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

Automated brain segmentation and volumetry in dementia diagnostics: a narrative review with emphasis on FreeSurfer

Background

Dementia can be caused by numerous different diseases that present variable clinical courses and reveal multiple patterns of brain atrophy, making its accurate early diagnosis by conventional examinative means challenging. Although highly accurate and powerful, magnetic resonance imaging (MRI) currently plays only a supportive role in dementia diagnosis, largely due to the enormous volume and diversity of data it generates. AI-based software solutions/algorithms that can perform automated segmentation and volumetry analyses of MRI data are being increasingly used to address this issue. Numerous commercial and non-commercial software solutions for automated brain segmentation and volumetry exist, with FreeSurfer being the most frequently used.

Objectives

This Review is an account of the current situation regarding the application of automated brain segmentation and volumetry to dementia diagnosis.

Methods

We performed a PubMed search for “FreeSurfer AND Dementia” and obtained 493 results. Based on these search results, we conducted an in-depth source analysis to identify additional publications, software tools, and methods. Studies were analyzed for design, patient collective, and for statistical evaluation (mathematical methods, correlations).

Results

In the studies identified, the main diseases and cohorts represented were Alzheimer’s disease (n = 276), mild cognitive impairment (n = 157), frontotemporal dementia (n = 34), Parkinson’s disease (n = 29), dementia with Lewy bodies (n = 20), and healthy controls (n = 356). The findings and methods of a selection of the studies identified were summarized and discussed.

Conclusion

Our evaluation showed that, while a large number of studies and software solutions are available, many diseases are underrepresented in terms of their incidence. There is therefore plenty of scope for targeted research.

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.

MRI-based axis-referenced morphometric model corresponding to lamellar organization for assessing hippocampal atrophy in dementia

Research on the local hippocampal atrophy for early detection of dementia has gained considerable attention. However, accurately quantifying subtle atrophy remains challenging in existing morphological methods due to the lack of consistent biological correspondence with the complex curving regions like the hippocampal head. Thereby, this article presents an innovative axis-referenced morphometric model (ARMM) that follows the anatomical lamellar organization of the hippocampus, which capture its precise and consistent longitudinal curving trajectory. Specifically, we establish an "axis-referenced coordinate system" based on a 7 T ex vivo hippocampal atlas following its entire curving longitudinal axis and orthogonal distributed lamellae. We then align individual hippocampi by deforming this template coordinate system to target spaces using boundary-guided diffeomorphic transformation, while ensuring that the lamellar vectors adhere to the constraint of medial-axis geometry. Finally, we measure local thickness and curvatures based on the coordinate system and boundary surface reconstructed from vector tips. The morphometric accuracy is evaluated by comparing reconstructed surfaces with those directly extracted from 7 T and 3 T MRI hippocampi. The results demonstrate that ARMM achieves the best performance, particularly in the curving head, surpassing the state-of-the-art morphological models. Additionally, morphological measurements from ARMM exhibit higher discriminatory power in distinguishing early Alzheimer's disease from mild cognitive impairment compared to volume-based measurements. Overall, the ARMM offers a precise morphometric assessment of hippocampal morphology on MR images, and sheds light on discovering potential image markers for neurodegeneration associated with hippocampal impairment.

The spatial distribution of coupling between tau and neurodegeneration in amyloid-β positive mild cognitive impairment

Synergies between amyloid-β (Aβ), tau, and neurodegeneration persist along the Alzheimer's disease (AD) continuum. This study aimed to evaluate the extent of spatial coupling between tau and neurodegeneration (atrophy) and its relation to Aβ positivity in mild cognitive impairment (MCI). Data from 409 participants were included (95 cognitively normal controls, 158 Aβ positive (Aβ+) MCI, and 156 Aβ negative (Aβ-) MCI). Florbetapir PET, Flortaucipir PET, and structural MRI were used as biomarkers for Aβ, tau and atrophy, respectively. Individual correlation matrices for tau load and atrophy were used to layer a multilayer network, with separate layers for tau and atrophy. A measure of coupling between corresponding regions of interest (ROIs) in the tau and atrophy layers was computed, as a function of Aβ positivity. Fewer than 25% of the ROIs across the brain showed heightened coupling between tau and atrophy in Aβ+ , relative to Aβ- MCI. Coupling strengths in the right rostral middle frontal and right paracentral gyri, in particular, mediated the association between Aβ burden and cognition in this sample.

Examining Frontal Lobe Asymmetry and Its Potential Role in Aggressive Behaviors in Early Alzheimer's Disease

Background

Neuropsychiatric symptoms (NPS) in patients with dementia lead to caregiver burdens and worsen the patient's prognosis. Although many neuroimaging studies have been conducted, the etiology of NPS remains complex. We hypothesize that brain structural asymmetry could play a role in the appearance of NPS.

Objective

This study explores the relationship between NPS and brain asymmetry in patients with Alzheimer's disease (AD).

Methods

Demographic and MRI data for 121 mild AD cases were extracted from a multicenter Japanese database. Brain asymmetry was assessed by comparing the volumes of gray matter in the left and right brain regions. NPS was evaluated using the Neuropsychiatric Inventory (NPI). Subsequently, a comprehensive assessment of the correlation between brain asymmetry and NPS was conducted.

Results

Among each NPS, aggressive NPS showed a significant correlation with asymmetry in the frontal lobe, indicative of right-side atrophy (r = 0.235, p = 0.009). This correlation remained statistically significant even after adjustments for multiple comparisons (p < 0.01). Post-hoc analysis further confirmed this association (p < 0.05). In contrast, no significant correlations were found for other NPS subtypes, including affective and apathetic symptoms.

Conclusions

The study suggests frontal lobe asymmetry, particularly relative atrophy in the right hemisphere, may be linked to aggressive behaviors in early AD. These findings shed light on the neurobiological underpinnings of NPS, contributing to the development of potential interventions.

Handgrip strength asymmetry and cognitive impairment risk: Insights from a seven-year prospective cohort study

OBJECTIVES

This study aimed to explore the links of handgrip strength and asymmetry with cognitive impairment.

DESIGN

This was a seven-year prospective cohort study.

SETTING AND PARTICIPANTS

We used data from wave 3 (2015-2017) to wave 5 (2019-2022) from the ongoing Taiwan Initiative of Geriatric Epidemiological Research (TIGER), with wave 3 as the baseline (n = 446). The study included community-dwelling participants aged 65 years or older.

MEASUREMENTS

Handgrip strength was measured, and abnormalities were determined based on handgrip strength weakness and asymmetry. Handgrip strength asymmetry was categorized into three groups at baseline based on the handgrip strength ratio (left handgrip strength/right handgrip strength). Cognitive tests evaluating global and specific cognitive domains were conducted at baseline and two biennial follow-ups. Generalized linear mixed models were utilized to assess the associations of abnormal handgrip strength with global cognition and multiple cognitive domain progression over time.

RESULTS

This study included 392 dementia-free participants, with an average age of 75.8 years and 179 (45.7%) males. Mild handgrip strength asymmetry was present in 88 participants (22.4%), while 53 (13.5%) exhibited moderate asymmetry. In men, the coexistence of low handgrip strength and handgrip strength asymmetry was linked to cognitive impairment over time. These associations were observed in global cognition (β^ = -1.76, 95% CI: -2.79 to -0.74), memory (immediate free recall: β^ = -0.67, 95% CI: -1.17 to -0.17), executive function (Trail Making Test-A: β^ = -0.54, 95% CI: -0.94 to -0.13), and attention (Digit span-forward: β^ = -1.00, 95% CI: -1.46 to -0.54).

CONCLUSIONS

This study found that individuals with reduced handgrip strength and handgrip strength asymmetry had an increased risk of cognitive impairment across various domains. Moreover, this association appears to be more pronounced among men than women. Incorporating these simple assessments into regular clinical practice improves the allocation of limited screening resources and timely clinical interventions in older adults.

Cortical gray matter and cerebral white matter atrophy and asymmetry in Parkinson's disease patients with normal cognitive precede

BACKGROUND

Parkinson's disease is the second most common neurodegenerative disorder with complex and distributed motor and non-motor symptoms. In this study, cortical gray matter (GM) and cerebral white matter (WM) overall atrophy, and asymmetry of atrophy are investigated in PD with normal cognitive function.

METHOD

Forty-eight male Parkinson's disease(PD) patients with normal cognitive precede (PD-NC), and thirty matched healthy control (HC) subjects were selected from the Parkinson's Progression Markers Initiative (PPMI) database. Brain structures volumes were extracted using Freesurfer software based on subject 3 tesla MRI images. The normalized volume of cortical GM and cerebral WM were compared in two study groups, and then the asymmetry index (AI) of GM and WM atrophy was also assessed in two groups. Statistical analysis was constructed using a t-test with p < 0.05 of significance.

RESULTS

No significant difference was observed in the volume of cortical GM and cerebral WM in the two study groups. The cortical GM asymmetry index in the PD-NC group was significantly (p = 0.01) higher than the HC group, however, no difference was observed for the cerebral WM asymmetry index.

CONCLUSION

Atrophy in cortical GM and WM was not observed between the PD-NC and the HC group, however, the asymmetry index in GM was significant between the two group. It seems that the brain's bilateral balance has ruptured in PD. Cortical GM asymmetry in PD-NC can be considered a potent biomarker and should be investigated more in the future. In future studies, construction of a longitudinal study on this issue could be useful.

Machine learning classifiers and associations of cognitive performance with hippocampal subfields in amnestic mild cognitive impairment

Background

Neuroimaging studies have demonstrated alterations in hippocampal volume and hippocampal subfields among individuals with amnestic mild cognitive impairment (aMCI). However, research on using hippocampal subfield volume modeling to differentiate aMCI from normal controls (NCs) is limited, and the relationship between hippocampal volume and overall cognitive scores remains unclear.

Methods

We enrolled 50 subjects with aMCI and 44 NCs for this study. Initially, a univariate general linear model was employed to analyze differences in the volumes of hippocampal subfields. Subsequently, two sets of dimensionality reduction methods and four machine learning techniques were applied to distinguish aMCI from NCs based on hippocampal subfield volumes. Finally, we assessed the correlation between the relative volumes of hippocampal subfields and cognitive test variables (Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment Scale (MoCA)).

Results

Significant volume differences were observed in several hippocampal subfields, notably in the left hippocampus. Specifically, the volumes of the hippocampal tail, subiculum, CA1, presubiculum, molecular layer, GC-ML-DG, CA3, CA4, and fimbria differed significantly between the two groups. The highest area under the curve (AUC) values for left and right hippocampal machine learning classifiers were 0.678 and 0.701, respectively. Moreover, the volumes of the left subiculum, left molecular layer, right subiculum, right CA1, right molecular layer, right GC-ML-DG, and right CA4 exhibited the strongest and most consistent correlations with MoCA scores.

Conclusion

Hippocampal subfield volume may serve as a predictive marker for aMCI. These findings underscore the sensitivity of hippocampal subfield volume to overall cognitive performance.