Hippocampal volume and asymmetry in mild cognitive impairment and Alzheimer's disease: Meta-analyses of MRI studies

Left lateralized cerebral glucose metabolism declines in amyloid-β positive persons with mild cognitive impairment

Background

Previous publications indicate that Alzheimer's Disease (AD) related cortical atrophy may develop in asymmetric patterns, with accentuation of the left hemisphere. Since fluorodeoxyglucose positron emission tomography (FDG PET) measurements of the regional cerebral metabolic rate of glucose (rCMRgl) provide a sensitive and specific marker of neurodegenerative disease progression, we sought to investigate the longitudinal pattern of rCMRgl in amyloid-positive persons with mild cognitive impairment (MCI) and dementia, hypothesizing asymmetric declines of cerebral glucose metabolism.

Methods

Using florbetapir PET and cerebrospinal fluid (CSF) measures to define amyloid-β (Aβ) positivity, 40 Aβ negative (Aβ-) cognitively unimpaired controls (CU; 76 ± 5y), 76 Aβ positive (Aβ+) persons with MCI (76 ± 7y) and 51 Aβ + persons with probable AD dementia (75 ± 7y) from the AD Neuroimaging Initiative (ADNI) were included in this study with baseline and 2-year follow-up FDG PET scans. The degree of lateralization of longitudinal rCMRgl declines in subjects with Aβ + MCI and AD in comparison with Aβ- CU were statistically quantified via bootstrapped lateralization indices [(LI); range − 1 (right) to 1 (left)].

Results

Compared to Aβ- CU, Aβ + MCI patients showed marked left hemispheric lateralization (LI: 0.78). In contrast, modest right hemispheric lateralization (LI: −0.33) of rCMRgl declines was found in Aβ + persons with probable AD dementia. Additional comparisons of Aβ + groups (i.e. MCI and probable AD dementia) consequently indicated right hemispheric lateralization (LI: −0.79) of stronger rCMRgl declines in dementia stages of AD. For all comparisons, voxel-based analyses confirmed significant (pFWE<0.05) declines of rCMRgl within AD-typical brain regions. Analyses of cognitive data yielded predominant decline of memory functions in both MCI and dementia stages of AD.

Conclusions

These data indicate that in early stages, AD may be characterized by a more lateralized pattern of left hemispheric rCMRgl declines. However, metabolic differences between hemispheres appear to diminish with further progression of the disease.

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Lateralized cerebral glucose metabolism declines in Alzheimer's Disease.

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Early stages show strong left-hemispheric lateralization.

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Advanced stages show weak right-hemispheric lateralization.

Insulin-like growth factor binding protein-2 interactions with Alzheimer's disease biomarkers

Plasma levels of insulin-like growth factor binding protein-2 (IGFBP-2) have been associated with Alzheimer's disease (AD) and brain atrophy. Some evidence suggests a potential synergistic effect of IGFBP-2 and AD neuropathology on neurodegeneration, while other evidence suggests the effect of IGFBP-2 on neurodegeneration is independent of AD neuropathology. Therefore, the current study investigated the interaction between plasma IGFBP-2 and cerebrospinal fluid (CSF) biomarkers of AD neuropathology on hippocampal volume and cognitive function. AD Neuroimaging Initiative data were accessed (n = 354, 75 ± 7 years, 38 % female), including plasma IGFBP-2, CSF total tau, CSF Aβ-42, MRI-quantified hippocampal volume, and neuropsychological performances. Mixed effects regression models evaluated the interaction between IGFBP-2 and AD biomarkers on hippocampal volume and neuropsychological performance, adjusting for age, sex, education, APOE ε4 status, and cognitive diagnosis. A baseline interaction between IGFBP-2 and CSF Aβ-42 was observed in relation to left (t(305) = -6.37, p = 0.002) and right hippocampal volume (t(305) = -7.74, p = 0.001). In both cases, higher IGFBP-2 levels were associated with smaller hippocampal volumes but only among amyloid negative individuals. The observed interaction suggests IGFBP-2 drives neurodegeneration through a separate pathway independent of AD neuropathology.

Longitudinal Assessment of Hippocampal Atrophy in Midlife and Early Old Age: Contrasting Manual Tracing and Semi-automated Segmentation (FreeSurfer)

It is important to have accurate estimates of normal age-related brain structure changes and to understand how the choice of measurement technique may bias those estimates. We compared longitudinal change in hippocampal volume, laterality and atrophy measured by manual tracing and FreeSurfer (version 5.3) in middle age (n = 244, 47.2[1.4] years) and older age (n = 199, 67.0[1.4] years) individuals over 8 years. The proportion of overlap (Dice coefficient) between the segmented hippocampi was calculated and we hypothesised that the proportion of overlap would be higher for older individuals as a consequence of higher atrophy. Hippocampal volumes produced by FreeSurfer were larger than manually traced volumes. Both methods produced a left less than right volume laterality difference. Over time this laterality difference increased for manual tracing and decreased for FreeSurfer leading to laterality differences in left and right estimated atrophy rates. The overlap proportion between methods was not significantly different for older individuals, but was greater for the right hippocampus. Estimated middle age annualised atrophy rates were - 0.39(1.0) left, 0.07(1.01) right, - 0.17(0.88) total for manual tracing and - 0.15(0.69) left, - 0.20(0.63) right, - 0.18(0.57) total for FreeSurfer. Older age atrophy rates were - 0.43(1.32) left, - 0.15(1.41) right, - 0.30 (1.23) total for manual tracing and - 0.34(0.79) left, - 0.68(0.78) right, - 0.51(0.65) total for FreeSurfer. FreeSurfer reliably segments the hippocampus producing atrophy rates that are comparable to manual tracing with some biases that need to be considered in study design. FreeSurfer is suited for use in large longitudinal studies where it is not cost effective to use manual tracing.

Consciousness in a multilevel architecture: Evidence from the right side of the brain

By taking into account Bruce Bridgeman's interest in an evolutionary framing of human cognition, we examine effective (cause-and-effect) connectivity among cortical structures related to different parts of the triune phylogenetic stratification: archicortex, paleocortex and neocortex. Using resting-state functional magnetic resonance imaging data from 25 healthy subjects and spectral Dynamic Causal Modeling, we report interactions among 10 symmetrical left and right brain areas. Our results testify to general rightward and top-down biases in excitatory interactions of these structures during resting state, when self-related contemplation prevails over more objectified conceptual thinking. The right hippocampus is the only structure that shows bottom-up excitatory influences extending to the frontopolar cortex. The right ventrolateral cortex also plays a prominent role as it interacts with the majority of nodes within and between evolutionary distinct brain subdivisions. These results suggest the existence of several levels of cognitive-affective organization in the human brain and their profound lateralization.

Impairment of memory generalization in preclinical autosomal dominant Alzheimer's disease mutation carriers

Fast, inexpensive, and noninvasive identification of Alzheimer's disease (AD) before clinical symptoms emerge would augment our ability to intervene early in the disease. Individuals with fully penetrant genetic mutations causing autosomal dominant Alzheimer's disease (ADAD) are essentially certain to develop the disease, providing a unique opportunity to examine biomarkers during the preclinical stage. Using a generalization task that has previously shown to be sensitive to medial temporal lobe pathology, we compared preclinical individuals carrying ADAD mutations to noncarrying kin to determine whether generalization (the ability to transfer previous learning to novel but familiar recombinations) is vulnerable early, before overt cognitive decline. As predicted, results revealed that preclinical ADAD mutation carriers made significantly more errors during generalization than noncarrying kin, despite no differences between groups during learning or retention. This impairment correlated with the left hippocampal volume, particularly in mutation carriers. Such identification of generalization deficits in early ADAD may provide an easily implementable and potentially linguistically and culturally neutral way to identify and track cognition in ADAD.

Morphological Biomarker Differentiating MCI Converters from Nonconverters: Longitudinal Evidence Based on Hemispheric Asymmetry

Identifying subjects with mild cognitive impairment (MCI) who may probably progress to Alzheimer's disease (AD) is important for better understanding the disease mechanisms and facilitating early treatments. In addition to the direct volumetric and thickness measurement based on high-resolution magnetic resonance imaging (MRI), hemispheric asymmetry could be a potential index to detect morphological variations in MCI patients with a high risk of conversion to AD. The present study collected a set of longitudinal MRI data from 53 MCI converters and nonconverters and investigated the asymmetry differences between groups. Asymmetry variation was observed in the medial temporal lobe, especially in the entorhinal cortex, between converters and nonconverters 3 years before the former developed AD. The proposed asymmetry analysis was observed to be sensitive to detect morphological changes between groups as compared to the methods of voxel-based morphometry (VBM) and thickness measurement. Hemispheric asymmetry in specific brain regions as a neuroimaging biomarker can provide helpful information for prediction of MCI conversion.

Gender-Specific Degeneration of Dementia-Related Subcortical Structures Throughout the Lifespan

Age-related changes in brain structure are a question of interest to a broad field of research. Structural decline has been consistently, but not unambiguously, linked to functional consequences, including cognitive impairment and dementia. One of the areas considered of crucial importance throughout this process is the medial temporal lobe, and primarily the hippocampal region. Gender also has a considerable effect on volume deterioration of subcortical grey matter (GM) structures, such as the hippocampus. The influence of age×gender interaction on disproportionate GM volume changes might be mediated by hormonal effects on the brain. Hippocampal volume loss appears to become accelerated in the postmenopausal period. This decline might have significant influences on neuroplasticity in the CA1 region of the hippocampus highly vulnerable to pathological influences. Additionally, menopause has been associated with critical pathobiochemical changes involved in neurodegeneration. The micro- and macrostructural alterations and consequent functional deterioration of critical hippocampal regions might result in clinical cognitive impairment-especially if there already is a decline in the cognitive reserve capacity. Several lines of potential vulnerability factors appear to interact in the menopausal period eventually leading to cognitive decline, mild cognitive impairment, or Alzheimer's disease. This focused review aims to delineate the influence of unmodifiable risk factors of neurodegenerative processes, i.e., age and gender, on critical subcortical GM structures in the light of brain derived estrogen effects. The menopausal period appears to be of key importance for the risk of cognitive decline representing a time of special vulnerability for molecular, structural, and functional influences and offering only a narrow window for potential protective effects.

Working Memory And Brain Tissue Microstructure: White Matter Tract Integrity Based On Multi-Shell Diffusion MRI

Working memory is a complex cognitive process at the intersection of sensory processing, learning, and short-term memory and also has a general executive attention component. Impaired working memory is associated with a range of neurological and psychiatric disorders, but very little is known about how working memory relates to underlying white matter (WM) microstructure. In this study, we investigate the association between WM microstructure and performance on working memory tasks in healthy adults (right-handed, native English speakers). We combine compartment specific WM tract integrity (WMTI) metrics derived from multi-shell diffusion MRI as well as diffusion tensor/kurtosis imaging (DTI/DKI) metrics with Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) subtests tapping auditory working memory. WMTI is a novel tool that helps us describe the microstructural characteristics in both the intra- and extra-axonal environments of WM such as axonal water fraction (AWF), intra-axonal diffusivity, extra-axonal axial and radial diffusivities, allowing a more biophysical interpretation of WM changes. We demonstrate significant positive correlations between AWF and letter-number sequencing (LNS), suggesting that higher AWF with better performance on complex, more demanding auditory working memory tasks goes along with greater axonal volume and greater myelination in specific regions, causing efficient and faster information process.

Changes in Brain Lateralization in Patients with Mild Cognitive Impairment and Alzheimer's Disease: A Resting-State Functional Magnetic Resonance Study from Alzheimer's Disease Neuroimaging Initiative

Purpose

To detect changes in brain lateralization in patients with mild cognitive impairment (MCI) and Alzheimer’s disease (AD) using resting-state functional magnetic resonance imaging (fMRI).

Materials and methods

Data from 61 well-matched right-handed subjects were obtained from the Alzheimer’s Disease Neuroimaging Initiative, including 19 healthy controls (HCs), 25 patients with MCI, and 17 patients with AD. First, we divided 256 pairs of seed regions from each hemisphere covering the entire cerebral gray matter. Then, we used the intrinsic laterality index (iLI) approach to quantify the functional laterality using fMRI. One-way ANOVA was employed to estimate the differences in iLI among the three groups. The sum, number and mean value of the iLI were calculated within the thresholds of 0 < |iLI| < 0.2, 0.2 ≤ |iLI| < 0.4, 0.4 ≤ |iLI| < 0.8, and |iLI| ≥ 0.8, to explore the changes in the lateralization of resting-state brain function in patients with MCI and AD.

Results

One-way ANOVA revealed that the iLIs of the three groups were significantly different. The HCs showed a significant leftward interhemispheric difference within |iLI| ≥ 0.8. Compared with the HCs, the patients with MCI manifested a distinct abnormal rightward interhemispheric asymmetry, mainly within the thresholds of 0.2 ≤ |iLI| < 0.4 and 0.4 ≤ |iLI| < 0.8; in the patients with AD, the normal leftward lateralization that was observed in the HCs disappeared, and an abnormal rightward laterality was expressed within 0.4 ≤ |iLI| < 0.8. By directly comparing the patients with MCI with the patients with AD, an exclusive abnormal rightward laterality was observed in the patients with MCI within the 0.2 ≤ |iLI| < 0.4 threshold, and the normal leftward asymmetry vanished in the patients with AD within the |iLI| ≥ 0.8 threshold.

Conclusion

Global brain lateralization was different among three groups. The abnormal rightward dominance observed in the patients with MCI and AD may indicate that these patients use additional brain resources to compensate for the loss of cognitive function, and the observed disappearance of the leftward laterality in the patients with AD was likely associated with the damage in the left hemisphere. The observed disappearance of the rightward asymmetry in the patients with AD using the 0.2 ≤ |iLI| < 0.4 threshold was likely a sign of decompensation. Our study provides new insights that may improve our understanding of MCI and AD.

Fluid and imaging biomarkers for Alzheimer's disease: Where we stand and where to head to

There is increasing evidence that a number of potentially informative biomarkers for Alzheimer disease (AD) can improve the accuracy of diagnosing this form of dementia, especially when used as a panel of diagnostic assays and interpreted in the context of neuroimaging and clinical data. Moreover, by combining the power of CSF biomarkers with neuroimaging techniques to visualize Aβ deposits (or neurodegenerative lesions), it might be possible to better identify individuals at greatest risk for developing MCI and converting to AD. The objective of this article was to review recent progress in selected imaging and chemical biomarkers for prediction, early diagnosis and progression of AD. We present our view point of a scenario that places CSF and imaging markers on the verge of general utility based on accuracy levels that already match (or even surpass) current clinical precision.

Hippocampal atrophy, asymmetry, and cognition in type 2 diabetes mellitus

INTRODUCTION

Type 2 diabetes mellitus is associated with global and hippocampal atrophy and cognitive deficits, and some studies suggest that the right hippocampus may display greater vulnerability than the left.

METHODS

Hippocampal volumes, the hippocampal asymmetry index, and cognitive functioning were assessed in 120 nondemented adults with long duration type 2 diabetes.

RESULTS

The majority of the sample displayed left greater than right hippocampal asymmetry (which is the reverse of the expected direction seen with normal aging). After adjustment for age, sex, and IQ, right (but not left) hippocampal volumes were negatively associated with memory, executive function, and semantic fluency. These associations were stronger with the hippocampal asymmetry index and remained significant for memory and executive function after additional adjustment for global brain atrophy.

CONCLUSIONS

We conclude that asymmetric hippocampal atrophy may occur in type 2 diabetes, with greater atrophy occurring in the right than the left hippocampus, and that this may contribute to cognitive impairment in this disorder. These cross-sectional associations require further verification but may provide clues into the pathogenesis of cognitive disorders in type 2 diabetes.

Asymmetry of Hippocampus and Amygdala Defect in Subjective Cognitive Decline Among the Community Dwelling Chinese

Background: Subjective cognitive decline (SCD) may be the first clinical sign of Alzheimer's disease (AD). SCD individuals with normal cognition may already have significant medial temporal lobe atrophy. However, few studies have been devoted to exploring the alteration of left-right asymmetry with hippocampus and amygdala in SCD. The aim of this study was to compare SCD individuals with amnestic mild cognitive impairment (MCI) patients and the normal population for volume and asymmetry of hippocampus, amygdala and temporal horn, and to assess their relationship with cognitive function in elderly population living in China. Methods: 111 SCD, 30 MCI, and 67 healthy controls (HC) underwent a standard T1-weighted MRI, from which the volumes of the hippocampus and amygdala were calculated and compared. Then we evaluated the pattern and extent of asymmetry in hippocampus and amygdala of these samples. Furthermore, we also investigated the relationship between the altered brain regions and cognitive function. Results: Among the three groups, SCD showed more depressive symptoms (p < 0.001) and higher percentage of heart disease (16.4% vs. 35.1%, p = 0.007) than controls. In terms of brain data, significant differences were found in the volume and asymmetry of both hippocampus and amygdala among the three groups (P < 0.05). In logistic analysis controlled by age, gender, education level, depression symptoms, anxiety symptom, somatic disease and lifestyle in terms of smoking, both SCD and MCI individuals showed significant decreased right hippocampal and amygdala volume than controls. For asymmetry pattern, a ladder-shaped difference of left-larger-than-right asymmetry was found in amygdala with MCI>SCD>HC, and an opposite asymmetry of left-less-than-right pattern was found with HC>SCD>MCI in hippocampus. Furthermore, correlation was shown between the volume of right hippocampus and right amygdala with MMSE and MoCA in SCD group. Conclusion: Our results supported that SCD individuals are biologically distinguishable from HC, and this may relate to cognitive impairment, although more longitudinal studies are need to investigate this further.Moreover, different levels of asymmetry in hippocampus and amygdala might be a potential dividing factor to differentiate clinical diagnosis.

Disease-modifying benefit of Fyn blockade persists after washout in mouse Alzheimer's model

Alzheimer's disease remains without a disease-modifying therapy that improves symptoms after therapy withdrawal. Because no investigational agents have demonstrated disease-modifying effects clinically, we tested whether the Fyn inhibitor, saracatinib, provides persistent improvement in a transgenic model. Aged APPswe/PS1ΔE9 mice were treated with saracatinib or memantine for 4 weeks and spatial memory improved to control levels. After drug washout, there was sustained rescue of both memory function and synapse density by saracatinib, but a loss of benefit from memantine. These data demonstrate a disease-modifying persistent benefit for saracatinib in a preclinincal Alzheimer's model, and distinguish its action from that of memantine.

Clinical validity of medial temporal atrophy as a biomarker for Alzheimer's disease in the context of a structured 5-phase development framework

Research criteria for Alzheimer's disease recommend the use of biomarkers for diagnosis, but whether biomarkers improve the diagnosis in clinical routine has not been systematically assessed. The aim is to evaluate the evidence for use of medial temporal lobe atrophy (MTA) as a biomarker for Alzheimer's disease at the mild cognitive impairment stage in routine clinical practice, with an adapted version of the 5-phase oncology framework for biomarker development. A literature review on visual assessment of MTA and hippocampal volumetry was conducted with other biomarkers addressed in parallel reviews. Ample evidence is available for phase 1 (rationale for use) and phase 2 (discriminative ability between diseased and control subjects). Phase 3 (early detection ability) is partly achieved: most evidence is derived from research cohorts or clinical populations with short follow-up, but validation in clinical mild cognitive impairment cohorts is required. In phase 4, only the practical feasibility has been addressed for visual rating of MTA. The rest of phase 4 and phase 5 have not yet been addressed.

Lower cardiac index levels relate to lower cerebral blood flow in older adults

OBJECTIVE

To assess cross-sectionally whether lower cardiac index relates to lower resting cerebral blood flow (CBF) and cerebrovascular reactivity (CVR) among older adults.

METHODS

Vanderbilt Memory & Aging Project participants free of stroke, dementia, and heart failure were studied (n = 314, age 73 ± 7 years, 59% male, 39% with mild cognitive impairment). Cardiac index (liters per minute per meter squared) was quantified from echocardiography. Resting CBF (milliliters per 100 grams per minute) and hypercapnia-induced CVR were quantified from pseudo-continuous arterial spin-labeling MRI. Linear regressions with ordinary least-square estimates related cardiac index to regional CBF, with adjustment for age, education, race/ethnicity, Framingham Stroke Risk Profile score (systolic blood pressure, antihypertensive medication use, diabetes mellitus, current cigarette smoking, left ventricular hypertrophy, prevalent cardiovascular disease [CVD], atrial fibrillation), APOE ε4 status, cognitive diagnosis, and regional tissue volume.

RESULTS

Lower cardiac index corresponded to lower resting CBF in the left (β = 2.4, p = 0.001) and right (β = 2.5, p = 0.001) temporal lobes. Results were similar when participants with prevalent CVD and atrial fibrillation were excluded (left temporal lobe β = 2.3, p = 0.003; right temporal lobe β = 2.5, p = 0.003). Cardiac index was unrelated to CBF in other regions assessed (p > 0.25) and CVR in all regions (p > 0.05). In secondary cardiac index × cognitive diagnosis interaction models, cardiac index and CBF associations were present only in cognitively normal participants and affected a majority of regions assessed with effects strongest in the left (p < 0.0001) and right (p < 0.0001) temporal lobes.

CONCLUSIONS

Among older adults without stroke, dementia, or heart failure, systemic blood flow correlates with cerebral CBF in the temporal lobe, independently of prevalent CVD, but not CVR.

Association of imaging abnormalities of the subcallosal septal area with Alzheimer's disease and mild cognitive impairment

AIM

To evaluate the use the distance between the adjacent septal nuclei as a surrogate marker of septal area atrophy seen in Alzheimer's disease (AD).

MATERIALS & METHODS

Interseptal distance (ISD) was measured, blind to clinical details, in 250 patients who underwent computed tomography (CT) of the brain at University Hospital of Wales. Clinical details including memory problem history were retrieved. An ISD cut-off value that discriminated those with and without memory symptoms was sought. ISD measurements were also made in 20 AD patients. To test both the method and the defined cut-off, measurements were then made in an independent cohort of 21 mild cognitive impairment (MCI) patients and 45 age-matched healthy controls, in a randomised and blinded fashion.

RESULTS

ISD measurement was achieved in all patients. In 28 patients with memory symptoms, the mean ISD was 5.9 mm compared with 2.3 mm in those without overt symptoms (p=0.001). The optimum ISD cut-off value was 4 mm (sensitivity 85.7% and specificity 85.8%). All AD patients had an ISD of >4 mm (mean ISD= 6.1 mm). The mean ISD for MCI patients was 3.84 mm compared with 2.18 mm in age-matched healthy controls (p=0.001). Using a 4 mm cut-off correctly categorised 10 mild cognitive impairment patients (47.6%) and 38 healthy controls (84.4%).

CONCLUSION

ISD is a simple and reliable surrogate measurement for septal area atrophy, applicable to CT and magnetic resonance imaging (MRI). It can be used to help select patients for further investigation.

Mean diffusivity in cortical gray matter in Alzheimer's disease: The importance of partial volume correction

Mean diffusivity (MD) measured by diffusion tensor imaging can reflect microstructural alterations of the brain's gray matter (GM). Therefore, GM MD may be a sensitive marker of neurodegeneration related to Alzheimer's Disease (AD). However, due to partial volume effects (PVE), differences in MD may be overestimated because of a higher degree of brain atrophy in AD patients and in cases with mild cognitive impairment (MCI). Here, we evaluated GM MD changes in AD and MCI compared with healthy controls, and the effect of partial volume correction (PVC) on diagnostic utility of MD. We determined region of interest (ROI) and voxel-wise group differences and diagnostic accuracy of MD and volume measures between matched samples of 39 AD, 39 MCI and 39 healthy subjects before and after PVC. Additionally, we assessed whether effects of GM MD values on diagnosis were mediated by volume. ROI and voxel-wise group differences were reduced after PVC. When using these ROIs for predicting group separation in logistic models, both PVE corrected and uncorrected GM MD values yielded a poorer diagnostic accuracy in single predictor models than regional volume. For the discrimination of AD patients and healthy controls, the effect of GM MD on diagnosis was significantly mediated by volume of hippocampus and posterior cingulate ROIs. Our results suggest that GM MD measurements are strongly confounded by PVE in the presence of brain atrophy, underlining the necessity of PVC when using these measurements as specific metrics of microstructural tissue degeneration. Independently of PVC, regional MD was not superior to regional volume in separating prodromal and clinical stages of AD from healthy controls.

Human subcortical brain asymmetries in 15,847 people worldwide reveal effects of age and sex

The two hemispheres of the human brain differ functionally and structurally. Despite over a century of research, the extent to which brain asymmetry is influenced by sex, handedness, age, and genetic factors is still controversial. Here we present the largest ever analysis of subcortical brain asymmetries, in a harmonized multi-site study using meta-analysis methods. Volumetric asymmetry of seven subcortical structures was assessed in 15,847 MRI scans from 52 datasets worldwide. There were sex differences in the asymmetry of the globus pallidus and putamen. Heritability estimates, derived from 1170 subjects belonging to 71 extended pedigrees, revealed that additive genetic factors influenced the asymmetry of these two structures and that of the hippocampus and thalamus. Handedness had no detectable effect on subcortical asymmetries, even in this unprecedented sample size, but the asymmetry of the putamen varied with age. Genetic drivers of asymmetry in the hippocampus, thalamus and basal ganglia may affect variability in human cognition, including susceptibility to psychiatric disorders.

FGWAS: Functional genome wide association analysis

Functional phenotypes (e.g., subcortical surface representation), which commonly arise in imaging genetic studies, have been used to detect putative genes for complexly inherited neuropsychiatric and neurodegenerative disorders. However, existing statistical methods largely ignore the functional features (e.g., functional smoothness and correlation). The aim of this paper is to develop a functional genome-wide association analysis (FGWAS) framework to efficiently carry out whole-genome analyses of functional phenotypes. FGWAS consists of three components: a multivariate varying coefficient model, a global sure independence screening procedure, and a test procedure. Compared with the standard multivariate regression model, the multivariate varying coefficient model explicitly models the functional features of functional phenotypes through the integration of smooth coefficient functions and functional principal component analysis. Statistically, compared with existing methods for genome-wide association studies (GWAS), FGWAS can substantially boost the detection power for discovering important genetic variants influencing brain structure and function. Simulation studies show that FGWAS outperforms existing GWAS methods for searching sparse signals in an extremely large search space, while controlling for the family-wise error rate. We have successfully applied FGWAS to large-scale analysis of data from the Alzheimer's Disease Neuroimaging Initiative for 708 subjects, 30,000 vertices on the left and right hippocampal surfaces, and 501,584 SNPs.

Classifying MCI Subtypes in Community-Dwelling Elderly Using Cross-Sectional and Longitudinal MRI-Based Biomarkers

Amnestic MCI (aMCI) and non-amnestic MCI (naMCI) are considered to differ in etiology and outcome. Accurately classifying MCI into meaningful subtypes would enable early intervention with targeted treatment. In this study, we employed structural magnetic resonance imaging (MRI) for MCI subtype classification. This was carried out in a sample of 184 community-dwelling individuals (aged 73-85 years). Cortical surface based measurements were computed from longitudinal and cross-sectional scans. By introducing a feature selection algorithm, we identified a set of discriminative features, and further investigated the temporal patterns of these features. A voting classifier was trained and evaluated via 10 iterations of cross-validation. The best classification accuracies achieved were: 77% (naMCI vs. aMCI), 81% (aMCI vs. cognitively normal (CN)) and 70% (naMCI vs. CN). The best results for differentiating aMCI from naMCI were achieved with baseline features. Hippocampus, amygdala and frontal pole were found to be most discriminative for classifying MCI subtypes. Additionally, we observed the dynamics of classification of several MRI biomarkers. Learning the dynamics of atrophy may aid in the development of better biomarkers, as it may track the progression of cognitive impairment.

Prediction of Treatment Response to Donepezil using Automated Hippocampal Subfields Volumes Segmentation in Patients with Mild Alzheimer's Disease

Previous studies reported some relationships between donepezil treatment and hippocampus in Alzheimer's disease (AD). However, due to methodological limitations, their close relationships remain unclear. The aim of this study is to predict treatment response to donepezil by utilizing the automated segmentation of hippocampal subfields volumes (ASHS) in AD. Sixty four AD patients were prescribed with donepezil and were followed up for 24 weeks. Cognitive function was measured to assess whether there was a response from the donepezil treatment. ASHS was implemented on non-responder (NR) and responder (TR) groups, and receiver operator characteristic (ROC) analysis was conducted to evaluate the sensitivity, specificity, and accuracy of hippocampal subfields in predicting response to donepezil. The left total hippocampus and the CA1 area of the NR were significantly smaller than those of the TR group. The ROC curve analysis showed the left CA1 volumes showed highest area under curve (AUC) of 0.85 with a sensitivity of 88.0%, a specificity of 74.0% in predicting treatment response to donepezil treatment. We expect that hippocampal subfields volume measurements that predict treatment responses to current AD drugs will enable more evidence-based, individualized prescription of medications that will lead to more favorable treatment outcomes.

Visualizing Hyperactivation in Neurodegeneration Based on Prefrontal Oxygenation: A Comparative Study of Mild Alzheimer's Disease, Mild Cognitive Impairment, and Healthy Controls

Background: Cognitive performance is relatively well preserved during early cognitive impairment owing to compensatory mechanisms. Methods: We explored functional near-infrared spectroscopy (fNIRS) alongside a semantic verbal fluency task (SVFT) to investigate any compensation exhibited by the prefrontal cortex (PFC) in Mild Cognitive Impairment (MCI) and mild Alzheimer's disease (AD). In addition, a group of healthy controls (HC) was studied. A total of 61 volunteers (31 HC, 12 patients with MCI and 18 patients with mild AD) took part in the present study. Results: Although not statistically significant, MCI exhibited a greater mean activation of both the right and left PFC, followed by HC and mild AD. Analysis showed that in the left PFC, the time taken for HC to achieve the activation level was shorter than MCI and mild AD (p = 0.0047 and 0.0498, respectively); in the right PFC, mild AD took a longer time to achieve the activation level than HC and MCI (p = 0.0469 and 0.0335, respectively); in the right PFC, HC, and MCI demonstrated a steeper slope compared to mild AD (p = 0.0432 and 0. 0107, respectively). The results were, however, not significant when corrected by the Bonferroni-Holm method. There was also found to be a moderately positive correlation (R = 0.5886) between the oxygenation levels in the left PFC and a clinical measure [Mini-Mental State Examination (MMSE) score] in MCI subjects uniquely. Discussion: The hyperactivation in MCI coupled with a better SVFT performance may suggest neural compensation, although it is not known to what degree hyperactivation manifests as a potential indicator of compensatory mechanisms. However, hypoactivation plus a poorer SVFT performance in mild AD might indicate an inability to compensate due to the degree of structural impairment. Conclusion: Consistent with the scaffolding theory of aging and cognition, the task-elicited hyperactivation in MCI might reflect the presence of compensatory mechanisms and hypoactivation in mild AD could reflect an inability to compensate. Future studies will investigate the fNIRS parameters with a larger sample size, and their validity as prognostic biomarkers of neurodegeneration.

The Abnormality of Topological Asymmetry between Hemispheric Brain White Matter Networks in Alzheimer's Disease and Mild Cognitive Impairment

A large number of morphology-based studies have previously reported a variety of regional abnormalities in hemispheric asymmetry in Alzheimer’s disease (AD). Recently, neuroimaging studies have revealed changes in the topological organization of the structural network in AD. However, little is known about the alterations in topological asymmetries. In the present study, we used diffusion tensor image tractography to construct the hemispheric brain white matter networks of 25 AD patients, 95 mild cognitive impairment (MCI) patients, and 48 normal control (NC) subjects. Graph theoretical approaches were then employed to estimate hemispheric topological properties. Rightward asymmetry in both global and local network efficiencies were observed between the two hemispheres only in AD patients. The brain regions/nodes exhibiting increased rightward asymmetry in both AD and MCI patients were primarily located in the parahippocampal gyrus and cuneus. The observed rightward asymmetry was attributed to changes in the topological properties of the left hemisphere in AD patients. Finally, we found that the abnormal hemispheric asymmetries of brain network properties were significantly correlated with memory performance (Rey’s Auditory Verbal Learning Test). Our findings provide new insights into the lateralized nature of hemispheric disconnectivity and highlight the potential for using hemispheric asymmetry of brain network measures as biomarkers for AD.

Cortical signature of clock drawing performance in Alzheimer's disease and mild cognitive impairment

It is unclear whether clock drawing test (CDT) performance relies on a widely distributed cortical network, or whether this test predominantly taps into parietal cortex function. So far, associations between cortical integrity and CDT impairment in Alzheimer's disease (AD) and mild cognitive impairment (MCI) largely stem from cortical volume analyses. Given that volume is a product of thickness and surface area, investigation of the relationship between CDT and these two cortical measures might contribute to better understanding of this cognitive screening tool for AD. 38 patients with AD, 38 individuals with MCI and 31 healthy controls (HC) underwent CDT assessment and MRI at 3 Tesla. The surface-based analysis via Freesurfer enabled calculation of cortical thickness and surface area. CDT was scored according to the method proposed by Shulman and related to the two distinct cortical measurements. Higher CDT scores across the entire sample were associated with cortical thickness in bilateral temporal gyrus, the right supramarginal gyrus, and the bilateral parietal gyrus, respectively (p < 0.001 CWP corr.). Significant associations between CDT and cortical thickness reduction in the parietal lobe remained significant when analyses were restricted to AD individuals. There was no statistically significant association between CDT scores and surface area (p < 0.001 CWP corr.). In conclusion, CDT performance may be driven by cortical thickness alterations in regions previously identified as "AD vulnerable", i.e. regions predominantly including temporal and parietal lobes. Our results suggest that cortical features of distinct evolutionary and genetic origin differently contribute to CDT performance.

Moderate alcohol consumption as risk factor for adverse brain outcomes and cognitive decline: longitudinal cohort study

Objectives To investigate whether moderate alcohol consumption has a favourable or adverse association or no association with brain structure and function.Design Observational cohort study with weekly alcohol intake and cognitive performance measured repeatedly over 30 years (1985-2015). Multimodal magnetic resonance imaging (MRI) was performed at study endpoint (2012-15).Setting Community dwelling adults enrolled in the Whitehall II cohort based in the UK (the Whitehall II imaging substudy).Participants 550 men and women with mean age 43.0 (SD 5.4) at study baseline, none were "alcohol dependent" according to the CAGE screening questionnaire, and all safe to undergo MRI of the brain at follow-up. Twenty three were excluded because of incomplete or poor quality imaging data or gross structural abnormality (such as a brain cyst) or incomplete alcohol use, sociodemographic, health, or cognitive data.Main outcome measures Structural brain measures included hippocampal atrophy, grey matter density, and white matter microstructure. Functional measures included cognitive decline over the study and cross sectional cognitive performance at the time of scanning.Results Higher alcohol consumption over the 30 year follow-up was associated with increased odds of hippocampal atrophy in a dose dependent fashion. While those consuming over 30 units a week were at the highest risk compared with abstainers (odds ratio 5.8, 95% confidence interval 1.8 to 18.6; P≤0.001), even those drinking moderately (14-21 units/week) had three times the odds of right sided hippocampal atrophy (3.4, 1.4 to 8.1; P=0.007). There was no protective effect of light drinking (1-<7 units/week) over abstinence. Higher alcohol use was also associated with differences in corpus callosum microstructure and faster decline in lexical fluency. No association was found with cross sectional cognitive performance or longitudinal changes in semantic fluency or word recall.Conclusions Alcohol consumption, even at moderate levels, is associated with adverse brain outcomes including hippocampal atrophy. These results support the recent reduction in alcohol guidance in the UK and question the current limits recommended in the US.

Brain MR Image Classification for Alzheimer's Disease Diagnosis Based on Multifeature Fusion

We propose a novel classification framework to precisely identify individuals with Alzheimer's disease (AD) or mild cognitive impairment (MCI) from normal controls (NC). The proposed method combines three different features from structural MR images: gray-matter volume, gray-level cooccurrence matrix, and Gabor feature. These features can obtain both the 2D and 3D information of brains, and the experimental results show that a better performance can be achieved through the multifeature fusion. We also analyze the multifeatures combination correlation technologies and improve the SVM-RFE algorithm through the covariance method. The results of comparison experiments on public Alzheimer's Disease Neuroimaging Initiative (ADNI) database demonstrate the effectiveness of the proposed method. Besides, it also indicates that multifeatures combination is better than the single-feature method. The proposed features selection algorithm could effectively extract the optimal features subset in order to improve the classification performance.

The Effect of Apolipoprotein E ε4 (APOE ε4) on Visuospatial Working Memory in Healthy Elderly and Amnestic Mild Cognitive Impairment Patients: An Event-Related Potentials Study

Background: Apolipoprotein E (APOE) ε4 is the only established risk gene for late-onset, sporadic Alzheimer’s disease (AD). Previous studies have provided inconsistent evidence for the effect of APOE ε4 status on the visuospatial working memory (VSWM).

Objective: The aim was to investigate the effect of APOE ε4 on VSWM with an event-related potential (ERP) study in healthy controls (HC) and amnestic mild cognitive impairment (aMCI) patients.

Methods: The study recorded 39 aMCI patients (27 APOE ε4 non-carriers and 12 APOE ε4 carriers) and their 43 matched controls (25 APOE ε4 non-carriers and 18 APOE ε4 carriers) with an 64-channel electroencephalogram. Participants performed an N-back task, a VSWM paradigm that manipulated the number of items to be stored in memory.

Results: The present study detected reduced accuracy and delayed mean correct response time (RT) in aMCI patients compared to HC. P300, a positive component that peaks between 300 and 500 ms, was elicited by the VSWM task. In addition, aMCI patients showed decreased P300 amplitude at the central–parietal (CP1, CPz, and CP2) and parietal (P1, Pz, and P2) electrodes in 0- and 1-back task compared to HC. In both HC and aMCI patients, APOE ε4 carriers showed reduced P300 amplitude with respect to non-carriers, whereas no significant differences in accuracy or RT were detected between APOE ε4 carriers and non-carriers. Additionally, standardized low-resolution brain electromagnetic tomography analysis (s-LORETA) showed enhanced brain activation in the right parahippocampal gyrus (PHG) during P300 time range in APOE ε4 carriers with respect to non-carriers in aMCI patients.

Conclusion: It demonstrated that P300 amplitude could predict VSWM deficits in aMCI patients and contribute to early detection of VSWM deficits in APOE ε4 carriers.

Different Hippocampus Functional Connectivity Patterns in Healthy Young Adults with Mutations of APP/Presenilin-1/2 and APOEε4

This study aims to explore the hippocampus-based functional connectivity patterns in young, healthy APP and/or presenilin-1/2 mutation carriers and APOE ε4 subjects. Seventy-eight healthy young adults (33 male, mean age 24.0 ± 2.2 years; 18 APP and/or presenilin1/2 mutation carriers [APP/presenilin-1/2 group], 30 APOE ε4 subjects [APOE ε4 group], and 30 subjects without the above-mentioned genes [control group]) underwent resting-state functional MR imaging and neuropsychological assessments. Bilateral hippocampus functional connectivity patterns were compared among three groups. The brain regions with statistical differences were then extracted, and correlation analyses were performed between Z values of the brain regions and neuropsychological results. Compared with control group, both APOE ε4 group and APP/presenilin-1/2 group showed increased functional connectivity in medial prefrontal cortex and precuneus for the seeds of bilateral hippocampi. The APOE ε4 group displayed increased functional connectivity from bilateral hippocampi to the left middle temporal gyrus compared with the control group. Moreover, compared with the APP/presenilin-1/2 group, the APOE ε4 group also had markedly increased functional connectivity in right hippocampus-left middle temporal gyrus. The Z values of right hippocampus-left middle temporal gyrus correlated with various neuropsychological results across all the subjects, as well as in APOE ε4 group. Young healthy adults carrying APOE ε4 and APP/presenilin-1/2 displayed different hippocampus functional connectivity patterns, which may underlie the discrepant mechanisms of gene-modulated cognitive dysfunction in Alzheimer's disease.

Structural neuroimaging in preclinical dementia: From microstructural deficits and grey matter atrophy to macroscale connectomic changes

The last decade has witnessed a proliferation of neuroimaging studies characterising brain changes associated with Alzheimer's disease (AD), where both widespread atrophy and 'signature' brain regions have been implicated. In parallel, a prolonged latency period has been established in AD, with abnormal cerebral changes beginning many years before symptom onset. This raises the possibility of early therapeutic intervention, even before symptoms, when treatments could have the greatest effect on disease-course modification. Two important prerequisites of this endeavour are (1) accurate characterisation or risk stratification and (2) monitoring of progression using neuroimaging outcomes as a surrogate biomarker in those without symptoms but who will develop AD, here referred to as preclinical AD. Structural neuroimaging modalities have been used to identify brain changes related to risk factors for AD, such as familial genetic mutations, risk genes (for example apolipoprotein epsilon-4 allele), and/or family history. In this review, we summarise structural imaging findings in preclinical AD. Overall, the literature suggests early vulnerability in characteristic regions, such as the medial temporal lobe structures and the precuneus, as well as white matter tracts in the fornix, cingulum and corpus callosum. We conclude that while structural markers are promising, more research and validation studies are needed before future secondary prevention trials can adopt structural imaging biomarkers as either stratification or surrogate biomarkers.

Neurologic Applications of PET/MR Imaging

PET/MR imaging benefits neurologic clinical care and research by providing spatially and temporally matched anatomic MR imaging, advanced MR physiologic imaging, and metabolic PET imaging. MR imaging sequences and PET tracers can be modified to target physiology specific to a neurologic disease process, with applications in neurooncology, epilepsy, dementia, cerebrovascular disease, and psychiatric and neurologic research. Simultaneous PET/MR imaging provides efficient acquisition of multiple temporally matched datasets, and opportunities for motion correction and improved anatomic assignment of PET data. Current challenges include optimizing MR imaging-based attenuation correction and necessity for dual expertise in PET and MR imaging.

Hippocampal formation alterations differently contribute to autobiographic memory deficits in mild cognitive impairment and Alzheimer's disease

Autobiographical memory (AM) is part of declarative memory and includes both semantic and episodic aspects. AM deficits are among the major complaints of patients with Alzheimer's disease (AD) even in early or preclinical stages. Previous MRI studies in AD patients have showed that deficits in semantic and episodic AM are associated with hippocampal alterations. However, the question which specific hippocampal subfields and adjacent extrahippocampal structures contribute to deficits of AM in individuals with mild cognitive impairment (MCI) and AD patients has not been investigated so far. Hundred and seven participants (38 AD patients, 38 MCI individuals and 31 healthy controls [HC]) underwent MRI at 3 Tesla. AM was assessed with a semi-structured interview (E-AGI). FreeSurfer 5.3 was used for hippocampal parcellation. Semantic and episodic AM scores were related to the volume of 5 hippocampal subfields and cortical thickness in the parahippocampal and entorhinal cortex. Both semantic and episodic AM deficits were associated with bilateral hippocampal alterations. These associations referred mainly to CA1, CA2-3, presubiculum, and subiculum atrophy. Episodic, but not semantic AM loss was associated with cortical thickness reduction of the bilateral parahippocampal and enthorinal cortex. In MCI individuals, episodic, but not semantic AM deficits were associated with alterations of the CA1, presubiculum and subiculum. Our findings support the crucial role of CA1, presubiculum, and subiculum in episodic memory. The present results implicate that in MCI individuals, semantic and episodic AM deficits are subserved by distinct neuronal systems.

Midlife managerial experience is linked to late life hippocampal morphology and function

An active cognitive lifestyle has been suggested to have a protective role in the long-term maintenance of cognition. Amongst healthy older adults, more managerial or supervisory experiences in midlife are linked to a slower hippocampal atrophy rate in late life. Yet whether similar links exist in individuals with Mild Cognitive Impairment (MCI) is not known, nor whether these differences have any functional implications. 68 volunteers from the Sydney SMART Trial, diagnosed with non-amnestic MCI, were divided into high and low managerial experience (HME/LME) during their working life. All participants underwent neuropsychological testing, structural and resting-state functional MRI. Group comparisons were performed on hippocampal volume, morphology, hippocampal seed-based functional connectivity, memory and executive function and self-ratings of memory proficiency. HME was linked to better memory function (p = 0.024), mediated by larger hippocampal volume (p = 0.025). More specifically, deformation analysis found HME had relatively more volume in the CA1 sub-region of the hippocampus (p < 0.05). Paradoxically, this group rated their memory proficiency worse (p = 0.004), a result correlated with diminished functional connectivity between the right hippocampus and right prefrontal cortex (p < 0.001). Finally, hierarchical regression modelling substantiated this double dissociation.

Multimodality Review of Amyloid-related Diseases of the Central Nervous System

Amyloid-β (Aβ) is ubiquitous in the central nervous system (CNS), but pathologic accumulation of Aβ results in four distinct neurologic disorders that affect middle-aged and elderly adults, with diverse clinical presentations ranging from chronic debilitating dementia to acute life-threatening intracranial hemorrhage. The characteristic imaging patterns of Aβ-related CNS diseases reflect the pathophysiology of Aβ deposition in the CNS. Aβ is recognized as a key component in the neuronal damage that characterizes the pathophysiology of Alzheimer disease, the most common form of dementia. Targeted molecular imaging shows pathologic accumulation of Aβ and tau protein, and fluorine 18 fluorodeoxyglucose positron emission tomography and anatomic imaging allow differentiation of typical patterns of neuronal dysfunction and loss in patients with Alzheimer disease from those seen in patients with other types of dementia. Cerebral amyloid angiopathy (CAA) is an important cause of cognitive impairment and spontaneous intracerebral hemorrhage in the elderly. Hemorrhage and white matter injury seen at imaging reflect vascular damage caused by the accumulation of Aβ in vessel walls. The rare forms of inflammatory angiopathy attributed to Aβ, Aβ-related angiitis and CAA-related inflammation, cause debilitating neurologic symptoms that improve with corticosteroid therapy. Imaging shows marked subcortical and cortical inflammation due to perivascular inflammation, which is incited by vascular Aβ accumulation. In the rarest of the four disorders, cerebral amyloidoma, the macroscopic accumulation of Aβ mimics the imaging appearance of tumors. Knowledge of the imaging patterns and pathophysiology is essential for accurate diagnosis of Aβ-related diseases of the CNS. (©)RSNA, 2016.

Magnetic resonance imaging and positron emission tomography in the diagnosis of neurodegenerative dementias

Neuroimaging, both with magnetic resonance imaging (MRI) and positron emission tomography (PET), has gained a pivotal role in the diagnosis of primary neurodegenerative diseases. These two techniques are used as biomarkers of both pathology and progression of Alzheimer's disease (AD) and to differentiate AD from other neurodegenerative diseases. MRI is able to identify structural changes including patterns of atrophy characterizing neurodegenerative diseases, and to distinguish these from other causes of cognitive impairment, e.g. infarcts, space-occupying lesions and hydrocephalus. PET is widely used to identify regional patterns of glucose utilization, since distinct patterns of distribution of cerebral glucose metabolism are related to different subtypes of neurodegenerative dementia. The use of PET in mild cognitive impairment, though controversial, is deemed helpful for predicting conversion to dementia and the dementia clinical subtype. Recently, new radiopharmaceuticals for the in vivo imaging of amyloid burden have been licensed and more tracers are being developed for the assessment of tauopathies and inflammatory processes, which may underlie the onset of the amyloid cascade. At present, the cerebral amyloid burden, imaged with PET, may help to exclude the presence of AD as well as forecast its possible onset. Finally PET imaging may be particularly useful in ongoing clinical trials for the development of dementia treatments. In the near future, the use of the above methods, in accordance with specific guidelines, along with the use of effective treatments will likely lead to more timely and successful treatment of neurodegenerative dementias.

Spatial navigation deficits in amnestic mild cognitive impairment with neuropsychiatric comorbidity

AIMS

To find out whether neuropsychiatric comorbidity (comMCI) influences spatial navigation performance in amnestic mild cognitive impairment (aMCI).

METHODS

We recruited aMCI patients with (n = 21) and without (n = 21) neuropsychiatric comorbidity or alcohol abuse, matched for global cognitive impairment and cognitively healthy elderly participants (HE, n = 22). They completed the Mini-Mental State Examination and a virtual Hidden Goal Task in egocentric, allocentric, and delayed recall subtests.

RESULTS

In allocentric navigation, aMCI and comMCI performed significantly worse than HE and similarly to each other. Although aMCI performed significantly worse at egocentric navigation than HE, they performed significantly better than patients with comMCI.

CONCLUSIONS

Despite the growing burden of dementia and the prevalence of neuropsychiatric symptoms in the elderly population, comMCI remains under-studied. Since trials often assess "pure" aMCI, we may underestimate patients' navigation and other deficits. This finding emphasizes the importance of taking account of the cognitive effects of psychiatric disorders in aMCI.

Prediction of Mild Cognitive Impairment Conversion Using a Combination of Independent Component Analysis and the Cox Model

Mild cognitive impairment (MCI) represents a transitional stage from normal aging to Alzheimer’s disease (AD) and corresponds to a higher risk of developing AD. Thus, it is necessary to explore and predict the onset of AD in MCI stage. In this study, we propose a combination of independent component analysis (ICA) and the multivariate Cox proportional hazards regression model to investigate promising risk factors associated with MCI conversion among 126 MCI converters and 108 MCI non-converters from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. Using structural magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) data, we extracted brain networks from AD and normal control groups via ICA and then constructed Cox models that included network-based neuroimaging factors for the MCI group. We carried out five separate Cox analyses and the two-modality neuroimaging Cox model identified three significant network-based risk factors with higher prediction performance (accuracy = 73.50%) than those in either single-modality model (accuracy = 68.80%). Additionally, the results of the comprehensive Cox model, including significant neuroimaging factors and clinical variables, demonstrated that MCI individuals with reduced gray matter volume in a temporal lobe-related network of structural MRI [hazard ratio (HR) = 8.29E-05 (95% confidence interval (CI), 5.10E- 07 ~ 0.013)], low glucose metabolism in the posterior default mode network based on FDG-PET [HR = 0.066 (95% CI, 4.63E-03 ~ 0.928)], positive apolipoprotein E ε4-status [HR = 1. 988 (95% CI, 1.531 ~ 2.581)], increased Alzheimer’s Disease Assessment Scale-Cognitive Subscale scores [HR = 1.100 (95% CI, 1.059 ~ 1.144)] and Sum of Boxes of Clinical Dementia Rating scores [HR = 1.622 (95% CI, 1.364 ~ 1.930)] were more likely to convert to AD within 36 months after baselines. These significant risk factors in such comprehensive Cox model had the best prediction ability (accuracy = 84.62%, sensitivity = 86.51%, specificity = 82.41%) compared to either neuroimaging factors or clinical variables alone. These results suggested that a combination of ICA and Cox model analyses could be used successfully in survival analysis and provide a network-based perspective of MCI progression or AD-related studies.

Computational imaging reveals shape differences between normal and malignant prostates on MRI

We seek to characterize differences in the shape of the prostate and the central gland (combined central and transitional zones) between men with biopsy confirmed prostate cancer and men who were identified as not having prostate cancer either on account of a negative biopsy or had pelvic imaging done for a non-prostate malignancy. T2w MRI from 70 men were acquired at three institutions. The cancer positive group (PCa+) comprised 35 biopsy positive (Bx+) subjects from three institutions (Gleason scores: 6–9, Stage: T1–T3). The negative group (PCa−) combined 24 biopsy negative (Bx−) from two institutions and 11 subjects diagnosed with rectal cancer but with no clinical or MRI indications of prostate cancer (Cl−). The boundaries of the prostate and central gland were delineated on T2w MRI by two expert raters and were used to construct statistical shape atlases for the PCa+, Bx− and Cl− prostates. An atlas comparison was performed via per-voxel statistical tests to localize shape differences (significance assessed at p < 0.05). The atlas comparison revealed central gland hypertrophy in the Bx− subpopulation, resulting in significant volume and posterior side shape differences relative to PCa+ group. Significant differences in the corresponding prostate shapes were noted at the apex when comparing the Cl− and PCa+ prostates.

Identification of Early-Stage Alzheimer's Disease Using Sulcal Morphology and Other Common Neuroimaging Indices

Identifying Alzheimer’s disease (AD) at its early stage is of major interest in AD research. Previous studies have suggested that abnormalities in regional sulcal width and global sulcal index (g-SI) are characteristics of patients with early-stage AD. In this study, we investigated sulcal width and three other common neuroimaging morphological measures (cortical thickness, cortical volume, and subcortical volume) to identify early-stage AD. These measures were evaluated in 150 participants, including 75 normal controls (NC) and 75 patients with early-stage AD. The global sulcal index (g-SI) and the width of five individual sulci (the superior frontal, intra-parietal, superior temporal, central, and Sylvian fissure) were extracted from 3D T1-weighted images. The discriminative performances of the other three traditional neuroimaging morphological measures were also examined. Information Gain (IG) was used to select a subset of features to provide significant information for separating NC and early-stage AD subjects. Based on the four modalities of the individual measures, i.e., sulcal measures, cortical thickness, cortical volume, subcortical volume, and combinations of these individual measures, three types of classifiers (Naïve Bayes, Logistic Regression and Support Vector Machine) were applied to compare the classification performances. We observed that sulcal measures were either superior than or equal to the other measures used for classification. Specifically, the g-SI and the width of the Sylvian fissure were two of the most sensitive sulcal measures and could be useful neuroanatomical markers for detecting early-stage AD. There were no significant differences between the three classifiers that we tested when using the same neuroanatomical features.

Morphological and Microstructural Changes of the Hippocampus in Early MCI: A Study Utilizing the Alzheimer's Disease Neuroimaging Initiative Database

Background and Purpose

With the aim of facilitating the early detection of Alzheimer's disease, the Alzheimer's Disease Neuroimaging Initiative proposed two stages based on the memory performance: early mild cognitive impairment (EMCI) and late mild cognitive impairment (LMCI). The current study was designed to investigate structural differences in terms of surface atrophy and microstructural changes of the hippocampus in EMCI and LMCI.

Methods

Hippocampal shape modeling based on progressive template surface deformation was performed on T1-weighted MRI images obtained from 20 cognitive normal (CN) subjects, 17 EMCI patients, and 20 LMCI patients. A template surface in CN was used as a region of interest for diffusion-tensor imaging (DTI) voxel-based morphometry (VBM) analysis. Cluster-wise group comparison was performed based on DTI indices within the hippocampus. Linear regression was performed to identify correlations between DTI metrics and clinical scores.

Results

The hippocampal surface analysis showed significant atrophies in bilateral CA1 regions and the right ventral subiculum in EMCI, in contrast to widespread atrophy in LMCI. DTI VBM analysis showed increased diffusivity in the CA2–CA4 regions in EMCI and additionally in the subiculum region in LMCI. Hippocampal diffusivity was significantly correlated with scores both for the Mini Mental State Examination and on the Modified Alzheimer Disease Assessment Scale cognitive subscale. However, the hippocampal diffusivity did not vary significantly with the fractional anisotropy.

Conclusions

EMCI showed hippocampal surface changes mainly in the CA1 region and ventral subiculum. Diffusivity increased mainly in the CA2–CA4 regions in EMCI, while it decreased throughout the hippocampus in LMCI. Although axial diffusivity showed prominent changes in the right hippocampus in EMCI, future studies need to confirm the presence of this laterality difference. In addition, diffusivity is strongly correlated with the cognitive performance, indicating the possibility of using diffusivity as a biomarker for disease progression.

Lateralized occipital degeneration in posterior cortical atrophy predicts visual field deficits

Background

Posterior cortical atrophy (PCA), the visual variant of Alzheimer's disease, leads to high-level visual deficits such as alexia or agnosia. Visual field deficits have also been identified, but often inconsistently reported. Little is known about the pattern of visual field deficits or the underlying cortical changes leading to this visual loss.

Methods

Multi-modal magnetic resonance imaging was used to investigate differences in gray matter volume, cortical thickness, white matter microstructure and functional activity in patients with PCA compared to age-matched controls. Additional analyses investigated hemispheric asymmetries in these metrics according to the visual field most affected by the disease.

Results

Analysis of structural data indicated considerable loss of gray matter in the occipital and parietal cortices, lateralized to the hemisphere contralateral to the visual loss. This lateralized pattern of gray matter loss was also evident in the hippocampus and parahippocampal gyrus. Diffusion-weighted imaging showed considerable effects of PCA on white matter microstructure in the occipital cortex, and in the corpus callosum. The change in white matter was only lateralized in the occipital lobe, however, with greatest change in the optic radiation contralateral to the visual field deficit. Indeed, there was a significant correlation between the laterality of the optic radiation microstructure and visual field loss.

Conclusions

Detailed brain imaging shows that the asymmetric visual field deficits in patients with PCA reflect the pattern of degeneration of both white and gray matter in the occipital lobe. Understanding the nature of both visual field deficits and the neurodegenerative brain changes in PCA may improve diagnosis and understanding of this disease.

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Patients with posterior cortical atrophy show asymmetric visual field deficits manifesting as hemianopia.

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Both gray and white matter show lateralized degeneration corresponding to the most affected visual field.

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Laterality of microstructure in the optic radiation correlates with visual field loss.

Multimodal Brain Imaging Reveals Structural Differences in Alzheimer's Disease Polygenic Risk Carriers: A Study in Healthy Young Adults

BACKGROUND

Recent genome-wide association studies have identified genetic loci that jointly make a considerable contribution to risk of developing Alzheimer's disease (AD). Because neuropathological features of AD can be present several decades before disease onset, we investigated whether effects of polygenic risk are detectable by neuroimaging in young adults. We hypothesized that higher polygenic risk scores (PRSs) for AD would be associated with reduced volume of the hippocampus and other limbic and paralimbic areas. We further hypothesized that AD PRSs would affect the microstructure of fiber tracts connecting the hippocampus with other brain areas.

METHODS

We analyzed the association between AD PRSs and brain imaging parameters using T1-weighted structural (n = 272) and diffusion-weighted scans (n = 197).

RESULTS

We found a significant association between AD PRSs and left hippocampal volume, with higher risk associated with lower left hippocampal volume (p = .001). This effect remained when the APOE gene was excluded (p = .031), suggesting that the relationship between hippocampal volume and AD is the result of multiple genetic factors and not exclusively variability in the APOE gene. The diffusion tensor imaging analysis revealed that fractional anisotropy of the right cingulum was inversely correlated with AD PRSs (p = .009). We thus show that polygenic effects of AD risk variants on brain structure can already be detected in young adults.

CONCLUSIONS

This finding paves the way for further investigation of the effects of AD risk variants and may become useful for efforts to combine genotypic and phenotypic data for risk prediction and to enrich future prevention trials of AD.

Assessing Spatial Learning and Memory in Small Squamate Reptiles

Clinical research has leveraged a variety of paradigms to assess cognitive decline, commonly targeting spatial learning and memory abilities. However, interest in the cognitive processes of nonmodel species, typically within an ecological context, has also become an emerging field of study. In particular, interest in the cognitive processes in reptiles is growing although experimental studies on reptilian cognition are sparse. The few reptilian studies that have experimentally tested for spatial learning and memory have used rodent paradigms modified for use in reptiles. However, ecologically important aspects of the physiology and behavior of this taxonomic group must be taken into account when testing for spatially based cognition. Here, we describe modifications of the dry land Barnes maze and associated testing protocol that can improve performance when probing for spatial learning and memory ability in small squamate reptiles. The described paradigm and procedures were successfully used with male side-blotched lizards (Uta stansburiana), demonstrating that spatial learning and memory can be assessed in this taxonomic group with an ecologically relevant apparatus and protocol.

Cognitive dysfunction in major depression and Alzheimer's disease is associated with hippocampal-prefrontal cortex dysconnectivity

Cognitive dysfunction is prevalent in psychiatric disorders. Deficits are observed in multiple domains, including working memory, executive function, attention, and information processing. Disability caused by cognitive dysfunction is frequently as debilitating as the prominent emotional disturbances. Interactions between the hippocampus and the prefrontal cortex are increasingly appreciated as an important link between cognition and emotion. Recent developments in optogenetics, imaging, and connectomics can enable the investigation of this circuit in a manner that is relevant to disease pathophysiology. The goal of this review is to shed light on the contributions of this circuit to cognitive dysfunction in neuropsychiatric disorders, focusing on Alzheimer's disease and depression.

Selection bias in the reported performances of AD classification pipelines

The last decade has seen a great proliferation of supervised learning pipelines for individual diagnosis and prognosis in Alzheimer's disease. As more pipelines are developed and evaluated in the search for greater performance, only those results that are relatively impressive will be selected for publication. We present an empirical study to evaluate the potential for optimistic bias in classification performance results as a result of this selection. This is achieved using a novel, resampling-based experiment design that effectively simulates the optimisation of pipeline specifications by individuals or collectives of researchers using cross validation with limited data. Our findings indicate that bias can plausibly account for an appreciable fraction (often greater than half) of the apparent performance improvement associated with the pipeline optimisation, particularly in small samples. We discuss the consistency of our findings with patterns observed in the literature and consider strategies for bias reduction and mitigation.

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Demonstration and measurement of selection bias in AD classification experiments

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Bias accounts for much of the performance improvement seen with pipeline optimisation.

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Assessment of key risk factors and guidance on best research practices

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Evidence of selection bias in results collected by a recent literature review

Cognitive Aging and the Hippocampus in Older Adults

The hippocampus is one of the most well studied structures in the human brain. While age-related decline in hippocampal volume is well documented, most of our knowledge about hippocampal structure-function relationships was discovered in the context of neurological and neurodegenerative diseases. The relationship between cognitive aging and hippocampal structure in the absence of disease remains relatively understudied. Furthermore, the few studies that have investigated the role of the hippocampus in cognitive aging have produced contradictory results. To address these issues, we assessed 93 older adults from the general community (mean age = 71.9 ± 9.3 years) on the Montreal Cognitive Assessment (MoCA), a brief cognitive screening measure for dementia, and the NIH Toolbox-Cognitive Battery (NIHTB-CB), a computerized neurocognitive battery. High-resolution structural magnetic resonance imaging (MRI) was used to estimate hippocampal volume. Lower MoCA Total (p = 0.01) and NIHTB-CB Fluid Cognition (p < 0.001) scores were associated with decreased hippocampal volume, even while controlling for sex and years of education. Decreased hippocampal volume was significantly associated with decline in multiple NIHTB-CB subdomains, including episodic memory, working memory, processing speed and executive function. This study provides important insight into the multifaceted role of the hippocampus in cognitive aging.

Whole-brain analysis reveals increased neuroanatomical asymmetries in dementia for hippocampus and amygdala

Structural magnetic resonance imaging data are frequently analysed to reveal morphological changes of the human brain in dementia. Most contemporary imaging biomarkers are scalar values, such as the volume of a structure, and may miss the localized morphological variation of early presymptomatic disease progression. Neuroanatomical shape descriptors, however, can represent complex geometric information of individual anatomical regions and may demonstrate increased sensitivity in association studies. Yet, they remain largely unexplored. In this article, we introduce a novel technique to study shape asymmetries of neuroanatomical structures across subcortical and cortical brain regions. We demonstrate that neurodegeneration of subcortical structures in Alzheimer's disease is not symmetric. The hippocampus shows a significant increase in asymmetry longitudinally and both hippocampus and amygdala show a significantly higher asymmetry cross-sectionally concurrent with disease severity above and beyond an ageing effect. Our results further suggest that the asymmetry in these structures is undirectional and that primarily the anterior hippocampus becomes asymmetric. Based on longitudinal asymmetry measures we subsequently study the progression from mild cognitive impairment to dementia, demonstrating that shape asymmetry in hippocampus, amygdala, caudate and cortex is predictive of disease onset. The same analyses on scalar volume measurements did not produce any significant results, indicating that shape asymmetries, potentially induced by morphometric changes in subnuclei, rather than size asymmetries are associated with disease progression and can yield a powerful imaging biomarker for the early presymptomatic classification and prediction of Alzheimer's disease. Because literature has focused on contralateral volume differences, subcortical disease lateralization may have been overlooked thus far.