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.

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.

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.

Clinical Associations and Prognostic Value of MRI-Visible Perivascular Spaces in Patients With Ischemic Stroke or TIA: A Pooled Analysis

BACKGROUND AND OBJECTIVES: Visible perivascular spaces are an MRI marker of cerebral small vessel disease and might predict future stroke. However, results from existing studies vary. We aimed to clarify this through a large collaborative multicenter analysis. METHODS: We pooled individual patient data from a consortium of prospective cohort studies. Participants had recent ischemic stroke or transient ischemic attack (TIA), underwent baseline MRI, and were followed up for ischemic stroke and symptomatic intracranial hemorrhage (ICH). Perivascular spaces in the basal ganglia (BGPVS) and perivascular spaces in the centrum semiovale (CSOPVS) were rated locally using a validated visual scale. We investigated clinical and radiologic associations cross-sectionally using multinomial logistic regression and prospective associations with ischemic stroke and ICH using Cox regression. RESULTS: We included 7,778 participants (mean age 70.6 years; 42.7% female) from 16 studies, followed up for a median of 1.44 years. Eighty ICH and 424 ischemic strokes occurred. BGPVS were associated with increasing age, hypertension, previous ischemic stroke, previous ICH, lacunes, cerebral microbleeds, and white matter hyperintensities. CSOPVS showed consistently weaker associations. Prospectively, after adjusting for potential confounders including cerebral microbleeds, increasing BGPVS burden was independently associated with future ischemic stroke (versus 0-10 BGPVS, 11-20 BGPVS: HR 1.19, 95% CI 0.93-1.53; 21+ BGPVS: HR 1.50, 95% CI 1.10-2.06; p = 0.040). Higher BGPVS burden was associated with increased ICH risk in univariable analysis, but not in adjusted analyses. CSOPVS were not significantly associated with either outcome. DISCUSSION: In patients with ischemic stroke or TIA, increasing BGPVS burden is associated with more severe cerebral small vessel disease and higher ischemic stroke risk. Neither BGPVS nor CSOPVS were independently associated with future ICH.

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.

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.

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.

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.

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).

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.

Patterns of care and survival of Chinese glioblastoma patients in the temozolomide era: a Hong Kong population-level analysis over a 14-year period.

Background: The aim of this study is to address the paucity of epidemiological data regarding the characteristics, treatment patterns and survival outcomes of Chinese glioblastoma patients. Methods: This was a population-level study of Hong Kong adult (>18 years) Chinese patients with newly diagnosed histologically confirmed glioblastoma between 2006 and 2019. The age standardized incidence rate (ASIR), patient-, tumor- treatment-related characteristics, overall survival (OS) as well as its predictors were determined. Results: One thousand and ten patients with a median follow-up of 10.0 months were reviewed. The ASIR of glioblastoma was 1.0 per 100 000 population with no significant change during the study period. The mean age was 57 + 14 years. The median OS was 10.6 months (IQR: 5.2-18.4). Independent predictors for survival were: Karnofsky performance score >80 (adjusted OR: 0.8; 95% CI: 0.6-0.9), IDH-1 mutant (aOR: 0.7; 95% CI: 0.5-0.9) or MGMT methylated (aOR: 0.7; 95% CI: 0.5-0.8) glioblastomas, gross total resection (aOR: 0.8; 95% CI: 0.5-0.8) and temozolomide chemoradiotherapy (aOR 0.4; 95% CI: 0.3-0.6). Despite the significant increased administration of temozolomide chemoradiotherapy from 39% (127/326) of patients in 2006-2010 to 63% (227/356) in 2015-2019 (P-value < .001), median OS did not improve (2006-2010: 10.3 months vs 2015-2019: 11.8 months) (OR: 1.1; 95% CI: 0.9-1.3). Conclusions: The incidence of glioblastoma in the Chinese general population is low. We charted the development of neuro-oncological care of glioblastoma patients in Hong Kong during the temozolomide era. Although there was an increased adoption of temozolomide chemoradiotherapy, a corresponding improvement in survival was not observed.

Stroke Risk and Antithrombotic Treatment During Follow-up of Patients With Ischemic Stroke and Cortical Superficial Siderosis.

BACKGROUND AND OBJECTIVES: In patients with ischemic stroke (IS) or transient ischemic attack (TIA) and cortical superficial siderosis (cSS), there are few data regarding the risk of future cerebrovascular events and also about the benefits and safety of antithrombotic drugs for secondary prevention. We investigated the associations of cSS and stroke risk in patients with recent IS or TIA. METHODS: We retrospectively analyzed the Microbleeds International Collaborative Network (MICON) database. We selected patients with IS or TIA from cohorts who had MRI-assessed cSS, available data on antithrombotic treatments, recurrent cerebrovascular events (intracranial hemorrhage [ICrH], IS, or any stroke [ICrH or IS]), and mortality. We calculated incidence rates (IRs) and performed univariable and multivariable Cox regression analyses. RESULTS: Of 12,669 patients (mean age 70.4 ± 12.3 years, 57.3% men), cSS was detected in 273 (2.2%) patients. During a mean follow-up of 24 ± 17 months, IS was more frequent than ICrH in both cSS (IR 57.1 vs 14.6 per 1,000 patient-years) and non-cSS (33.7 vs 6.3 per 1,000 patient-years) groups. Compared with the non-cSS group, cSS was associated with any stroke on multivariable analysis {IR 83 vs 42 per 1,000 patient-years, adjusted hazard ratio [HR] for cSS 1.62 (95% CI: 1.14-2.28; p = 0.006)}. This association was not significant in subgroups of patients treated with antiplatelet drugs (n = 6,554) or with anticoagulants (n = 4,044). Patients with cSS who were treated with both antiplatelet drugs and anticoagulants (n = 1,569) had a higher incidence of ICrH (IR 107.5 vs 4.9 per 1,000 patient-years, adjusted HR 13.26; 95% CI: 2.90-60.63; p = 0.001) and of any stroke (IR 198.8 vs 34.7 per 1,000 patient-years, adjusted HR 5.03; 95% CI: 2.03-12.44; p < 0.001) compared with the non-cSS group. DISCUSSION: Patients with IS or TIA with cSS are at increased risk of stroke (ICrH or IS) during follow-up; the risk of IS exceeds that of ICrH for patients receiving antiplatelet or anticoagulant treatment alone, but the risk of ICrH exceeds that of IS in patients receiving both treatments. The findings suggest that either antiplatelet or anticoagulant treatment alone should not be avoided in patients with cSS, but combined antithrombotic therapy might be hazardous. Our findings need to be confirmed by randomized clinical trials.

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.

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.

Level of Amyloid-ß (Aß) Binding Leading to Differential Effects on Resting State Functional Connectivity in Major Brain Networks.

INTRODUCTION: Amyloid-ß protein (Aß) is one of the biomarkers for Alzheimer's disease (AD). The recent application of interhemispheric functional connectivity (IFC) in resting-state fMRI has been used as a non-invasive diagnostic tool for early dementia. In this study, we focused on the level of Aß accumulated and its effects on the major functional networks, including default mode network (DMN), central executive network (CEN), salience network (SN), self-referential network (SRN) and sensory motor network (SMN). METHODS: 58 participants (27 Hi Aß (HiAmy) and 31 low Aß (LowAmy)) and 25 healthy controls (HC) were recruited. [18F]flutemetamol PET/CT was performed for diseased groups, and MRI scanning was done for all participants. Voxel-by-voxel correlation analysis was done for both groups in all networks. RESULTS: In HiAmy, IFC was reduced in all networks except SN. A negative correlation in DMN, CEN, SRN and SMN suggests high Aß related to IFC reduction; However, a positive correlation in SN suggests high Aß related to an increase in IFC. In LowAmy, IFC increased in CEN, SMN, SN and SRN. Positive correlation in all major brain networks. CONCLUSION: The level of Aß accumulated demonstrated differential effects on IFC in various brain networks. As the treatment to reduce Aß plaque deposition is available in the market, it may be an option for the HiAmy group to improve their IFC in major brain networks.

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.

Striatal dopamine synthesis capacity and its association with negative symptoms upon resolution of positive symptoms in first-episode schizophrenia and delusional disorder.

RATIONALE: How striatal dopamine synthesis capacity (DSC) contributes to the pathogenesis of negative symptoms in first-episode schizophrenia (SZ) and delusional disorder (DD) has seldom been explored. As negative symptoms during active psychotic episodes can be complicated by secondary influences, such as positive symptoms, longitudinal investigations may help to clarify the relationship between striatal DSC and negative symptoms and differentiate between primary and secondary negative symptoms. OBJECTIVE: A longitudinal study was conducted to examine whether baseline striatal DSC would be related to negative symptoms at 3 months in first-episode SZ and DD patients. METHODS: Twenty-three first-episode age- and gender-matched patients (11 DD and 12 SZ) were consecutively recruited through an early intervention service for psychosis in Hong Kong. Among them, 19 (82.6%) patients (9 DD and 10 SZ) were followed up at 3 months. All patients received an 18F-DOPA PET/MR scan at baseline. RESULTS: Baseline striatal DSC (Kocc;30-60) was inversely associated with negative symptoms at 3 months in first-episode SZ patients (rs = - 0.80, p = 0.010). This association remained in SZ patients even when controlling for baseline negative, positive, and depressive symptoms, as well as cumulative antipsychotic dosage (ß = - 0.69, p = 0.012). Such associations were not observed in first-episode DD patients. Meanwhile, the severity of negative symptoms at 3 months was associated with more positive symptoms in DD patients (rs = 0.74, p = 0.010) and not in SZ patients. CONCLUSIONS: These findings highlight the role of striatal DSC in negative symptoms upon resolution of active psychotic episodes among first-episode SZ patients. Baseline striatal dopamine activity may inform future symptom expression with important treatment implications.