Distinct Atrophy Pattern of Hippocampal Subfields in Patients with Progressive and Stable Mild Cognitive Impairment: A Longitudinal MRI Study

Association between retinal layer thickness and postoperative delirium in older patients

Background

Postoperative delirium is one of the most common complications in the older surgical population, but its pathogenesis and biomarkers are largely undetermined. Retinal layer thickness has been demonstrated to be associated with cognitive function in mild cognitive impairment and patients with Alzheimer's disease. However, relatively little is known about possible retinal layer thickness among patients with postoperative delirium.

Aims

We aimed to investigate the relationship between retinal layer thickness and postoperative delirium in this cross-sectional study.

Methods

The participants (≥65 years old) having elective surgery under general anaesthesia were screened via medical records from Shanghai 10th People's Hospital. Preoperative macular thickness and peripapillary retinal nerve fibre layer (RNFL) thickness were measured using optical coherence tomography (OCT). The Confusion Assessment Method (CAM) algorithm and CAM-Severity (CAM-S) were used to assess the incidence and severity of postoperative delirium on the first, second and third days after surgery.

Results

Among 169 participants (mean (standard deviation (SD) 71.15 (4.36) years), 40 (24%) developed postoperative delirium. Notably, individuals who developed postoperative delirium exhibited thicker preoperative macular thickness in the right eye compared with those who did not (mean (SD) 283.35 (27.97) µm vs 273.84 (20.14) µm, p=0.013). Furthermore, the thicker preoperative macular thickness of the right eye was associated with a higher incidence of postoperative delirium (adjusted odds ratio 1.593, 95% confidence interval (CI) 1.093 to 2.322, p=0.015) and greater severity (adjusted mean difference (β)=0.256, 95% CI 0.037 to 0.476, p=0.022) after adjustment for age, sex and Mini-Mental State Examination (MMSE) scores. However, such a difference or association did not appear in the left macular or bilateral peripapillary RNFL thicknesses.

Conclusions

Current findings demonstrated that preoperative macular thickness might serve as a potential non-invasive marker for the vulnerability of developing postoperative delirium in older surgical patients. Further large-scale validation studies should be performed to confirm these results.

Mendelian randomization in Alzheimer's disease and mild cognitive impairment: Hippocampal volume associations

This study investigates the association between cognitive dysfunction and hippocampal volumes in Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI) using Mendelian randomization. A meta-analysis of 503 healthy controls, 562 MCI patients, and 389 CE patients revealed significant reductions in hippocampal and subregion volumes in MCI and AD compared to controls. While various subregions showed volume reductions, no causal relationship between hippocampal volume and AD was established through Mendelian randomization analysis. In conclusion, significant volume reductions were observed in MCI and AD patients, highlighting the complexity of the relationship between hippocampal volume and cognitive impairment.

Progression of hippocampal subfield atrophy and asymmetry in Alzheimer's disease

Alzheimer's disease (AD) affects the hippocampus during its progression, but the specific observable changes of hippocampal subfields during disease progression remain poorly understood. In this study, we employed an event-based model (EBM) to determine the sequence of occurrence of hippocampal subfield atrophy in mild cognitive impairment (MCI) and AD cohorts. Subjects (207) were included: 86 MCI, 53 AD, and 68 healthy controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Participants underwent structural magnetic resonance imaging (MRI) scans to analyse the hippocampal subfields. We assigned each patient to a specific EBM stage, based on the number of their abnormal subfields. A combination of 2-year follow-up MRI scans were applied to demonstrate the longitudinal consistency and utility of the model's staging system. The model estimated that the earliest atrophy occurs in the hippocampal fissure, then spreading to other subregions in both MCI and AD. We identified a marked divergence between the sequences of left and right hippocampal subfields atrophy, so inter-hemispheric asymmetry pattern was further analysed. The sequence of asymmetry index (AI) increases beginning in the molecular and granule cell layers of the dentate gyrus (GC-ML-DG), cornus ammonis (CA) 4, and the molecular layer (ML). Longitudinal analysis confirms the efficacy of the model. In addition, the model stages were significantly correlated with patients' memory scores (p < .05). Collectively, we used a data-driven method to provide new insight into AD hippocampal progression. The present model could aid in understanding of the disease stages, as well as tracking memory decline.

Synergistic effect of folate and MTHFR C677T on hippocampal subfields and perfusion in Alzheimer's disease

BACKGROUND

Low folate intake and methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism have been suggested to increase the risk of Alzheimer's disease (AD). However, the synergistic effects and their impact on brain structure and perfusion remain unclear.

METHODS

This study explored the effects of dietary and genetic deficiencies in folate metabolism on the volume of the hippocampal subregions, cerebral perfusion, and cognitive decline in 71 cognitively unimpaired (CU) individuals and 102 patients with mild cognitive impairment (MCI) due to AD or AD. All participants underwent magnetic resonance imaging, laboratory examinations, and neuropsychological assessments. The hippocampal subfields were segmented using Freesurfer, and arterial spin labeling was used to measure the cerebral blood flow.

RESULTS

We found a significant group-by-MTHFR interaction effect on folate. Patients with AD and the 677 T allele showed hypoperfusion in the left precuneus compared to patients without this mutation, which mediated the relationship between low folate level and cognitive decline in patients carrying the 677 T allele. Moreover, a synergistic effect was observed for the combination of decreased folate concentrations and the presence of the MTHFR 677 T allele on the atrophy of specific hippocampal subregions in patients with AD.

CONCLUSIONS

In addition to offering insights into the neuronal mechanism underlying gene-dependent folate-induced cognitive impairment in AD, these findings may have clinical significance for the allocation of auxiliary folate supplementation therapy in patients with AD with low folate levels and carrying the MTHFR 677 T allele and may eventually promote the selection of early individualized AD drug therapy.

Integrative approach of omics and imaging data to discover new insights for understanding brain diseases

Treatments that can completely resolve brain diseases have yet to be discovered. Omics is a novel technology that allows researchers to understand the molecular pathways underlying brain diseases. Multiple omics, including genomics, transcriptomics and proteomics, and brain imaging technologies, such as MRI, PET and EEG, have contributed to brain disease-related therapeutic target detection. However, new treatment discovery remains challenging. We focused on establishing brain multi-molecular maps using an integrative approach of omics and imaging to provide insights into brain disease diagnosis and treatment. This approach requires precise data collection using omics and imaging technologies, data processing and normalization. Incorporating a brain molecular map with the advanced technologies through artificial intelligence will help establish a system for brain disease diagnosis and treatment through regulation at the molecular level.

Alteration in amygdala subfield volumes and their association with cognition in mild cognitive impairment

BACKGROUND

The amygdala has an important role in cognitive and affective functions. The involvement of amygdala and related limbic structures is implicated in many aspects of memory and emotion in mild cognitive impairment (MCI). In the present study, we aimed to compare the volumetric measurements of amygdala and its subfields as well as their association with cognitive functions in stable MCI (sMCI).

METHODS

We performed Addenbrooke's cognitive examination III (ACE-III) test, as well as high-resolution T1-weighted images from 31 participants with sMCI and 31 age-matched healthy controls. The amygdala subfield volumes were extracted using Freesurfer software, and group differences were assessed using general linear model (GLM) with age, gender, education and estimated intracranial volume (ICV) as covariates. Partial correlation was also calculated between cognitive scores and volumes of amygdala subfields in healthy controls and sMCI participants controlling for estimated ICV.

RESULTS

sMCI participants exhibited significantly reduced volumes in most of the right amygdala subfields, including basal nucleus, accessory basal nucleus, central nucleus, medial nucleus, corticoamygdaloid transition area, and whole amygdala, as well as significantly reduced right amygdala/hippocampus ratio compared to healthy controls. In addition, our results revealed statistically significant positive correlations between ACE memory scores and the volumes of right central nucleus, right medial nucleus, right cortical nucleus, and the right whole amygdala, in sMCI.

CONCLUSIONS

Our findings revealed volumetric reductions in most of the right amygdala subfields along with its association with the memory functions in sMCI. These findings provide valuable insights into the underlying anatomical factors contributing to neurocognitive symptoms in MCI.

Structural and Functional Alterations of Hippocampal Subfields in Patients With Adult-Onset Primary Hypothyroidism

CONTEXT

Hypothyroidism is often associated with cognitive and emotional dysregulation; however, the underlying neuropathological mechanisms remain elusive.

OBJECTIVE

The study aimed to characterize abnormal alterations in hippocampal subfield volumes and functional connectivity (FC) in patients with subclinical hypothyroidism (SCH) and overt hypothyroidism (OH).

METHODS

This cross-sectional observational study comprised 47 and 40 patients with newly diagnosed adult-onset primary SCH and OH, respectively, and 53 well-matched healthy controls (HCs). The demographics, clinical variables, and neuropsychological scale scores were collected. Next, the hippocampal subfield volumes and seed-based FC were compared between the groups. Finally, correlation analyses were performed.

RESULTS

SCH and OH exhibited significant alterations in cognitive and emotional scale scores. Specifically, the volumes of the right granule cell molecular layer of the dentate gyrus (GC-ML-DG) head, cornu ammonis (CA) 4, and CA3 head were reduced in the SCH and OH groups. Moreover, the volumes of the right molecular layer head, CA1 body, left GC-ML-DG head, and CA4 head were lower in SCH. In addition, the hippocampal subfield volumes decreased more significantly in SCH than OH. The seed-based FC decreased in SCH but increased in OH compared with HCs. Correlation analyses revealed thyroid hormone was negatively correlated with FC values in hypothyroidism.

CONCLUSION

Patients with SCH and OH might be at risk of cognitive decline, anxiety, or depression, and exhibited alterations in volume and FC in specific hippocampal subfields. Furthermore, the reduction in volume was more pronounced in SCH. This study provides novel insights into the neuropathological mechanisms of brain impairment in hypothyroidism.

Estimating individual trajectories of structural and cognitive decline in mild cognitive impairment for early prediction of progression to dementia of the Alzheimer's type

Only a third of individuals with mild cognitive impairment (MCI) progress to dementia of the Alzheimer's type (DAT). Identifying biomarkers that distinguish individuals with MCI who will progress to DAT (MCI-Converters) from those who will not (MCI-Non-Converters) remains a key challenge in the field. In our study, we evaluate whether the individual rates of loss of volumes of the Hippocampus and entorhinal cortex (EC) with age in the MCI stage can predict progression to DAT. Using data from 758 MCI patients in the Alzheimer's Disease Neuroimaging Database, we employ Linear Mixed Effects (LME) models to estimate individual trajectories of regional brain volume loss over 12 years on average. Our approach involves three key analyses: (1) mapping age-related volume loss trajectories in MCI-Converters and Non-Converters, (2) using logistic regression to predict progression to DAT based on individual rates of hippocampal and EC volume loss, and (3) examining the relationship between individual estimates of these volumetric changes and cognitive decline across different cognitive functions-episodic memory, visuospatial processing, and executive function. We find that the loss of Hippocampal volume is significantly more rapid in MCI-Converters than Non-Converters, but find no such difference in EC volumes. We also find that the rate of hippocampal volume loss in the MCI stage is a significant predictor of conversion to DAT, while the rate of volume loss in the EC and other additional regions is not. Finally, individual estimates of rates of regional volume loss in both the Hippocampus and EC, and other additional regions, correlate strongly with individual rates of cognitive decline. Across all analyses, we find significant individual variation in the initial volumes and the rates of changes in volume with age in individuals with MCI. This study highlights the importance of personalized approaches in predicting AD progression, offering insights for future research and intervention strategies.

Associations between renal function, hippocampal volume, and cognitive impairment in 544 outpatients

Background

Cognitive impairment and brain atrophy are common in chronic kidney disease patients. It remains unclear whether differences in renal function, even within normal levels, influence hippocampal volume (HCV) and cognition. We aimed to investigate the association between estimated glomerular filtration rate (eGFR), HCV and cognition in outpatients.

Methods

This single-center retrospective study enrolled 544 nonrenal outpatients from our hospital. All participants underwent renal function assessment and 3.0 T magnetic resonance imaging (MRI) in the same year. HCV was also measured, and cognitive assessments were obtained. The correlations between eGFR, HCV, and cognitive function were analyzed. Logistic regression analysis was performed to identify the risk factors for hippocampal atrophy and cognitive impairment. Receiver-operator curves (ROCs) were performed to find the cut-off value of HCV that predicts cognitive impairment.

Results

The mean age of all participants was 66.5 ± 10.9 years. The mean eGFR of all participants was 88.5 ± 15.1 mL/min/1.73 m2. eGFR was positively correlated with HCV and with Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores. Univariate and multivariate logistic regression analysis showed Age ≥ 65 years, eGFR < 75 mL/min/1.73 m2, Glucose ≥6.1 mmol/L and combined cerebral microvascular diseases were independent risk factors for hippocampal atrophy and Age ≥ 65 years, left hippocampal volume (LHCV) <2,654 mm3 were independent risk factors for cognitive impairment in outpatients. Although initial unadjusted logistic regression analysis indicated that a lower eGFR (eGFR < 75 mL/min/1.73 m2) was associated with poorer cognitive function, this association was lost after adjusting for confounding variables. ROC curve analysis demonstrated that LHCV <2,654 mm3 had the highest AUROC [(0.842, 95% CI: 0.808-0.871)], indicating that LHCV had a credible prognostic value with a high sensitivity and specificity for predicting cognitive impairment compared with age in outpatients.

Conclusion

Higher eGFR was associated with higher HCV and better cognitive function. eGFR < 75 mL/min/1.73 m2 was an independent risk factor for hippocampal atrophy after adjusting for age. It is suggested that even eGFR < 75 mL/min/1.73 m2, lower eGFR may still be associated with hippocampal atrophy, which is further associated with cognitive impairment. LHCV was a favorable prognostic marker for predicting cognitive impairment rather than age.

Atrophy patterns in hippocampal subregions and their relationship with cognitive function in fibromyalgia patients with mild cognitive impairment

Objectives

Fibromyalgia (FM) has been associated with decreased hippocampal volume; however, the atrophy patterns of hippocampal subregions have not yet been identified. We therefore aimed to evaluate the volumes of hippocampal subregions in FM patients with mild cognitive impairment (MCI), and to explore the relationship between different subregional alterations and cognitive function.

Methods

The study included 35 FM patients (21 with MCI and 14 without MCI) and 35 healthy subjects. All subjects performed the Montreal Cognitive Assessment (MoCA) to assess cognitive function. FreeSurfer V.7.3.2 was used to calculate hippocampal subregion volumes. We then compared hippocampal subregion volumes between the groups, and analyzed the relationship between hippocampal subregion volume and cognitive function using a partial correlation analysis method.

Results

Compared with the healthy subjects, FM patients with MCI had smaller hippocampal volumes in the left and right CA1 head, Molecular layer head, GC-DG head, and CA4 head, and in the left Presubiculum head. Poorer executive function, naming ability, and attention were associated with left CA1 head and left Molecular layer head atrophy. By contrast, hippocampal subregion volumes in the FM patients without MCI were slightly larger than or similar to those in the healthy subjects, and were not significantly correlated with cognitive function.

Conclusion

Smaller volumes of left CA1 head and left Molecular layer head were associated with poorer executive function, naming ability, and attention in FM patients with MCI. However, these results were not observed in the FM patients without MCI. These findings suggest that the hippocampal subregions of FM patients might present compensatory mechanisms before cognitive decline occurs.

Atrophy of hippocampal subfields and amygdala nuclei in subjects with mild cognitive impairment progressing to Alzheimer's disease

The hippocampus and amygdala are the first brain regions to show early signs of Alzheimer's Disease (AD) pathology. AD is preceded by a prodromal stage known as Mild Cognitive Impairment (MCI), a crucial crossroad in the clinical progression of the disease. The topographical development of AD has been the subject of extended investigation. However, it is still largely unknown how the transition from MCI to AD affects specific hippocampal and amygdala subregions. The present study is set to answer that question. We analyzed data from 223 subjects: 75 healthy controls, 52 individuals with MCI, and 96 AD patients obtained from the ADNI. The MCI group was further divided into two subgroups depending on whether individuals in the 48 months following the diagnosis either remained stable (N = 21) or progressed to AD (N = 31). A MANCOVA test evaluated group differences in the volume of distinct amygdala and hippocampal subregions obtained from magnetic resonance images. Subsequently, a stepwise linear discriminant analysis (LDA) determined which combination of magnetic resonance imaging parameters was most effective in predicting the conversion from MCI to AD. The predictive performance was assessed through a Receiver Operating Characteristic analysis. AD patients displayed widespread subregional atrophy. MCI individuals who progressed to AD showed selective atrophy of the hippocampal subiculum and tail compared to stable MCI individuals, who were undistinguishable from healthy controls. Converter MCI showed atrophy of the amygdala's accessory basal, central, and cortical nuclei. The LDA identified the hippocampal subiculum and the amygdala's lateral and accessory basal nuclei as significant predictors of MCI conversion to AD. The analysis returned a sensitivity value of 0.78 and a specificity value of 0.62. These findings highlight the importance of targeted assessments of distinct amygdala and hippocampus subregions to help dissect the clinical and pathophysiological development of the MCI to AD transition.

Unraveling the link: white matter damage, gray matter atrophy and memory impairment in patients with subcortical ischemic vascular disease

Introduction

Prior MRI studies have shown that patients with subcortical ischemic vascular disease (SIVD) exhibited white matter damage, gray matter atrophy and memory impairment, but the specific characteristics and interrelationships of these abnormal changes have not been fully elucidated.

Materials and methods

We collected the MRI data and memory scores from 29 SIVD patients with cognitive impairment (SIVD-CI), 29 SIVD patients with cognitive unimpaired (SIVD-CU) and 32 normal controls (NC). Subsequently, the thicknesses and volumes of the gray matter regions that are closely related to memory function were automatically assessed using FreeSurfer software. Then, the volume, fractional anisotropy (FA), mean diffusivity (MD), amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) values of white matter hyperintensity (WMH) region and normal-appearing white matter (NAWM) were obtained using SPM, DPARSF, and FSL software. Finally, the analysis of covariance, spearman correlation and mediation analysis were used to analyze data.

Results

Compared with NC group, patients in SIVD-CI and SIVD-CU groups showed significantly abnormal volume, FA, MD, ALFF, and ReHo values of WMH region and NAWM, as well as significantly decreased volume and thickness values of gray matter regions, mainly including thalamus, middle temporal gyrus and hippocampal subfields such as cornu ammonis (CA) 1. These abnormal changes were significantly correlated with decreased visual, auditory and working memory scores. Compared with the SIVD-CU group, the significant reductions of the left CA2/3, right amygdala, right parasubiculum and NAWM volumes and the significant increases of the MD values in the WMH region and NAWM were found in the SIVD-CI group. And the increased MD values were significantly related to working memory scores. Moreover, the decreased CA1 and thalamus volumes mediated the correlations between the abnormal microstructure indicators in WMH region and the decreased memory scores in the SIVD-CI group.

Conclusion

Patients with SIVD had structural and functional damages in both WMH and NAWM, along with specific gray matter atrophy, which were closely related to memory impairment, especially CA1 atrophy and thalamic atrophy. More importantly, the volumes of some temporomesial regions and the MD values of WMH regions and NAWM may be potentially helpful neuroimaging indicators for distinguishing between SIVD-CI and SIVD-CU patients.

HCTMFS: A multi-modal feature selection framework with higher-order correlated topological manifold for ESRDaMCI

BACKGROUND AND OBJECTIVE

The diagnosis of end-stage renal disease associated with mild cognitive impairment (ESRDaMCI) mainly relies on objective cognitive assessment, clinical observation, and neuro-psychological evaluation, while only adopting clinical tools often limits the diagnosis accuracy.

METHODS

We proposed a multi-modal feature selection framework with higher-order correlated topological manifold (HCTMFS) to classify ESRDaMCI patients and identify the discriminative brain regions. It constructed brain structural and functional networks with diffuse kurtosis imaging (DKI) and functional magnetic resonance imaging (fMRI) data, and extracted node efficiency and clustering coefficient from the brain networks to construct multi-modal feature matrices. The topological relationship matrices were constructed to measure the lower-order topological correlation between features. Then the consensus matrices were learned to approximate the topological relationship matrices at different confidence levels and eliminate the noise influence of individual matrices.

RESULTS

The higher-order topological correlation between features was explored by the Laplacian matrix of the hypergraph, which was calculated through the consensus matrix. The new framework achieved an accuracy rate of 93.56 % for classifying ESRDaMCI patients, and outperformed the existing state-of-the-art methods in terms of sensitivity, specificity, and area under the curve.

CONCLUSIONS

This study contributes to effectively reflect the functional neural degradation of ESRDaMCI and provide a reference for the diagnosis of ESRDaMCI by selecting discriminative brain regions.

Hippocampal subfield volumes in mild cognitive impairment and alzheimer's disease: a systematic review and meta-analysis

The hippocampus is a complex structure that consists of several subfields with distinct and specialized functions. Although numerous studies have been performed to explore hippocampal atrophy at the sub-regional level in mild cognitive impairment (MCI) and Alzheimer's disease (AD), the results have been inconsistent especially for whether and which subfields can be served as the most potential biomarkers in MCI and AD. Herein, we used a meta-analytic approach to synthesize the extant literatures on hippocampal subfields in MCI and AD through PubMed, Web of Science, and Embase (PROSPERO CRD42021257586). As a result, a total of twenty studies using Freesurfer 5 and Freesurfer 6 were included in this investigation. These studies revealed that at the sub-regional level, hippocampal subfield volume reductions in MCI and AD were not restricted to specific subfields, and subiculum and presubiculum had the largest z-scores across most comparisons. However, none of the subfield performed much better in discriminating MCI and HC, AD and MCI, AD and HC as compared to whole hippocampus volume. These results suggested that we should explore the changes in the hippocampal subfields in subtypes of MCI or even at an earlier stage, that is subjective cognitive impairment.

MR-based spatiotemporal anisotropic atrophy evaluation of hippocampus in Alzheimer's disease progression by multiscale skeletal representation

Increasing evidence has shown a higher sensitivity of Alzheimer's disease (AD) progression by local hippocampal atrophy rather than the whole volume. However, existing morphological methods based on subfield-volume or surface in imaging studies are not capable to describe the comprehensive process of hippocampal atrophy as sensitive as histological findings. To map histological distinctive measurements onto medical magnetic resonance (MR) images, we propose a multiscale skeletal representation (m-s-rep) to quantify focal hippocampal atrophy during AD progression in longitudinal cohorts from the Alzheimer's Disease Neuroimaging Initiative (ADNI). The m-s-rep captures large-to-small-scale hippocampal morphology by spoke interpolation over label projection on skeletal models. To enhance morphological correspondence within subjects, we align the longitudinal m-s-reps by surface-based transformations from baseline to subsequent timepoints. Cross-sectional and longitudinal measurements derived from m-s-rep are statistically analyzed to comprehensively evaluate the bilateral hippocampal atrophy. Our findings reveal that during the early AD progression, atrophy primarily affects the lateral-medial extent of the hippocampus, with a difference of 1.8 mm in lateral-medial width in 2 years preceding conversion (p < .001), and the medial head exhibits a maximum difference of 3.05%/year in local atrophy rate (p = .011) compared to controls. Moreover, progressive mild cognitive impairment (pMCI) exhibits more severe and widespread atrophy in the head and body compared to stable mild cognitive impairment (sMCI), with a maximum difference of 1.21 mm in thickness in the medial head 1 year preceding conversion (p = .012). In summary, our proposed method can quantitatively measure the hippocampal morphological changes on 3T MR images, potentially assisting the pre-diagnosis and prognosis of AD.

Verbal memory depends on structural hippocampal subfield volume

Objective

To investigate correlates in hippocampal subfield volume and verbal and visual memory function in patients with temporal lobe epilepsy (TLE), mild amnestic cognitive impairment (MCI) and heathy participants (HP).

Methods

50 right-handed participants were included in this study; 11 patients with temporal lobe epilepsy (TLE), 18 patients with mild amnestic cognitive impairment (MCI) and 21 healthy participants (HP). Verbal memory performance was evaluated via the verbal memory test (VLMT) and visual memory performance via the diagnosticum for cerebral damage (DCM). Hippocampal subfield volumes of T1-weighted Magnetic Resonance Imaging (MRI) scans were computed with FreeSurfer version 7.1. Stepwise correlation analyses were performed between the left hippocampal subfield volumes and learning, free recall, consolidation and recognition performance scores of the VLMT as well as between right hippocampal subfield volumes and visual memory performance.

Results

The volume of the left subicular complex was highly correlated to learning performance (β = 0.284; p = 0.042) and free recall performance in the VLMT (β = 0.434; p = 0.001). The volume of the left CA3 subfield showed a significant correlation to the consolidation performance in the VLMT (β = 0.378; p = 0.006) and recognition performance in the VLMT (β = 0.290; p = 0.037). There was no significant correlation identified between the right hippocampal subfields and the visual memory performance.

Conclusion

The results of this study show verbal memory correlates with hippocampal subfields and support the role of left subiculum and left CA2/CA3 in verbal memory performance.

Multi-modal feature selection with self-expression topological manifold for end-stage renal disease associated with mild cognitive impairment

Effectively selecting discriminative brain regions in multi-modal neuroimages is one of the effective means to reveal the neuropathological mechanism of end-stage renal disease associated with mild cognitive impairment (ESRDaMCI). Existing multi-modal feature selection methods usually depend on the Euclidean distance to measure the similarity between data, which tends to ignore the implied data manifold. A self-expression topological manifold based multi-modal feature selection method (SETMFS) is proposed to address this issue employing self-expression topological manifold. First, a dynamic brain functional network is established using functional magnetic resonance imaging (fMRI), after which the betweenness centrality is extracted. The feature matrix of fMRI is constructed based on this centrality measure. Second, the feature matrix of arterial spin labeling (ASL) is constructed by extracting the cerebral blood flow (CBF). Then, the topological relationship matrices are constructed by calculating the topological relationship between each data point in the two feature matrices to measure the intrinsic similarity between the features, respectively. Subsequently, the graph regularization is utilized to embed the self-expression model into topological manifold learning to identify the linear self-expression of the features. Finally, the selected well-represented feature vectors are fed into a multicore support vector machine (MKSVM) for classification. The experimental results show that the classification performance of SETMFS is significantly superior to several state-of-the-art feature selection methods, especially its classification accuracy reaches 86.10%, which is at least 4.34% higher than other comparable methods. This method fully considers the topological correlation between the multi-modal features and provides a reference for ESRDaMCI auxiliary diagnosis.

Relations of hippocampal subfields atrophy patterns with memory and biochemical changes in end stage renal disease

End-stage renal disease (ESRD) results in hippocampal volume reduction, but the hippocampal subfields atrophy patterns cannot be identified. We explored the volumes and asymmetry of the hippocampal subfields and their relationships with memory function and biochemical changes. Hippocampal global and subfields volumes were derived from 33 ESRD patients and 46 healthy controls (HCs) from structural MRI. We compared the volume and asymmetric index of each subfield, with receiver operating characteristic curve analysis to evaluate the differentiation between ESRD and HCs. The relations of hippocampal subfield volumes with memory performance and biochemical data were investigated in ESRD group. ESRD patients had smaller hippocampal subfield volumes, mainly in the left CA1 body, left fimbria, right molecular layer head, right molecular layer body and right HATA. The right molecular layer body exhibited the highest accuracy for differentiating ESRD from HCs, with a sensitivity of 80.43% and specificity of 72.73%. Worse learning process (r = 0.414, p = 0.032), immediate recall (r = 0.396, p = 0.041) and delayed recall (r = 0.482, p = 0.011) was associated with left fimbria atrophy. The left fimbria volume was positively correlated with Hb (r = 0.388, p = 0.05); the left CA1 body volume was negatively correlated with Urea (r = - 0.469, p = 0.016). ESRD patients showed global and hippocampal subfields atrophy. Left fimbria atrophy was related to memory function. Anemia and Urea level may be associated with the atrophy of left fimbria and CA1 body, respectively.

Atrophy asymmetry in hippocampal subfields in patients with Alzheimer's disease and mild cognitive impairment

Volumetric analysis of hippocampal subfields and their asymmetry assessment recently has been useful biomarkers in neuroscience. In this study, hippocampal subfields atrophy and pattern of their asymmetry in the patient with Alzheimer's disease (AD) and mild cognitive impairment (MCI) were evaluated. MRI images of 20 AD patients, 20 MCI patients, and 20 healthy control (HC) were selected. The volumes of hippocampal subfields were extracted automatically using Freesurfer toolkit. The subfields asymmetry index (AI) and laterality ([Formula: see text]) were also evaluated. Analysis of covariance was used to compare the subfields volume between three patient groups (age and gender as covariates). We used ANOVA (P < 0.05) test for multiple comparisons with Bonferroni's post hoc correction method. Hippocampal subfields volume in AD patients were significantly lower than HC and MCI groups (P < 0.02); however, no significant difference was observed between MCI and HC groups. The asymmetry index (AI) in some subfields was significantly different between AD and MCI, as well as between AD and HC, while there was not any significant difference between MCI groups with HC. In all three patient groups, rightward laterality ([Formula: see text]) was seen in several subfields except subiculum, presubiculum, and parasubiculum, while in AD patient, rightward lateralization slightly decrease. Hippocampal subfields asymmetry can be used as a quantitative biomarker in neurocognitive disorders. In this study, it was observed that the asymmetry index of some subfields in AD is significantly different from MCI. In AD, patient rightward laterality was less MCI an HC group.

Polygenic hazard score modified the relationship between hippocampal subfield atrophy and episodic memory in older adults

BACKGROUND

Understanding genetic influences on Alzheimer's disease (AD) may improve early identification. Polygenic hazard score (PHS) is associated with the age of AD onset and cognitive decline. It interacts with other risk factors, but the nature of such combined effects remains poorly understood.

MATERIALS AND METHODS

We examined the effect of genetic risk and hippocampal atrophy pattern on episodic memory in a sample of older adults ranging from cognitively normal to those diagnosed with AD using structural MRI. Participants included 51 memory unimpaired normal control (NC), 69 mild cognitive impairment (MCI), and 43 AD adults enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Hierarchical linear regression analyses examined the main and interaction effects of hippocampal subfield volumes and PHS, indicating genetic risk for AD, on a validated episodic memory composite score. Diagnosis-stratified models further assessed the role of PHS.

RESULTS

Polygenic hazard score moderated the relationship between right fimbria/hippocampus volume ratio and episodic memory, such that patients with high PHS and lower volume ratio had lower episodic memory composite scores [ΔF = 6.730, p = 0.011, ΔR 2 = 0.059]. This effect was also found among individuals with MCI [ΔF = 4.519, p = 0.038, ΔR 2 = 0.050]. In contrast, no interaction effects were present for those NC or AD individuals. A follow-up mediation analysis also indicated that the right fimbria/hippocampus volume ratio might mediate the link between PHS and episodic memory performance in the MCI group, whereas no mediation effects were present for those NC or AD individuals.

CONCLUSION

These findings suggest that the interaction between AD genetic risk and hippocampal subfield volume ratio increases memory impairment among older adults. Also, the results highlighted a potential pathway in which genetic risk affects memory by degrading hippocampal subfield volume ratio in cognitive decline subjects.

Low Serum Insulin-like Growth Factor-I Is Associated with Decline in Hippocampal Volume in Stable Mild Cognitive Impairment but not in Alzheimer's Disease

Background:

Serum insulin-like growth factor-I (IGF-I) has shown some association with hippocampal volume in healthy subjects, but this relation has not been investigated in stable mild cognitive impairment (sMCI) or Alzheimer’s disease (AD).

Objective:

At a single memory clinic, we investigated whether serum IGF-I was associated with baseline magnetic resonance imaging (MRI)-estimated brain volumes and longitudinal alterations, defined as annualized changes, up to 6 years of follow-up.

Methods:

A prospective study of patients with sMCI (n = 110) and AD (n = 60). Brain regions included the hippocampus and amygdala as well as the temporal, parietal, frontal, and occipital lobes, respectively.

Results:

Serum IGF-I was statistically similar in sMCI and AD patients (112 versus 123 ng/mL, p = 0.31). In sMCI, serum IGF-I correlated positively with all baseline MRI variables except for the occipital lobe, and there was also a positive correlation between serum IGF-I and the annualized change in hippocampal volume (r_s = 0.32, p = 0.02). Furthermore, sMCI patients having serum IGF-I above the median had lower annual loss of hippocampal volume than those with IGF-I below the median (p = 0.02). In contrast, in AD patients, IGF-I did not associate with baseline levels or annualized changes in brain volumes.

Conclusion:

In sMCI patients, our results suggest that IGF-I exerted neuroprotective effects on the brain, thereby maintaining hippocampal volume. In AD, serum IGF-I did not associate with brain volumes, indicating that IGF-I could not induce neuroprotection in this disease. This supports the notion of IGF-I resistance in AD.

Diagnostic Performance of Generative Adversarial Network-Based Deep Learning Methods for Alzheimer's Disease: A Systematic Review and Meta-Analysis

Alzheimer's disease (AD) is the most common form of dementia. Currently, only symptomatic management is available, and early diagnosis and intervention are crucial for AD treatment. As a recent deep learning strategy, generative adversarial networks (GANs) are expected to benefit AD diagnosis, but their performance remains to be verified. This study provided a systematic review on the application of the GAN-based deep learning method in the diagnosis of AD and conducted a meta-analysis to evaluate its diagnostic performance. A search of the following electronic databases was performed by two researchers independently in August 2021: MEDLINE (PubMed), Cochrane Library, EMBASE, and Web of Science. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was applied to assess the quality of the included studies. The accuracy of the model applied in the diagnosis of AD was determined by calculating odds ratios (ORs) with 95% confidence intervals (CIs). A bivariate random-effects model was used to calculate the pooled sensitivity and specificity with their 95% CIs. Fourteen studies were included, 11 of which were included in the meta-analysis. The overall quality of the included studies was high according to the QUADAS-2 assessment. For the AD vs. cognitively normal (CN) classification, the GAN-based deep learning method exhibited better performance than the non-GAN method, with significantly higher accuracy (OR 1.425, 95% CI: 1.150-1.766, P = 0.001), pooled sensitivity (0.88 vs. 0.83), pooled specificity (0.93 vs. 0.89), and area under the curve (AUC) of the summary receiver operating characteristic curve (SROC) (0.96 vs. 0.93). For the progressing MCI (pMCI) vs. stable MCI (sMCI) classification, the GAN method exhibited no significant increase in the accuracy (OR 1.149, 95% CI: 0.878-1.505, P = 0.310) or the pooled sensitivity (0.66 vs. 0.66). The pooled specificity and AUC of the SROC in the GAN group were slightly higher than those in the non-GAN group (0.81 vs. 0.78 and 0.81 vs. 0.80, respectively). The present results suggested that the GAN-based deep learning method performed well in the task of AD vs. CN classification. However, the diagnostic performance of GAN in the task of pMCI vs. sMCI classification needs to be improved. Systematic Review Registration: [PROSPERO], Identifier: [CRD42021275294].

Proteomic Profiles of Neurodegeneration Among Mexican Americans and Non-Hispanic Whites in the HABS-HD Study

BACKGROUND

Hispanics are expected to experience the largest increase in Alzheimer's disease (AD) and AD related dementias over the next several decades. However, few studies have examined biomarkers of AD among Mexican Americans, the largest segment of the U.S. Hispanic population.

OBJECTIVE

We sought to examine proteomic profiles of an MRI-based marker of neurodegeneration from the AT(N) framework among a multi-ethnic, community-dwelling cohort.

METHODS

Community-dwelling Mexican Americans and non-Hispanic white adults and elders were recruited. All participants underwent comprehensive assessments including an interview, functional exam, clinical labs, informant interview, neuropsychological testing, and 3T MRI of the brain. A neurodegeneration MRI meta-ROI biomarker for the AT(N) framework was calculated.

RESULTS

Data was examined from n = 1,291 participants. Proteomic profiles were highly accurate for detecting neurodegeneration (i.e., N+) among both Mexican Americans (AUC = 1.0) and non-Hispanic whites (AUC = 0.98). The proteomic profile of N + was different between ethnic groups. Further analyses revealed that the proteomic profiles of N + varied by diagnostic status (control, MCI, dementia) and ethnicity (Mexican American versus non-Hispanic whites) though diagnostic accuracy was high for all classifications.

CONCLUSION

A proteomic profile of neurodegeneration has tremendous value and point towards novel diagnostic and intervention opportunities. The current findings demonstrate that the underlying biological factors associated with neurodegeneration are different between Mexican Americans versus non-Hispanic whites as well as at different levels of disease progression.

Hippocampo-Horn Percentage and Parietal Atrophy Score for Easy Visual Assessment of Brain Atrophy on Magnetic Resonance Imaging in Early- and Late-Onset Alzheimer's Disease

BACKGROUND

Magnetic resonance imaging (MRI) visual scales of brain atrophy are important for differential diagnosis of dementias in routine clinical practice. Atrophy patterns in early- and late-onset Alzheimer's disease (AD) can be different according to some studies.

OBJECTIVE

Our goal was to assess brain atrophy patterns in early- and late-onset AD using our recently developed simple MRI visual scales and evaluate their reliability.

METHODS

We used Hippocampo-horn percentage (Hip-hop) and Parietal Atrophy Score (PAS) to compare mediotemporal and parietal atrophy on brain MRI among 4 groups: 26 patients with early-onset AD, 21 younger cognitively normal persons, 32 patients with late-onset AD, and 36 older cognitively normal persons. Two raters scored all brain MRI to assess reliability of the Hip-hop and PAS. Brain MRIs were obtained from Alzheimer's Disease Neuroimaging Initiative (ADNI) database.

RESULTS

The patients with early-onset AD had significantly more pronounced mediotemporal and also parietal atrophy bilaterally compared to the controls (both p < 0.01). The patients with late-onset AD had significantly more pronounced only mediotemporal atrophy bilaterally compared to the controls (p < 0.000001), but parietal lobes were the same. Intra-rater and inter-rater reliability of both visual scales Hip-hop and PAS were almost perfect in all cases (weighted-kappa value ranged from 0.90 to 0.99).

CONCLUSION

While mediotemporal atrophy detected using Hip-hop is universal across the whole AD age spectrum, parietal atrophy detected using PAS is worth rating only in early-onset AD. Hip-hop and PAS are very reliable MRI visual scales.

Prediction of Subtle Cognitive Decline in Normal Aging: Added Value of Quantitative MRI and PET Imaging

Quantitative imaging processing tools have been proposed to improve clinic-radiological correlations but their added value at the initial stages of cognitive decline is still a matter of debate. We performed a longitudinal study in 90 community-dwelling elders with three neuropsychological assessments during a 4.5 year follow-up period, and visual assessment of medial temporal atrophy (MTA), white matter hyperintensities, cortical microbleeds (CMB) as well as amyloid positivity, and presence of abnormal FDG-PET patterns. Quantitative imaging data concerned ROI analysis of MRI volume, amyloid burden, and FDG-PET metabolism in several AD-signature areas. Multiple regression models, likelihood-ratio tests, and areas under the receiver operating characteristic curve (AUC) were used to compare quantitative imaging markers to visual inspection. The presence of more or equal to four CMB at inclusion and slight atrophy of the right MTL at follow-up were the only parameters to be independently related to the worst cognitive score explaining 6% of its variance. This percentage increased to 24.5% when the ROI-defined volume loss in the posterior cingulate cortex, baseline hippocampus volume, and MTL metabolism were also considered. When binary classification of cognition was made, the area under the ROC curve increased from 0.69 for the qualitative to 0.79 for the mixed imaging model. Our data reveal that the inclusion of quantitative imaging data significantly increases the prediction of cognitive changes in elderly controls compared to the single consideration of visual inspection.