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Background: Given the varying vulnerability of the rostral and caudal regions of the hippocampus to neuropathology in the Alzheimer's disease (AD) continuum, accurately assessing structural changes in these subregions is crucial for early AD detection. The development of reliable and robust automatic segmentation methods for hippocampal subregions (HS) is of utmost importance. Objective: Our aim is to propose and validate a HS segmentation model that is both training‐free and highly generalizable. This method should exhibit comparable accuracy and efficiency to state‐of‐the‐art techniques. The segmented HS can serve as a biomarker for studying the progression of AD. Methods: We utilized the functional magnetic resonance imaging of the Brain's Integrated Registration and Segmentation Tool (FIRST) to segment the entire hippocampus. By intersecting the segmentation results with the Brainnetome (BN) atlas, we obtained coarse segmentation of the four HS regions. This coarse segmentation was then employed as a shape prior term in the lattice Boltzmann (LB) model, as well as for initializing contours. Additionally, image gradients and local gray levels were integrated into the external force terms of the LB model to refine the coarse segmentation results. We assessed the segmentation accuracy of the model using the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset and evaluated the potential of the segmentation results as AD biomarkers on both the ADNI and Xuanwu datasets. Results: The median Dice similarity coefficients (DSC) for the left caudal, right caudal, left rostral, and right rostral hippocampus were 0.87, 0.88, 0.88, and 0.89, respectively. The proportion of segmentation results with a DSC exceeding 0.8 was 77%, 78%, 77%, and 94% for the respective regions. In terms of volume, the correlation coefficients between the segmentation results of the four HS regions and the gold standard were 0.95, 0.93, 0.96, and 0.96, respectively. Regarding asymmetry, the correlation coefficient between the segmentation result's right caudal minus left caudal and the corresponding gold standard was 0.91, while for right rostral minus left rostral, it was 0.93. Over time, we observed a decline in the volumes of the four HS regions and the total hippocampal volume of mild cognitive impairment (MCI) converters. Analysis of inter‐group differences revealed that, except for the right rostral region in the ADNI dataset, the p‐values for the four HS regions in the normal controls (NC), MCI, and AD groups from both datasets were all below 0.05. The right caudal hippocampal volume demonstrated correlation coefficients of 0.47 and 0.43 with the mini‐mental state examination (MMSE) and Montreal cognitive assessment (MoCA), respectively. Similarly, the left rostral hippocampal volume showed correlation coefficients of 0.50 and 0.58 with MMSE and MoCA, respectively. Conclusions: Our framework allows for direct application to different brain magnetic resonance (MR) datasets without the need for training. It eliminates the requirement for complex image preprocessing steps while achieving segmentation accuracy comparable to deep learning (DL) methods even with small sample sizes. Compared to traditional active contour models (ACM) and atlas‐based methods, our approach exhibits significant speed advantages. The segmented HS regions hold promise as potential biomarkers for studying the progression of AD. [ABSTRACT FROM AUTHOR]

Objective: To explore the association between the apolipoprotein E (APOE) genotype and objectively assessed cognitive function. Methods: In this cross-sectional study, 537 participants underwent a neuropsychological assessment for cognitive function and blood testing for APOE genotype. Based on cognitive test results, participants were stratified into two cohorts: Cognitively Unimpaired participants (CU) and Cognitively Impaired participants (CI). The CI group was further divided into Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD). Furthermore, we conducted age stratification, categorizing participants into three age groups: age 1: <65 years, age 2: 65–75 years, and age 3: >75 years. We assessed the disparities in cognitive function associated with ε4 carrier status across different age brackets. Plasma amyloid-β levels were measured in a cohort of 294 participants to investigate potential interactions involving ε4 carrier status, diagnosis, sex, or plasma markers. Results: The APOE genotypic distribution among the 537 participants was characterized as follows: ε2/ε2 (5 participants), ε2/ε3 (67), ε2/ε4 (13), ε3/ε3 (330), ε3/ε4 (113), and ε4/ε4 (9). Allele frequencies were: ε3 at 78.21%, ε4 at 13.41%, and ε2 at 8.38%. Notably, the ε4 carrier frequency was markedly elevated in the AD group at 81.8% when compared to MCI at 32.8% and CU at 21.3% (p < 0.05). Within the Cognitively Unimpaired (CU) cohort, the sole discernible contrast between ε4+ and ε4− emerged in STT-B (p < 0.05). Within the CI group, ε4 carriers showed statistically poorer scores as compared to non-ε4 carriers in several cognitive tests (p < 0.05). Age stratification result revealed that, among ε4 carriers, cognitive function scores within the age 3 group were significantly inferior to those of age 1 and age 2 groups (p < 0.05). Plasma amyloid-β detection was applied to the 294 participants. We tested plasma amyloid-β (Aβ42) and plasma amyloid-β (Aβ40) levels and calculated the Aβ42/Aβ40 ratio. We found that among female ε4 carriers, both Aβ42 and the Aβ42/Aβ40 ratio were notably lower than their male counterparts (p < 0.05). Conclusions: The ε3/ε3 was the most prevalent among participants, succeeded by ε3/ε4 and ε2/ε3. The least prevalent were ε2/ε4, ε4/ε4, and ε2/ε2 genotypes. The ε3 was predominant, followed by the ε4 and ε2. Individuals with the ε4 allele exhibited significant cognitive impairment, with an especially high prevalence in AD group at 81.8%. The study unveils a pronounced correlation between the ε4 allele and cognitive deficits, implying its potential role in the advancement and severity of cognitive disorders, notably Alzheimer's disease. Cognitive function declines with age in individuals carrying the ε4, and women are more affected by ε4. [ABSTRACT FROM AUTHOR]

Background: Developing biomarkers for early stage AD patients is crucial. Glucose metabolism measured by 18F-FDG PET is the most common biomarker for evaluating cellular energy metabolism to diagnose AD. Arterial spin labeling (ASL) MRI can potentially provide comparable diagnostic information to 18F-FDG PET in patients with neurodegenerative disorders. However, the conclusions about the diagnostic performance of AD are still controversial between 18F-FDG PET and ASL. This study aims to compare quantitative cerebral blood flow (CBF) and glucose metabolism measured by 18F-FDG PET diagnostic values in patients with Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI) using integrated PET/MR. Results: Analyses revealed overlapping between decreased regional rCBF and 18F-FDG PET SUVR in patients with AD compared with NC participants in the bilateral parietotemporal regions, frontal cortex, and cingulate cortex. Compared with NC participants, patients with aMCI exclusively demonstrated lower 18F-FDG PET SUVR in the bilateral temporal cortex, insula cortex, and inferior frontal cortex. Comparison of the rCBF in patients with aMCI and NC participants revealed no significant difference (P > 0.05). The ROC analysis of rCBF in the meta-ROI could diagnose patients with AD (AUC, 0.87) but not aMCI (AUC, 0.61). The specificity of diagnosing aMCI has been improved to 75.56% when combining rCBF and 18F-FDG PET SUVR. Conclusion: ASL could detect similar aberrant patterns of abnormalities compared to 18F-FDG PET in patients with AD compared with NC participants but not in aMCI. The diagnostic efficiency of 18F-FDG-PET for AD and aMCI patients remained higher to ASL. Our findings support that applying 18F-FDG PET may be preferable for diagnosing AD and aMCI. Key points: Hypometabolic brain areas are more widespread in patients with AD and aMCI than hypoperfused brain areas. 18F-FDG PET provides superior diagnostic performance over ASL for patients with AD and aMCI. After comprehensive consideration, PET alone is recommended for the diagnosis of AD and aMCI patients. [ABSTRACT FROM AUTHOR]