Machine learning application for classification of Alzheimer's disease stages using 18F-flortaucipir positron emission tomography.

BACKGROUND: The progression of Alzheimer's dementia (AD) can be classified into three stages: cognitive unimpairment (CU), mild cognitive impairment (MCI), and AD. The purpose of this study was to implement a machine learning (ML) framework for AD stage classification using the standard uptake value ratio (SUVR) extracted from 18F-flortaucipir positron emission tomography (PET) images. We demonstrate the utility of tau SUVR for AD stage classification. We used clinical variables (age, sex, education, mini-mental state examination scores) and SUVR extracted from PET images scanned at baseline. Four types of ML frameworks, such as logistic regression, support vector machine (SVM), extreme gradient boosting, and multilayer perceptron (MLP), were used and explained by Shapley Additive Explanations (SHAP) to classify the AD stage. RESULTS: Of a total of 199 participants, 74, 69, and 56 patients were in the CU, MCI, and AD groups, respectively; their mean age was 71.5 years, and 106 (53.3%) were men. In the classification between CU and AD, the effect of clinical and tau SUVR was high in all classification tasks and all models had a mean area under the receiver operating characteristic curve (AUC) > 0.96. In the classification between MCI and AD, the independent effect of tau SUVR in SVM had an AUC of 0.88 (p < 0.05), which was the highest compared to other models. In the classification between MCI and CU, the AUC of each classification model was higher with tau SUVR variables than with clinical variables independently, which yielded an AUC of 0.75(p < 0.05) in MLP, which was the highest. As an explanation by SHAP for the classification between MCI and CU, and AD and CU, the amygdala and entorhinal cortex greatly affected the classification results. In the classification between MCI and AD, the para-hippocampal and temporal cortex affected model performance. Especially entorhinal cortex and amygdala showed a higher effect on model performance than all clinical variables in the classification between MCI and CU. CONCLUSIONS: The independent effect of tau deposition indicates that it is an effective biomarker in classifying CU and MCI into clinical stages using MLP. It is also very effective in classifying AD stages using SVM with clinical information that can be easily obtained at clinical screening.

Association between Baseline Cognitive Function and Longitudinal Functional Outcome Change after Ischemic Stroke.

INTRODUCTION: Ischemic stroke can cause impairment of daily function and cognitive function. Higher cognitive function is reported in many studies to be associated with better functional outcomes; however, evidence from longitudinal study is lacking. Therefore, in the present study, the association between cognitive function and longitudinal changes of functional outcome was investigated based on stroke severity. Furthermore, whether the effect of cognitive function remained consistent after controlling for depression was investigated. METHODS: The data of 423 stroke patients (292 minor strokes, 93 moderate strokes, and 38 severe strokes) were collected. Baseline Mini-Mental State Examination (MMSE) score was considered a predictor, and change of modified Rankin Scale (mRS) score during 12 months of follow-up was the outcome. First, the association between the baseline MMSE score and longitudinal change in the mRS score was analyzed using linear mixed-effects models. Fixed effects were MMSE score group, time, and MMSE score group × time interaction. Additional adjustment was made for the Geriatric Depression Scale (GDS) score. RESULTS: Among the 423 subjects, the mean age was 73.5 years, and 43.4% were female. In the minor stroke group, the high MMSE score group had a decreased mRS score, and the low MMSE score group had an increased mRS score (p < 0.001). This association remained after additional adjustment of the GDS score. Association was not observed between cognitive function and functional recovery in the moderate or severe stroke group. CONCLUSION: After ischemic stroke, higher baseline global cognitive function was a predictive factor for better functional recovery regardless of depression symptoms in the minor stroke group.

Correction to: Staging and quantification of florbetaben PET images using machine learning: impact of predicted regional cortical tracer uptake and amyloid stage on clinical outcomes.

Incorrect acknowledgments.

Staging and quantification of florbetaben PET images using machine learning: impact of predicted regional cortical tracer uptake and amyloid stage on clinical outcomes.

PURPOSE: We developed a machine learning-based classifier for in vivo amyloid positron emission tomography (PET) staging, quantified cortical uptake of the PET tracer by using a machine learning method, and investigated the impact of these amyloid PET parameters on clinical and structural outcomes. METHODS: A total of 337 18F-florbetaben PET scans obtained at Samsung Medical Center were assessed. We defined a feature vector representing the change in PET tracer uptake from grey to white matter. Using support vector machine (SVM) regression and SVM classification, we quantified the cortical uptake as predicted regional cortical tracer uptake (pRCTU) and categorised the scans as positive and negative. Positive scans were further classified into two stages according to the striatal uptake. We compared outcome parameters among stages and further assessed the association between the pRCTU and outcome variables. Finally, we performed path analysis to determine mediation effects between PET variables. RESULTS: The classification accuracy was 97.3% for cortical amyloid positivity and 91.1% for striatal positivity. The left frontal and precuneus/posterior cingulate regions, as well as the anterior portion of the striatum, were important in determination of stages. The clinical scores and magnetic resonance imaging parameters showed negative associations with PET stage. However, except for the hippocampal volume, most outcomes were associated with the stage through the complete mediation effect of pRCTU. CONCLUSION: Using a machine learning algorithm, we achieved high accuracy for in vivo amyloid PET staging. The in vivo amyloid stage was associated with cognitive function and cerebral atrophy mostly through the mediation effect of cortical amyloid.

Correction to: Staging and quantification of florbetaben PET images using machine learning: impact of predicted regional cortical tracer uptake and amyloid stage on clinical outcomes.

The Table 2 in the original version of this article contained a mistake in the alignment. Correct Table 2 presentation is presented here.

Correction to: A new Centiloid method for 18F-florbetaben and 18F-flutemetamol PET without conversion to PiB.

Funding information from the original version of this article was incomplete. Complete information is presented here.

A new Centiloid method for 18F-florbetaben and 18F-flutemetamol PET without conversion to PiB.

PURPOSE: We developed a new method to directly calculate Centiloid (CL) units of 18F-florbetaben (FBB) and 18F-flutemetamol (FMM) without conversion to the PiB standardized uptake value ratio (SUVR). METHODS: Paired FBB and FMM PET scans were obtained from 20 Alzheimer's disease-related cognitive impairment patients, 16 old controls, and 20 young controls. We investigated the correlations between the FBB and FMM CL units using the direct comparison of FBB-FMM CL (dcCL) method and the standard CL method and compare differences in FBB and FMM CL units between dcCL method and the standard method. RESULTS: Following the conversion of FBB or FMM SUVRs into CL units, a direct relationship was formed between the FBB or FMM SUVRs and the CL units using dcCL method (FBB dcCL = 151.42 × FBB dcSUVR - 142.24 and FMM dcCL = 148.52 × FMM dcSUVR - 137.09). The FBB and FMM CL units were highly correlated in both our method (R2 = 0.97, FMM dcCL = 0.97 × FBB dcCL + 1.64) and the standard method (R2 = 0.97, FMM CLstandard = 0.79 × FBB CLstandard + 1.36). However, the CL variations between FBB and FMM were smaller when calculated by dcCL method (6.15) than when calculated by the previous method (10.22; P = 0.01). CONCLUSIONS: Our findings suggest that our direct comparison of FBB-FMM method, rather than the standard method, is a reasonable way to convert FBB or FMM SUVRs into CL units, at least in environments where FBB or FMM ligands are used frequently.

Application of an amyloid and tau classification system in subcortical vascular cognitive impairment patients.

OBJECTIVE: To apply an AT (Aß/tau) classification system to subcortical vascular cognitive impairment (SVCI) patients following recently developed biomarker-based criteria of Alzheimer's disease (AD), and to investigate its clinical significance. METHODS: We recruited 60 SVCI patients who underwent the neuropsychological tests, brain MRI, and 18F-florbetaben and 18F-AV1451 PET at baseline. As a control group, we further recruited 27 patients with AD cognitive impairment (ADCI; eight Aß PET-positive AD dementia and 19 amnestic mild cognitive impairment). ADCI and SVCI patients were classified as having normal or abnormal Aß (A-/A+) and tau (T-/T+) based on PET results. Across the three SVCI groups (A-, A+T-, and A+T+SVCI), we compared longitudinal changes in cognition, hippocampal volume (HV), and cortical thickness using linear mixed models. RESULTS: Among SVCI patients, 33 (55%), 20 (33.3%), and seven (11.7%) patients were A-, A+T-, and A+T+, respectively. The frequency of T+ was lower in A+SVCI (7/27, 25.9%) than in A+ADCI (14/20, 70.0%, p = 0.003) which suggested that cerebral small vessel disease affected cognitive impairments independently of A+. A+T-SVCI had steeper cognitive decline than A-SVCI. A+T+SVCI also showed steeper cognitive decline than A+T-SVCI. Also, A+T-SVCI had steeper decrease in HV than A-SVCI, while cortical thinning did not differ between the two groups. A+T+SVCI had greater global cortical thinning compared with A+T-SVCI, while declines in HV did not differ between the two groups. CONCLUSION: This study showed that the AT system successfully characterized SVCI patients, suggesting that the AT system may be usefully applied in a research framework for clinically diagnosed SVCI.

Functional connectivity associated with tau levels in ageing, Alzheimer's, and small vessel disease.

In Alzheimer's disease, tau pathology spreads hierarchically from the inferior temporal lobe throughout the cortex, ensuing cognitive decline and dementia. Similarly, circumscribed patterns of pathological tau have been observed in normal ageing and small vessel disease, suggesting a spatially ordered distribution of tau pathology across normal ageing and different diseases. In vitro findings suggest that pathological tau may spread 'prion-like' across neuronal connections in an activity-dependent manner. Supporting this notion, functional brain networks show a spatial correspondence to tau deposition patterns. However, it remains unclear whether higher network-connectivity facilitates tau propagation. To address this, we included 55 normal aged elderly (i.e. cognitively normal, amyloid-negative), 50 Alzheimer's disease patients (i.e. amyloid-positive) covering the preclinical to dementia spectrum, as well as 36 patients with pure (i.e. amyloid-negative) vascular cognitive impairment due to small vessel disease. All subjects were assessed with AV1451 tau-PET and resting-state functional MRI. Within each group, we computed atlas-based resting-state functional MRI functional connectivity across 400 regions of interest covering the entire neocortex. Using the same atlas, we also assessed within each group the covariance of tau-PET levels among the 400 regions of interest. We found that higher resting-state functional MRI assessed functional connectivity between any given region of interest pair was associated with higher covariance in tau-PET binding in corresponding regions of interest. This result was consistently found in normal ageing, Alzheimer's disease and vascular cognitive impairment. In particular, inferior temporal tau-hotspots, as defined by highest tau-PET uptake, showed high predictive value of tau-PET levels in functionally closely connected regions of interest. These associations between functional connectivity and tau-PET uptake were detected regardless of presence of dementia symptoms (mild cognitive impairment or dementia), amyloid deposition (as assessed by amyloid-PET) or small vessel disease. Our findings suggest that higher functional connectivity between brain regions is associated with shared tau-levels, supporting the view of prion-like tau spreading facilitated by neural activity.

Small vessel disease more than Alzheimer's disease determines diffusion MRI alterations in memory clinic patients.

INTRODUCTION: Microstructural alterations as assessed by diffusion tensor imaging (DTI) are key findings in both Alzheimer's disease (AD) and small vessel disease (SVD). We determined the contribution of each of these conditions to diffusion alterations. METHODS: We studied six samples (N = 365 participants) covering the spectrum of AD and SVD, including genetically defined samples. We calculated diffusion measures from DTI and free water imaging. Simple linear, multivariable random forest, and voxel-based regressions were used to evaluate associations between AD biomarkers (amyloid beta, tau), SVD imaging markers, and diffusion measures. RESULTS: SVD markers were strongly associated with diffusion measures and showed a higher contribution than AD biomarkers in multivariable analysis across all memory clinic samples. Voxel-wise analyses between tau and diffusion measures were not significant. DISCUSSION: In memory clinic patients, the effect of SVD on diffusion alterations largely exceeds the effect of AD, supporting the value of diffusion measures as markers of SVD.

Depressive symptoms are associated with worse cognitive prognosis in patients with newly diagnosed idiopathic Parkinson disease.

BACKGROUND: Although depression is very common in patients with Parkinson disease (PD), only a few studies have investigated the longitudinal effects of initial depression on cognitive decline in these patients. The purpose of this study was to investigate the effect of depression on cognitive functions in patients with PD. METHODS: We used data from the Parkinson Progression Markers Initiative (PPMI) to investigate the relationship between depression and PD. Depressive symptoms were measured in patients with PD based on the Geriatric Depression Scale (GDS) or Neuropsychiatric Inventory-Questionnaire (NPI-Q) scores obtained at baseline. We evaluated cognitive decline as whether a patient with PD progressed to PD with mild cognitive impairment (MCI) during a 4-year follow-up period. Multivariate Cox regression analysis was done to know whether depression can predict the conversion to MCI. In addition, a voxel-based morphometric analysis using volumetric brain magnetic resonance imaging was used to compare structural changes related to future cognitive decline as well as to reveal longitudinal effect of baseline depression on cortical atrophy. RESULTS: Data from 263 patients with cognitively normal de novo PD who were available for longitudinal cognitive testing were analysed. The multivariate Cox regression analysis revealed that the depressive symptoms were independent risk factors for conversion to MCI in patients with de novo PD after adjusting for covariates (hazards ratio (95% CI)) of depression defined by the GDS (1.753 (1.084-2.835)) and the NPI (1.815 (1.083-3.042)) scores, respectively. The significant structural changes in PD with MCI as well as longitudinal effect of baseline depression on subsequent cortical atrophy were found in multiple areas on the voxel-based morphometric analysis (P < 0.001, family-wise error rate corrected). CONCLUSIONS: Our study indicates that the presence of depressive symptoms in patients with early PD is associated with a higher risk of progression to MCI and early depression may reflect subsequent cortical atrophy.

Clinical significance of amyloid ß positivity in patients with probable cerebral amyloid angiopathy markers.

PURPOSE: We investigated the frequency and clinical significance of amyloid ß (Aß) positivity on PET in patients with cerebral amyloid angiopathy (CAA). METHODS: We recruited 65 patients who met the modified Boston criteria for probable CAA. All underwent amyloid PET, MRI, APOE genotyping and neuropsychological testing, and we obtained information on MRI markers of CAA and ischemic cerebral small-vessel disease (CSVD). We investigated the CAA/ischemic CSVD burden and APOE genotypes in relation to Aß positivity and investigated the effect of Aß positivity on longitudinal cognitive decline. RESULTS: Among the 65 CAA patients, 43 (66.2%) showed Aß PET positivity (Aß+). Patients with Aß+ CAA had more lobar microbleeds (median 9, interquartile range 2-41, vs. 3, 2-8; P = 0.045) and a higher frequency of cortical superficial siderosis (34.9% vs. 9.1%; P = 0.025), while patients with Aß- CAA had more lacunes (1, 0-2, vs. 0, 0-1; P = 0.029) and a higher frequency of severe white matter hyperintensities (45.5% vs. 20.9%; P = 0.040). The frequency of ε4 carriers was higher in Aß+ patients (57.1%) than in Aß- patients (18.2%; P = 0.003), while the frequency of ε2 carriers did not differ between the two groups. Finally, Aß positivity was associated with faster decline in multiple cognitive domains including language (P < 0.001), visuospatial function (P < 0.001), and verbal memory (P < 0.001) in linear mixed effects models. CONCLUSION: Our findings suggest that a significant proportion of patients with probable CAA in a memory clinic are Aß- on PET. Aß positivity in CAA patients is associated with a distinct pattern of CSVD biomarker expression, and a worse cognitive trajectory. Aß positivity has clinical relevance in CAA and might represent either advanced CAA or additional Alzheimer's disease neuropathological changes.

Amyloid involvement in subcortical regions predicts cognitive decline.

PURPOSE: We estimated whether amyloid involvement in subcortical regions may predict cognitive impairment, and established an amyloid staging scheme based on degree of subcortical amyloid involvement. METHODS: Data from 240 cognitively normal older individuals, 393 participants with mild cognitive impairment, and 126 participants with Alzheimer disease were acquired at Alzheimer's Disease Neuroimaging Initiative sites. To assess subcortical involvement, we analyzed amyloid deposition in amygdala, putamen, and caudate nucleus. We staged participants into a 3-stage model based on cortical and subcortical amyloid involvement: 382 with no cortical or subcortical involvement as stage 0, 165 with cortical but no subcortical involvement as stage 1, and 203 with both cortical and subcortical involvement as stage 2. RESULTS: Amyloid accumulation was first observed in cortical regions and spread down to the putamen, caudate nucleus, and amygdala. In longitudinal analysis, changes in MMSE, ADAS-cog 13, FDG PET SUVR, and hippocampal volumes were steepest in stage 2 followed by stage 1 then stage 0 (p value <0.001). Stage 2 showed steeper changes in MMSE score (ß [SE] = -0.02 [0.004], p < 0.001), ADAS-cog 13 (0.05 [0.01], p < 0.001), FDG PET SUVR (-0.0008 [0.0003], p = 0.004), and hippocampal volumes (-4.46 [0.65], p < 0.001) compared to stage 1. CONCLUSIONS: We demonstrated a downward spreading pattern of amyloid, suggesting that amyloid accumulates first in neocortex followed by subcortical structures. Furthermore, our new finding suggested that an amyloid staging scheme based on subcortical involvement might reveal how differential regional accumulation of amyloid affects cognitive decline through functional and structural changes of the brain.

Enrichment of infection-associated bacteria in the low biomass brain bacteriota of Alzheimer's disease patients.

Alzheimer's disease (AD) is a neurodegenerative disease accompanied by neuroimmune inflammation in the frontal cortex and hippocampus. Recently, the presence of bacteria in AD-affected brains has been documented, prompting speculation about their potential role in AD-associated neuroinflammation. However, the characterization of bacteriota in human brains affected by AD remains inconclusive. This study aimed to investigate potential associations between specific bacteria and AD pathology by examining brain tissues from AD-associated neurodegenerative regions (frontal cortex and hippocampus) and the non-AD-associated hypothalamus. Employing 16S rRNA gene sequencing, 30 postmortem brain tissue samples from four individuals with normal brain histology (N) and four AD patients were analyzed, along with three blank controls. A remarkably low biomass characterized the brain bacteriota, with their overall structures delineated primarily by brain regions rather than the presence of AD. While most analyzed parameters exhibited no significant distinction in the brain bacteriota between the N and AD groups, the unique detection of Cloacibacterium normanense in the AD-associated neurodegenerative regions stood out. Additionally, infection-associated bacteria, as opposed to periodontal pathogens, were notably enriched in AD brains. This study's findings provide valuable insights into potential link between bacterial infection and neuroinflammation in AD.

Lower-Body Fractures and the Risk of Dementia: A Nationwide Population-Based Study.

BACKGROUND AND PURPOSE: The association between physical activity and dementia has been shown in various observational studies. We aimed to determine the risk of dementia in the elderly with lower-body fractures. METHODS: We reconstructed a population-based matched cohort from the National Health Insurance Service-Senior Cohort data set that covers 511,953 recipients of medical insurance in South Korea. RESULTS: Overall 53,776 subjects with lower-body fractures were identified during 2006-2012, and triplicate control groups were matched randomly by sex, age, and years from the index date for each subject with a fracture. There were 3,573 subjects (6.6%) with and 7,987 subjects (4.9%) without lower-body fractures who developed dementia from 2008 up to 2015. Lower-body fractures were independently associated with a subsequent dementia diagnosis with a higher adjusted hazard ratio (aHR) (1.55, 95% confidence interval [CI]=1.49-1.62) compared with upper-body fractures (aHR=1.19, 95% CI=1.14-1.23). CONCLUSIONS: These results support the protective role of physical activity against dementia and highlight the importance of promoting fracture prevention in the elderly.

The Usefulness of 18F-FDG PET to Differentiate Subtypes of Dementia: The Systematic Review and Meta-Analysis.

Background and Purpose: Dementia subtypes, including Alzheimer's dementia (AD), dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD), pose diagnostic challenges. This review examines the effectiveness of 18F-Fluorodeoxyglucose Positron Emission Tomography (18F-FDG PET) in differentiating these subtypes for precise treatment and management. Methods: A systematic review following Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines was conducted using databases like PubMed and Embase to identify studies on the diagnostic utility of 18F-FDG PET in dementia. The search included studies up to November 16, 2022, focusing on peer-reviewed journals and applying the gold-standard clinical diagnosis for dementia subtypes. Results: From 12,815 articles, 14 were selected for final analysis. For AD versus FTD, the sensitivity was 0.96 (95% confidence interval [CI], 0.88-0.98) and specificity was 0.84 (95% CI, 0.70-0.92). In the case of AD versus DLB, 18F-FDG PET showed a sensitivity of 0.93 (95% CI 0.88-0.98) and specificity of 0.92 (95% CI, 0.70-0.92). Lastly, when differentiating AD from non-AD dementias, the sensitivity was 0.86 (95% CI, 0.80-0.91) and the specificity was 0.88 (95% CI, 0.80-0.91). The studies mostly used case-control designs with visual and quantitative assessments. Conclusions: 18F-FDG PET exhibits high sensitivity and specificity in differentiating dementia subtypes, particularly AD, FTD, and DLB. This method, while not a standalone diagnostic tool, significantly enhances diagnostic accuracy in uncertain cases, complementing clinical assessments and structural imaging.

Dementia Incidence Rate Before and After Implementing the National Responsibility Policy for Dementia Care in Patients With Vascular Risk Factors in Korea.

Background and Purpose: The National Responsibility Policy for Dementia Care was implemented in September 2017 in Korea. This study aimed to compare dementia incidence in Seoul and Gangwon-do before and after the implementation of this policy. Methods: We extracted insurance claim data from the Korean Health Insurance Review and Assessment Service for people diagnosed with diabetes, hypertension, or dyslipidemia for the first time in Seoul and Gangwon-do, Korea. We defined two enrollment groups based on the policy implementation date: 1) January 1, 2015 to December 31, 2016 (Index 1, pre-implementation), and 2) January 1, 2017 to December 31, 2018 (Index 2, post-implementation). Each group was followed up for 1 year from the time of enrollment. Then, we calculated hazard ratios to compare the incidence of dementia between the two groups, and between Seoul and Gangwon-do. Results: In Seoul, the incidence of dementia was significantly lower in Index 2 than in Index 1 (hazard ratio [HR], 0.926; 95% confidence interval [CI], 0.875-0.979). However, the incidence rate did not differ between the 2 groups (HR, 1.113; 95% CI, 0.966-1.281) in Gangwon-do. In Index 1, the incidence of dementia did not differ between Seoul and Gangwon-do (HR, 1.043; 95% CI, 0.941-1.156), but in Index 2, was significantly higher in Gangwon-do than in Seoul (HR, 1.240; 95% CI, 1.109-1.386). Conclusions: After implementing the National Responsibility Policy for Dementia Care, the dementia incidence rate decreased significantly in Seoul, consistent with other studies, but not in Gangwon-do.

Deep learning application for the classification of Alzheimer's disease using 18F-flortaucipir (AV-1451) tau positron emission tomography.

The positron emission tomography (PET) with 18F-flortaucipir can distinguish individuals with mild cognitive impairment (MCI) and Alzheimer's disease (AD) from cognitively unimpaired (CU) individuals. This study aimed to evaluate the utility of 18F-flortaucipir-PET images and multimodal data integration in the differentiation of CU from MCI or AD through DL. We used cross-sectional data (18F-flortaucipir-PET images, demographic and neuropsychological score) from the ADNI. All data for subjects (138 CU, 75 MCI, 63 AD) were acquired at baseline. The 2D convolutional neural network (CNN)-long short-term memory (LSTM) and 3D CNN were conducted. Multimodal learning was conducted by adding the clinical data with imaging data. Transfer learning was performed for classification between CU and MCI. The AUC for AD classification from CU was 0.964 and 0.947 in 2D CNN-LSTM and multimodal learning. The AUC of 3D CNN showed 0.947, and 0.976 in multimodal learning. The AUC for MCI classification from CU had 0.840 and 0.923 in 2D CNN-LSTM and multimodal learning. The AUC of 3D CNN showed 0.845, and 0.850 in multimodal learning. The 18F-flortaucipir PET is effective for the classification of AD stage. Furthermore, the effect of combination images with clinical data increased the performance of AD classification.

Influence of Sensory Impairments on Incidence of Dementia in the Korean Population.

OBJECTIVE: Previous studies have shown the influence of visual and auditory sensory impairment on dementia incidence. In this study, we tested the hypothesis that the incidence of dementia will increase with visual and auditory impairments than with visual or auditory impairment. METHODS: Data from the Korea National Health Insurance Service database were used, including disease and medication codes from 2009 to 2018, and the 2011 national health check-up results. Participants were grouped based on their sensory abilities: normal, visual impairment, auditory impairment, and both visual and auditory impairments (dual sensory impairment). To compare the incidence of dementia, hazard ratios were calculated for each group, with reference to the normal sensory (NS) group. Sensitivity analyses were performed comparing dementia incidence from 2014 to 2018, excluding the onset of the disease in 2012 and 2013. RESULTS: We identified 8,289 cases of dementia during the seven-year follow-up. In the multiple Cox regression analysis, adjusted for sex, social economic status, age, comorbidities, smoking, alcohol consumption, and activity level, the auditory impairment (hazard ratio= 1.1908) and visual impairment (hazard ratio=1.3553) groups showed a significantly higher dementia incidence than the NS group. Dual sensory impairment (hazard ratio=1.5267) showed the highest incidence. The sensitivity analysis yielded similar results. CONCLUSION: Visual and auditory impairments are associated with an increased risk of dementia, particularly in individuals with dual sensory impairment. Hence, visual and auditory impairments might have increased the risk of dementia through independent pathological processes. Therefore, preventing and correcting sensory impairment is necessary to reduce the risk of dementia.

Clinical outcomes of increased focal amyloid uptake in individuals with subthreshold global amyloid levels.

Background: Although the standardized uptake value ratio (SUVR) method is objective and simple, cut-off optimization using global SUVR values may not reflect focal increased uptake in the cerebrum. The present study investigated clinical and neuroimaging characteristics according to focally increased ß-amyloid (Aß) uptake and global Aß status. Methods: We recruited 968 participants with cognitive continuum. All participants underwent neuropsychological tests and 498 18F-florbetaben (FBB) amyloid positron emission tomography (PET) and 470 18F-flutemetamol (FMM) PET. Each PET scan was assessed in 10 regions (left and right frontal, lateral temporal, parietal, cingulate, and striatum) with focal-quantitative SUVR-based cutoff values for each region by using an iterative outlier approach. Results: A total of 62 (6.4%) subjects showed increased focal Aß uptake with subthreshold global Aß status [global (-) and focal (+) Aß group, G(-)F(+) group]. The G(-)F(+) group showed worse performance in memory impairment (p < 0.001), global cognition (p = 0.009), greater hippocampal atrophy (p = 0.045), compared to those in the G(-)F(-). Participants with widespread Aß involvement in the whole region [G(+)] showed worse neuropsychological (p < 0.001) and neuroimaging features (p < 0.001) than those with focal Aß involvement G(-)F(+). Conclusion: Our findings suggest that individuals show distinctive clinical outcomes according to focally increased Aß uptake and global Aß status. Thus, researchers and clinicians should pay more attention to focal increased Aß uptake in addition to global Aß status.