Differential and subtype-specific neuroimaging abnormalities in amnestic and nonamnestic mild cognitive impairment: A systematic review and meta-analysis

The Efficacy of a Metacognitive Training Program in Amnestic Mild Cognitive Impairment: A 6-Month Follow-Up Clinical Study

This study was conducted in response to the increasing prevalence of Alzheimer's disease (AD) dementia and the significant risk faced by individuals with amnestic mild cognitive impairment with multiple-domain deficits (aMCI-md). Given the promising effects of MTPs, the primary aim of this study was to further explore their impact by assessing the maintenance of their benefits. Thus, 45 participants were randomly allocated in two groups: the Experimental group (n = 22), which received the metacognitive training program (MTP), and the Control group (n = 23) that received the cognitive exercises program (CEP). The training programs-the MTP and the CEP-included 10 individual sessions of a one-hour duration and took place once per week. To test the efficacy of the MTP, cognitive and metacognitive outcomes were compared between two groups-Experimental (EG) and Control (CG)-at four distinct time points: before-after-3 months-6 months after intervention. Based on this study's findings, the positive effects of the MTP were evident over a six-month period. Specifically, already three months post-training, the CG began to show a decline in training-related gains. In contrast, the EG's performance consistently improved, highlighting the superior efficacy of the MTP. Gains attributed to the MTP were detected in cognitive measures: cognitive flexibility and immediate visual recall, as well as in metacognitive measures: metacognitive control, improved metacognitive beliefs of attention, and an increased use of cognitive strategies. In conclusion, the results demonstrated the sustained effects of the MTP in cognitive and metacognitive measures over a period of six months, providing novel insight into the application and efficacy of the MTP in individuals with MCI.

Changes in Community Structure of Brain Dynamic Functional Connectivity States in Mild Cognitive Impairment

Recent researches have noted many changes of short-term dynamic modalities in mild cognitive impairment (MCI) patients' brain functional networks. In this study, the dynamic functional brain networks of 82 MCI patients and 85 individuals in the normal control (NC) group were constructed using the sliding window method and Pearson correlation. The window size was determined using single-scale time-dependent (SSTD) method. Subsequently, k-means was applied to cluster all window samples, identifying three dynamic functional connectivity (DFC) states. Collective sparse symmetric non-negative matrix factorization (cssNMF) was then used to perform community detection on these states and quantify differences in brain regions. Finally, metrics such as within-community connectivity strength, community strength, and node diversity were calculated for further analysis. The results indicated high similarity between the two groups in state 2, with no significant differences in optimal community quantity and functional segregation (p < 0.05). However, for state 1 and state 3, the optimal community quantity was smaller in MCI patients compared to the NC group. In state 1, MCI patients had lower within-community connectivity strength and overall strength than the NC group, whereas state 3 showed results opposite to state 1. Brain regions with statistical difference included MFG.L, ORBinf.R, STG.R, IFGtriang.L, CUN.L, CUN.R, LING.R, SOG.L, and PCUN.R. This study on DFC states explores changes in the brain functional networks of patients with MCI from the perspective of alterations in the community structures of DFC states. The findings could provide new insights into the pathological changes in the brains of MCI patients.

Altered regional homogeneity following moxibustion in mild cognitive impairment

Moxibustion has a definite clinical effect in improving the cognitive condition in individuals with mild cognitive impairment (MCI), but its underlying neural mechanism remains elusive. This study aimed to investigate the alterations in spontaneous brain activity and cognitive function following moxibustion therapy in MCI patients. This study enrolled a cohort of 33 MCI subjects and 30 matched healthy controls (HCs). MCI subjects underwent a two-month regimen of moxibustion. Employing resting-state functional magnetic resonance imaging, we utilized regional homogeneity (ReHo) analysis to evaluate the changes in brain activity. Cognitive function was evaluated by using the Mini-Mental State Examination and Montreal Cognitive Assessment. There existed aberrant ReHo values in different brain areas mainly involved in the default mode network (DMN) in MCI subjects compared with HCs. After moxibustion treatment, MCI subjects showed an inverse in ReHo values from baseline in the hippocampus/parahippocampus and insula, as well as an increase in ReHo value in the middle frontal gyrus. Notably, the ReHo alterations in the left hippocampus/parahippocampus and middle frontal gyrus were associated with cognitive improvement in MCI patients. Abnormal neural activity occurred in MCI subjects mainly within the DMN. Moxibustion therapy may facilitate cognitive improvement in MCI subjects by modulating brain activity, particularly by reversing the neural activity within the DMN and salience network. These results underscore the therapeutic potential of moxibustion as an early intervention strategy for Alzheimer's disease.

Multiparametric hippocampal signatures for early diagnosis of Alzheimer's disease using 18F-FDG PET/MRI Radiomics

PURPOSE

This study aimed to explore the utility of hippocampal radiomics using multiparametric simultaneous positron emission tomography (PET)/magnetic resonance imaging (MRI) for early diagnosis of Alzheimer's disease (AD).

METHODS

A total of 53 healthy control (HC) participants, 55 patients with amnestic mild cognitive impairment (aMCI), and 51 patients with AD were included in this study. All participants accepted simultaneous PET/MRI scans, including 18F-fluorodeoxyglucose (18F-FDG) PET, 3D arterial spin labeling (ASL), and high-resolution T1-weighted imaging (3D T1WI). Radiomics features were extracted from the hippocampus region on those three modal images. Logistic regression models were trained to classify AD and HC, AD and aMCI, aMCI and HC respectively. The diagnostic performance and radiomics score (Rad-Score) of logistic regression models were evaluated from 5-fold cross-validation.

RESULTS

The hippocampal radiomics features demonstrated favorable diagnostic performance, with the multimodal classifier outperforming the single-modal classifier in the binary classification of HC, aMCI, and AD. Using the multimodal classifier, we achieved an area under the receiver operating characteristic curve (AUC) of 0.98 and accuracy of 96.7% for classifying AD from HC, and an AUC of 0.86 and accuracy of 80.6% for classifying aMCI from HC. The value of Rad-Score differed significantly between the AD and HC (p < 0.001), aMCI and HC (p < 0.001) groups. Decision curve analysis showed superior clinical benefits of multimodal classifiers compared to neuropsychological tests.

CONCLUSION

Multiparametric hippocampal radiomics using PET/MRI aids in the identification of early AD, and may provide a potential biomarker for clinical applications.

Altered cortical and subcortical morphometric features and asymmetries in the subjective cognitive decline and mild cognitive impairment

Introduction

This study aimed to evaluate morphological changes in cortical and subcortical regions and their asymmetrical differences in individuals with subjective cognitive decline (SCD) and mild cognitive impairment (MCI). These morphological changes may provide valuable insights into the early diagnosis and treatment of Alzheimer's disease (AD).

Methods

We conducted structural MRI scans on a cohort comprising 62 SCD patients, 97 MCI patients, and 70 age-, sex-, and years of education-matched healthy controls (HC). Using Freesurfer, we quantified surface area, thickness, the local gyrification index (LGI) of cortical regions, and the volume of subcortical nuclei. Asymmetry measures were also calculated. Additionally, we explored the correlation between morphological changes and clinical variables related to cognitive decline.

Results

Compared to HC, patients with MCI exhibited predominantly left-sided surface morphological changes in various brain regions, including the transverse temporal gyrus, superior temporal gyrus, insula, and pars opercularis. SCD patients showed relatively minor surface morphological changes, primarily in the insula and pars triangularis. Furthermore, MCI patients demonstrated reduced volumes in the anterior-superior region of the right hypothalamus, the fimbria of the bilateral hippocampus, and the anterior region of the left thalamus. These observed morphological changes were significantly associated with clinical ratings of cognitive decline.

Conclusion

The findings of this study suggest that cortical and subcortical morphometric changes may contribute to cognitive impairment in MCI, while compensatory mechanisms may be at play in SCD to preserve cognitive function. These insights have the potential to aid in the early diagnosis and treatment of AD.

Adjunctive transcranial direct current stimulation (tDCS) plus sodium benzoate for the treatment of early-phase Alzheimer's disease: A randomized, double-blind, placebo-controlled trial

Previous studies found that an NMDA receptor (NMDAR) enhancer, sodium benzoate, improved cognitive function of patients with early-phase Alzheimer's disease (AD). Transcranial direct current stimulation (tDCS) induces NMDAR-dependent synaptic plasticity and strengthens cognitive function of AD patients. This study aimed to evaluate efficacy and safety of tDCS plus benzoate in early-phase dementia. In this 24-week randomized, double-blind, placebo-controlled trial, 97 patients with early-phase AD received 10-session tDCS during the first 2 weeks. They then took benzoate or placebo for 24 weeks. We assessed the patients using Alzheimer's disease assessment scale - cognitive subscale (ADAS-cog), Clinician's Interview-Based Impression of Change plus Caregiver Input, Mini Mental Status Examination, Alzheimer's disease Cooperative Study scale for ADL in MCI, and a battery of additional cognitive tests. Forty-seven patients received sodium benzoate, and the other 50 placebo. The two treatment groups didn't differ significantly in ADAS-cog or other measures. Addition of benzoate to tDCS didn't get extra benefit or side effect in this study. For more thoroughly studying the potential of combining tDCS with benzoate in the AD treatment, future research should use other study designs, such as longer-term benzoate treatment, adding benzoate in the middle of tDCS trial sessions, or administering benzoate then tDCS.

Abnormal white matter changes in Alzheimer's disease based on diffusion tensor imaging: A systematic review

Alzheimer's disease (AD) is a degenerative neurological disease in elderly individuals. Subjective cognitive decline (SCD), mild cognitive impairment (MCI) and further development to dementia (d-AD) are considered to be major stages of the progressive pathological development of AD. Diffusion tensor imaging (DTI), one of the most important modalities of MRI, can describe the microstructure of white matter through its tensor model. It is widely used in understanding the central nervous system mechanism and finding appropriate potential biomarkers for the early stages of AD. Based on the multilevel analysis methods of DTI (voxelwise, fiberwise and networkwise), we summarized that AD patients mainly showed extensive microstructural damage, structural disconnection and topological abnormalities in the corpus callosum, fornix, and medial temporal lobe, including the hippocampus and cingulum. The diffusion features and structural connectomics of specific regions can provide information for the early assisted recognition of AD. The classification accuracy of SCD and normal controls can reach 92.68% at present. And due to the further changes of brain structure and function, the classification accuracy of MCI, d-AD and normal controls can reach more than 97%. Finally, we summarized the limitations of current DTI-based AD research and propose possible future research directions.