Search

Background: Patients with early-onset Alzheimer's disease (EOAD) may differ from those with late-onset Alzheimer's disease (LOAD) in cognitive impairment profiles and clinical course. Postmortem studies also reported that EOAD has a greater pathologic burden than LOAD. We examined the effects of age at onset on the burden and distribution of amyloid plaques in patients with AD, using a statistical parametric mapping (SPM) and regions of interest (ROIs) analyses of the Pittsburgh compound B (PiB)-PET. Methods: We initially recruited 72 patients with AD who had completed the [11C] PiB-PET scan, but four patients were excluded due to familial AD or incomplete MRI data. Of the 68 patients, 61 were classified as PiB-positive (PiB+) and seven as PiB-negative (PiB-) using the measured global PiB uptake ratio values. Of the 61 patients with PiB+ AD, in order to maximize the effect of onset age, we excluded 20 patients in their 60 s. Thus among the remaining 41 patients, the amyloid deposition of only 17 patients with EOAD (age onset <60 years) and 24 patients with LOAD (onset age &nvge;70 years) were compared. Results: There were no significant differences in the global mean PiB index between EOAD and LOAD patients, whereas SPM and ROIs analyses showed that those with EOAD retained higher levels of PiB in the bilateral basal ganglia, bilateral thalamus, left superior temporal cortex, and left cuneus compared to those with LOAD. Conclusion: Our findings demonstrated that EOAD patients differed from those with LOAD in the topography of amyloid deposition, which may partly account for the findings from previous studies that extrapyramidal symptoms and frontal dysfunction are more common in EOAD than in LOAD patients. [ABSTRACT FROM AUTHOR]

Abstract: Amnestic mild cognitive impairment (aMCI) can be classified into single domain (S-aMCI) and multiple domain (M-aMCI) subtypes. However, there have been no studies that specifically investigate the structural differences that support this classification. In an attempt to compare regional cortical thickness in two subtypes of aMCI, we aimed to map the distribution of cortical thinning using a surface based cortical analysis of magnetic resonance imaging. The cortical thickness across the entire brain was measured in 9 patients with S-aMCI, 22 patients with M-aMCI, and 61 normal healthy subjects. Differences in the patterns of cortical thinning between S-aMCI and M-aMCI were assessed using ANCOVA on a vertex-by-vertex basis, and statistical maps of differences in cortical thickness between the groups were constructed using a surface model. Relative to controls, S-aMCI patients showed cortical thinning in the left medial temporal lobe, and M-aMCI patients showed cortical thinning in the left medial temporal lobe, precuneus, and anterior and inferior basal temporal, insular, and temporal association cortices. When the two MCI groups were directly compared, M-aMCI patients showed cortical thinning in left precuneus. Our studies suggest that M-aMCI is a transitional state between S-aMCI and Alzheimer''s disease, and that the cortical thinning is evidence that the precuneus is responsible for the multiple cognitive impairments in M-aMCI. [Copyright &y& Elsevier]

Background: The standard Centiloid (CL) method was proposed to harmonize and quantify global 18F-labeled amyloid beta (Aβ) PET ligands using MRI as an anatomical reference. However, there is need for harmonizing and quantifying regional Aβ uptakes between ligands using CT as an anatomical reference. In the present study, we developed and validated a CT-based regional direct comparison of 18F-florbetaben (FBB) and 18F-flutemetamol (FMM) Centiloid (rdcCL). Methods: For development of MRI-based or CT-based rdcCLs, the cohort consisted of 63 subjects (20 young controls (YC) and 18 old controls (OC), and 25 participants with Alzheimer's disease dementia (ADD)). We performed a direct comparison of the FMM-FBB rdcCL method using MRI and CT images to define a common target region and the six regional VOIs of frontal, temporal, parietal, posterior cingulate, occipital, and striatal regions. Global and regional rdcCL scales were compared between MRI-based and CT-based methods. For clinical validation, the cohort consisted of 2245 subjects (627 CN, 933 MCI, and 685 ADD). Results: Both MRI-based and CT-based rdcCL scales showed that FMM and FBB were highly correlated with each other, globally and regionally (R2 = 0.96~0.99). Both FMM and FBB showed that CT-based rdcCL scales were highly correlated with MRI-based rdcCL scales (R2 = 0.97~0.99). Regarding the absolute difference of rdcCLs between FMM and FBB, the CT-based method was not different from the MRI-based method, globally or regionally (p value = 0.07~0.95). In our clinical validation study, the global negative group showed that the regional positive subgroup had worse neuropsychological performance than the regional negative subgroup (p < 0.05). The global positive group also showed that the striatal positive subgroup had worse neuropsychological performance than the striatal negative subgroup (p < 0.05). Conclusions: Our findings suggest that it is feasible to convert regional FMM or FBB rdcSUVR values into rdcCL scales without additional MRI scans. This allows a more easily accessible method for researchers that can be applicable to a variety of different conditions. [ABSTRACT FROM AUTHOR]

Cortical atrophy is measured clinically according to established visual rating scales based on magnetic resonance imaging (MRI). Although brain MRI is the primary imaging marker for neurodegeneration, computed tomography (CT) is also widely used for the early detection and diagnosis of dementia. However, they are seldom investigated. Therefore, we developed a machine learning algorithm for the automatic estimation of cortical atrophy on brain CT. Brain CT images (259 Alzheimer's dementia and 55 cognitively normal subjects) were visually rated by three neurologists and used for training. We constructed an algorithm by combining the convolutional neural network and regularized logistic regression (RLR). Model performance was then compared with that of neurologists, and feature importance was measured. RLR provided fast and reliable automatic estimations of frontal atrophy (75.2% accuracy, 93.6% sensitivity, 67.2% specificity, and 0.87 area under the curve [AUC]), posterior atrophy (79.6% accuracy, 87.2% sensitivity, 75.9% specificity, and 0.88 AUC), right medial temporal atrophy (81.2% accuracy, 84.7% sensitivity, 79.6% specificity, and 0.88 AUC), and left medial temporal atrophy (77.7% accuracy, 91.1% sensitivity, 72.3% specificity, and 0.90 AUC). We concluded that RLR-based automatic estimation of brain CT provided a comprehensive rating of atrophy that can potentially support physicians in real clinical settings. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) and normal pressure hydrocephalus (NPH) commonly coexist.Objective: We aimed to characterize an overlapping syndrome of AD and NPH that presents with gait disturbance, ventriculomegaly on magnetic resonance imaging, and significant amyloid deposition on positron emission tomography (PET).Methods: Of 114 patients who underwent cerebrospinal fluid (CSF) drainage for a possible diagnosis of NPH between 2015 and 2020 in Samsung Medical Center, we identified 24 patients (21.1%) with the NPH patients with amyloid deposition on PET, which we referred to as hydrocephalic AD in this study. We compared their clinical and imaging findings with those of 123 typical AD without hydrocephalic signs/symptoms. We also investigated the frequency and potential predictors of the tap test response in hydrocephalic AD.Results: Evans' index was 0.36±0.03, and a disproportionately enlarged subarachnoid space was present in 54.2% of the hydrocephalic AD patients. The mean age (75.2±7.3 years) and the APOE4 frequency (68.2%) did not differ from those of AD controls. However, the hydrocephalic AD patients showed better memory and language performance, and a thinner cingulate cortex. About 42% of the hydrocephalic AD patients responded to the tap test, of whom seven underwent shunt surgery. Cognition did not improve, whereas gait improved after shunt surgery in all.Conclusion: Hydrocephalic AD has different neuropsychological and imaging characteristics from typical AD. Future studies are warranted to further investigate the effect of CSF removal on their clinical course and to elucidate the pathophysiological interaction between amyloid and NPH. [ABSTRACT FROM AUTHOR]

Background: An association between Helicobacter pylori (H. pylori) infection and dementia was reported in previous studies; however, the evidence is inconsistent.Objective: In the present study, the association between H. pylori infection and brain cortical thickness as a biomarker of neurodegeneration was investigated.Methods: A cross-sectional study of 822 men who underwent a medical health check-up, including an esophagogastroduodenoscopy and 3.0 T magnetic resonance imaging, was performed. H. pylori infection status was assessed based on histology. Multiple linear regression analyses were conducted to evaluate the relationship between H. pylori infection and brain cortical thickness.Results: Men with H. pylori infection exhibited overall brain cortical thinning (p = 0.022), especially in the parietal (p = 0.008) and occipital lobes (p = 0.050) compared with non-infected men after adjusting for age, educational level, alcohol intake, smoking status, and intracranial volume. 3-dimentional topographical analysis showed that H. pylori infected men had cortical thinning in the bilateral lateral temporal, lateral frontal, and right occipital areas compared with non-infected men with the same adjustments (false discovery rate corrected, Q < 0.050). The association remained significant after further adjusting for inflammatory marker (C-reactive protein) and metabolic factors (obesity, dyslipidemia, fasting glucose, and blood pressure).Conclusion: Our results indicate H. pylori infection is associated with neurodegenerative changes in cognitive normal men. H. pylori infection may play a pathophysiologic role in the neurodegeneration and further studies are needed to validate this association. [ABSTRACT FROM AUTHOR]

Brain atrophy is related to vascular risk factors and can increase cognitive dysfunction risk. This community-based, cross-sectional study investigated whether glucose metabolic disorders due to body fatness are linked to regional changes in brain structure and a decline in neuropsychological function in cognitively healthy older adults. From 2016 to 2019, 429 participants underwent measurements for cortical thickness and subcortical volume using 3 T magnetic resonance imaging and for cognitive function using the neuropsychological screening battery. The effects of body fatness mediated by impaired glucose metabolism on neuroimaging markers and cognitive function was investigated using partial least square structural equation modeling. Total grey matter volume (β = −0.020; bias-corrected (BC) 95% confidence interval (CI) = -0.047 to −0.006), frontal (β = −0.029; BC 95% CI = −0.063 to −0.005) and temporal (β = −0.022; BC 95% CI = −0.051 to −0.004) lobe cortical thickness, and hippocampal volume (β = −0.029; BC 95% CI = −0.058 to −0.008) were indirectly related to body fatness. Further, frontal/temporal lobe thinning was associated with recognition memory (β = −0.005; BC 95% CI = −0.012 to −0.001/β = −0.005; BC 95% CI = −0.013 to −0.001) and delayed recall for visual information (β = −0.005; BC 95% CI = −0.013 to −0.001/β = −0.005; BC 95% CI = −0.013 to −0.001). Additionally, the smaller the hippocampal volume, the lower the score in recognition memory (β = −0.005; BC 95% CI = −0.012 to −0.001), delayed recall for visual information (β = −0.005; BC 95% CI = −0.012 to −0.001), and verbal learning (β = −0.008; BC 95% CI = −0.017 to −0.002). Our findings indicate that impaired glucose metabolism caused by excess body fatness affects memory decline as well as regional grey matter atrophy in elderly individuals with no neurological disease. • Partial least squares path modeling was tested among the cognitively intact elderly. • Body fatness is associated with brain atrophy via impaired glucose metabolism (IGM). • Body fatness relates to memory functions via IGM & observed regional atrophy. [ABSTRACT FROM AUTHOR]

Background: As Alzheimer's disease (AD) and cerebral small vessel disease (CSVD) commonly coexist, the interaction between two has been of the considerable interest.Objective: We determined whether the association of Aβ and tau with cognitive decline differs by the presence of significant CSVD.Methods: We included 60 subcortical vascular cognitive impairment (SVCI) from Samsung Medical Center and 82 Alzheimer's disease-related cognitive impairment (ADCI) from ADNI, who underwent Aβ (florbetaben or florbetapir) and tau (flortaucipir, FTP) PET imaging. They were retrospectively assessed for 5.0±3.9 and 5.6±1.9 years with Clinical Dementia Rating-sum of boxes (CDR-SB)/Mini-Mental State Examination (MMSE). Mixed effects models were used to investigate the interaction between Aβ/tau and group on CDR-SB/MMSE changes.Results: The frequency of Aβ positivity (45% versus 54.9%, p = 0.556) and mean global FTP SUVR (1.17±0.21 versus 1.16±0.17, p = 0.702) were not different between the two groups. We found a significant interaction effect of Aβ positivity and SVCI group on CDR-SB increase/MMSE decrease (p = 0.013/p < 0.001), and a significant interaction effect of global FTP uptake and SVCI group on CDR-SB increase/MMSE decrease (p < 0.001 and p = 0.030). Finally, the interaction effects of regional tau and group were prominent in the Braak III/IV (p = 0.001) and V/VI (p = 0.003) not in Braak I/II region (p = 0.398).Conclusion: The association between Aβ/tau and cognitive decline is stronger in SVCI than in ADCI. Therefore, our findings suggested that Aβ positivity or tau burden (particularly in the Braak III/IV or V/VI regions) and CSVD might synergistically affect cognitive decline. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Cerebral cortical thickness is a neuroimaging biomarker to predict cognitive decline, and kidney dysfunction (KD) is associated with cortical thinning.Objective: This study aimed to investigate the effects of KD and cortical thinning on cognitive change in a prospective cohort study.Methods: A total of 244 non-demented participants were recruited from elderly health checkup program and received cognitive exams including Montreal Cognitive Assessment (MoCA) and different cognitive domains at baseline and three biannual follow-ups afterwards. KD was defined as having either glomerular filtration rate <60 ml/min/1.73 m2 or proteinuria. Cortical thickness of global, lobar, and Alzheimer's disease (AD) signature area were derived from magnetic resonance imaging at baseline, and cortical thinning was defined as the lowest tertile of cortical thickness. Generalized linear mixed models were applied to evaluate the effects of KD and cortical thinning on cognitive changes.Results: KD was significantly associated with the decline in attention function (β= -0.29). Thinning of global (β= -0.06), AD signature area (β= -0.06), temporal (β= -0.06), and parietal lobes (β= -0.06) predicted poor verbal fluency over time, while temporal lobe thinning also predicted poor MoCA score (β= -0.19). KD modified the relationship between thinning of global, frontal, and limbic, and change of logical memory function (pinteraction < 0.05). When considering jointly, participants with both KD and cortical thinning had greatest decline in attention function compared with those without KD or cortical thinning (β= -0.51, ptrend = 0.008).Conclusions: KD and cortical thinning have joint effect on cognitive decline, especially the attention function. Reverse associations may exist between cortical thinning and memory function in participants with KD, though the results should be interpreted cautiously as an exploratory analysis. [ABSTRACT FROM AUTHOR]

Background: The retina and the brain share anatomic, embryologic, and physiologic characteristics. Therefore, retinal imaging in patients with brain disorders has been of significant interest. Using optical coherence tomography angiography (OCTA), a novel quantitative method of measuring retinal vasculature, we aimed to evaluate radial peripapillary capillary (RPC) network density and retinal nerve fiber layer (RNFL) thickness in cognitively impaired patients and determine their association with brain imaging markers. Methods: In this prospective cross-sectional study, a total of 69 patients (138 eyes) including 29 patients with amyloid-positive Alzheimer's disease-related cognitive impairment (ADCI), 25 patients with subcortical vascular cognitive impairment (SVCI), and 15 amyloid-negative cognitively normal (CN) subjects were enrolled. After excluding eyes with an ophthalmologic disease or poor image quality, 117 eyes of 60 subjects were included in the final analyses. Retinal vascular [capillary density (CD) of the radial peripapillary capillary (RPC) network] and neurodegeneration markers [retinal nerve fiber layer (RNFL) thickness at four quadrants] were measured using OCTA and OCT imaging. Brain vascular (CSVD score) and neurodegeneration markers (cortical thickness) were assessed using 3D brain magnetic resonance imaging. The CD and RNFL thickness and their correlation with brain imaging markers were investigated. Results: The SVCI group showed lower CD in the temporal quadrant of the RPC network compared to the CN group (mean (SD), 42.34 (6.29) vs 48.45 (7.08); p = 0.001). When compared to the ADCI group, the SVCI showed lower CD in the superior quadrant (mean (SD), 60.14 (6.42) vs 64.15 (6.39); p = 0. 033) as well as in the temporal quadrant (ADCI 45.76, SVCI 42.34; p = 0.048) of the RPC network. The CD was negatively correlated with CSVD score in the superior (B (95%CI), − 0.059 (− 0.097 to − 0.021); p = 0.003) and temporal (B (95%CI), − 0.048 (− 0.080 to − 0.017); p = 0.003) quadrants of the RPC network. RNFL thickness did not differ among the groups nor did it correlate with cortical thickness. Conclusions and relevance: The microvasculature of the RPC network was related to the CSVD burden. However, the RNFL thickness did not reflect cerebral neurodegeneration. Noninvasive and rapid acquisition of the OCTA image might have the potential to be used as a screening tool to detect CSVD. [ABSTRACT FROM AUTHOR]

Objective: This study investigated the association between small vessel disease (SVD) burden, a combination of multiple SVD markers and cognitive dysfunction after stroke.Methods: The study sample comprised 451 patients with first-ever acute ischemic stroke. Cognitive functions were assessed with the Mini-Mental State Examination (MMSE) at 3, 9, and 15 months after the index stroke. Cognitive impairment was defined as an MMSE score of ≤26. A total SVD score, indicating SVD burden, was constructed by summing the scores of the 4 SVD markers (white matter hyperintensities [WMHs], lacunes, cerebral microbleeds, and perivascular spaces) ascertained by magnetic resonance imaging (range: 0-4). The association between SVD burden and cognitive dysfunction was assessed with linear mixed models or generalized estimating equation models, as appropriate.Results: The majority of patients had mild-to-moderate stroke and at least one identifiable SVD marker. Cognitive impairment was found in about one-third of patients. After adjusting for confounding factors, the SVD burden was associated with MMSE scores (β = -0.37, P = .003) and cognitive impairment (odds ratio [OR] = 1.20, 95% confidence interval [CI] = 1.02-1.42). SVD burden was specifically associated with the performance of MMSE subscores including orientation to place and time, calculation, and word recall. Of the SVD markers, WMHs was the most robust predictor of decrease in MMSE scores (β = -0.25, P = .01) and cognitive impairment (OR = 1.14, 95% CI = 1.01-1.29).Conclusion: Cerebral SVD burden is associated with decreased MMSE scores, suggesting cognitive dysfunction during the first year after mild-to-moderate acute ischemic stroke. [ABSTRACT FROM AUTHOR]

Purpose: We investigated the frequency and clinical significance of amyloid β (Aβ) 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 Aβ positivity and investigated the effect of Aβ positivity on longitudinal cognitive decline. Results: Among the 65 CAA patients, 43 (66.2%) showed Aβ PET positivity (Aβ+). Patients with Aβ+ 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 Aβ− 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 Aβ+ patients (57.1%) than in Aβ− patients (18.2%; P = 0.003), while the frequency of ε2 carriers did not differ between the two groups. Finally, Aβ 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 Aβ− on PET. Aβ positivity in CAA patients is associated with a distinct pattern of CSVD biomarker expression, and a worse cognitive trajectory. Aβ positivity has clinical relevance in CAA and might represent either advanced CAA or additional Alzheimer's disease neuropathological changes. [ABSTRACT FROM AUTHOR]

Abstract We analyzed 18F-flortaucipir uptake patterns and structural changes in patients with subtypes of primary progressive aphasia (PPA) using 18F-flortaucipir positron emission tomography and volumetric magnetic resonance imaging. We enrolled 34 consecutive patients with PPA (10 nonfluent/agrammatic PPA [nfvPPA], 18 semantic variant PPA [svPPA], and 6 logopenic variant PPA [lvPPA], as well as 20 healthy controls, and 20 patients with Alzheimer's disease. 18F-flortaucipir uptake was increased in the frontal cortex and underlying white matter, and subcortical nuclei in the 10 nfvPPA and 8 nfvPPA-amyloid-β (Aβ)− subgroup patients. In the svPPA patients (both the 13 svPPA-Aβ− and 5 svPPA-Aβ+), uptake generally increased in the widespread neocortex with left anterior temporal predominance. 18F-flortaucipir uptake patterns in the 6 lvPPA and the 5 lvPPA-Aβ+ subgroup patients were similar to those seen in the patients with Alzheimer's disease with mild predominance in the left lateral temporal cortex. Cortical thinning in each PPA subtype corresponded with increased 18F-flortaucipir uptake. 18F-flortaucipir uptake patterns and cortical atrophy were distinct and corresponded to areas related to the specific language functions that are impaired in each subtype of PPA. Highlights • We compared 18F-flortaucipir uptake and structural changes in PPA subtypes. • Increased 18F-flortaucipir uptake corresponds to areas related to language functions. • Cortical thinning in each PPA subtype corresponded to increased 18F-flortaucipir uptake. • 18F-flortaucipir uptake and cortical atrophy were distinct in each subtype of PPA. [ABSTRACT FROM AUTHOR]

Background/objective: In this study, we investigated a long-term trajectory of brain aging (from the 20 s to over-80) in cognitively normal (CN) individuals. We further determined whether differences in sex, education years, and apolipoprotein E ε 4 status affect age-related cortical thinning.Methods: A total of 2,944 CN individuals who underwent high-resolution (3.0-Tesla) magnetic resonance imaging were included in this study. Cortical thickness was measured using a surface-based method. Multiple linear regression analyses were performed to evaluate age-related cortical thinning and related factors.Results: Compared to those in their 20 s/30 s, participants in their 40 s showed thinning primarily in the medial and lateral frontal and inferior parietal regions, and cortical thinning occurred across most of the cortices with increasing age. Notably, the precuneus, inferior temporal and lateral occipital regions were relatively spared until later in life. Male and lower education years were associated with greater cortical thinning with distinct regional specificity.Conclusion: Our findings provide an important clue to understanding the mechanism of age-related cognitive decline and new strategies for preventing the acceleration of pathological brain aging. [ABSTRACT FROM AUTHOR]

Background: Sex effects on the progression of Alzheimer's disease (AD) have received less attention than other demographic factors, including onset age and education.Objective: The aim of this study was to investigate whether sex affected cortical thinning in the disease progression of AD.Methods: We prospectively recruited 36 patients with early-stage AD and 14 people with normal cognition. All subjects were assessed with magnetic resonance imaging at baseline, Year 1, Year 3, and Year 5. We performed cortical thickness analyses using surface-based morphometry on magnetic resonance imaging.Results: Women with AD showed more rapid cortical thinning in the left dorsolateral frontal cortex, left superior temporal gyrus, bilateral temporo-parietal association cortices, bilateral anterior cingulate gyri, bilateral medial frontal cortices, and bilateral occipital cortices over 5 years than men with AD, even though there was no difference in cortical thickness at baseline. In contrast, there were no regions of significantly more rapid atrophy in men with AD.Conclusions: Our findings suggest that women deteriorate faster than men in the progression of AD. [ABSTRACT FROM AUTHOR]

Background: Recent evidence suggests that combining individual imaging markers of cerebral small vessel disease (SVD) may more accurately reflect its overall burden and better correlate with clinical measures.Objective: We wished to establish the clinical relevance of the total SVD score in a memory clinic population by investigating the association with SVD score and cognitive performance, cortical atrophy, and structural network measures, after adjusting for amyloid-β burden.Methods: We included 243 patients with amnestic mild cognitive impairment (MCI), Alzheimer's disease dementia, subcortical vascular MCI, or subcortical vascular dementia. All underwent MR and [11C] PiB-PET scanning and had standardized cognitive testing. Multiple linear regression was used to evaluate the relationships between SVD score and cognition, cortical thickness, and structural network measures. Path analyses were performed to evaluate whether network disruption mediates the effects of SVD score on cortical thickness and cognition.Results: Total SVD score was associated with the performance of frontal (β - 4.31, SE 2.09, p = 0.040) and visuospatial (β - 0.95, SE 0.44, p = 0.032) tasks, and with reduced cortical thickness in widespread brain regions. Total SVD score was negatively correlated with nodal efficiency, as well as changes in brain network organization, with evidence of reduced integration and increasing segregation. Path analyses showed that the associations between SVD score and frontal and visuospatial scores were partially mediated by decreases in their corresponding nodal efficiency and cortical thickness.Conclusion: Total SVD burden has clinical relevance in a memory clinic population and correlates with cognition, and cortical atrophy, as well as structural network disruption. [ABSTRACT FROM AUTHOR]

Recent advances in neuroimaging technology have shown that rich club organization in human brain networks plays a crucial role in global communication and cognitive functionality. In this study, we investigated rich club organization within white matter structural brain networks in two common types of dementia, Alzheimer's disease (AD) and subcortical vascular dementia (SVaD). We recruited 30 AD patients ([11C] Pittsburgh compound-B (PiB) PET positive), 39 SVaD patients (PiB negative), and 72 age-, gender-, and education-matched cognitively normal (CN) subjects. Rich club organization was significantly disrupted in both dementia patient groups, which exhibited higher rich club coefficients than the CN group. Rich club organization in the patient groups was primarily disrupted over the left frontal and left middle temporal areas when compared to the CN group. The number of rich club nodes was significantly reduced in the dementia groups, which was more severe in SVaD (p = 0.0107, permutation-based t-test). Although rich club organization was disrupted both in the patient groups, its disruption pattern is different between them. The rich-club connections normalized by degree-and-strength preserved random networks were significantly increased in the dementia groups with SVaD more severely, and feeder connections were reduced more significantly than in AD. Furthermore, SVaD patients exhibited more sporadic disruption in white matter connectivity than AD patients, with local connections showing a more significant degree of deterioration. Combined with the distinct disruption in rich club nodes, these findings may imply a differing role for rich club organization in AD and SVaD, due to different pathological mechanisms. [ABSTRACT FROM AUTHOR]

The authors discuss a study as part of the Clinical Research Center for Dementia of South Korea Study (CREDOS) to assess the occurrence of and risk factors for cognitive disorders, including age, chronic kidney disease, and anemia, that found a lower glomerular filtration rate (GFR) was associated with white matter hyperintensities (WMHs) in vascular dementia (VaD) more than in Alzheimer's disease (AD) or mild cognitive impairment (MCI). A discussion of the results is presented.

Parcellation of the human cortex has important implications in neuroscience. Parcellation is often a crucial requirement before meaningful regional analysis can occur. The human cortex can be parcellated into distinct regions based on structural features, such as gyri and sulci. Brain network patterns in a given region with respect to its neighbors, known as connectional fingerprints, can be used to parcellate the cortex. Distinct imaging modalities might provide complementary information for brain parcellation. Here, we established functional connectivity with time series data from functional MRI (fMRI) combined with a correlation map of cortical thickness obtained from T1-weighted MRI. We aimed to extend the previous study, which parcellated the medial frontal cortex (MFC) using functional connectivity, and to test the value of additional information regarding cortical thickness. Two types of network information were used to parcellate the MFC into two sub-regions with spectral and Ward’s clustering approaches. The MFC region was defined using manual delineation based on in-house data (n = 12). Parcellation was applied to independent large-scale data obtained from the Human Connectome Project (HCP, n = 248). Agreement between parcellation using fMRI- and thickness-driven connectivity yielded dice coefficient overlaps of 0.74 (Ward’s clustering) and 0.54 (spectral clustering). We also explored whole brain connectivity using the MFC sub-regions as seed regions based on these two types of information. The results of whole brain connectivity analyses were also consistent for both types of information. We observed that an inter-regional correlation map derived from cortical thickness strongly reflected the underlying functional connectivity of MFC region. [ABSTRACT FROM AUTHOR]

Recently, we reported that earlier stages of Alzheimer's disease (AD) can be categorized into 3 following anatomical subtypes using a hierarchical cluster analysis of cortical thickness across the entire brain: medial temporal-dominant (MT), parietal-dominant (P), and diffuse atrophy (D). The goal of this study was to investigate the rates of cognitive decline in these anatomical subtypes. Of the patients included in the prior study, 100 AD patients (MT, n = 36; P, n = 20; D, n = 44) who underwent follow-up neuropsychological assessments over a 3-year period were included. A linear mixed model analysis was performed to compare the longitudinal changes in neuropsychological test scores. The P subtype exhibited the most rapid cognitive decline in attention, language, visuospatial, memory, and frontal executive function, whereas MT and D subtypes did not differ in their longitudinal decline. When repeating the analyses with early-onset AD, which is known to progress faster than late-onset AD, only the P subtype showed such rapid progression. The P subtype appears to be a unique subtype of AD characterized by an aggressive rate of progression. [ABSTRACT FROM AUTHOR]

Background We compared the validity of models of subcortical ischemic depression (SID) and depression-executive dysfunction syndrome (DED) in predicting functional disability in the elderly. Methods We obtained data from elderly Korean subjects (n = 1356) aged 60 years or older at baseline from the CREDOS study from November 2005 to July 2014. A generalized estimating equation (GEE) model was constructed to measure functional disability using instrumental activity of daily living as a primary outcome. A risk factor of interest was SID and DED evaluated by a visual rating scale of deep white matter hyperintensity in MRI, Stroop test and Geriatric Depression Scale (GDS) score. Receiver-operating-characteristic plots and area under the curve (AUC) test were applied to examine the difference of the two definitions of vascular depression with predicted values of functional disability outcome. Results The mean (SD) follow-up duration of the participants was 1.7 (0.9) years. The GEE model showed that presence of SID at baseline predicted functional disability compared to non-depressed subjects (GDS score: Odds ratio [OR] 1.76; 95% CI 1.23, 2.53; p = 0.002). The association was also statistically significant among the DED group (OR 1.48; 95% CI 1.15, 1.92; p = 0.003). There were no significant differences in predicting functional disability (95% CI: −0.003 to 0.009, p = 0.366) according to AUC differences between SID and DED. Conclusions The results will be useful in evaluating the cardinal features of the vascular depression hypothesis in predicting functional disability. [ABSTRACT FROM AUTHOR]

Recent studies of functional connectivity MR imaging have revealed that the default-mode network activity is disrupted in diseases such as Alzheimer's disease (AD). However, there is not yet a consensus on the preferred method for resting-state analysis. Because the brain is reported to have complex interconnected networks according to graph theoretical analysis, the independency assumption, as in the popular independent component analysis (ICA) approach, often does not hold. Here, rather than using the independency assumption, we present a new statistical parameter mapping (SPM)-type analysis method based on a sparse graph model where temporal dynamics at each voxel position are described as a sparse combination of global brain dynamics. In particular, a new concept of a spatially adaptive design matrix has been proposed to represent local connectivity that shares the same temporal dynamics. If we further assume that local network structures within a group are similar, the estimation problem of global and local dynamics can be solved using sparse dictionary learning for the concatenated temporal data across subjects. Moreover, under the homoscedasticity variance assumption across subjects and groups that is often used in SPM analysis, the aforementioned individual and group analyses using sparse dictionary learning can be accurately modeled by a mixed-effect model, which also facilitates a standard SPM-type group-level inference using summary statistics. Using an extensive resting fMRI data set obtained from normal, mild cognitive impairment (MCI), and Alzheimer's disease patient groups, we demonstrated that the changes in the default mode network extracted by the proposed method are more closely correlated with the progression of Alzheimer's disease. [ABSTRACT FROM AUTHOR]

Background: We aimed to examine differential effects of WMH on progression of depressive symptoms according to APOE ε4 status in the elderly.Methods: We obtained data from elderly Korean subjects (n=707) aged 60 years or older at baseline from the CREDOS study from November 2005 to July 2014. A linear mixed model stratified according to APOE genotype (APOE ε4 carrier vs. non-carrier) was constructed using GDS score as a primary outcome and degree of overall, deep, periventricular WMH evaluated by a visual rating scale as a risk factor of interest. We also tested interaction between APOE ε4, WMH and time as predictors of clinical progression on GDS scores to examine the moderating effect of APOE ε4 allele on the relationship between degree of WMH and progression of geriatric depressive symptoms.Results: The mean (SD) follow-up duration of the participants was 2.0 (0.8) years. Among APOE ε4 carriers, a severe degree of overall and deep WMH, but not periventricular WMH, predicted progression of geriatric depressive symptoms (overall WMH: coefficient=0.96, p=0.010; deep WMH: 0.87, p=0.016). There were significant interaction between APOE ε4, degree of WMH and time in predicting GDS increase (5df, F=2.28, p=0.046).Limitations: Only subjects seeking medical attention and with follow-up measurements were enrolled in this study. Specific location of WMH and use of antidepressant were uncontrolled.Conclusions: Considering biological markers such as degree of WMH and APOE ε4 status may be clinically relevant to predicting progression of geriatric depressive symptoms. [ABSTRACT FROM AUTHOR]

Resting-state functional magnetic resonance imaging (RS FMRI) has been widely used to analyze functional alterations in amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) patients. Although many clinical studies of aMCI and AD patients using RS FMRI have been undertaken, conducting a meta-analysis has not been easy because of seed selection bias by the investigators. The purpose of our study was to investigate the functional differences in aMCI and AD patients compared with healthy subjects in a meta-analysis. Thus, a multimethod approach using regional homogeneity, amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and global brain connectivity was used to investigate differences between three groups based on previously published data. According to the choice of RS FMRI approach used, the patterns of functional alteration were slightly different. Nevertheless, patients with aMCI and AD displayed consistently decreased functional characteristics with all approaches. All approaches showed that the functional characteristics in the left parahippocampal gyrus were decreased in AD patients compared with healthy subjects. Although some regions were slightly different according to the different RS FMRI approaches, patients with aMCI and AD showed a consistent pattern of decreased functional characteristics with all approaches. [ABSTRACT FROM AUTHOR]

The hippocampus has been known to be an important structure as a biomarker for Alzheimer’s disease (AD) and other neurological and psychiatric diseases. However, it requires accurate, robust and reproducible delineation of hippocampal structures. In this study, an automated hippocampal segmentation method based on a graph-cuts algorithm combined with atlas-based segmentation and morphological opening was proposed. First of all, the atlas-based segmentation was applied to define initial hippocampal region for a priori information on graph-cuts. The definition of initial seeds was further elaborated by incorporating estimation of partial volume probabilities at each voxel. Finally, morphological opening was applied to reduce false positive of the result processed by graph-cuts. In the experiments with twenty-seven healthy normal subjects, the proposed method showed more reliable results (similarity index=0.81±0.03) than the conventional atlas-based segmentation method (0.72±0.04). Also as for segmentation accuracy which is measured in terms of the ratios of false positive and false negative, the proposed method (precision=0.76±0.04, recall=0.86±0.05) produced lower ratios than the conventional methods (0.73±0.05, 0.72±0.06) demonstrating its plausibility for accurate, robust and reliable segmentation of hippocampus. [ABSTRACT FROM AUTHOR]

Abstract: Prior studies have shown that patients with AD have decreased functional or structural connectivity between the hippocampus and other brain areas. To the best of our knowledge, however, there have been no studies investigating the topography of cortical thinning areas and correlations with HA using surface based morphometry of three-dimensional (3D) T1-weighted magnetic resonance (MR) images. Cortical thickness was measured using SBM, and hippocampal volume was measured using an automated method, in 219 patients with AD and 54 subjects with no cognitive impairment (NCI). A partial correlation model was used in analysis of cortical thinning related to HA. Cortical thinning areas related to HA were found mostly within areas associated with polysynaptic or direct pathways of the hippocampus, a finding consistent with the disconnection hypothesis. Therefore, the cortical atrophy related to HA in patients with AD may represent disrupted cortical brain networks in connection with HA. However, since the topography of HA-related cortical thinning in groups with Clinical Dementia Ratings (CDR) of 0.5 and 1 corresponded to the stages I–II and III–IV of Braak and Braak staging, respectively, we could not exclude the possibility of the “concomitant hypothesis,” i.e. that these areas are affected concomitantly with the hippocampus. [Copyright &y& Elsevier]

ABSTRACT BACKGROUND AND PURPOSE Patients with small vessel disease show high-signal intensity on T2-weighted magnetic resonance (MR) images that represent ischemic cell damage. However, despite a similar degree of ischemic change, the amount and the severity of clinical presentations may vary. We investigated the clinical correlations of ischemic changes using voxel-based morphometric analyses of diffusion tensor imaging (DTI). METHODS Twenty-seven MCI and 34 dementia patients were included who all had significant small vessel disease on magnetic resonance imaging (MRI). In all patients, neuropsychological tests, a rating on the Pyramidal and Extrapyramidal scale (PEPS) for motor deficits, and 3-Tesla MRI including DTI scans were performed. Voxel-based analysis of the fractional anisotropy and mean diffusivity maps were computed. RESULTS Cognitive scores correlated with the DTI abnormalities in supratentorial areas with regional specificity according to each cognitive test. Unexpectedly, cognitive deficits in most neuropsychological tests, even in some frontal tasks, were associated with disruption of posterior white matter integrities. Motor deficits correlated with both supra- and infratentorial lesions. CONCLUSION Our findings suggest that in patients with small vessel disease who show cognitive and motor impairments, a specific distribution of fiber tract damage is more related with clinical deficits than is the severity of the total ischemia. [ABSTRACT FROM AUTHOR]

Background: White matter hyperintensities (WMH) increase cognitive impairment in patients with dementia. Objective: We investigated the impact of WMH on the neuropsychological profiles in patients with mild to moderate dementia. Methods: We consecutively recruited newly diagnosed patients with mild to moderate dementia across South Korea for 1 year. The participants completed neuropsychological tests, magnetic resonance imaging, and structured neurological evaluations. The patients were divided into 3 categories, i.e. minimal, moderate, and severe WMH groups, according to the proportional degree of WMH. Results: 289 patients were recruited; 140 (48.3%) for the minimal WMH group, 99 (34.2%) for the moderate group, and 50 (17.5%) for the severe group. Both advanced age and low general cognitive level were significant contributors to WMH in patients with dementia. After adjusting for age, the neuropsychological correlates of the proportional impact of WMH were frontal executive, language, and attention profiles. However, the only significant neuropsychological correlate was the recognition memory profile after adjusting for both age and general cognitive level simultaneously. Conclusion: The results suggest that the most significant neuropsychological profile impacting the burden of WMH in patients with mild to moderate dementia was the recognition memory profile, regardless of age and general cognitive function. Copyright © 2011 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

The general population is exposed to numerous environmental pollutants, and it remains unclear which pollutants affect the brain, accelerating brain aging and increasing the risk of dementia. The Environmental-Pollution-Induced Neurological Effects study is a multi-city prospective cohort study aiming to comprehensively investigate the effect of different environmental pollutants on brain structures, neuropsychological function, and the development of dementia in adults. The baseline data of 3,775 healthy elderly people were collected from August 2014 to March 2018. The eligibility criteria were age ≥50 years and no self-reported history of dementia, movement disorders, or stroke. The assessment included demographics and anthropometrics, laboratory test results, and individual levels of exposure to air pollution. A neuroimaging sub-cohort was also recruited with 1,022 participants during the same period, and brain magnetic resonance imaging and neuropsychological tests were conducted. The first follow-up environmental pollutant measurements will start in 2022 and the follow-up for the sub-cohort will be conducted every 3-4 years. We have found that subtle structural changes in the brain may be induced by exposure to airborne pollutants such as particulate matter 10 μm or less in diameter (PM10), particulate matter 2.5 μm or less in diameter (PM2.5) and Mn10, manganese in PM10; Mn2.5, manganese in PM2.5. PM10, PM2.5, and nitrogen dioxide in healthy adults. This study provides a basis for research involving large-scale, long-term neuroimaging assessments in community-based populations. [ABSTRACT FROM AUTHOR]

Although Alzheimer's disease (AD) is the most common neurodegenerative disease, there are still no drugs available to treat or prevent AD effectively. Here, we examined changes in levels of selected proteins implicated in the pathogenesis of AD using plasma samples of control subjects and patients with cognition impairment. To precisely categorize the disease, fifty-six participants were examined with clinical cognitive tests, amyloid positron emission tomography (PET) scan, and white matter hyperintensities scored by magnetic resonance imaging. Plasma cathepsin D levels of the subjects were examined by immunoblotting and enzyme-linked immunosorbent assay (ELISA). Correlation of plasma cathepsin D levels with AD-related factors and clinical characteristics were examined by statistical analysis. By analyzing quantitative immunoblot and ELISA, we found that the plasma level of cathepsin D, a major lysosomal protease, was decreased in the group with amyloid plaque deposition at the brain compared to the control group. The level of plasma cathepsin D was negatively correlated with clinical dementia rating scale sum of boxes (CDR-SB) scores. In addition, our integrated multivariable logistic regression model suggests the high performance of plasma cathepsin D level for discriminating AD from non-AD. These results suggest that the plasma cathepsin D level could be developed as a diagnostic biomarker candidate for AD. [ABSTRACT FROM AUTHOR]

Amyloid-β(Aβ) PET positivity in patients with suspected cerebral amyloid angiopathy (CAA) MRI markers is predictive of a worse cognitive trajectory, and it provides insights into the underlying vascular pathology (CAA vs. hypertensive angiopathy) to facilitate prognostic prediction and appropriate treatment decisions. In this study, we applied two interpretable machine learning algorithms, gradient boosting machine (GBM) and random forest (RF), to predict Aβ PET positivity in patients with CAA MRI markers. In the GBM algorithm, the number of lobar cerebral microbleeds (CMBs), deep CMBs, lacunes, CMBs in dentate nuclei, and age were ranked as the most influential to predict Aβ positivity. In the RF algorithm, the absence of diabetes was additionally chosen. Cut-off values of the above variables predictive of Aβ positivity were as follows: (1) the number of lobar CMBs > 16.4(GBM)/14.3(RF), (2) no deep CMBs(GBM/RF), (3) the number of lacunes > 7.4(GBM/RF), (4) age > 74.3(GBM)/64(RF), (5) no CMBs in dentate nucleus(GBM/RF). The classification performances based on the area under the receiver operating characteristic curve were 0.83 in GBM and 0.80 in RF. Our study demonstrates the utility of interpretable machine learning in the clinical setting by quantifying the relative importance and cutoff values of predictive variables for Aβ positivity in patients with suspected CAA markers. [ABSTRACT FROM AUTHOR]

White matter hyperintensity (WMH) has been recognised as a surrogate marker of small vessel disease and is associated with cognitive impairment. We investigated the dynamic change in WMH in patients with severe WMH at baseline, and the effects of longitudinal change of WMH volume on cognitive decline and cortical thinning. Eighty-seven patients with subcortical vascular mild cognitive impairment were prospectively recruited from a single referral centre. All of the patients were followed up with annual neuropsychological tests and 3T brain magnetic resonance imaging. The WMH volume was quantified using an automated method and the cortical thickness was measured using surface-based methods. Participants were classified into WMH progression and WMH regression groups based on the delta WMH volume between the baseline and the last follow-up. To investigate the effects of longitudinal change in WMH volume on cognitive decline and cortical thinning, a linear mixed effects model was used. Seventy patients showed WMH progression and 17 showed WMH regression over a three-year period. The WMH progression group showed more rapid cortical thinning in widespread regions compared with the WMH regression group. However, the rate of cognitive decline in language, visuospatial function, memory and executive function, and general cognitive function was not different between the two groups. The results of this study indicated that WMH volume changes are dynamic and WMH progression is associated with more rapid cortical thinning. [ABSTRACT FROM AUTHOR]

Background: Although amnestic mild cognitive impairment (aMCI) is generally considered to be a prodromal stage of Alzheimer's disease, patients with aMCI show heterogeneous patterns of progression. Moreover, there are few studies investigating data-driven cognitive trajectory in aMCI. We therefore classified patients with aMCI based on their cognitive trajectory, measured by clinical dementia rating sum of boxes (CDR-SOB). Then, we compared the clinical and neuroimaging features among groups classified by cognitive trajectory. Methods: We retrospectively recruited 278 patients with aMCI who underwent three or more timepoints of neuropsychological testing. They also had magnetic resonance imaging (MRI) including structured three-dimensional volume images. Cortical thickness was measured using surface-based methods. We performed trajectory analyses to classify our aMCI patients according to their progression and investigate their cognitive trajectory using CDR-SOB. Results: Trajectory analyses showed that patients with aMCI were divided into three groups: stable (61.8%), slow decliner (31.7%), and fast decliner (6.5%). Changes throughout a mean follow-up duration of 3.7 years in the CDR-SOB for the subgroups of stable/slow/fast decliners were 1.3-, 6.4-, and 12-point increases, respectively. Decliners were older and carried apolipoprotein E4 (APOE4) genotypes more frequently than stable patients. Compared with the stable group, decliners showed a higher frequency of aMCI patients with both visual and verbal memory dysfunction, late stage aMCI, and multiple domain dysfunction. In addition, compared with the stable group, the slow decliners showed cortical thinning predominantly in bilateral parietotemporal areas, while the fast decliners showed cortical thinning predominantly in bilateral frontotemporal areas. Both decliner groups showed worse cognitive function in attention, language, visuospatial, memory, and frontal/executive domains than the stable group. Conclusions: Our data-driven trajectory analysis provides new insights into heterogeneous cognitive trajectories of aMCI and further suggests that baseline clinical and neuroimaging profiles might predict aMCI patients with poor prognosis. [ABSTRACT FROM AUTHOR]

Abstract: Early-onset Alzheimer''s disease (EOAD) has been shown to progress more rapidly than late-onset Alzheimer''s disease (LOAD). However, no studies have compared the topography of brain volume reduction over time. The purpose of this 3-year longitudinal study was to compare EOAD and LOAD in terms of their rates of decline in cognitive testing and topography of cortical thinning. We prospectively recruited 36 patients with AD (14 EOAD and 22 LOAD) and 14 normal controls. All subjects were assessed with neuropsychological tests and with magnetic resonance imaging at baseline, Year 1, and Year 3. The EOAD group showed more rapid decline than the LOAD group in attention, language, and frontal-executive tests. The EOAD group also showed more rapid cortical thinning in widespread association cortices. In contrast, the LOAD group presented more rapid cortical thinning than the EOAD group only in the left parahippocampal gyrus. Our study suggests that patients with EOAD show more rapid cortical atrophy than patients with LOAD, which accounts for faster cognitive decline on neuropsychological tests. [Copyright &y& Elsevier]