Local amygdala structural differences with 3T MRI in patients with Alzheimer disease

Association between subcortical nuclei volume changes and cognition in preschool-aged children with tetralogy of Fallot after corrective surgery: a cross-sectional study

BACKGROUND

Neurocognitive disorders frequently occur in patients with cyanotic congenital heart disease (CCHD) because of the hemodynamic abnormalities induced by preoperative cardiac structural changes. We aimed to evaluate subcortical nuclei volume changes and cognition in postoperative tetralogy of Fallot (TOF) children, and analyze their relationship with preoperative cardiac structural changes.

METHODS

This case-control study involved thirty-six children with repaired TOF and twenty-nine healthy controls (HCs). We utilized three-dimensional (3D) T1-weighted high-resolution structural images alongside the Wechsler Preschool and Primary Scale of Intelligence-Fourth Edition (WPPSI-IV) to evaluate the cognitive differences between the TOF and HC group.

RESULTS

We observed notable differences in subcortical nuclei volume between the TOF and HC group, specifically in the left amygdala nucleus (LAM, TOF: 1292.60 ± 155.57; HC: 1436.27 ± 140.62, p < 0.001), left thalamus proper nucleus (LTHA, TOF: 6771.54 ± 666.03; HC: 7435.36 ± 532.84, p < 0.001), and right thalamus proper nucleus (RTHA, TOF: 6514.61 ± 715.23; HC: 7162.94 ± 554.60, p < 0.001). Furthermore, a diminished integrity of LAM ( β:-19.828, 95% CI: -36.462, -3.193), which showed an inverse relationship with the size of the preoperative ventricular septal defect (VSD), correlated with lower working memory indices in children with TOF.

CONCLUSIONS

Our findings indicate that subcortical nuclei structural injuries possibly potentially stemming from cardiac anatomical abnormalities, are associated with impaired working memory in preschool-aged children with TOF. The LAM in particular may serve as a potential biomarker for neurocognitive deficits in TOF, offering predictive value for future neurodevelopmental outcomes, and shedding light on the neurophysiological mechanisms of these cognitive impairments.

Alcohol Use Disorder and Dementia: A Review

PURPOSE

By 2040, 21.6% of Americans will be over age 65, and the population of those older than age 85 is estimated to reach 14.4 million. Although not causative, older age is a risk factor for dementia: every 5 years beyond age 65, the risk doubles; approximately one-third of those older than age 85 are diagnosed with dementia. As current alcohol consumption among older adults is significantly higher compared to previous generations, a pressing question is whether drinking alcohol increases the risk for Alzheimer's disease or other forms of dementia.

SEARCH METHODS

Databases explored included PubMed, Web of Science, and ScienceDirect. To accomplish this narrative review on the effects of alcohol consumption on dementia risk, the literature covered included clinical diagnoses, epidemiology, neuropsychology, postmortem pathology, neuroimaging and other biomarkers, and translational studies. Searches conducted between January 12 and August 1, 2023, included the following terms and combinations: "aging," "alcoholism," "alcohol use disorder (AUD)," "brain," "CNS," "dementia," "Wernicke," "Korsakoff," "Alzheimer," "vascular," "frontotemporal," "Lewy body," "clinical," "diagnosis," "epidemiology," "pathology," "autopsy," "postmortem," "histology," "cognitive," "motor," "neuropsychological," "magnetic resonance," "imaging," "PET," "ligand," "degeneration," "atrophy," "translational," "rodent," "rat," "mouse," "model," "amyloid," "neurofibrillary tangles," "α-synuclein," or "presenilin." When relevant, "species" (i.e., "humans" or "other animals") was selected as an additional filter. Review articles were avoided when possible.

SEARCH RESULTS

The two terms "alcoholism" and "aging" retrieved about 1,350 papers; adding phrases-for example, "postmortem" or "magnetic resonance"-limited the number to fewer than 100 papers. Using the traditional term, "alcoholism" with "dementia" resulted in 876 citations, but using the currently accepted term "alcohol use disorder (AUD)" with "dementia" produced only 87 papers. Similarly, whereas the terms "Alzheimer's" and "alcoholism" yielded 318 results, "Alzheimer's" and "alcohol use disorder (AUD)" returned only 40 citations. As pertinent postmortem pathology papers were published in the 1950s and recent animal models of Alzheimer's disease were created in the early 2000s, articles referenced span the years 1957 to 2024. In total, more than 5,000 articles were considered; about 400 are herein referenced.

DISCUSSION AND CONCLUSIONS

Chronic alcohol misuse accelerates brain aging and contributes to cognitive impairments, including those in the mnemonic domain. The consensus among studies from multiple disciplines, however, is that alcohol misuse can increase the risk for dementia, but not necessarily Alzheimer's disease. Key issues to consider include the reversibility of brain damage following abstinence from chronic alcohol misuse compared to the degenerative and progressive course of Alzheimer's disease, and the characteristic presence of protein inclusions in the brains of people with Alzheimer's disease, which are absent in the brains of those with AUD.

Identification of amnestic mild cognitive impairment by structural and functional MRI using a machine-learning approach

OBJECTIVE

The importance of early treatment for mild cognitive impairment (MCI) has been extensively shown. However, classifying patients presenting with memory complaints in clinical practice as having MCI vs normal results is difficult. Herein, we assessed the feasibility of applying a machine learning approach based on structural volumes and functional connectomic profiles to classify the cognitive levels of cognitively unimpaired (CU) and amnestic MCI (aMCI) groups. We further applied the same method to distinguish aMCI patients with a single memory impairment from those with multiple memory impairments.

METHODS

Fifty patients with aMCI were enrolled and classified as having either verbal or visual-aMCI (verbal or visual memory impairment), or both aMCI (verbal and visual memory impairments) based on memory test results. In addition, 26 CU patients were enrolled in the control group. All patients underwent structural T1-weighted magnetic resonance imaging (MRI) and resting-state functional MRI. We obtained structural volumes and functional connectomic profiles from structural and functional MRI, respectively, using graph theory. A support vector machine (SVM) algorithm was employed, and k-fold cross-validation was performed to discriminate between groups.

RESULTS

The SVM classifier based on structural volumes revealed an accuracy of 88.9% at classifying the cognitive levels of patients with CU and aMCI. However, when the structural volumes and functional connectomic profiles were combined, the accuracy increased to 92.9%. In the classification of verbal or visual-aMCI (n = 22) versus both aMCI (n = 28), the SVM classifier based on structural volumes revealed a low accuracy of 36.7%. However, when the structural volumes and functional connectomic profiles were combined, the accuracy increased to 53.1%.

CONCLUSION

Structural volumes and functional connectomic profiles obtained using a machine learning approach can be used to classify cognitive levels to distinguish between aMCI and CU patients. In addition, combining the functional connectomic profiles with structural volumes results in a better classification performance than the use of structural volumes alone for identifying both "aMCI versus CU" and "verbal- or visual-aMCI versus both aMCI" patients.

Fine-grained features characterize hippocampal and amygdaloid change pattern in Parkinson's disease and discriminate cognitive-deficit subtype

AIMS

To extract vertex-wise features of the hippocampus and amygdala in Parkinson's disease (PD) with mild cognitive impairment (MCI) and normal cognition (NC) and further evaluate their discriminatory efficacy.

METHODS

High-resolution 3D-T1 data were collected from 68 PD-MCI, 211 PD-NC, and 100 matched healthy controls (HC). Surface geometric features were captured using surface conformal representation, and surfaces were registered to a common template using fluid registration. The statistical tests were performed to detect differences between groups. The disease-discriminatory ability of features was also tested in the ensemble classifiers.

RESULTS

The amygdala, not the hippocampus, showed significant overall differences among the groups. Compared with PD-NC, the right amygdala in MCI patients showed expansion (anterior cortical, anterior amygdaloid, and accessory basal areas) and atrophy (basolateral ventromedial area) subregions. There was notable atrophy in the right CA1 and hippocampal subiculum of PD-MCI. The accuracy of classifiers with multivariate morphometry statistics as features exceeded 85%.

CONCLUSION

PD-MCI is associated with multiscale morphological changes in the amygdala, as well as subtle atrophy in the hippocampus. These novel metrics demonstrated the potential to serve as biomarkers for PD-MCI diagnosis. Overall, these findings from this study help understand the role of subcortical structures in the neuropathological mechanisms of PD cognitive impairment.

Differential alterations of amygdala nuclei volumes in acutely ill patients with anorexia nervosa and their associations with leptin levels

BACKGROUND

The amygdala is a subcortical limbic structure consisting of histologically and functionally distinct subregions. New automated structural magnetic resonance imaging (MRI) segmentation tools facilitate the in vivo study of individual amygdala nuclei in clinical populations such as patients with anorexia nervosa (AN) who show symptoms indicative of limbic dysregulation. This study is the first to investigate amygdala nuclei volumes in AN, their relationships with leptin, a key indicator of AN-related neuroendocrine alterations, and further clinical measures.

METHODS

T1-weighted MRI scans were subsegmented and multi-stage quality controlled using FreeSurfer. Left/right hemispheric amygdala nuclei volumes were cross-sectionally compared between females with AN (n = 168, 12-29 years) and age-matched healthy females (n = 168) applying general linear models. Associations with plasma leptin, body mass index (BMI), illness duration, and psychiatric symptoms were analyzed via robust linear regression.

RESULTS

Globally, most amygdala nuclei volumes in both hemispheres were reduced in AN v. healthy control participants. Importantly, four specific nuclei (accessory basal, cortical, medial nuclei, corticoamygdaloid transition in the rostral-medial amygdala) showed greater volumetric reduction even relative to reductions of whole amygdala and total subcortical gray matter volumes, whereas basal, lateral, and paralaminar nuclei were less reduced. All rostral-medially clustered nuclei were positively associated with leptin in AN independent of BMI. Amygdala nuclei volumes were not associated with illness duration or psychiatric symptom severity in AN.

CONCLUSIONS

In AN, amygdala nuclei are altered to different degrees. Severe volume loss in rostral-medially clustered nuclei, collectively involved in olfactory/food-related reward processing, may represent a structural correlate of AN-related symptoms. Hypoleptinemia might be linked to rostral-medial amygdala alterations.

Atrophy of specific amygdala subfields in subjects converting to mild cognitive impairment

Introduction

Accumulating evidence indicates that the amygdala exhibits early signs of Alzheimer's disease (AD) pathology. However, it is still unknown whether the atrophy of distinct subfields of the amygdala also participates in the transition from healthy cognition to mild cognitive impairment (MCI).

Methods

Our sample was derived from the AD Neuroimaging Initiative 3 and consisted of 97 cognitively healthy (HC) individuals, sorted into two groups based on their clinical follow-up: 75 who remained stable (s-HC) and 22 who converted to MCI within 48 months (c-HC). Anatomical magnetic resonance (MR) images were analyzed using a semi-automatic approach that combines probabilistic methods and a priori information from ex vivo MR images and histology to segment and obtain quantitative structural metrics for different amygdala subfields in each participant. Spearman's correlations were performed between MR measures and baseline and longitudinal neuropsychological measures. We also included anatomical measurements of the whole amygdala, the hippocampus, a key target of AD-related pathology, and the whole cortical thickness as a test of spatial specificity.

Results

Compared with s-HC individuals, c-HC subjects showed a reduced right amygdala volume, whereas no significant difference was observed for hippocampal volumes or changes in cortical thickness. In the amygdala subfields, we observed selected atrophy patterns in the basolateral nuclear complex, anterior amygdala area, and transitional area. Macro-structural alterations in these subfields correlated with variations of global indices of cognitive performance (measured at baseline and the 48-month follow-up), suggesting that amygdala changes shape the cognitive progression to MCI.

Discussion

Our results provide anatomical evidence for the early involvement of the amygdala in the preclinical stages of AD.

Highlights

Amygdala's atrophy marks elderly progression to mild cognitive impairment (MCI).Amygdala's was observed within the basolateral and amygdaloid complexes.Macro-structural alterations were associated with cognitive decline.No atrophy was found in the hippocampus and cortex.

Neuroimaging modalities in the detection of Alzheimer's disease-associated biomarkers

Alzheimer's disease (AD) is the most common cause of dementia. Neuropathological changes in AD patients occur up to 10-20 years before the emergence of clinical symptoms. Specific diagnosis and appropriate intervention strategies are crucial during the phase of mild cognitive impairment (MCI) and AD. The detection of biomarkers has emerged as a promising tool for tracking the efficacy of potential therapies, making an early disease diagnosis, and prejudging treatment prognosis. Specifically, multiple neuroimaging modalities, including magnetic resonance imaging (MRI), positron emission tomography, optical imaging, and single photon emission-computed tomography, have provided a few potential biomarkers for clinical application. The MRI modalities described in this review include structural MRI, functional MRI, diffusion tensor imaging, magnetic resonance spectroscopy, and arterial spin labelling. These techniques allow the detection of presymptomatic diagnostic biomarkers in the brains of cognitively normal elderly people and might also be used to monitor AD disease progression after the onset of clinical symptoms. This review highlights potential biomarkers, merits, and demerits of different neuroimaging modalities and their clinical value in MCI and AD patients. Further studies are necessary to explore more biomarkers and overcome the limitations of multiple neuroimaging modalities for inclusion in diagnostic criteria for AD.

A comparison of the five-minute cognitive test with the mini-mental state examination in the elderly for cognitive impairment screening

The five-minute cognitive test (FCT) is a novel cognitive screening method with the quick and reliable merit for detecting cognitive impairment at an early stage. The diagnostic power of FCT in differentiating subjects with cognitive impairment from people with cognition in a normal range was demonstrated effective as that of the Mini-Mental Status Evaluation (MMSE) in a previous cohort study. Here, we analyzed the effect of sociodemographic and health-related factors on FCT performance and further investigated the consistency of FCT. Then, we compared the correlation of subitem scores of FCT or MMSE with a comprehensive battery of neuropsychological tests that focus on specific domains of cognition. Finally, the association of the total FCT scores with the volumes of brain subregions was investigated. There were 360 subjects aged 60 years or above enrolled in this study, including 226 adults with cognitive abilities in normal range, 107 subjects with mild cognitive impairment (MCI) and 27 mild Alzheimer's disease (AD). The results showed that the total FCT scores was negatively associated with increasing age (β = -0.146, p < 0.001), and positively associated with education attainment (β = 0.318, p < 0.001), dwelling condition with family (β = 0.153, p < 0.001) and the Body Mass Index (β = 1.519, p < 0.01). The internal consistency of the FCT (Cronbach's α) was 0.644. The sub-scores of FCT showed a significant correlation with other specific neuropsychological tests. Impressively, the total FCT scores showed a significantly positive association with the volumes of hippocampus related subregions (r = 0.523, p < 0.001) and amygdala (r = 0.479, p < 0.001), but not with cerebellum (r = 0.158, p > 0.05) or subcortical subregions (r = 0.070, p > 0.05). Combining with previous data, FCT is a reliable and valid cognitive screening test for detecting cognitive impairment in a community setting.

Amygdala activity and amygdala-hippocampus connectivity: Metabolic diseases, dementia, and neuropsychiatric issues

With rapid aging of the population worldwide, the number of people with dementia is dramatically increasing. Some studies have emphasized that metabolic syndrome, which includes obesity and diabetes, leads to increased risks of dementia and cognitive decline. Factors such as insulin resistance, hyperglycemia, high blood pressure, dyslipidemia, and central obesity in metabolic syndrome are associated with synaptic failure, neuroinflammation, and imbalanced neurotransmitter levels, leading to the progression of dementia. Due to the positive correlation between diabetes and dementia, some studies have called it "type 3 diabetes". Recently, the number of patients with cognitive decline due to metabolic imbalances has considerably increased. In addition, recent studies have reported that neuropsychiatric issues such as anxiety, depressive behavior, and impaired attention are common factors in patients with metabolic disease and those with dementia. In the central nervous system (CNS), the amygdala is a central region that regulates emotional memory, mood disorders, anxiety, attention, and cognitive function. The connectivity of the amygdala with other brain regions, such as the hippocampus, and the activity of the amygdala contribute to diverse neuropathological and neuropsychiatric issues. Thus, this review summarizes the significant consequences of the critical roles of amygdala connectivity in both metabolic syndromes and dementia. Further studies on amygdala function in metabolic imbalance-related dementia are needed to treat neuropsychiatric problems in patients with this type of dementia.

18F-AV45 PET and MRI Reveal the Influencing Factors of Alzheimer's Disease Biomarkers in Subjective Cognitive Decline Population

BACKGROUND

Subjective cognitive decline (SCD) is a self-perceived decline in cognitive ability, which exhibits no objective impairment but increased risk of conversion to mild cognitive impairment and Alzheimer's disease (AD).

OBJECTIVE

To investigate how influencing factors (risk gene, age, sex, and education) affect amyloid-β (Aβ) deposition and gray matter (GM) atrophy in SCD population.

METHODS

281 SCD subjects were included in this study, who underwent clinical evaluation, cognitive ability assessment, apolipoprotein E (APOE) genotyping, 18F-Florbetapir positron emission computed tomography, and magnetic resonance imaging screening. Two-sample t tests and analysis of variance were performed based on voxel-wise outcome.

RESULTS

In 281 SCD subjects with an average age of 63.86, 194 subjects (69.04%) were female, and 56 subjects carried APOE ɛ4 genes. Statistical results revealed APOE ɛ4 gene, age, and sex influenced Aβ deposition in different brain regions; moreover, only the interaction exhibited between age and APOE ɛ4 genes. The GM atrophy of hippocampal, amygdala, precentral, and occipital lobes occurred in the group age over 60. The GM volume of the hippocampal, frontal, and occipital lobe in females was less than males. Education has an effect only on cognitive function.

CONCLUSION

In SCD, APOE ɛ4 gene, age, and sex significantly influenced Aβ deposition and APOE ɛ4 gene can interact with age in impacting Aβ deposition. Both age and sex can affect GM atrophy. The results suggested that female SCD with APOE ɛ4 genes and aged more than 60 years old might exhibit advanced AD biomarkers.

Functional Magnetic Resonance Spectroscopy of Lactate in Alzheimer Disease: A Comprehensive Review of Alzheimer Disease Pathology and the Role of Lactate

ABSTRACT

Functional 1H magnetic resonance spectroscopy (fMRS) is a derivative of dynamic MRS imaging. This modality links physiologic metabolic responses with available activity and measures absolute or relative concentrations of various metabolites. According to clinical evidence, the mitochondrial glycolysis pathway is disrupted in many nervous system disorders, especially Alzheimer disease, resulting in the activation of anaerobic glycolysis and an increased rate of lactate production. Our study evaluates fMRS with J-editing as a cutting-edge technique to detect lactate in Alzheimer disease. In this modality, functional activation is highlighted by signal subtractions of lipids and macromolecules, which yields a much higher signal-to-noise ratio and enables better detection of trace levels of lactate compared with other modalities. However, until now, clinical evidence is not conclusive regarding the widespread use of this diagnostic method. The complex machinery of cellular and noncellular modulators in lactate metabolism has obscured the potential roles fMRS imaging can have in dementia diagnosis. Recent developments in MRI imaging such as the advent of 7 Tesla machines and new image reconstruction methods, coupled with a renewed interest in the molecular and cellular basis of Alzheimer disease, have reinvigorated the drive to establish new clinical options for the early detection of Alzheimer disease. Based on the latter, lactate has the potential to be investigated as a novel diagnostic and prognostic marker for Alzheimer disease.

Periodic limb movements in sleep are linked to decreased hippocampus and amygdala volumes in the population-based BiDirect Study

STUDY OBJECTIVES

Even though numerous studies indicate that sleep disorders are associated with altered brain morphology, MRI studies focusing on periodic limb movements in sleep (PLMS) are scarce. Our aim was to investigate the association of PLMS with global and regional gray matter volumes as well as white matter hyperintensity (WMH) volume.

METHODS

One hundred and eighty-nine subjects (57.0 ± 7.8 years, women: 50.5%) of the population-based BiDirect Study underwent a single-night polysomnography (PSG). Standard criteria of the American Academy of Sleep Medicine were applied to evaluate sleep characteristics and calculate the PLMS index (PLMSI). T1w and FLAIR images were acquired with cerebral MRI at 3 Tesla. Voxel-based morphometry was performed to determine the total gray matter volume as well as the volume of cortical segments and subcortical gray matter areas using SPM12 and CAT12. The WMH volume was quantified with the Brain Intensity AbNormality Classification Algorithm. The independent relationship between MRI markers and PLMSI was analyzed using multivariable linear regression with adjustment for age, sex, body mass index, intracranial volume, PSG scorer, PSG device, sleep apnea, and the use of antidepressants.

RESULTS

PLMSI was not significantly related to global gray matter volume and WMH volume. However, significant inverse associations of the PLMSI with the volume of the hippocampus (left and right hemisphere) and left amygdala were observed.

CONCLUSIONS

A significant relationship between a higher PLMSI and lower volumes of the hippocampus and amygdala was found among the participants of the BiDirect Study. Since these associations are based on exploratory analyses, further replications are required before drawing firm conclusions.

Individuals with cannabis use are associated with widespread morphological alterations in the subregions of the amygdala, hippocampus, and pallidum

BACKGROUND

Cannabis is the most frequently used illicit drug worldwide. Although multiple structural MRI studies of individuals with cannabis use (CB) have been undertaken, the reports of the volume alterations in the amygdala, hippocampus, and pallidum are not consistent. This study aims to detect subregion-level morphological alterations, analyze the correlation areas with cannabis usage characteristics, and gain new insights into the neuro mechanisms of CB.

METHODS

By leveraging the novel surface-based subcortical morphometry method, 20 CB and 22 age- and sex-matched healthy controls (HC) were included to explore their volumetric and morphological differences in the three subcortical structures. Afterward, the correlation analysis between surface morphological eigenvalues and cannabis usage characteristics was performed.

RESULTS

Compared with volumetric measures, the surface-based subcortical morphometry method detected more significant global morphological deformations in the left amygdala, right hippocampus, and right pallidum (overall-p < 0.05, corrected). More obvious morphological alterations (atrophy or expansion) were observed in specific subregions (vertex-based p-value<0.05, uncorrected) of the three subcortical structures. Both positive and negative subregional correlation areas were reported by the correlation analysis.

CONCLUSIONS

The current study illuminated new pathophysiologic mechanisms in the amygdala, hippocampus, and pallidum at the subregion level, which may inform the subsequent smaller-scale CB research.

Diagnosis of Alzheimer's Disease using Structure Highlighting Key Slice Stacking and Transfer Learning

BACKGROUND

In recent years, two-dimensional convolutional neural network (2D CNN) have been widely used in the diagnosis of Alzheimer's disease (AD) based on structural magnetic resonance imaging (sMRI). However, due to the lack of targeted processing of the key slices of sMRI images, the classification performance of the CNN model needs to be improved.

PURPOSE

Therefore, in this paper, we propose a key slice processing technique called the structural highlighting key slice stacking (SHKSS) technique, and we apply it to a 2D transfer learning model for AD classification.

METHODS

Specifically, first, 3D MR images were preprocessed. Second, the 2D axial middle-layer image was extracted from the MR image as a key slice. Then, the image was normalized by intensity and mapped to the RGB space, and histogram specification was performed on the obtained RGB image to generate the final three-channel image. The final three-channel image was input into a pre-trained CNN model for AD classification. Finally, classification and generalization experiments were conducted to verify the validity of the proposed method.

RESULTS

The experimental results on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset show that our SHKSS method can effectively highlight the structural information in MRI slices. Compared with existing key slice processing techniques, our SHKSS method has an average accuracy improvement of at least 26% on the same test dataset, and it has better performance and generalization ability.

CONCLUSIONS

Our SHKSS method not only converts single-channel images into three-channel images to match the input requirements of the 2D transfer learning model but also highlights the structural information of MRI slices to improve the accuracy of AD diagnosis. This article is protected by copyright. All rights reserved.

Correlation Between Amygdala Nuclei Volumes and Memory in Cognitively Normal Adults Carrying the ApoE ε3/ε3 Allele

The amygdala is known to be related to cognitive function. In this study, we used an automated approach to segment the amygdala into nine nuclei and evaluated amygdala and nuclei volumetric changes across the adult lifespan in subjects carrying the apolipoprotein E (ApoE) ε3/ε3 allele, and we related those changes to memory function alteration. We found that except the left medial nucleus (Me), whose volume decreased in the old group compared with the middle-early group, all other nuclei volumes presented a significant decline in the old group compared with the young group. Left accessory basal nucleus (AB) and left cortico-amygdaloid transition area (CAT) volumes were also diminished in the middle-late group. In addition, immediate memory recall is impaired by the process of aging, whereas delayed recall and delayed recognition memory functions were not significantly changed. We found significant positive correlations between immediate recall scores and volumes of the bilateral basal nucleus (Ba), AB, anterior amygdaloid area (AAA), CAT, whole amygdala, left lateral nucleus (La), left paralaminar nucleus (PL), and right cortical nucleus (Co). The results suggest that immediate recall memory decline might be associated with volumetric reduction of the amygdala and its nuclei, and the left AB and left CAT might be considered as potential imaging biomarkers of memory decline in aging.

Synergistic Effects of APOE and CLU May Increase the Risk of Alzheimer's Disease: Acceleration of Atrophy in the Volumes and Shapes of the Hippocampus and Amygdala

BACKGROUND

The volume loss of the hippocampus and amygdala in non-demented individuals has been reported to increase the risk of developing Alzheimer's disease (AD). Many neuroimaging genetics studies mainly focused on the individual effects of APOE and CLU on neuroimaging to understand their neural mechanisms, whereas their synergistic effects have been rarely studied.

OBJECTIVE

To assess whether APOE and CLU have synergetic effects, we investigated the epistatic interaction and combined effects of the two genetic variants on morphological degeneration of hippocampus and amygdala in the non-demented elderly at baseline and 2-year follow-up.

METHODS

Besides the widely-used volume indicator, the surface-based morphometry method was also adopted in this study to evaluate shape alterations.

RESULTS

Our results showed a synergistic effect of homozygosity for the CLU risk allele C in rs11136000 and APOEɛ4 on the hippocampal and amygdalar volumes during a 2-year follow-up. Moreover, the combined effects of APOEɛ4 and CLU C were stronger than either of the individual effects in the atrophy progress of the amygdala.

CONCLUSION

These findings indicate that brain morphological changes are caused by more than one gene variant, which may help us to better understand the complex endogenous mechanism of AD.

High-resolution Structural Magnetic Resonance Imaging and Quantitative Susceptibility Mapping

High-resolution 7-T imaging and quantitative susceptibility mapping produce greater anatomic detail compared with conventional strengths because of improvements in signal/noise ratio and contrast. The exquisite anatomic details of deep structures, including delineation of microscopic architecture using advanced techniques such as quantitative susceptibility mapping, allows improved detection of abnormal findings thought to be imperceptible on clinical strengths. This article reviews caveats and techniques for translating sequences commonly used on 1.5 or 3 T to high-resolution 7-T imaging. It discusses for several broad disease categories how high-resolution 7-T imaging can advance the understanding of various diseases, improve diagnosis, and guide management.

Diagnostic value of amygdala volume on structural magnetic resonance imaging in Alzheimer’s disease

BACKGROUND

The main clinical manifestation of Alzheimer’s disease (AD) is memory loss, which can be accompanied by neuropsychiatric symptoms at different stages of the disease. Amygdala is closely related to emotion and memory.

AIM

To evaluate the diagnostic value of amygdala on structural magnetic resonance imaging (sMRI) for AD.

METHODS

In this study, 22 patients with AD and 26 controls were enrolled. Their amygdala volumes were measured by sMRI and analyzed using an automatic analysis software.

RESULTS

The bilateral amygdala volumes of AD patients were significantly lower than those of the controls and were positively correlated with the hippocampal volumes. Receiver operating characteristic curve analyses showed that the sensitivity of the left and right amygdala volumes in diagnosing AD was 80.8% and 88.5%, respectively. Subgroup analyses showed that amygdala atrophy was more serious in AD patients with neuropsychiatric symptoms, which mainly included irritability (22.73%), sleep difficulties (22.73%), apathy (18.18%), and hallucination (13.64%).

CONCLUSION

Amygdala volumes measured by sMRI can be used to diagnose AD, and amygdala atrophy is more serious in patients with neuropsychiatric symptoms.

Volume Analysis of Brain Cognitive Areas in Alzheimer's Disease: Interim 3-Year Results from the ASCOMALVA Trial

Background:

Cerebral atrophy is a common feature of several neurodegenerative disorders, including Alzheimer’s disease (AD). In AD, brain atrophy is associated with loss of gyri and sulci in the temporal and parietal lobes, and in parts of the frontal cortex and cingulate gyrus.

Objective:

The ASCOMALVA trial has assessed, in addition to neuropsychological analysis, whether the addition of the cholinergic precursor choline alphoscerate to treatment with donepezil has an effect on brain volume loss in patients affected by AD associated with cerebrovascular injury.

Methods:

56 participants to the randomized, placebo-controlled, double-blind ASCOMALVA trial were assigned to donepezil + placebo (D + P) or donepezil + choline alphoscerate (D + CA) treatments and underwent brain magnetic resonance imaging and neuropsychological tests every year for 4 years. An interim analysis of 3-year MRI data was performed by voxel morphometry techniques.

Results:

The D + P group (n = 27) developed atrophy of the gray and white matter with concomitant increase in ventricular space volume. In the D + CA group (n = 29) the gray matter atrophy was less pronounced compared to the D + P group in frontal and temporal lobes, hippocampus, and amygdala. These morphological data are consistent with the results of the neuropsychological tests.

Conclusion:

Our findings indicate that the addition of choline alphoscerate to standard treatment with the cholinesterase inhibitor donepezil counters to some extent the loss in volume occurring in some brain areas of AD patients. The observation of parallel less pronounced decrease in cognitive and functional tests in patients with the same treatment suggests that the morphological changes observed may have functional relevance.

System-Level Analysis of Alzheimer's Disease Prioritizes Candidate Genes for Neurodegeneration

Alzheimer’s disease (AD) is a debilitating neurodegenerative disorder. Since the advent of the genome-wide association study (GWAS) we have come to understand much about the genes involved in AD heritability and pathophysiology. Large case-control meta-GWAS studies have increased our ability to prioritize weaker effect alleles, while the recent development of network-based functional prediction has provided a mechanism by which we can use machine learning to reprioritize GWAS hits in the functional context of relevant brain tissues like the hippocampus and amygdala. In parallel with these developments, groups like the Alzheimer’s Disease Neuroimaging Initiative (ADNI) have compiled rich compendia of AD patient data including genotype and biomarker information, including derived volume measures for relevant structures like the hippocampus and the amygdala. In this study we wanted to identify genes involved in AD-related atrophy of these two structures, which are often critically impaired over the course of the disease. To do this we developed a combined score prioritization method which uses the cumulative distribution function of a gene’s functional and positional score, to prioritize top genes that not only segregate with disease status, but also with hippocampal and amygdalar atrophy. Our method identified a mix of genes that had previously been identified in AD GWAS including APOE, TOMM40, and NECTIN2(PVRL2) and several others that have not been identified in AD genetic studies, but play integral roles in AD-effected functional pathways including IQSEC1, PFN1, and PAK2. Our findings support the viability of our novel combined score as a method for prioritizing region- and even cell-specific AD risk genes.

Hippocampal and Amygdalar Morphological Abnormalities in Alzheimer's Disease Based on Three Chinese MRI Datasets

BACKGROUND

Early detection of Alzheimer's disease (AD) and its early stage, the mild cognitive impairment (MCI), has important scientific, clinical and social significance. Magnetic resonance imaging (MRI) based statistical shape analysis provides an opportunity to detect regional structural abnormalities of brain structures caused by AD and MCI.

OBJECTIVE

In this work, we aimed to employ a well-established statistical shape analysis pipeline, in the framework of large deformation diffeomorphic metric mapping, to identify and quantify the regional shape abnormalities of the bilateral hippocampus and amygdala at different prodromal stages of AD, using three Chinese MRI datasets collected from different domestic hospitals.

METHODS

We analyzed the region-specific shape abnormalities at different stages of the neuropathology of AD by comparing the localized shape characteristics of the bilateral hippocampi and amygdalas between healthy controls and two disease groups (MCI and AD). In addition to group comparison analyses, we also investigated the association between the shape characteristics and the Mini Mental State Examination (MMSE) of each structure of interest in the disease group (MCI and AD combined) as well as the discriminative power of different morphometric biomarkers.

RESULTS

We found the strongest disease pathology (regional atrophy) at the subiculum and CA1 subregions of the hippocampus and the basolateral, basomedial as well as centromedial subregions of the amygdala. Furthermore, the shape characteristics of the hippocampal and amygdalar subregions exhibiting the strongest AD related atrophy were found to have the most significant positive associations with the MMSE. Employing the shape deformation marker of the hippocampus or the amygdala for automated MCI or AD detection yielded a significant accuracy boost over the corresponding volume measurement.

CONCLUSION

Our results suggested that the amygdalar and hippocampal morphometrics, especially those of shape morphometrics, can be used as auxiliary indicators for monitoring the disease status of an AD patient.

Oxytocin and elderly MRI-based hippocampus and amygdala volume: a 7-year follow-up study

Oxytocin is deeply involved in human relations. In recent years, it is becoming clear that oxytocin is also involved in social cognition and social behaviour. Oxytocin receptors are also thought to be present in the hippocampus and amygdala, and the relationship between oxytocin and the structure and function of the hippocampus and amygdala has been reported. However, a few studies have investigated oxytocin and its relationship to hippocampus and amygdala volume in elderly people. The aim of this study is to investigate the association between serum oxytocin levels and hippocampus and amygdala volume in elderly people. The survey was conducted twice in Kurokawa-cho, Imari, Saga Prefecture, Japan, among people aged 65 years and older. We collected data from 596 residents. Serum oxytocin level measurements, brain MRI, Mini–Mental State Examination and Clinical Dementia Rating were performed in Time 1 (2009–11). Follow-up brain MRI, Mini–Mental State Examination and Clinical Dementia Rating were performed in Time 2 (2016–17). The interval between Time 1 and Time 2 was about 7 years. Fifty-eight participants (14 men, mean age 72.36 ± 3.41 years, oxytocin 0.042 ± 0.052 ng/ml; 44 women, mean age 73.07 ± 4.38 years, oxytocin 0.123 ± 0.130 ng/ml) completed this study. We analysed the correlation between serum oxytocin levels (Time 1) and brain volume (Time 1, Time 2 and Times 1–2 difference) using voxel-based morphometry implemented with Statistical Parametric Mapping. Analysis at the cluster level (family-wise error; P < 0.05) showed a positive correlation between serum oxytocin levels (Time 1) and brain volume of the region containing the left hippocampus and amygdala (Time 2). This result suggests that oxytocin in people aged 65 years and older may be associated with aging-related changes in hippocampus and amygdala volume.

Morphological changes in subregions of hippocampus and amygdala in major depressive disorder patients

Despite many neuroimaging studies in the past years, the neuroanatomical substrates of major depressive disorder (MDD) subcortical structures are still not well understood. Since hippocampus and amygdala are the two vital subcortical structures that most susceptible to MDD, finding the evidence of morphological changes in their subregions may bring some new insights for MDD research. Combining structural magnetic resonance imaging (MRI) with novel morphometry analysis methods, we recruited 25 MDD patients and 28 healthy controls (HC), and investigated their volume and morphological differences in hippocampus and amygdala. Relative to volumetric method, our methods detected more significant global morphological atrophies (p<0.05). More precisely, subiculum and cornu ammonis (CA) 1 subregions of bilateral hippocampus, lateral (LA) and basolateral ventromedial (BLVM) of left amygdala and LA, BLVM, central (CE), amygdalostriatal transition area (ASTR), anterior cortical (ACO) and anterior amygdaloid area (AAA) of right amygdala were demonstrated prone to atrophy. Correlation analyses between each subject's surface eigenvalues and Hamilton Depression Scale (HAMD) were then performed. Correlation results showed that atrophy areas in hippocampus and amygdala have slight tendencies of expanding into other subregions with the development of MDD. Finally, we performed group morphometric analysis and drew the atrophy and expansion areas between MDD-Medicated group (only 19 medicated subjects in MDD group were included) and HC group, found some preliminary evidence about subregional morphological resilience of hippocampus and amygdala. These findings revealed new pathophysiologic patterns in the subregions of hippocampus and amygdala, which can help with subsequent smaller-scale MDD research.

Amygdalar nuclei and hippocampal subfields on MRI: Test-retest reliability of automated volumetry across different MRI sites and vendors

BACKGROUND

The amygdala and the hippocampus are two limbic structures that play a critical role in cognition and behavior, however their manual segmentation and that of their smaller nuclei/subfields in multicenter datasets is time consuming and difficult due to the low contrast of standard MRI. Here, we assessed the reliability of the automated segmentation of amygdalar nuclei and hippocampal subfields across sites and vendors using FreeSurfer in two independent cohorts of older and younger healthy adults.

METHODS

Sixty-five healthy older (cohort 1) and 68 younger subjects (cohort 2), from the PharmaCog and CoRR consortia, underwent repeated 3D-T1 MRI (interval 1-90 days). Segmentation was performed using FreeSurfer v6.0. Reliability was assessed using volume reproducibility error (ε) and spatial overlapping coefficient (DICE) between test and retest session.

RESULTS

Significant MRI site and vendor effects (p ​< ​.05) were found in a few subfields/nuclei for the ε, while extensive effects were found for the DICE score of most subfields/nuclei. Reliability was strongly influenced by volume, as ε correlated negatively and DICE correlated positively with volume size of structures (absolute value of Spearman's r correlations >0.43, p ​< ​1.39E-36). In particular, volumes larger than 200 ​mm³ (for amygdalar nuclei) and 300 ​mm³ (for hippocampal subfields, except for molecular layer) had the best test-retest reproducibility (ε ​< ​5% and DICE ​> ​0.80).

CONCLUSION

Our results support the use of volumetric measures of larger amygdalar nuclei and hippocampal subfields in multisite MRI studies. These measures could be useful for disease tracking and assessment of efficacy in drug trials.

Brain Structural Correlates of Odor Identification in Mild Cognitive Impairment and Alzheimer's Disease Revealed by Magnetic Resonance Imaging and a Chinese Olfactory Identification Test

Alzheimer's disease (AD) is a common memory-impairment disorder frequently accompanied by olfactory identification (OI) impairments. In fact, OI is a valuable marker for distinguishing AD from normal age-related cognitive impairment and may predict the risk of mild cognitive impairment (MCI)-to-AD transition. However, current olfactory tests were developed based on Western social and cultural conditions, and are not very suitable for Chinese patients. Moreover, the neural substrate of OI in AD is still unknown. The present study investigated the utility of a newly developed Chinese smell identification test (CSIT) for OI assessment in Chinese AD and MCI patients. We then performed a correlation analysis of gray matter volume (GMV) at the voxel and region-of-interest (ROI) levels to reveal the neural substrates of OI in AD. Thirty-seven AD, 27 MCI, and 30 normal controls (NCs) completed the CSIT and MRI scans. Patients (combined AD plus MCI) scored significantly lower on the CSIT compared to NCs [F(2,91) = 62.597, p < 0.001)]. Voxel-level GMV analysis revealed strong relationships between CSIT score and volumes of the left precentral gyrus and left inferior frontal gyrus (L-IFG). In addition, ROI-level GMV analysis revealed associations between CSIT score and left amygdala volumes. Our results suggest the following: (1) OI, as measured by the CSIT, is impaired in AD and MCI patients compared with healthy controls in the Chinese population; (2) the severity of OI dysfunction can distinguish patients with cognitive impairment from controls and AD from MCI patients; and (3) the left-precentral cortex and L-IFG may be involved in the processing of olfactory cues.

Electrophysiological evidence of altered facial expressions recognition in Alzheimer's disease: A comprehensive ERP study

OBJECTIVES

The present study aims to evaluate the amplitude and latency of event-related potentials (ERPs) P100, N170, VPP and N230 in individuals with Alzheimer's disease (AD) compared to healthy elderly controls, using a passive viewing task of emotional facial expressions.

METHODS

Twenty-four individuals with mild to moderate AD and 23 demographically matched healthy elderly controls were included in the study. ERP P100, N170, VPP and N230 amplitude and latency values were compared between groups.

RESULTS

The categorization of emotional facial expressions was intact; yet, increased P100 amplitude and latency, decreased N170 amplitude, and increased VPP amplitude were observed in AD compared to controls. Increased N230 amplitude and latency were observed in response to angry expressions, while neutral expressions elicited decreased amplitude and latency.

CONCLUSIONS

Increased P100 amplitude and latency may reflect reduced amygdala volume and disruptions in the visual system, while decreased N170 and increased VPP amplitudes may reflect impaired perceptual processing, mitigated by a greater involvement of prefrontal areas for task performance in AD.

SIGNIFICANCE

This study is the first to report a complex pattern of ERPs to emotional facial expressions in individuals with AD.

Associations of amygdala volume and shape with transactive response DNA-binding protein 43 (TDP-43) pathology in a community cohort of older adults

Transactive response DNA-binding protein 43 (TDP-43) pathology is common in old age and is strongly associated with cognitive decline and dementia above and beyond contributions from other neuropathologies. TDP-43 pathology in aging typically originates in the amygdala, a brain region also affected by other age-related neuropathologies such as Alzheimer's pathology. The purpose of this study was two-fold: to determine the independent effects of TDP-43 pathology on the volume, as well as shape, of the amygdala in a community cohort of older adults, and to determine the contribution of amygdala volume to the variance of the rate of cognitive decline after accounting for the contributions of neuropathologies and demographics. Cerebral hemispheres from 198 participants of the Rush Memory and Aging Project and the Religious Orders Study were imaged with MRI ex vivo and underwent neuropathologic examination. Measures of amygdala volume and shape were extracted for all participants. Regression models controlling for neuropathologies and demographics showed an independent negative association of TDP-43 with the volume of the amygdala. Shape analysis revealed a unique pattern of amygdala deformation associated with TDP-43 pathology. Finally, mixed-effects models showed that amygdala volume explained an additional portion of the variance of the rate of decline in global cognition, episodic memory, semantic memory, and perceptual speed, above and beyond what was explained by demographics and neuropathologies.

Lifespan Changes of the Human Brain In Alzheimer's Disease

Brain imaging studies have shown that slow and progressive cerebral atrophy characterized the development of Alzheimer's Disease (AD). Despite a large number of studies dedicated to AD, key questions about the lifespan evolution of AD biomarkers remain open. When does the AD model diverge from the normal aging model? What is the lifespan trajectory of imaging biomarkers for AD? How do the trajectories of biomarkers in AD differ from normal aging? To answer these questions, we proposed an innovative way by inferring brain structure model across the entire lifespan using a massive number of MRI (N = 4329). We compared the normal model based on 2944 control subjects with the pathological model based on 3262 patients (AD + Mild cognitive Impaired subjects) older than 55 years and controls younger than 55 years. Our study provides evidences of early divergence of the AD models from the normal aging trajectory before 40 years for the hippocampus, followed by the lateral ventricles and the amygdala around 40 years. Moreover, our lifespan model reveals the evolution of these biomarkers and suggests close abnormality evolution for the hippocampus and the amygdala, whereas trajectory of ventricular enlargement appears to follow an inverted U-shape. Finally, our models indicate that medial temporal lobe atrophy and ventricular enlargement are two mid-life physiopathological events characterizing AD brain.

Magnetic resonance imaging in Alzheimer's disease and mild cognitive impairment

Research utilizing magnetic resonance imaging (MRI) has been crucial to the understanding of the neuropathological mechanisms behind and clinical identification of Alzheimer’s disease (AD) and mild cognitive impairment (MCI). MRI modalities show patterns of brain damage that discriminate AD from other brain illnesses and brain abnormalities that are associated with risk of conversion to AD from MCI and other behavioural outcomes. This review discusses the application of various MRI techniques to and their clinical usefulness in AD and MCI. MRI modalities covered include structural MRI, diffusion tensor imaging (DTI), arterial spin labelling (ASL), magnetic resonance spectroscopy (MRS), and functional MRI (fMRI). There is much evidence supporting the validity of MRI as a biomarker for these disorders; however, only traditional structural imaging is currently recommended for routine use in clinical settings. Future research is needed to warrant the inclusion for more advanced MRI methodology in forthcoming revisions to diagnostic criteria for AD and MCI.

Multi-Template Mesiotemporal Lobe Segmentation: Effects of Surface and Volume Feature Modeling

Numerous neurological disorders are associated with atrophy of mesiotemporal lobe structures, including the hippocampus (HP), amygdala (AM), and entorhinal cortex (EC). Accurate segmentation of these structures is, therefore, necessary for understanding the disease process and patient management. Recent multiple-template segmentation algorithms have shown excellent performance in HP segmentation. Purely surface-based methods precisely describe structural boundary but their performance likely depends on a large template library, as segmentation suffers when the boundaries of template and individual MRI are not well aligned while volume-based methods are less dependent. So far only few algorithms attempted segmentation of entire mesiotemporal structures including the parahippocampus. We compared performance of surface- and volume-based approaches in segmenting the three mesiotemporal structures and assess the effects of different environments (i.e., size of templates, under pathology). We also proposed an algorithm that combined surface- with volume-derived similarity measures for optimal template selection. To further improve the method, we introduced two new modules: (1) a non-linear registration that is driven by volume-based intensities and features sampled on deformable template surfaces; (2) a shape averaging based on regional weighting using multi-scale global-to-local icosahedron sampling. Compared to manual segmentations, our approach, namely HybridMulti showed high accuracy in 40 healthy controls (mean Dice index for HP/AM/EC = 89.7/89.3/82.9%) and 135 patients with temporal lobe epilepsy (88.7/89.0/82.6%). This accuracy was comparable across two different datasets of 1.5T and 3T MRI. It resulted in the best performance among tested multi-template methods that were either based on volume or surface data alone in terms of accuracy and sensitivity to detect atrophy related to epilepsy. Moreover, unlike purely surface-based multi-template segmentation, HybridMulti could maintain accurate performance even with a 50% template library size.

Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology

The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of systems dysfunction within distinct molecular, cellular, and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an "omics"-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical, and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND. The goals are to identify common biological denominators or differentiating classifiers across the continuum of ND during detectable stages of pathophysiological progression, characterize systems-based intermediate endophenotypes, validate multi-modal novel diagnostic systems biomarkers, and advance clinical intervention trial designs by utilizing systems-based intermediate endophenotypes and candidate surrogate markers. Achieving these goals is key to the ultimate development of early and effective individualized treatment of ND, such as Alzheimer's disease. The Alzheimer Precision Medicine Initiative (APMI) and cohort program (APMI-CP), as well as the Paris based core of the Sorbonne University Clinical Research Group "Alzheimer Precision Medicine" (GRC-APM) were recently launched to facilitate the passageway from conventional clinical diagnostic and drug development toward breakthrough innovation based on the investigation of the comprehensive biological nature of aging individuals. The APMI movement is gaining momentum to systematically apply both systems neurophysiology and systems biology in exploratory translational neuroscience research on ND.

Exercise decreases BACE and APP levels in the hippocampus of a rat model of Alzheimer's disease

We investigated the effect of treadmill exercise training on the levels of Alzheimer's disease (AD)-related protein molecules in the DG and CA1 areas of a rat model of AD, i.c.v. infusion of Aβ1-42 peptide, 2weeks (250pmol/day). Aβ infusion markedly increased protein levels of amyloid precursor protein (APP), the secretase beta-site APP cleaving enzyme-1 (BACE-1) and Aβ in the CA1 and DG areas. The results also revealed that 4weeks of treadmill exercise prevented the increase in the levels of APP, BACE-1 and Aβ proteins in both hippocampal areas. Exercise, however, did not affect the levels of these proteins in normal rats. We suggest that exercise might be changing the equilibrium of APP processing pathway towards the nonpathogenic pathway most probably via increasing BDNF levels in the brain of AD model.

BIOMARKER CHANGE-POINT ESTIMATION WITH RIGHT CENSORING IN LONGITUDINAL STUDIES

We consider in this paper a statistical two-phase regression model in which the change point of a disease biomarker is measured relative to another point in time, such as the manifestation of the disease, which is subject to right-censoring (i.e., possibly unobserved over the entire course of the study). We develop point estimation methods for this model, based on maximum likelihood, and bootstrap validation methods. The effectiveness of our approach is illustrated by numerical simulations, and by the estimation of a change point for amygdalar atrophy in the context of Alzheimer's disease, wherein it is related to the cognitive manifestation of the disease.

Multimodal Magnetic Resonance Imaging in Alzheimer's Disease Patients at Prodromal Stage

One objective of modern neuroimaging is to identify markers that can aid in diagnosis, monitor disease progression, and impact long-term drug analysis. In this study, physiopathological modifications in seven subcortical structures of patients with mild cognitive impairment (MCI) due to Alzheimer’s disease (AD) were characterized by simultaneously measuring quantitative magnetic resonance parameters that are sensitive to complementary tissue characteristics (e.g., volume atrophy, shape changes, microstructural damage, and iron deposition). Fourteen MCI patients and fourteen matched, healthy subjects underwent 3T-magnetic resonance imaging with whole-brain, T1-weighted, T2^*-weighted, and diffusion-tensor imaging scans. Volume, shape, mean R2^*, mean diffusivity (MD), and mean fractional anisotropy (FA) in the thalamus, hippocampus, putamen, amygdala, caudate nucleus, pallidum, and accumbens were compared between MCI patients and healthy subjects. Comparisons were then performed using voxel-based analyses of R2^*, MD, FA maps, and voxel-based morphometry to determine which subregions showed the greatest difference for each parameter. With respect to the micro- and macro-structural patterns of damage, our results suggest that different and distinct physiopathological processes are present in the prodromal phase of AD. MCI patients had significant atrophy and microstructural changes within their hippocampi and amygdalae, which are known to be affected in the prodromal stage of AD. This suggests that the amygdala is affected in the same, direct physiopathological process as the hippocampus. Conversely, atrophy alone was observed within the thalamus and putamen, which are not directly involved in AD pathogenesis. This latter result may reflect another mechanism, whereby atrophy is linked to indirect physiopathological processes.

Brain atrophy in Alzheimer's Disease and aging

Thanks to its safety and accessibility, magnetic resonance imaging (MRI) is extensively used in clinical routine and research field, largely contributing to our understanding of the pathophysiology of neurodegenerative disorders such as Alzheimer's disease (AD). This review aims to provide a comprehensive overview of the main findings in AD and normal aging over the past twenty years, focusing on the patterns of gray and white matter changes assessed in vivo using MRI. Major progresses in the field concern the segmentation of the hippocampus with novel manual and automatic segmentation approaches, which might soon enable to assess also hippocampal subfields. Advancements in quantification of hippocampal volumetry might pave the way to its broader use as outcome marker in AD clinical trials. Patterns of cortical atrophy have been shown to accurately track disease progression and seem promising in distinguishing among AD subtypes. Disease progression has also been associated with changes in white matter tracts. Recent studies have investigated two areas often overlooked in AD, such as the striatum and basal forebrain, reporting significant atrophy, although the impact of these changes on cognition is still unclear. Future integration of different MRI modalities may further advance the field by providing more powerful biomarkers of disease onset and progression.

Diffeomorphic Surface Registration with Atrophy Constraints

Diffeomorphic registration using optimal control on the diffeomorphism group and on shape spaces has become widely used since the development of the large deformation diffeomorphic metric mapping (LDDMM) algorithm. More recently, a series of algorithms involving sub-Riemannian constraints have been introduced in which the velocity fields that control the shapes in the LDDMM framework are constrained in accordance with a specific deformation model. Here, we extend this setting by considering, for the first time, inequality constraints in order to estimate surface deformations that only allow for atrophy, introducing for this purpose an algorithm that uses the augmented Lagrangian method. We prove the existence of solutions of the associated optimal control problem and the consistency of our approximation scheme. These developments are illustrated by numerical experiments on simulated and real data.

Shape and diffusion tensor imaging based integrative analysis of the hippocampus and the amygdala in Alzheimer's disease

We analyzed, in an integrative fashion, the morphometry and structural integrity of the bilateral hippocampi and amygdalas in Alzheimer's disease (AD) using T1-weighted images and diffusion tensor images (DTIs). We detected significant hippocampal and amygdalar volumetric atrophies in AD relative to healthy controls (HCs). Shape analysis revealed significant region-specific atrophies with the hippocampal atrophy mainly being concentrated on the CA1 and CA2 while the amygdalar atrophy was concentrated on the basolateral and basomedial. In all structures, the structural integrity displayed a significantly decreased mean fractional anisotropy (FA) value and an increased mean trace value in AD. In addition to the inter-group comparisons, we systematically evaluated the discriminative power of our three types of features (volume, shape, and DTI), both individually and in their possible combinations, when differentiating between AD and HCs. We found the volume features to be redundant when the more sophisticated shape features were available. A combination of the shape and DTI features of the right hippocampus, with classification automatically performed by support vector machine, yielded the strongest classification result (overall accuracy, 94.6%; sensitivity, 95.5%; specificity, 93.3%).

Sex differences in amygdala shape: Insights from Turner syndrome

OBJECTIVE

Sex differences in the manifestation of psychiatric disorders, including anxiety disorders, are among the most prominent findings in psychiatry. The study of Turner syndrome (TS), caused by X-monosomy, has the potential to reveal mechanisms that underline male/female differences in neuropsychiatric disorders. The amygdala has been implicated in numerous neuropsychiatric disorders. Previous studies suggest an effect of TS on amygdala volume as well as on amygdala-related behaviors such as anxiety. Our objective is to investigate the amygdala shape in TS. Specifically, we tested whether amygdala enlargements in TS are localized to specific nuclei implicated in anxiety, such as the basomedial nucleus.

EXPERIMENTAL DESIGN

We use a surface-based analytical modeling approach to contrast 41 pre-estrogen treatment girls with TS (mean age 8.6 ± 2.4) with 34 age-and sex-matched typically developing (TD) controls (mean age 8.0 ± 2.8). Anxiety symptoms were assessed using the Revised Children's Manifest Anxiety Scale - 2 (RCMAS-2) in both groups.

PRINCIPAL OBSERVATIONS

TS was associated with anomalous enlargement of the amygdala. Surface-based modeling revealed shape differences (increased radial-distances) in bilateral basal and basomedial nuclei within the basolateral complex. RCMAS-2 Total Anxiety t-score was significantly higher in participants with TS compared with TD controls (P = 0.012).

CONCLUSIONS

Group differences in global amygdala volumes were driven by local morphological increases in areas that are critically involved in face emotion processing and anxiety. In the context of increased amygdala volumes in TS, our results also showed increased worry and social anxiety in young girls with TS compared with TD.

Interneurons in the human olfactory system in Alzheimer's disease

The principal olfactory structures display Alzheimer's disease (AD) related pathology at early stages of the disease. Consequently, olfactory deficits are among the earliest symptoms. Reliable olfactory tests for accurate clinical diagnosis are rarely made. In addition, neuropathological analysis postmortem of olfactory structures is often not made. Therefore, the relationship between the clinical features and the underlying pathology is poorly defined. Traditionally, research into Alzheimer's disease has focused on the degeneration of cortical temporal projection neurons and cholinergic neurons. Recent evidence has demonstrated the neurodegeneration of interneuron populations in AD. This review provides an updated overview of the pathological involvement of interneuron populations in the human olfactory system in Alzheimer's disease.

The basolateral amygdala γ-aminobutyric acidergic system in health and disease

The brain comprises an excitatory/inhibitory neuronal network that maintains a finely tuned balance of activity critical for normal functioning. Excitatory activity in the basolateral amygdala (BLA), a brain region that plays a central role in emotion and motivational processing, is tightly regulated by a relatively small population of γ-aminobutyric acid (GABA) inhibitory neurons. Disruption in GABAergic inhibition in the BLA can occur when there is a loss of local GABAergic interneurons, an alteration in GABAA receptor activation, or a dysregulation of mechanisms that modulate BLA GABAergic inhibition. Disruptions in GABAergic control of the BLA emerge during development, in aging populations, or after trauma, ultimately resulting in hyperexcitability. BLA hyperexcitability manifests behaviorally as an increase in anxiety, emotional dysregulation, or development of seizure activity. This Review discusses the anatomy, development, and physiology of the GABAergic system in the BLA and circuits that modulate GABAergic inhibition, including the dopaminergic, serotonergic, noradrenergic, and cholinergic systems. We highlight how alterations in various neurotransmitter receptors, including the acid-sensing ion channel 1a, cannabinoid receptor 1, and glutamate receptor subtypes, expressed on BLA interneurons, modulate GABAergic transmission and how defects of these systems affect inhibitory tonus within the BLA. Finally, we discuss alterations in the BLA GABAergic system in neurodevelopmental (autism/fragile X syndrome) and neurodegenerative (Alzheimer's disease) diseases and after the development of epilepsy, anxiety, and traumatic brain injury. A more complete understanding of the intrinsic excitatory/inhibitory circuit balance of the amygdala and how imbalances in inhibitory control contribute to excessive BLA excitability will guide the development of novel therapeutic approaches in neuropsychiatric diseases.

Amyloid burden, cortical thickness, and cognitive function in the Wisconsin Registry for Alzheimer's Prevention

There is a growing interest in understanding how amyloid β (Aβ) accumulation in preclinical Alzheimer's disease relates to brain morphometric measures and cognition. Existing investigations in this area have been primarily conducted in older cognitively normal (CN) individuals. Therefore, not much is known about the associations between Aβ burden, cortical thickness, and cognition in midlife. We examined this question in 109, CN, late to middle-aged adults (mean age = 60.72 ± 5.65 years) from the Wisconsin Registry for Alzheimer's Prevention. They underwent Pittsburgh Compound B (PiB) and anatomical magnetic resonance (MR) imaging, and a comprehensive cognitive examination. Blinded visual rating of the PiB scans was used to classify the participants as Aβ+ or Aβ−. Cortical thickness measurements were derived from the MR images. The Aβ+ group exhibited significant thinning of the entorhinal cortex and accelerated age-associated thinning of the parahippocampal gyrus compared with the Aβ− group. The Aβ+ group also had numerically lower, but nonsignificant, test scores on all cognitive measures, and significantly faster age-associated cognitive decline on measures of Speed & Flexibility, Verbal Ability, and Visuospatial Ability. Our findings suggest that early Aβ aggregation is associated with deleterious changes in brain structure and cognitive function, even in midlife, and that the temporal lag between Aβ deposition and the inception of neurodegenerative/cognitive changes might be narrower than currently thought.

The diffeomorphometry of regional shape change rates and its relevance to cognitive deterioration in mild cognitive impairment and Alzheimer's disease

We proposed a diffeomorphometry-based statistical pipeline to study the regional shape change rates of the bilateral hippocampus, amygdala, and ventricle in mild cognitive impairment (MCI) and Alzheimer's disease (AD) compared with healthy controls (HC), using sequential magnetic resonance imaging (MRI) scans of 713 subjects (3,123 scans in total). The subgroup shape atrophy rates of the bilateral hippocampus and amygdala, as well as the expansion rates of the bilateral ventricles, for a majority of vertices were found to follow the order of AD>MCI>HC. The bilateral hippocampus and the left amygdala were subsegmented into multiple functionally meaningful subregions with the help of high-field MRI scans. The largest group differences in localized shape atrophy rates on the hippocampus were found to occur in CA1, followed by subiculum, CA2, and finally CA3/dentate gyrus, which is consistent with the neurofibrillary tangle accumulation trajectory. Highly nonuniform group differences were detected on the amygdala; vertices on the core amygdala (basolateral and lateral nucleus) revealed much larger atrophy rates, whereas those on the noncore amygdala (mainly centromedial) displayed similar or even smaller atrophy rates in AD relative to HC. The temporal horns of the ventricles were observed to have the largest localized ventricular expansion rate differences; with the AD group showing larger localized expansion rates on the anterior horn and the body part of the ventricles as well. Significant correlations were observed between the localized shape change rates of each of these six structures and the cognitive deterioration rates as quantified by the Alzheimer's Disease Assessment Scale-Cognitive Behavior Section increase rate and the Mini Mental State Examination decrease rate.

Medial temporal atrophy in early and late-onset Alzheimer's disease

Late-onset and early-onset Alzheimer's disease (LOAD, EOAD) affect different neural systems and may be separate nosographic entities. The most striking differences are in the medial temporal lobe, severely affected in LOAD and relatively spared in EOAD. We assessed amygdalar morphology and volume in 18 LOAD and 18 EOAD patients and 36 aged-matched controls and explored their relationship with the hippocampal volume. Three-dimensional amygdalar shape was reconstructed with the radial atrophy mapping technique, hippocampal volume was measured using a manual method. Atrophy was greater in LOAD than EOAD: 25% versus 17% in the amygdala and 20% versus 13% in the hippocampus. In the amygdala, LOAD showed significantly greater tissue loss than EOAD in the right dorsal central, lateral, and basolateral nuclei (20%-30% loss, p < 0.03), all known to be connected to limbic regions. In LOAD but not EOAD, greater hippocampal atrophy was associated with amygdalar atrophy in the left dorsal central and medial nuclei (r = 0.6, p < 0.05) also part of the limbic system. These findings support the notion that limbic involvement is a prominent feature of LOAD but not EOAD.

Amygdalar atrophy in symptomatic Alzheimer's disease based on diffeomorphometry: the BIOCARD cohort

This article examines the diffeomorphometry of magnetic resonance imaging-derived structural markers for the amygdala, in subjects with symptomatic Alzheimer's disease (AD). Using linear mixed-effects models we show differences between those with symptomatic AD and controls. Based on template centered population analysis, the distribution of statistically significant change is seen in both the volume and shape of the amygdala in subjects with symptomatic AD compared with controls. We find that high-dimensional vertex based markers are statistically more significantly discriminating (p < 0.00001) than lower-dimensional markers and volumes, consistent with comparable findings in presymptomatic AD. Using a high-field 7T atlas, significant atrophy was found to be centered in the basomedial and basolateral subregions, with no evidence of centromedial involvement.

Inferring changepoint times of medial temporal lobe morphometric change in preclinical Alzheimer's disease

This paper uses diffeomorphometry methods to quantify the order in which statistically significant morphometric change occurs in three medial temporal lobe regions, the amygdala, entorhinal cortex (ERC), and hippocampus among subjects with symptomatic and preclinical Alzheimer's disease (AD). Magnetic resonance imaging scans were examined in subjects who were cognitively normal at baseline, some of whom subsequently developed clinical symptoms of AD. The images were mapped to a common template, using shape-based diffeomorphometry. The multidimensional shape markers indexed through the temporal lobe structures were modeled using a changepoint model with explicit parameters, specifying the number of years preceding clinical symptom onset. Our model assumes that the atrophy rate of a considered brain structure increases years before detectable symptoms.

The results demonstrate that the atrophy changepoint in the ERC occurs first, indicating significant change 8–10 years prior to onset, followed by the hippocampus, 2–4 years prior to onset, followed by the amygdala, 3 years prior to onset. The ERC is significant bilaterally, in both our local and global measures, with estimates of ERC surface area loss of 2.4% (left side) and 1.6% (right side) annually. The same changepoint model for ERC volume gives 3.0% and 2.7% on the left and right sides, respectively. Understanding the order in which changes in the brain occur during preclinical AD may assist in the design of intervention trials aimed at slowing the evolution of the disease.

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We use diffeomorphometry to quantify the order in which statistically significant morphometric change occurs in three medial temporal lobe regions, the amygdala, entorhinal cortex (ERC), and hippocampus among subjects with symptomatic and preclinical Alzheimer's disease (AD).

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We introduce a model on anatomical shape change in which changepoint is inferred, taking place some period of time before cognitive onset of AD.

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The analysis uses a dataset arising from the BIOCARD study, in which all subjects were cognitively normal at baseline, some of whom subsequently developed clinical symptoms of AD.

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The results demonstrate that the atrophy changepoint in the ERC occurs first, indicating significant change 8-10 years prior to onset, followed by hippocampus, 2-4 years prior to onset, followed by amygdala, 3 years prior to onset.

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The ERC is significant bilaterally, in both our local and global measures, with estimates of ERC surface area loss of 2.4% (left side) and 1.6% (right side) annually.

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Understanding the order in which changes in the brain occur during preclinical AD may assist in the design of intervention trials aimed at slowing the evolution of the disease.

Shape abnormalities of subcortical and ventricular structures in mild cognitive impairment and Alzheimer's disease: detecting, quantifying, and predicting

This article assesses the feasibility of using shape information to detect and quantify the subcortical and ventricular structural changes in mild cognitive impairment (MCI) and Alzheimer's disease (AD) patients. We first demonstrate structural shape abnormalities in MCI and AD as compared with healthy controls (HC). Exploring the development to AD, we then divide the MCI participants into two subgroups based on longitudinal clinical information: (1) MCI patients who remained stable; (2) MCI patients who converted to AD over time. We focus on seven structures (amygdala, hippocampus, thalamus, caudate, putamen, globus pallidus, and lateral ventricles) in 754 MR scans (210 HC, 369 MCI of which 151 converted to AD over time, and 175 AD). The hippocampus and amygdala were further subsegmented based on high field 0.8 mm isotropic 7.0T scans for finer exploration. For MCI and AD, prominent ventricular expansions were detected and we found that these patients had strongest hippocampal atrophy occurring at CA1 and strongest amygdala atrophy at the basolateral complex. Mild atrophy in basal ganglia structures was also detected in MCI and AD. Stronger atrophy in the amygdala and hippocampus, and greater expansion in ventricles was observed in MCI converters, relative to those MCI who remained stable. Furthermore, we performed principal component analysis on a linear shape space of each structure. A subsequent linear discriminant analysis on the principal component values of hippocampus, amygdala, and ventricle leads to correct classification of 88% HC subjects and 86% AD subjects.

Regional analysis of the magnetization transfer ratio of the brain in mild Alzheimer disease and amnestic mild cognitive impairment

BACKGROUND AND PURPOSE

Manually drawn VOI-based analysis shows a decrease in magnetization transfer ratio in the hippocampus of patients with Alzheimer disease. We investigated with whole-brain voxelwise analysis the regional changes of the magnetization transfer ratio in patients with mild Alzheimer disease and patients with amnestic mild cognitive impairment.

MATERIALS AND METHODS

Twenty patients with mild Alzheimer disease, 27 patients with amnestic mild cognitive impairment, and 30 healthy elderly control subjects were examined with high-resolution T1WI and 3-mm-thick magnetization transfer images. Whole-brain voxelwise analysis of magnetization transfer ratio maps was performed by use of Statistical Parametric Mapping 8 software and was supplemented by the analysis of the magnetization transfer ratio in FreeSurfer parcellation-derived VOIs.

RESULTS

Voxelwise analysis showed 2 clusters of significantly decreased magnetization transfer ratio in the left hippocampus and amygdala and in the left posterior mesial temporal cortex (fusiform gyrus) of patients with Alzheimer disease as compared with control subjects but no difference between patients with amnestic mild cognitive impairment and either patients with Alzheimer disease or control subjects. VOI analysis showed that the magnetization transfer ratio in the hippocampus and amygdala was significantly lower (bilaterally) in patients with Alzheimer disease when compared with control subjects (ANOVA with Bonferroni correction, at P < .05). Mean magnetization transfer ratio values in the hippocampus and amygdala in patients with amnestic mild cognitive impairment were between those of healthy control subjects and those of patients with mild Alzheimer disease. Support vector machine-based classification demonstrated improved classification performance after inclusion of magnetization transfer ratio-related features, especially between patients with Alzheimer disease versus healthy subjects.

CONCLUSIONS

Bilateral but asymmetric decrease of magnetization transfer ratio reflecting microstructural changes of the residual GM is present not only in the hippocampus but also in the amygdala in patients with mild Alzheimer disease.