain changes were evaluated. RESULTS: None of the conventional DTI measurements displayed statistically significant changes during the follow-up period; however, the nodal degree, nodal efficiency, and nodal path length of the left middle frontal gyrus and bilateral inferior frontal gyrus, opercular part showed significant longitudinal changes between baseline and at 12 months, respectively. CONCLUSIONS: The nodal degree, nodal efficiency, and nodal path length of the left middle frontal gyrus and bilateral inferior frontal gyrus, opercular part may be used to monitor brain changes over time in MS.

Cuprizone drives divergent neuropathological changes in different mouse models of Alzheimer's disease.

Myelin degradation is a normal feature of brain aging that accelerates in Alzheimer's disease (AD). To date, however, the underlying biological basis of this correlation remains elusive. The amyloid cascade hypothesis predicts that demyelination is caused by increased levels of the ß-amyloid (Aß) peptide. Here we report on work supporting the alternative hypothesis that early demyelination is upstream of amyloid. We challenged two different mouse models of AD (R1.40 and APP/PS1) using cuprizone-induced demyelination and tracked the responses with both neuroimaging and neuropathology. In oppose to amyloid cascade hypothesis, R1.40 mice, carrying only a single human mutant APP (Swedish; APP SWE ) transgene, showed a more abnormal changes of magnetization transfer ratio and diffusivity than in APP/PS1 mice, which carry both APP SWE and a second PSEN1 transgene (delta exon 9; PSEN1 dE9 ). Although cuprizone targets oligodendrocytes (OL), magnetic resonance spectroscopy and targeted RNA-seq data in R1.40 mice suggested a possible metabolic alternation in axons. In support of alternative hypotheses, cuprizone induced significant intraneuronal amyloid deposition in young APP/PS1, but not in R1.40 mice, and it suggested the presence of PSEN deficiencies, may accelerate Aß deposition upon demyelination. In APP/PS1, mature OL is highly vulnerable to cuprizone with significant DNA double strand breaks (53BP1 + ) formation. Despite these major changes in myelin, OLs, and Aß immunoreactivity, no cognitive impairment or hippocampal pathology was detected in APP/PS1 mice after cuprizone treatment. Together, our data supports the hypothesis that myelin loss can be the cause, but not the consequence, of AD pathology. SIGNIFICANCE STATEMENT: The causal relationship between early myelin loss and the progression of Alzheimer's disease remains unclear. Using two different AD mouse models, R1.40 and APP/PS1, our study supports the hypothesis that myelin abnormalities are upstream of amyloid production and deposition. We find that acute demyelination initiates intraneuronal amyloid deposition in the frontal cortex. Further, the loss of oligodendrocytes, coupled with the accelerated intraneuronal amyloid deposition, interferes with myelin tract diffusivity at a stage before any hippocampus pathology or cognitive impairments occur. We propose that myelin loss could be the cause, not the consequence, of amyloid pathology during the early stages of Alzheimer's disease.

A Pilot Study of Short-Course Oral Vitamin A and Aerosolised Diffuser Olfactory Training for the Treatment of Smell Loss in Long COVID.

Background: Olfactory dysfunction (OD) is a common neurosensory manifestation in long COVID. An effective and safe treatment against COVID-19-related OD is needed. Methods: This pilot trial recruited long COVID patients with persistent OD. Participants were randomly assigned to receive short-course (14 days) oral vitamin A (VitA; 25,000 IU per day) and aerosolised diffuser olfactory training (OT) thrice daily (combination), OT alone (standard care), or observation (control) for 4 weeks. The primary outcome was differences in olfactory function by butanol threshold tests (BTT) between baseline and end-of-treatment. Secondary outcomes included smell identification tests (SIT), structural MRI brain, and serial seed-based functional connectivity (FC) analyses in the olfactory cortical network by resting-state functional MRI (rs-fMRI). Results: A total of 24 participants were randomly assigned to receive either combination treatment (n = 10), standard care (n = 9), or control (n = 5). Median OD duration was 157 days (IQR 127-175). Mean baseline BTT score was 2.3 (SD 1.1). At end-of-treatment, mean BTT scores were significantly higher for the combination group than control (p < 0.001, MD = 4.4, 95% CI 1.7 to 7.2) and standard care (p = 0.009) groups. Interval SIT scores increased significantly (p = 0.009) in the combination group. rs-fMRI showed significantly higher FC in the combination group when compared to other groups. At end-of-treatment, positive correlations were found in the increased FC at left inferior frontal gyrus and clinically significant improvements in measured BTT (r = 0.858, p < 0.001) and SIT (r = 0.548, p = 0.042) scores for the combination group. Conclusions: Short-course oral VitA and aerosolised diffuser OT was effective as a combination treatment for persistent OD in long COVID.

Disrupted Structural White Matter Network in Alzheimer's Disease Continuum, Vascular Dementia, and Mixed Dementia: A Diffusion Tensor Imaging Study.

BACKGROUND: Dementia presents a significant burden to patients and healthcare systems worldwide. Early and accurate diagnosis, as well as differential diagnosis of various types of dementia, are crucial for timely intervention and management. However, there is currently a lack of clinical tools for accurately distinguishing between these types. OBJECTIVE: This study aimed to investigate the differences in the structural white matter (WM) network among different types of cognitive impairment/dementia using diffusion tensor imaging, and to explore the clinical relevance of the structural network. METHODS: A total of 21 normal control, 13 subjective cognitive decline (SCD), 40 mild cognitive impairment (MCI), 22 Alzheimer's disease (AD), 13 mixed dementia (MixD), and 17 vascular dementia (VaD) participants were recruited. Graph theory was utilized to construct the brain network. RESULTS: Our findings revealed a monotonic trend of disruption in the brain WM network (VaD > MixD > AD > MCI > SCD) in terms of decreased global efficiency, local efficiency, and average clustering coefficient, as well as increased characteristic path length. These network measurements were significantly associated with the clinical cognition index in each disease group separately. CONCLUSION: These findings suggest that structural WM network measurements can be utilized to differentiate between different types of cognitive impairment/dementia, and these measurements can provide valuable cognition-related information.

The Use of Diffusion Kurtosis Imaging for the Differential Diagnosis of Alzheimer's Disease Spectrum.

Structural and diffusion kurtosis imaging (DKI) can be used to assess hippocampal macrostructural and microstructural alterations respectively, in Alzheimer's disease (AD) spectrum, spanning from subjective cognitive decline (SCD) to mild cognitive impairment (MCI) and AD. In this study, we explored the diagnostic performance of structural imaging and DKI of the hippocampus in the AD spectrum. Eleven SCD, thirty-seven MCI, sixteen AD, and nineteen age- and sex-matched normal controls (NCs) were included. Bilateral hippocampal volume, mean diffusivity (MD), and mean kurtosis (MK) were obtained. We detected that in AD vs. NCs, the right hippocampal volume showed the most prominent AUC value (AUC = 0.977); in MCI vs. NCs, the right hippocampal MD was the most sensitive discriminator (AUC = 0.819); in SCD vs. NCs, the left hippocampal MK was the most sensitive biomarker (AUC = 0.775). These findings suggest that, in the predementia stage (SCD and MCI), hippocampal microstructural changes are predominant, and the best discriminators are microstructural measurements (left hippocampal MK for SCD and right hippocampal MD for MCI); while in the dementia stage (AD), hippocampal macrostructural alterations are superior, and the best indicator is the macrostructural index (right hippocampal volume).

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.

Associations of sleep apnea risk and oxygen desaturation indices with cerebral small vessel disease burden in patients with stroke.

Background: Obstructive sleep apnea (OSA) is associated with cerebral small vessel disease (CSVD). Nonetheless, whether OSA-risk determined by a simple screening questionnaire or indices quantifying nocturnal hypoxemia other than the conventional apnea-hypopnea index (AHI) by the home sleep apnea test (HSAT) associated with CSVD burden remains uncertain. Methods: From 2018 to 2021, we recruited patients with transient ischemic attack (TIA)/minor stroke from the Queen Mary Hospital Acute Stroke Unit and TIA/Stroke Outpatient Clinics. Logistic regression models were applied to determine the association of baseline OSA-risk (on STOP-BANG questionnaire) or HSAT-derived indices quantifying nocturnal hypoxemia with global burden/individual markers of CSVD on MRI. Indices included oxygen desaturation (≥3%) index (ODI), minimum oxygen saturation (SpO2), percentage of total sleep time with an oxygen saturation <90% (CT90%), and desaturation duration (≥3%, DesDur). Results: In 283 patients with TIA/minor stroke (mean age 65 years, 64% men), OSA-risk was significantly associated with total CSVD score (multivariate-adjusted odds ratio: 1.23, 95% confidence interval 1.01-1.51), presence of lacunes [1.39 (1.09-1.79)] and burden of basal ganglia PVSs [1.32 (1.06-1.67)]. In 85/283 patients who completed HSAT, neither AHI, minimum SpO2 nor CT90% was associated with CSVD burden. Nonetheless, ODI and DesDur remained significantly associated with total CSVD score after covariate adjustment: ODI [1.04 (1.01-1.07)] and DesDur [1.04 (1.01-1.08)]. Conclusion: In patients with TIA/minor stroke, high OSA-risk was associated with a greater CSVD burden. Oxygen desaturation indices (ODI and DesDur) rather than AHI were independently associated with global CSVD burden, indicating that longer and more severe desaturations may contribute to the pathogenesis of CSVD.

The fractional amplitude of low-frequency fluctuations signals related to amyloid uptake in high-risk populations-A pilot fMRI study.

Background: Patients with type 2 diabetes mellitus (T2DM) and subjective cognitive decline (SCD) have a higher risk to develop Alzheimer's Disease (AD). Resting-state-functional magnetic resonance imaging (rs-fMRI) was used to document neurological involvement in the two groups from the aspect of brain dysfunction. Accumulation of amyloid-ß (Aß) starts decades ago before the onset of clinical symptoms and may already have been associated with brain function in high-risk populations. However, this study aims to compare the patterns of fractional amplitude of low-frequency fluctuations (fALFF) maps between cognitively normal high-risk groups (SCD and T2DM) and healthy elderly and evaluate the association between regional amyloid deposition and local fALFF signals in certain cortical regions. Materials and methods: A total of 18 T2DM, 11 SCD, and 18 healthy elderlies were included in this study. The differences in the fALFF maps were compared between HC and high-risk groups. Regional amyloid deposition and local fALFF signals were obtained and further correlated in two high-risk groups. Results: Compared to HC, the altered fALFF signals of regions were shown in SCD such as the left posterior cerebellum, left putamen, and cingulate gyrus. The T2DM group illustrated altered neural activity in the superior temporal gyrus, supplementary motor area, and precentral gyrus. The correlation between fALFF signals and amyloid deposition was negative in the left anterior cingulate cortex for both groups. In the T2DM group, a positive correlation was shown in the right occipital lobe and left mesial temporal lobe. Conclusion: The altered fALFF signals were demonstrated in high-risk groups compared to HC. Very early amyloid deposition in SCD and T2DM groups was observed to affect the neural activity mainly involved in the default mode network (DMN).

Incremental diagnostic value of 18F-Fluetemetamol PET in differential diagnoses of Alzheimer's Disease-related neurodegenerative diseases from an unselected memory clinic cohort.

To evaluate the incremental diagnostic value of 18F-Flutemetamol PET following MRI measurements on an unselected prospective cohort collected from a memory clinic. A total of 84 participants was included in this study. A stepwise study design was performed including initial analysis (based on clinical assessments), interim analysis (revision of initial analysis post-MRI) and final analysis (revision of interim analysis post-18F-Flutemetamol PET). At each time of evaluation, every participant was categorized into SCD, MCI or dementia syndromal group and further into AD-related, non-AD related or non-specific type etiological subgroup. Post 18F-Flutemetamol PET, the significant changes were seen in the syndromal MCI group (57%, p < 0.001) involving the following etiological subgroups: AD-related MCI (57%, p < 0.01) and non-specific MCI (100%, p < 0.0001); and syndromal dementia group (61%, p < 0.0001) consisting of non-specific dementia subgroup (100%, p < 0.0001). In the binary regression model, amyloid status significantly influenced the diagnostic results of interim analysis (p < 0.01). 18F-Flutemetamol PET can have incremental value following MRI measurements, particularly reflected in the change of diagnosis of individuals with unclear etiology and AD-related-suspected patients due to the role in complementing AD-related pathological information.

Changes in the Intranetwork and Internetwork Connectivity of the Default Mode Network and Olfactory Network in Patients with COVID-19 and Olfactory Dysfunction.

Olfactory dysfunction (OD) is a common symptom in coronavirus disease 2019 (COVID-19) patients. Moreover, many neurological manifestations have been reported in these patients, suggesting central nervous system involvement. The default mode network (DMN) is closely associated with olfactory processing. In this study, we investigated the internetwork and intranetwork connectivity of the DMN and the olfactory network (ON) in 13 healthy controls and 22 patients presenting with COVID-19-related OD using independent component analysis and region of interest functional magnetic resonance imaging (fMRI) analysis. There was a significant correlation between the butanol threshold test (BTT) and the intranetwork connectivity in ON. Meanwhile, the COVID-19 patients with OD showed significantly higher intranetwork connectivity in the DMN, as well as higher internetwork connectivity between ON and DMN. However, no significant difference was found between groups in the intranetwork connectivity within ON. We postulate that higher intranetwork functional connectivities compensate for the deficits in olfactory processing and general well-being in COVID-19 patients. Nevertheless, the compensation process in the ON may not be obvious at this stage. Our results suggest that resting-state fMRI is a potentially valuable tool to evaluate neurosensory dysfunction in COVID-19 patients.

A data-driven deep learning pipeline for quantitative susceptibility mapping (QSM).

PURPOSE: This study developed a data-driven optimization to improve the accuracy of deep learning QSM quantification. METHODS: The proposed deep learning QSM pipeline consisted of two projections onto convex set (POCS) models designed to decouple trainable network components with the spherical mean value (SMV) filters and dipole kernel in the data-driven optimization. They were a background field removal network (named POCSnet1) and a dipole inversion network (named POCSnet2). Both POCSnet1 and POCSnet2 were the unrolled V-Net with iterative data-driven optimization to enforce the data fidelity. For training POCSnet1, we simulated phantom data with random geometric shapes as the background susceptibility sources. For training POCSnet2, we used geometric shapes to mimic the QSM. The evaluation was performed on synthetic data, a public COSMOS (N = 1), and clinical data from a Parkinson's disease cohort (N = 71) and small-vessel disease cohort (N = 26). For comparison, DLL2, FINE, and autoQSM, were implemented and tested under the same experimental setting. RESULTS: On COSMOS, results from POCSnet1 were more similar to that of the V-SHARP method with NRMSE = 23.7% and SSIM = 0.995, compared with the NRMSE = 62.7% and SSIM = 0.975 for SHARQnet, a naïve V-Net model. On COSMOS, the NRMSE and HFEN for POCSnet2 were 58.1% and 56.7%; while for DLL2, FINE, and autoQSM, they were 62.0% and 61.2%, 69.8% and 67.5%, and 87.5% and 85.3%, respectively. On the Parkinson's disease cohort, our results were consistent with those obtained from VSHARP+STAR-QSM with biases <3% and outperformed the SHARQnet+DeepQSM that had biases of 7% to 10%. The sensitivity of cerebral microbleed detection using our pipeline was 100%, compared with 92% by SHARQnet+DeepQSM. CONCLUSION: Data-driven optimization improved the accuracy of QSM quantification compared with that of naïve V-Net models.

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.

Low-Density Lipoprotein Cholesterol and Risk of Recurrent Vascular Events in Chinese Patients With Ischemic Stroke With and Without Significant Atherosclerosis.

Background Recent trials have shown that low-density lipoprotein cholesterol (LDL-C) <1.80 mmol/L (<70 mg/dL) is associated with a reduced risk of major adverse cardiovascular events in White patients with ischemic stroke with atherosclerosis. However, it remains uncertain whether the findings can be generalized to Asian patients, or that similar LDL-C targets should be adopted in patients with stroke without significant atherosclerosis. Methods and Results We performed a prospective cohort study and recruited consecutive Chinese patients with ischemic stroke with magnetic resonance angiography of the intra- and cervicocranial arteries performed at the University of Hong Kong between 2008 and 2014. Serial postevent LDL-C measurements were obtained. Risk of major adverse cardiovascular events in patients with mean postevent LDL-C <1.80 versus ≥1.80 mmol/L, stratified by presence or absence of significant (≥50%) large-artery disease (LAD) and by ischemic stroke subtypes, were compared. Nine hundred four patients (mean age, 69±12 years; 60% men) were followed up for a mean 6.5±2.4 years (mean, 9±5 LDL-C readings per patient). Regardless of LAD status, patients with a mean postevent LDL-C <1.80 mmol/L were associated with a lower risk of major adverse cardiovascular events (with significant LAD: multivariable-adjusted subdistribution hazard ratio, 0.65; 95% CI, 0.42-0.99; without significant LAD: subdistribution hazard ratio, 0.53; 95% CI, 0.32-0.88) (both P<0.05). Similar findings were noted in patients with ischemic stroke attributable to large-artery atherosclerosis (subdistribution hazard ratio, 0.48; 95% CI, 0.28-0.84) and in patients with other ischemic stroke subtypes (subdistribution hazard ratio, 0.64; 95% CI, 0.43-0.95) (both P<0.05). Conclusions A mean LDL-C <1.80 mmol/L was associated with a lower risk of major adverse cardiovascular events in Chinese patients with ischemic stroke with and without significant LAD. Further randomized trials to determine the optimal LDL-C cutoff in stroke patients without significant atherosclerosis are warranted.

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.

Neurosensory Rehabilitation and Olfactory Network Recovery in Covid-19-related Olfactory Dysfunction.

Non-conductive olfactory dysfunction (OD) is an important extra-pulmonary manifestation of coronavirus disease 2019 (COVID-19). Olfactory bulb (OB) volume loss and olfactory network functional connectivity (FC) defects were identified in two patients suffering from prolonged COVID-19-related OD. One patient received olfactory treatment (OT) by the combination of oral vitamin A and smell training via the novel electronic portable aromatic rehabilitation (EPAR) diffusers. After four-weeks of OT, clinical recuperation of smell was correlated with interval increase of bilateral OB volumes [right: 22.5 mm3 to 49.5 mm3 (120%), left: 37.5 mm3 to 42 mm3 (12%)] and improvement of mean olfactory FC [0.09 to 0.15 (66.6%)].

Evaluation of the Cognitive Performance of Hypertensive Patients with Silent Cerebrovascular Lesions.

Evidence accumulated from the last decade has proven that silent cerebrovascular lesions (SCLs) and their underlying pathogenic processes contribute to cognitive decline in the elderly. However, the distinct effects of each type of the lesions on cognitive performance remain unclear. Moreover, research data from Chinese elderly with SCLs is scarce. In this study, 398 otherwise healthy hypertensive elderly subjects (median age 72 years) were included and assessed. All participates were required to complete a battery of structured neuropsychological assessment, including forward and backward digit span tests, symbol digit modalities test, Stroop test, verbal fluency test and Montreal Cognitive Assessment. These tests were used to assess attention, executive function, information processing speed, language, memory and visuospatial function. A multi-sequence 3T MRI scanning was arranged within one month of the neuropsychological assessment to evaluate the burden of SCLs. SCLs were rated visually. Cerebral microbleeds (CMBs) and silent lacunes (SLs) were identified as strictly lobar CMBs and SLs or deep CMBs and SLs according to their locations, respectively. Similarly, white matter hyperintensities (WMHs) were separated into periventricular WMHs (PVHs) and deep WMHs (DWMHs). A series of linear regression models were used to assess the correlation between each type of SCLs and individual cognitive function domain. The results showed that CMBs tend to impair language-related cognition. Deep SLs affect executive function, but this association disappeared after controlling for other types of SCLs. PVHs, rather than DWMHs, are associated with cognitive decline, especially in executive function and processing speed. It is concluded that different aspects of SCLs have differential impact on cognitive performance in hypertensive elderly Chinese.

Development of imaging-based risk scores for prediction of intracranial haemorrhage and ischaemic stroke in patients taking antithrombotic therapy after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies.

BACKGROUND: Balancing the risks of recurrent ischaemic stroke and intracranial haemorrhage is important for patients treated with antithrombotic therapy after ischaemic stroke or transient ischaemic attack. However, existing predictive models offer insufficient performance, particularly for assessing the risk of intracranial haemorrhage. We aimed to develop new risk scores incorporating clinical variables and cerebral microbleeds, an MRI biomarker of intracranial haemorrhage and ischaemic stroke risk. METHODS: We did a pooled analysis of individual-patient data from the Microbleeds International Collaborative Network (MICON), which includes 38 hospital-based prospective cohort studies from 18 countries. All studies recruited participants with previous ischaemic stroke or transient ischaemic attack, acquired baseline MRI allowing quantification of cerebral microbleeds, and followed-up participants for ischaemic stroke and intracranial haemorrhage. Participants not taking antithrombotic drugs were excluded. We developed Cox regression models to predict the 5-year risks of intracranial haemorrhage and ischaemic stroke, selecting candidate predictors on biological relevance and simplifying models using backward elimination. We derived integer risk scores for clinical use. We assessed model performance in internal validation, adjusted for optimism using bootstrapping. The study is registered on PROSPERO, CRD42016036602. FINDINGS: The included studies recruited participants between Aug 28, 2001, and Feb 4, 2018. 15 766 participants had follow-up for intracranial haemorrhage, and 15 784 for ischaemic stroke. Over a median follow-up of 2 years, 184 intracranial haemorrhages and 1048 ischaemic strokes were reported. The risk models we developed included cerebral microbleed burden and simple clinical variables. Optimism-adjusted c indices were 0·73 (95% CI 0·69-0·77) with a calibration slope of 0·94 (0·81-1·06) for the intracranial haemorrhage model and 0·63 (0·62-0·65) with a calibration slope of 0·97 (0·87-1·07) for the ischaemic stroke model. There was good agreement between predicted and observed risk for both models. INTERPRETATION: The MICON risk scores, incorporating clinical variables and cerebral microbleeds, offer predictive value for the long-term risks of intracranial haemorrhage and ischaemic stroke in patients prescribed antithrombotic therapy for secondary stroke prevention; external validation is warranted. FUNDING: British Heart Foundation and Stroke Association.

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.

Heterogeneity of Amyloid Binding in Cognitively Impaired Patients Consecutively Recruited from a Memory Clinic: Evaluating the Utility of Quantitative 18F-Flutemetamol PET-CT in Discrimination of Mild Cognitive Impairment from Alzheimer's Disease and Other Dementias.

BACKGROUND: With the more widespread use of 18F-radioligand-based amyloid-ß (Aß) PET-CT imaging, we evaluated Aß binding and the utility of neocortical 18F-Flutemetamol standardized uptake value ratio (SUVR) as a biomarker. OBJECTIVE: 18F-Flutemetamol SUVR was used to differentiate 1) mild cognitive impairment (MCI) from Alzheimer's disease (AD), and 2) MCI from other non-AD dementias (OD). METHODS: 109 patients consecutively recruited from a University memory clinic underwent clinical evaluation, neuropsychological test, MRI and 18F-Flutemetamol PET-CT. The diagnosis was made by consensus of a panel consisting of 1 neuroradiologist and 2 geriatricians. The final cohort included 13 subjective cognitive decline (SCD), 22 AD, 39 MCI, and 35 OD. Quantitative analysis of 16 region-of-interests made by Cortex ID software (GE Healthcare). RESULTS: The global mean 18F-Flutemetamol SUVR in SCD, MCI, AD, and OD were 0.50 (SD-0.08), 0.53 (SD-0.16), 0.76 (SD-0.10), and 0.56 (SD-0.16), respectively, with SUVR in SCD and MCI and OD being significantly lower than AD. Aß binding in SCD, MCI, and OD was heterogeneous, being 23%, 38.5%, and 42.9% respectively, as compared to 100% amyloid positivity in AD. Using global SUVR, ROC analysis showed AUC of 0.868 and 0.588 in differentiating MCI from AD and MCI from OD respectively. CONCLUSION: 18F-Flutemetamol SUVR differentiated MCI from AD with high efficacy (high negative predictive value), but much lower efficacy from OD. The major benefit of the test was to differentiate cognitively impaired patients (either SCD, MCI, or OD) without AD-related-amyloid-pathology from AD in the clinical setting, which was under-emphasized in the current guidelines proposed by Amyloid Imaging Task Force.