Alzheimer disease: new concepts on its neurobiology and the clinical role imaging will play

Personalized medicine in old age psychiatry and Alzheimer's disease

Elderly patients show us unfolded lives with unique individual characteristics. An increasing life span is associated with increasing physical and mental disease burden. Alzheimer's disease (AD) is an increasing challenge in old age. AD cannot be cured but it can be treated. The complexity of old age and AD offer targets for personalized medicine (PM). Targets for stratification of patients, detection of patients at risk for AD or for future targeted therapy are plentiful and can be found in several omic-levels.

Comparison of Inter-Method Agreement and Reliability for Automatic Brain Volumetry Using Three Different Clinically Available Software Packages

Background and Objectives: No comparative study has evaluated the inter-method agreement and reliability between Heuron AD and other clinically available brain volumetric software packages. Hence, we aimed to investigate the inter-method agreement and reliability of three clinically available brain volumetric software packages: FreeSurfer (FS), NeuroQuant® (NQ), and Heuron AD (HAD). Materials and Methods: In this study, we retrospectively included 78 patients who underwent conventional three-dimensional (3D) T1-weighed imaging (T1WI) to evaluate their memory impairment, including 21 with normal objective cognitive function, 24 with mild cognitive impairment, and 33 with Alzheimer's disease (AD). All 3D T1WI scans were analyzed using three different volumetric software packages. Repeated-measures analysis of variance, intraclass correlation coefficient, effect size measurements, and Bland-Altman analysis were used to evaluate the inter-method agreement and reliability. Results: The measured volumes demonstrated substantial to almost perfect agreement for most brain regions bilaterally, except for the bilateral globi pallidi. However, the volumes measured using the three software packages showed significant mean differences for most brain regions, with consistent systematic biases and wide limits of agreement in the Bland-Altman analyses. The pallidum showed the largest effect size in the comparisons between NQ and FS (5.20-6.93) and between NQ and HAD (2.01-6.17), while the cortical gray matter showed the largest effect size in the comparisons between FS and HAD (0.79-1.91). These differences and variations between the software packages were also observed in the subset analyses of 45 patients without AD and 33 patients with AD. Conclusions: Despite their favorable reliability, the software-based brain volume measurements showed significant differences and systematic biases in most regions. Thus, these volumetric measurements should be interpreted based on the type of volumetric software used, particularly for smaller structures. Moreover, users should consider the replaceability-related limitations when using these packages in real-world practice.

Mathematical modeling of human memory

The mathematical study of human memory is still an open challenge. Cognitive psychology and neuroscience have given a big contribution to understand how the human memory is structured and works. Cognitive psychologists developed experimental paradigms, conceived quantitative measures of performance in memory tasks for both healthy people and patients with memory disorders, but in terms of mathematical modeling human memory there is still a lot to do. There are many ways to mathematically model human memory, for example, by using mathematical analysis, linear algebra, statistics, and artificial neural networks. The aim of this study is to provide the reader with a description of some prominent models, involving mathematical analysis and linear algebra, designed to describe how memory works by predicting the results of psychological experiments. We have ordered the models from a chronological point of view and, for each model, we have emphasized what are, in our opinion, the strong and weak points. We are aware that this study covers just a part of human memory modeling as well as that we have made a personal selection, which is arguable. Nevertheless, our hope is to help scientists to modeling human memory and its diseases.

Metabolite Variations in the Hippocampus and Corpus Callosum of Patients with Mild Cognitive Impairment Using Magnetic Resonance Spectroscopy with Three-Dimensional Chemical Shift Images

This study compared the metabolites in the brain regions of hippocampus and corpus callosum between patients with mild cognitive impairment (MCI) and healthy controls using no-radiation and high-sensitivity magnetic resonance spectroscopy (MRS) with three-dimensional chemical shift images (3D-CSI). Twenty volunteers (seven patients with MCI and 13 healthy controls) aged 50-71 years were recruited for this prospective study. MRS with 3D-CSI images of a variety of metabolites was collected from the hippocampus and corpus callosum. Sex and weight showed no significant differences between the two groups. The metabolite levels in the hippocampus and corpus callosum of the MCI group were generally lower than in those of the healthy group, especially for creatine (p < 0.001 in the hippocampus and p = 0.020 in the corpus callosum) and N-acetyl aspartate/creatine (p < 0.001 in the hippocampus and p = 0.020 in the corpus callosum); however, choline/creatine showed a significant difference (p < 0.001) only in the hippocampus, and myo-inositol/creatine showed a significant difference (p < 0.001) only in the corpus callosum. Our study demonstrated that MRS with 3D-CSI can be used to measure these metabolite levels to determine the differences between patients with MCI and healthy individuals. This would aid early diagnosis of MCI in clinical practice, and patients could receive prompt intervention to improve their quality of life.

Prediction of Amyloid β-Positivity with both MRI Parameters and Cognitive Function Using Machine Learning

Purpose

To investigate the MRI markers for the prediction of amyloid β (Aβ)-positivity in mild cognitive impairment (MCI) and Alzheimer's disease (AD), and to evaluate the differences in MRI markers between Aβ-positive (Aβ [+]) and -negative groups using the machine learning (ML) method.

Materials and Methods

This study included 139 patients with MCI and AD who underwent amyloid PET-CT and brain MRI. Patients were divided into Aβ (+) (n = 84) and Aβ-negative (n = 55) groups. Visual analysis was performed with the Fazekas scale of white matter hyperintensity (WMH) and cerebral microbleeds (CMB) scores. The WMH volume and regional brain volume were quantitatively measured. The multivariable logistic regression and ML using support vector machine, and logistic regression were used to identify the best MRI predictors of Aβ-positivity.

Results

The Fazekas scale of WMH (p = 0.02) and CMB scores (p = 0.04) were higher in Aβ (+). The volumes of hippocampus, entorhinal cortex, and precuneus were smaller in Aβ (+) (p < 0.05). The third ventricle volume was larger in Aβ (+) (p = 0.002). The logistic regression of ML showed a good accuracy (81.1%) with mini-mental state examination (MMSE) and regional brain volumes.

Conclusion

The application of ML using the MMSE, third ventricle, and hippocampal volume is helpful in predicting Aβ-positivity with a good accuracy.

Longitudinal Assessment of Intravoxel Incoherent Motion Diffusion-Weighted MRI Metrics in Cognitive Decline

BACKGROUND

Advanced diffusion-based MRI biomarkers may provide insight into microstructural and perfusion changes associated with neurodegeneration and cognitive decline.

PURPOSE

To assess longitudinal microstructural and perfusion changes using apparent diffusion coefficient (ADC) and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) parameters in cognitively impaired (CI) and healthy control (HC) groups.

STUDY TYPE

Prospective/longitudinal.

POPULATION

Twelve CI patients (75% female) and 13 HC subjects (69% female).

FIELD STRENGTH/SEQUENCE

3 T; Spin-Echo-IVIM-DWI.

ASSESSMENT

Two MRI scans were performed with a 12-month interval. ADC and IVIM-DWI metrics (diffusion coefficient [D] and perfusion fraction [f]) were generated from monoexponential and biexponential fits, respectively. Additionally, voxel-based correlations were evaluated between change in Montreal Cognitive Assessment (ΔMoCA) and baseline imaging parameters.

STATISTICAL TESTS

Analysis of covariance with sex and age as covariates was performed for main effects of group and time (false discovery rate [FDR] corrected) with post hoc comparisons using Bonferroni correction. Partial-η² and Hedges' g were used for effect-size analysis. Spearman's correlations (FDR corrected) were used for the relationship between ΔMoCA score and imaging. P < 0.05 was considered statistically significant.

RESULTS

Significant differences were found for the main effects of group (HC vs. CI) and time. For group effects, higher ADC, IVIM-D, and IVIM-f were observed in the CI group compared to HC (ADC: 1.23 ± 0.08^. 10^-3 vs. 1.09 ± 0.07^. 10^-3  mm² /sec; IVIM-D: 0.82 ± 0.01^. 10^-3 vs. 0.73 ± 0.01^. 10^-3  mm² /sec; and IVIM-f: 0.317 ± 0.008 vs. 0.253 ± 0.009). Significantly higher ADC, IVIM-D, and IVIM-f values were observed in the CI group after 12 months (ADC: 1.45 ± 0.05^. 10^-3 vs. 1.50 ± 0.07^. 10^-3  mm² /sec; IVIM-D: 0.87 ± 0.01^. 10^-3 vs. 0.94 ± 0.02^. 10^-3  mm² /sec; and IVIM-f: 0.303 ± 0.007 vs. 0.332 ± 0.008), but not in the HC group at large effect size. ADC, IVIM-D, and IVIM-f negatively correlated with ΔMoCA score (ρ = -0.49, -0.51, and -0.50, respectively).

DATA CONCLUSION

These findings demonstrate that longitudinal differences between CI and HC cohorts can be measured using IVIM-based metrics.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY STAGE: 2.

Regularized Buckley-James method for right-censored outcomes with block-missing multimodal covariates

High-dimensional data with censored outcomes of interest are prevalent in medical research. To analyze such data, the regularized Buckley-James estimator has been successfully applied to build accurate predictive models and conduct variable selection. In this paper, we consider the problem of parameter estimation and variable selection for the semiparametric accelerated failure time model for high-dimensional block-missing multimodal neuroimaging data with censored outcomes. We propose a penalized Buckley-James method that can simultaneously handle block-wise missing covariates and censored outcomes. This method can also perform variable selection. The proposed method is evaluated by simulations and applied to a multimodal neuroimaging dataset and obtains meaningful results.

Agreement and Reliability between Clinically Available Software Programs in Measuring Volumes and Normative Percentiles of Segmented Brain Regions

OBJECTIVE

To investigate the agreement and reliability of estimating the volumes and normative percentiles (N%) of segmented brain regions among NeuroQuant (NQ), DeepBrain (DB), and FreeSurfer (FS) software programs, focusing on the comparison between NQ and DB.

MATERIALS AND METHODS

Three-dimensional T1-weighted images of 145 participants (48 healthy participants, 50 patients with mild cognitive impairment, and 47 patients with Alzheimer's disease) from a single medical center (SMC) dataset and 130 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset were included in this retrospective study. All images were analyzed with DB, NQ, and FS software to obtain volume estimates and N% of various segmented brain regions. We used Bland-Altman analysis, repeated measures ANOVA, reproducibility coefficient, effect size, and intraclass correlation coefficient (ICC) to evaluate inter-method agreement and reliability.

RESULTS

Among the three software programs, the Bland-Altman plot showed a substantial bias, the ICC showed a broad range of reliability (0.004-0.97), and repeated-measures ANOVA revealed significant mean volume differences in all brain regions. Similarly, the volume differences of the three software programs had large effect sizes in most regions (0.73-5.51). The effect size was largest in the pallidum in both datasets and smallest in the thalamus and cerebral white matter in the SMC and ADNI datasets, respectively. N% of NQ and DB showed an unacceptably broad Bland-Altman limit of agreement in all brain regions and a very wide range of ICC values (-0.142-0.844) in most brain regions.

CONCLUSION

NQ and DB showed significant differences in the measured volume and N%, with limited agreement and reliability for most brain regions. Therefore, users should be aware of the lack of interchangeability between these software programs when they are applied in clinical practice.

Neuroimaging Markers for Determining Former American Football Players at Risk for Alzheimer's Disease

NFL players, by virtue of their exposure to traumatic brain injury (TBI), are at higher risk of developing dementia and Alzheimer's disease (AD) than the general population. Early recognition and intervention before the onset of clinical symptoms could potentially avert/delay the long-term consequences of these diseases. Given that AD is thought to have a long pre-clinical incubation period, the aim of the current research was to determine whether former NFL players show evidence of incipient dementia in their structural imaging before diagnosis of AD. To identify neuroimaging markers of AD, against which former NFL players would be compared, we conducted a whole-brain volumetric analysis using a cohort of AD patients (ADNI clinical database) to produce a set of brain regions demonstrating sensitivity to early AD pathology (i.e., the “AD fingerprint”). A group of 46 former NFL players' brain magnetic resonance images were then interrogated using the AD fingerprint, that is, the former NFL subjects were compared volumetrically to AD patients using a T1-weighted magnetization-prepared rapid gradient echo sequence. The FreeSurfer image analysis suite (version 6.0) was used to obtain volumetric and cortical thickness data. The Automated Neuropsychological Assessment Metric-Version 4 was used to assess current cognitive functioning. A total of 55 brain regions demonstrated significant atrophy or ex vacuo dilatation bilaterally in AD patients versus controls. Of the 46 former NFL players, 41% demonstrated a greater than expected number of atrophied/dilated AD regions compared with age-matched controls, presumably reflecting AD pathology.

BACE1: A Key Regulator in Alzheimer's Disease Progression and Current Development of its Inhibitors

BACKGROUND

Alzheimer's disease (AD) is a chronic neurodegenerative disease with no specific disease-modifying treatment. β-secretase (BACE1) is considered the potential and rationale target because it is involved in the rate-limiting step, which produces toxic Aβ₄₂ peptides that leads to deposits in the form of amyloid plaques extracellularly, resulting in AD.

OBJECTIVE

This study aims to discuss the role and implications of BACE1 and its inhibitors in the management of AD.

METHODS

We have searched and collected the relevant quality work from PubMed using the following keywords "BACE1", BACE2", "inhibitors", and "Alzheimer's disease". In addition, we included the work which discusses the role of BACE1 in AD and the recent work on its inhibitors.

RESULTS

In this review, we have discussed the importance of BACE1 in regulating AD progression and the current development of BACE1 inhibitors. However, the development of a BACE1 inhibitor is very challenging due to the large active site of BACE1. Nevertheless, some of the BACE1 inhibitors have managed to enter advanced phases of clinical trials, such as MK-8931 (Verubecestat), E2609 (Elenbecestat), AZD3293 (Lanabecestat), and JNJ-54861911 (Atabecestat). This review also sheds light on the prospect of BACE1 inhibitors as the most effective therapeutic approach in delaying or preventing AD progression.

CONCLUSION

BACE1 is involved in the progression of AD. The current ongoing or failed clinical trials may help understand the role of BACE1 inhibition in regulating the Aβ load and cognitive status of AD patients.

[Brain MRI-Based Artificial Intelligence Software in Patients with Neurodegenerative Diseases: Current Status]

The incidence of neurodegenerative diseases in the older population has increased in recent years. A considerable number of studies have been performed to characterize these diseases. Imaging analysis is an important biomarker for the diagnosis of neurodegenerative disease. Objective and reliable assessment and precise detection are important for the early diagnosis of neurodegenerative diseases. Artificial intelligence (AI) using brain MRI applied to the study of neurodegenerative diseases could promote early diagnosis and optimal decisions for treatment plans. MRI-based AI software have been developed and studied worldwide. Representatively, there are MRI-based volumetry and segmentation software. In this review, we present the development process of brain volumetry analysis software in neurodegenerative diseases, currently used and developed AI software for neurodegenerative disease in the Republic of Korea, probable uses of AI in the future, and AI software limitations.

Emotion Processing Dysfunction in Alzheimer's Disease: An Overview of Behavioral Findings, Systems Neural Correlates, and Underlying Neural Biology

We described behavioral studies to highlight emotional processing deficits in Alzheimer's disease (AD). The findings suggest prominent deficit in recognizing negative emotions, pronounced effect of positive emotion on enhancing memory, and a critical role of cognitive deficits in manifesting emotional processing dysfunction in AD. We reviewed imaging studies to highlight morphometric and functional markers of hippocampal circuit dysfunction in emotional processing deficits. Despite amygdala reactivity to emotional stimuli, hippocampal dysfunction conduces to deficits in emotional memory. Finally, the reviewed studies implicating major neurotransmitter systems in anxiety and depression in AD supported altered cholinergic and noradrenergic signaling in AD emotional disorders. Overall, the studies showed altered emotions early in the course of illness and suggest the need of multimodal imaging for further investigations. Particularly, longitudinal studies with multiple behavioral paradigms translatable between preclinical and clinical models would provide data to elucidate the time course and underlying neurobiology of emotion processing dysfunction in AD.

Quantitative assessment of AD markers using naked eyes: point-of-care testing with paper-based lateral flow immunoassay

Aβ42 is one of the most extensively studied blood and Cerebrospinal fluid (CSF) biomarkers for the diagnosis of symptomatic and prodromal Alzheimer's disease (AD). Because of the heterogeneity and transient nature of Aβ42 oligomers (Aβ42Os), the development of technologies for dynamically detecting changes in the blood or CSF levels of Aβ42 monomers (Aβ42Ms) and Aβ42Os is essential for the accurate diagnosis of AD. The currently commonly used Aβ42 ELISA test kits usually mis-detected the elevated Aβ42Os, leading to incomplete analysis and underestimation of soluble Aβ42, resulting in a comprised performance in AD diagnosis. Herein, we developed a dual-target lateral flow immunoassay (dLFI) using anti-Aβ42 monoclonal antibodies 1F12 and 2C6 for the rapid and point-of-care detection of Aβ42Ms and Aβ42Os in blood samples within 30 min for AD diagnosis. By naked eye observation, the visual detection limit of Aβ42Ms or/and Aβ42Os in dLFI was 154 pg/mL. The test results for dLFI were similar to those observed in the enzyme-linked immunosorbent assay (ELISA). Therefore, this paper-based dLFI provides a practical and rapid method for the on-site detection of two biomarkers in blood or CSF samples without the need for additional expertise or equipment.

Cnidoscolus aconitifolius-supplemented diet enhanced neurocognition, endogenous antioxidants and cholinergic system and maintains hippocampal neuronal integrity in male Wistar rats

OBJECTIVES

Cnidoscolus aconitifolius have been investigated to have abundant phytochemicals. However, study on the effect of Cnidoscolus aconitifolius on neurobehavioral performance when supplemented with diet is lacking. The study is aimed at investigating the memory-enhancing effect of Cnidoscolus aconitifolius-supplemented diet (CAD) using Morris water maze and Novel object recognition test.

METHODS

Ninety male Wistar rats (80-100 g) were fed with CAD (1, 2.5, 5 and 10%) continuously for a period of 4, 8 and 12 weeks respectively. Six animals per group were used for assessment of memory performance (Morris water maze [MWM] and Novel object recognition test [NORT]); afterwards the brain tissues were harvested for malondialdehyde (MDA), glutathione (GSH) and catalase (CAT) estimation. Acetylcholinesterase (AChE) concentration was also determined. Hippocampal architectural change in the neuron was examined using hematoxylin and eosin (H&E) and cresyl fast violet (Nissl) stain.

RESULTS

Higher percentage of CAD significantly (p<0.05) improve memory performance with time-dependent effects in rats fed with CAD on MMW and NORT. MDA significantly (p<0.05) reduce in 1 and 2.5% CAD groups at 4th weeks and in 2.5 and 5% CAD groups at 8th weeks while GSH concentration significantly (p<0.05) increase at 12th weeks in 2.5 and 10% CAD groups. However, CAT concentration significantly (p<0.05) increase in 2.5, and 5%, CAD groups, 1, 5, and 10% CAD groups and in 5, and 10% CAD groups at 4th, 8th and 12th weeks. AChE significantly (p<0.05) reduce at 4th and 12th weeks. Histological assessment reveals no neuronal and pyramidal degeneration (chromatolysis) at the hippocampal Cornu Ammonis 3 (CA3) region.

CONCLUSIONS

The results suggest that CAD boost memory performance in rats through positive modulation of oxidative stress, cholinergic system and degeneration of hippocampal neurons.

Cnidoscolus aconitifolius-supplemented diet enhanced neurocognition, endogenous antioxidants and cholinergic system and maintains hippocampal neuronal integrity in male Wistar rats

OBJECTIVES

Cnidoscolus aconitifolius have been investigated to have abundant phytochemicals. However, study on the effect of Cnidoscolus aconitifolius on neurobehavioral performance when supplemented with diet is lacking. The study is aimed at investigating the memory-enhancing effect of Cnidoscolus aconitifolius-supplemented diet (CAD) using Morris water maze and Novel object recognition test.

METHODS

Ninety male Wistar rats (80-100 g) were fed with CAD (1, 2.5, 5 and 10%) continuously for a period of 4, 8 and 12 weeks respectively. Six animals per group were used for assessment of memory performance (Morris water maze [MWM] and Novel object recognition test [NORT]); afterwards the brain tissues were harvested for malondialdehyde (MDA), glutathione (GSH) and catalase (CAT) estimation. Acetylcholinesterase (AChE) concentration was also determined. Hippocampal architectural change in the neuron was examined using hematoxylin and eosin (H&E) and cresyl fast violet (Nissl) stain.

RESULTS

Higher percentage of CAD significantly (p<0.05) improve memory performance with time-dependent effects in rats fed with CAD on MMW and NORT. MDA significantly (p<0.05) reduce in 1 and 2.5% CAD groups at 4th weeks and in 2.5 and 5% CAD groups at 8th weeks while GSH concentration significantly (p<0.05) increase at 12th weeks in 2.5 and 10% CAD groups. However, CAT concentration significantly (p<0.05) increase in 2.5, and 5%, CAD groups, 1, 5, and 10% CAD groups and in 5, and 10% CAD groups at 4th, 8th and 12th weeks. AChE significantly (p<0.05) reduce at 4th and 12th weeks. Histological assessment reveals no neuronal and pyramidal degeneration (chromatolysis) at the hippocampal Cornu Ammonis 3 (CA3) region.

CONCLUSIONS

The results suggest that CAD boost memory performance in rats through positive modulation of oxidative stress, cholinergic system and degeneration of hippocampal neurons.

Glucagon-like peptide-1 attenuated carboxymethyl lysine induced neuronal apoptosis via peroxisome proliferation activated receptor-γ

Backgrounds and aims: The role of peroxisome proliferator activated receptor-γ (PPAR-γ) in neuronal apoptosis remains unclear. We aim to investigate the role of PPAR-γ in glucagon-like peptide-1 (GLP-1) alleviated neuronal apoptosis induced by carboxymethyl-lysine (CML).

Materials and Methods: In vitro, PC12 cells were treated by CML/GLP-1. Moreover. the function of PPAR-γ was blocked by GW9662. In vivo, streptozotocin (STZ) was used to induce diabetic rats with neuronal apoptosis. The cognitive function of rats was observed by Morris water maze. Apoptosis was detected by TUNEL assay. Bcl2, Bax, PPAR-γ and receptor of GLP-1 (GLP-1R) were measured by western blotting or immunofluorescence.

Results: In vitro experiment, CML triggered apoptosis, down-regulated GLP-1R and PPAR-γ. Moreover, GLP-1 not only alleviated the apoptosis, but also increased levels of PPAR-γ. GW9662 abolished the neuroprotective effect of GLP-1 on PC12 cells from apoptosis. Furthermore, GLP-1R promoter sequences were detected in the PPAR-γ antibody pulled mixture. GPL-1 levels decreased, while CML levels increased in diabetic rats, compared with control rats. Additionally, we observed elevated bax, decreased bcl2, GLP-1R and PPAR-γ in diabetic rats.

Conclusions: GLP-1 could attenuate neuronal apoptosis induced by CML. Additionally, PPAR-γ involves in this process.

Characteristics of Regional Cerebral Blood Flow in Alzheimer Disease and Amnestic Mild Cognitive Impairment by Single-Photon Emission Computerized Tomography: A Cross-Sectional Study

Introduction

The regional cerebral blood flow (rCBF) distribution can affect brain functioning, leading to amnestic mild cognitive impairment (aMCI) and mild Alzheimer disease (AD). This study aimed to clarify the detailed characteristics of rCBF distribution in patients with mild AD and aMCI.

Methods

This cross-sectional study from April 2015 to March 2018 included 103 older adults (mean age 78.9 years; 60% females), out of a total of 302 adults, and categorized them into 3 groups according to cognitive symptoms. The normal control (NC), aMCI, and mild AD groups included 20, 50, and 33 participants, respectively. The primary outcome was rCBF, which was compared among the 3 groups using a 2-sample t test without correction for multiple comparisons.

Results

In the aMCI group, the rCBF decreased in the bilateral parietal and left frontal association cortex and the bilateral premotor cortex (p < 0.01) but increased in the bilateral cerebellum (p < 0.01). In the mild AD group, the rCBF decreased in the bilateral parietal and occipital association cortex, the bilateral premotor cortex, the left temporal and frontal association cortex, and the left limbic lobe (p < 0.01). Conversely, the rCBF increased in some parts of the cerebellum, the bilateral frontal and temporal association cortex, the left occipital association cortex, and the right premotor cortex (p < 0.01).

Conclusion

Based on the analysis of the values obtained, it was inferred that the rCBF undergoes reduction and elevation in aMCI and AD patients.

Physical activity is associated with lower cerebral beta-amyloid and cognitive function benefits from lifetime experience-a study in exceptional aging

BACKGROUND

Exceptional agers (85+ years) are characterized by preserved cognition presumably due to high cognitive reserve. In the current study, we examined whether personality, risk and protective factors for dementia as well as quality of life are associated with core features of Alzheimer's disease (amyloid-deposition and hippocampal volume) as well as cognition in exceptional aging.

METHODS

We studied 49 exceptional agers (average 87.8 years, range 84-94 years), with preserved activities of daily living and absence of dementia. All participants received a detailed clinical and neuropsychological examination. We used established questionnaires to measure lifetime experience, personality, recent physical and cognitive activity as well as quality of life. Cerebral amyloid-deposition was estimated by 18-[F]-Flutemetamol-PET and manual hippocampal volumetry was performed on 3D T1 MRI images.

RESULTS

In this sample of exceptional agers with preserved activities of daily living, we found intact cognitive performance in the subjects with the highest amyloid-load in the brain, but a lower quality of life with respect to autonomy as well as higher neuroticism. Higher self-reported physical activity in the last twelve months went with a lower amyloid load. Higher self-reported leisure-time/ not work-related activity went with better executive functioning at older age.

CONCLUSION

Even in exceptional aging, high amyloid load may subtly influence personality and quality of life. Our findings support a close relationship between high physical activity and low amyloid-deposition and underscore the importance of extracurricular activities for executive functions. As executive functions are known to be a central resource for everyday functioning in fostering extracurricular activities may be effective in delaying the onset of dementia.

The application of multifunctional nanomaterials in Alzheimer's disease: A potential theranostics strategy

By virtue of their small size, nanomaterials can cross the blood-brain barrier and, when modified to target specific cells or regions, can achieve high bioavailability at the intended site of action. Modified nanomaterials are therefore promising agents for the diagnosis and treatment of neurodegenerative diseases such as Alzheimer's disease (AD). Here we review the roles and mechanisms of action of nanomaterials in AD. First, we discuss the general characteristics of nanomaterials and their application to nanomedicine. Then, we summarize recent studies on the diagnosis and treatment of AD using modified nanomaterials. These studies indicate that using nanomaterials is a potential strategy for AD treatment by slowing the progression of AD through enhanced therapeutic effects.

Expert Opinions and Recommendations for the Clinical Use of Quantitative Analysis Software for MRI-Based Brain Volumetry

치매를 비롯한 퇴행성 신경 질환의 초기 진단에 자기공명영상을 이용한 뇌 위축 평가와 정량적 용적 분석이 중요하다. 뇌 위축의 시각적 평가는 주관적으로 평가자에 따라 다른 결과를 보여주기 때문에, 객관적인 결과를 제공하면서 임상 적용도 가능한 소프트웨어의 수요와 개발이 늘어나고 있다. 이러한 임상용 소프트웨어의 실제 임상 적용은 영상 검사의 표준화가 선행되어야 하고, 개발된 소프트웨어의 검증이 반드시 필요하다. 따라서 대한신경두경부영상의학회는 뇌용적 분석 임상용 소프트웨어의 임상적 활용에 대한 의견을 제시하기 위해 전문위원회를 구성하고 현재까지 발표된 연구를 정리하였다. 그리고, 정량화 분석을 위한 영상 검사의 표준화 및 소프트웨어의 임상 적용에 대한 전문가 의견을 제시하기 위하여 공동 작업을 수행하였다. 본 종설에서는 뇌 자기공명영상의 정량화 분석의 필요성 및 배경, 정량화 분석을 위한 임상용 소프트웨어의 소개 및 기존의 표준품(reference standard)과의 진단능 비교, 영상 획득의 표준화, 분석 및 평가의 표준화, 소프트웨어의 임상 적용에 대한 전문가 의견, 제한점 및 대처 방법 등 대한신경두경부영상의학회의 전문가 권고안을 소개하는 것이 목적이다.

Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation

Multimodal fusion in neuroimaging combines data from multiple imaging modalities to overcome the fundamental limitations of individual modalities. Neuroimaging fusion can achieve higher temporal and spatial resolution, enhance contrast, correct imaging distortions, and bridge physiological and cognitive information. In this study, we analyzed over 450 references from PubMed, Google Scholar, IEEE, ScienceDirect, Web of Science, and various sources published from 1978 to 2020. We provide a review that encompasses (1) an overview of current challenges in multimodal fusion (2) the current medical applications of fusion for specific neurological diseases, (3) strengths and limitations of available imaging modalities, (4) fundamental fusion rules, (5) fusion quality assessment methods, and (6) the applications of fusion for atlas-based segmentation and quantification. Overall, multimodal fusion shows significant benefits in clinical diagnosis and neuroscience research. Widespread education and further research amongst engineers, researchers and clinicians will benefit the field of multimodal neuroimaging.

Predicting Alzheimer's conversion in mild cognitive impairment patients using longitudinal neuroimaging and clinical markers

Patients with mild cognitive impairment (MCI) have a high risk for conversion to Alzheimer's disease (AD). Early diagnose of AD in MCI subjects could help to slow or halt the disease progression. Selecting a set of relevant markers from multimodal data to predict conversion from MCI to probable AD has become a challenging task. The aim of this paper is to quantify the impact of longitudinal predictive models with single- or multisource data for predicting MCI-to-AD conversion and identifying a very small subset of features that are highly predictive of conversion. We developed predictive models of MCI-to-AD progression that combine magnetic resonance imaging (MRI)-based markers (cortical thickness and volume of subcortical structures) with neuropsychological tests. These models were built with longitudinal data and validated using baseline values. By using a linear mixed effects approach, we modeled the longitudinal trajectories of the markers. A set of longitudinal features potentially discriminating between MCI subjects who convert to dementia and those who remain stable over a period of 3 years was obtained. Classifier were trained using the marginal longitudinal trajectory residues from the selected features. Our best models predicted conversion with 77% accuracy at baseline (AUC = 0.855, 84% sensitivity, 70% specificity). As more visits were available, longitudinal predictive models improved their predictions with 84% accuracy (AUC = 0.912, 83% sensitivity, 84% specificity). The proposed approach was developed, trained and evaluated using the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset with a total of 2491 visits from 610 subjects.

Clinically Available Software for Automatic Brain Volumetry: Comparisons of Volume Measurements and Validation of Intermethod Reliability

OBJECTIVE

To compare two clinically available MR volumetry software, NeuroQuant® (NQ) and Inbrain® (IB), and examine the inter-method reliabilities and differences between them.

MATERIALS AND METHODS

This study included 172 subjects (age range, 55-88 years; mean age, 71.2 years), comprising 45 normal healthy subjects, 85 patients with mild cognitive impairment, and 42 patients with Alzheimer's disease. Magnetic resonance imaging scans were analyzed with IB and NQ. Mean differences were compared with the paired t test. Inter-method reliability was evaluated with Pearson's correlation coefficients and intraclass correlation coefficients (ICCs). Effect sizes were also obtained to document the standardized mean differences.

RESULTS

The paired t test showed significant volume differences in most regions except for the amygdala between the two methods. Nevertheless, inter-method measurements between IB and NQ showed good to excellent reliability (0.72 < r < 0.96, 0.83 < ICC < 0.98) except for the pallidum, which showed poor reliability (left: r = 0.03, ICC = 0.06; right: r = -0.05, ICC = -0.09). For the measurements of effect size, volume differences were large in most regions (0.05 < r < 6.15). The effect size was the largest in the pallidum and smallest in the cerebellum.

CONCLUSION

Comparisons between IB and NQ showed significantly different volume measurements with large effect sizes. However, they showed good to excellent inter-method reliability in volumetric measurements for all brain regions, with the exception of the pallidum. Clinicians using these commercial software should take into consideration that different volume measurements could be obtained depending on the software used.

RE-PERG in early-onset Alzheimer's disease: A double-blind, electrophysiological pilot study

PURPOSE

To evaluate the ability of re-test pattern electroretinogram (RE-PERG), a non-invasive and fast steady-state PERG, to detect inner retinal bioelectric function anomalies in patients with early-onset Alzheimer's disease (AD).

METHODS

The study population consisted of 17 patients with AD-related mild cognitive impairment (MCI), 16 patients with vascular dementia (VD)-related MCI, both assessed using the neuropsychological Mini-Mental State Examination (MMSE) and by structural magnetic resonance imaging, and 19 healthy, age-matched normal controls (NC). All participants were visually asymptomatic, had normal or near-normal general cognitive functioning and no or minimal impairments in daily life activities. Visual field (VF) test, optical coherence tomography (OCT) and RE-PERG, sampled in five consecutive blocks of 130 events, were performed.

RESULTS

There was no statistically significant difference among the three groups with respect to age, VF parameters (mean and pattern standard deviations) and OCT parameters (ganglion cell complex thickness and retinal nerve fiber layer thickness). The mean amplitude in the RE-PERG was significantly lower, but only weakly in the AD group than in NC (p = 0.1) whereas the intrinsic variability of the 2nd harmonic phase was significantly higher in the AD group than in either the VD or NC group (p<0.001).

CONCLUSIONS

RE-PERG is altered in early-stage AD, showing a reduced amplitude with high intrinsic phase variability. It also allows the discrimination of AD from VD. A high intrinsic variability in the PERG signal, determined using RE-PERG, may thus be a new promising test for neurodegenerative diseases.

Longitudinal survival analysis and two-group comparison for predicting the progression of mild cognitive impairment to Alzheimer's disease

BACKGROUND

Longitudinal studies using structural magnetic resonance imaging (MRI) and neuropsychological measurements (NMs) allow a noninvasive means of following the subtle anatomical changes occurring during the evolution of AD.

NEW METHOD

This paper compared two approaches for the construction of longitudinal predictive models: a) two-group comparison between converter and nonconverter MCI subjects and b) longitudinal survival analysis. Predictive models combined MRI-based markers with NMs and included demographic and clinical information as covariates. Both approaches employed linear mixed effects modeling to capture the longitudinal trajectories of the markers. The two-group comparison approaches used linear discriminant analysis and the survival analysis used risk ratios obtained from the extended Cox model and logistic regression.

RESULTS

The proposed approaches were developed and evaluated using the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset with a total of 1330 visits from 321 subjects. With both approaches, a very small number of features were selected. These markers are easily interpretable, generating robust, verifiable and reliable predictive models. Our best models predicted conversion with 78% accuracy at baseline (AUC = 0.860, 79% sensitivity, 76% specificity). As more visits were made, longitudinal predictive models improved their predictions with 85% accuracy (AUC = 0.944, 86% sensitivity, 85% specificity).

COMPARISON WITH EXISTING METHOD

Unlike the recently published models, there was also an improvement in the prediction accuracy of the conversion to AD when considering the longitudinal trajectory of the patients.

CONCLUSIONS

The survival-based predictive models showed a better balance between sensitivity and specificity with respect to the models based on the two-group comparison approach.

Ultrasonic Assessment of the Medial Temporal Lobe Tissue Displacements in Alzheimer’s Disease

We aim to estimate brain tissue displacements in the medial temporal lobe (MTL) using backscattered ultrasound radiofrequency (US RF) signals, and to assess the diagnostic ability of brain tissue displacement parameters for the differentiation of patients with Alzheimer’s disease (AD) from healthy controls (HC). Standard neuropsychological evaluation and transcranial sonography (TCS) for endogenous brain tissue motion data collection are performed for 20 patients with AD and for 20 age- and sex-matched HC in a prospective manner. Essential modifications of our previous method in US waveform parametrization, raising the confidence of micrometer-range displacement signals in the presence of noise, are done. Four logistic regression models are constructed, and receiver operating characteristic (ROC) curve analyses are applied. All models have cut-offs from 61.0 to 68.5% and separate AD patients from HC with a sensitivity of 89.5% and a specificity of 100%. The area under a ROC curve of predicted probability in all models is excellent (from 95.2 to 95.7%). According to our models, AD patients can be differentiated from HC by a sharper morphology of some individual MTL spatial point displacements (i.e., by spreading the spectrum of displacements to the high-end frequencies with higher variability across spatial points within a region), by lower displacement amplitude differences between adjacent spatial points (i.e., lower strain), and by a higher interaction of these attributes.

Comparative Utility of Manual versus Automated Segmentation of Hippocampus and Entorhinal Cortex Volumes in a Memory Clinic Sample

Structural neuroimaging is a useful non-invasive biomarker commonly employed to evaluate the integrity of mesial temporal lobe structures that are typically compromised in Alzheimer's disease. Advances in quantitative neuroimaging have permitted the development of automated segmentation protocols (e.g., FreeSurfer) with significantly increased efficiency compared to earlier manual techniques. While these protocols have been found to be suitable for large-scale, multi-site research studies, we were interested in assessing the practical utility and reliability of automated FreeSurfer protocols compared to manual volumetry on routinely acquired clinical scans. Independent validation studies with newer automated segmentation protocols are scarce. Two FreeSurfer protocols for each of two regions of interest-the hippocampus and entorhinal cortex-were compared against manual volumetry. High reliability and agreement was found between FreeSurfer and manual hippocampal protocols, however, there was lower reliability and agreement between FreeSurfer and manual entorhinal protocols. Although based on a the relatively small sample of subjects drawn from a memory clinic (n = 27), our study findings suggest further refinements to improve measurement error and most accurately depict true regional brain volumes using automated segmentation protocols are required, especially for non-hippocampal mesial temporal structures, to achieve maximal utility for routine clinical evaluations.

ACR Appropriateness Criteria® Dementia

Degenerative disease of the central nervous system is a growing public health concern. The primary role of neuroimaging in the workup of patients with probable or possible Alzheimer disease has typically been to exclude other significant intracranial abnormalities. In general, the imaging findings in structural studies, such as MRI, are nonspecific and have limited potential in differentiating different types of dementia. Advanced imaging methods are not routinely used in community or general practices for the diagnosis or differentiation of forms of dementia. Nonetheless, in patients who have been evaluated by a dementia expert, FDG-PET helps to distinguish Alzheimer disease from frontotemporal dementia. In patients with suspected dementia with Lewy bodies, functional imaging of the dopamine transporter (ioflupane) using SPECT may be helpful. In patients with suspected normal-pressure hydrocephalus, DTPA cisternography and HMPAO SPECT/CT brain may provide assessment. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Ligustilide improves aging-induced memory deficit by regulating mitochondrial related inflammation in SAMP8 mice

Alzheimer’s disease (AD) is an age-related neurodegenerative disease. The main active component in Angelica sinensis, ligustilide, has been reported to have the protective effect on AD. Whether ligustilide could protect against age-induced dementia is still unknown. In this study, we used an aging model, SAMP8 mice to investigate the neuroprotective effect of ligustilide. The behavioral tests (Morris water maze, object recognition task, open field test and elevated plus maze) results showed that ligustilide could improve the memory deficit in SAMP8 mice. For mechanism study, we found that the protein level of P-Drp1 (fission) was decreased and the levels of Mfn1 and Mfn2 (fusion) were increased after ligustilide treatment in animals and cells. Ligustilide increased P-AMPK and ATP levels. Malondialdehyde and superoxide dismutase activity results indicated that ligustilide exerts antioxidant effects by reducing the level of oxidative stress markers. In addition, ligustilide improved neural function and alieved apoptosis and neuroinflammation. These findings have shown that ligustilide treatment improves mitochondrial function in SAMP8 mice, and improves memory loss.

Prediction of Amyloid Positivity in Mild Cognitive Impairment Using Fully Automated Brain Segmentation Software

OBJECTIVE

To assess the predictive ability of regional volume information provided by fully automated brain segmentation software for cerebral amyloid positivity in mild cognitive impairment (MCI).

METHODS

This study included 130 subjects with amnestic MCI who participated in the Korean brain aging study of early diagnosis and prediction of Alzheimer's disease, an ongoing prospective cohort. All participants underwent comprehensive clinical assessment as well as ¹¹C-labeled Pittsburgh compound PET/MRI scans. The predictive ability of volumetric results provided by automated brain segmentation software was evaluated using binary logistic regression and receiver operating characteristic curve analysis.

RESULTS

Subjects were divided into two groups: one with Aβ deposition (58 subjects) and one without Aβ deposition (72 subjects). Among the varied volumetric information provided, the hippocampal volume percentage of intracranial volume (%HC/ICV), normative percentiles of hippocampal volume (HC_norm), and gray matter volume were associated with amyloid-β (Aβ) positivity (all P < 0.01). Multivariate analyses revealed that both %HC/ICV and HC_norm were independent significant predictors of Aβ positivity (all P < 0.001). In addition, prediction scores derived from %HC/ICV with age and HC_norm showed moderate accuracy in predicting Aβ positivity in MCI subjects (the areas under the curve: 0.739 and 0.723, respectively).

CONCLUSION

Relative hippocampal volume measures provided by automated brain segmentation software can be useful for screening cerebral Aβ positivity in clinical practice for patients with amnestic MCI. The information may also help clinicians interpret structural MRI to predict outcomes and determine early intervention for delaying the progression to Alzheimer's disease dementia.

Elevation of plasma soluble amyloid precursor protein beta in Alzheimer's disease

INTRODUCTION

Beta-amyloid is considered to be a pathophysiological marker in Alzheimer's disease (AD). Soluble amyloid precursor proteins (sAPPs) -α (sAPPα) and -β (sAPPβ), which are the byproducts of non-amyloidogenic and amyloidogenic process of APP, respectively, have been repeatedly observed in the cerebrospinal fluids (CSF) of AD patients. The present study focused on the determination of sAPP levels in peripheral blood.

METHODS

The plasma protein levels of sAPPα and sAPPβ were measured with ELISA. Plasma from 52 AD patients, 98 amnestic mild cognitive impairment (MCI) patients, and 114 cognitively normal controls were compared.

RESULTS

The plasma level of sAPPβ was significantly increased in AD patients than in cognitively healthy controls. However, no significant change in plasma sAPPα was observed among the three groups. Furthermore, the plasma sAPPβ levels significantly correlated with cognitive assessment scales, such as clinical dementia rating (CDR), and mini-mental status examination (MMSE). Interestingly, sAPPα and sAPPβ had a positive correlation with each other in blood plasma, similar to previous studies on CSF sAPP. This correlation was stronger in the MCI and AD groups than in the cognitively healthy controls.

CONCLUSIONS

These results suggest that individuals with elevated plasma sAPPβ levels are at an increased risk of AD; elevation in these levels may reflect the progression of disease.

Genetic deletion of soluble epoxide hydrolase delays the progression of Alzheimer's disease

Background

Soluble epoxide hydrolase (sEH) is a bifunctional enzyme with COOH-terminal hydrolase and NH2-terminal lipid phosphatase activities. It is expressed in various cell types in the brain and is involved in the pathogenesis of inflammatory and neurodegenerative diseases. Alzheimer’s disease (AD) is a progressive neuroinflammatory and neurodegenerative disease. However, the pathological significance of sEH and underlying molecular mechanism in AD remain unclear.

Methods

To examine the role of sEH in pathogenesis of AD, we used wild-type (WT) mice, soluble epoxide hydrolase deficient (sEH^−/−) and two mouse models of AD, including amyloid precursor protein (APP)/presenilin 1 (PS1) transgenic (APP/PS1 Tg) and APP/PS1 Tg/sEH^−/− mice. Western blotting analysis and immunohistochemistry assay were performed to evaluate the protein expression. Locomotion, nesting building ability, Y-maze, and Morris water maze tests were conducted to study mouse behavior. The levels of interleukin (IL)-1β, IL-4, IL-6, and IL-10 and the activities of NF-κB and nuclear factor of activated T cells (NFAT) were measured by commercial assay kits. The quantitative protein level profiling in the brain lysate was analyzed using LC-MS/MS approaches.

Results

We demonstrated that the level of sEH was increased in the brain and predominantly appeared in hippocampal astrocytes of APP/PS1 Tg mice. Genetic ablation of sEH in APP/PS1 Tg mice delayed the progression of AD as evidenced by the alleviation in behavior outcomes and Aβ plaque deposition. In addition, loss of the function of sEH in APP/PS1 Tg mice increased astrogliosis and the production of astrocyte-derived anti-inflammatory cytokines including IL-1β, IL-4, and IL-10, as well as the activity of NF-kB and NFAT. Moreover, analysis of gene ontology in the AD brain revealed that important signaling pathways and processes related to AD pathogenesis such as translational regulation, oxidative stress, cytoskeleton reorganization, and small GTPase signal transduction were altered in APP/PS1 Tg/sEH^−/− mice compared with APP/PS1 Tg mice.

Conclusion

Our results suggest that sEH is a crucial regulator in the progression of AD and might be a potential therapeutic target for the treatment of AD.

APOE Promoter Polymorphism-219T/G is an Effect Modifier of the Influence of APOE ε4 on Alzheimer's Disease Risk in a Multiracial Sample

Variants in the APOE gene region may explain ethnic differences in the association of Alzheimer’s disease (AD) with ε4. Ethnic differences in allele frequencies for three APOE region SNPs (single nucleotide polymorphisms) were identified and tested for association in 19,398 East Asians (EastA), including Koreans and Japanese, 15,836 European ancestry (EuroA) individuals, and 4985 African Americans, and with brain imaging measures of cortical atrophy in sub-samples of Koreans and EuroAs. Among ε4/ε4 individuals, AD risk increased substantially in a dose-dependent manner with the number of APOE promoter SNP rs405509 T alleles in EastAs (TT: OR (odds ratio) = 27.02, p = 8.80 × 10⁻⁹⁴; GT: OR = 15.87, p = 2.62 × 10⁻⁹) and EuroAs (TT: OR = 18.13, p = 2.69 × 10⁻¹⁰⁸; GT: OR = 12.63, p = 3.44 × 10⁻⁶⁴), and rs405509-T homozygotes had a younger onset and more severe cortical atrophy than those with G-allele. Functional experiments using APOE promoter fragments demonstrated that TT lowered APOE expression in human brain and serum. The modifying effect of rs405509 genotype explained much of the ethnic variability in the AD/ε4 association, and increasing APOE expression might lower AD risk among ε4 homozygotes.

Mitigating Alzheimer’s Disease with Natural Polyphenols: A Review

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According to Alzheimer’s Disease International (ADI), nearly 50 million people worldwide were living with dementia in 2017, and this number is expected to triple by 2050. Despite years of research in this field, the root cause and mechanisms responsible for Alzheimer’s disease (AD) have not been fully elucidated yet. Moreover, promising preclinical results have repeatedly failed to translate into patient treatments. Until now, none of the molecules targeting AD has successfully passed the Phase III trial. Although natural molecules have been extensively studied, they normally require high concentrations to be effective; alternately, they are too large to cross the blood-brain barrier (BBB).

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In this review, we report AD treatment strategies, with a virtually exclusive focus on green chemistry (natural phenolic molecules). These include therapeutic strategies for decreasing amyloid-β (Aβ) production, preventing and/or altering Aβ aggregation, and reducing oligomers cytotoxicity such as curcumin, (-)-epigallocatechin-3-gallate (EGCG), morin, resveratrol, tannic acid, and other natural green molecules. We also examine whether consideration should be given to potential candidates used outside of medicine and nutrition, through a discussion of two intermediate-sized green molecules, with very similar molecular structures and key properties, which exhibit potential in mitigating Alzheimer’s disease.

Observation of Angular Dependence of T1 in the Human White Matter at 3T

BACKGROUND AND OBJECTIVE

Multiple factors including chemical composition and microstructure influence relaxivity of tissue water in vivo. We have quantified T1 in the human white mater (WM) together with diffusion tensor imaging to study a possible relationship between water T1, diffusional fractional anisotropy (FA) and fibre-to-field angle.

METHODS

An inversion recovery (IR) pulse sequence with 6 inversion times for T1 and a multi-band diffusion tensor sequence with 60 diffusion sensitizing gradient directions for FA and the fibre-to-field angle θ (between the principal direction of diffusion and B₀) were used at 3 Tesla in 40 healthy subjects. T1 was assessed using the method previously applied to anisotropy of coherence lifetime to provide a heuristic demonstration as a surface plot of T1 as a function of FA and the angle θ.

RESULTS

Our data show that in the WM voxels with FA > 0.3 T1 becomes longer (i.e. 1/T1 = R1 slower) when fibre-to-field angle is 50-60°, approximating the magic angle of 54.7°. The longer T1 around the magic angle was found in a number of WM tracts independent of anatomy. S0 signal intensity, computed from IR fits, mirrored that of T1 being greater in the WM voxels when the fibre-to-field angle was 50-60°.

CONCLUSIONS

The current data point to fibre-to-field-angle dependent T1 relaxation in WM as an indication of effects of microstructure on the longitudinal relaxation of water.

Cerebral small vessel disease and cognitive impairment

Cerebral small vessel disease (CSVD) is a pathophysiological process involving small arteries such as cerebellar arteries, arterioles, capillaries, and veinlets. Imaging features vary; they are mainly composed of recent subcortical infarcts, lacunes of presumed vascular origin, white matter hyperintensities (WMHs) of presumed vascular origin, cerebral microbleeds, enlarged perivascular spaces, and global and regional brain atrophy. CSVD is a common cause of vascular cognitive dysfunction, and in its end stage, dementia often develops. CSVD has been a major research hotspot; however, its causes are poorly understood. Neuroimaging markers of CSVD can be used as the basis for etiological analysis. This review highlights the relevance of neuroimaging markers and cognitive impairment, providing a new direction for the early recognition, treatment, and prevention of cognitive dysfunction in small cerebral angiopathy.

Magnetic resonance imaging in dementia

OBJECTIVE

To describe and illustrate the key findings on structural magnetic resonance imaging (MRI) in the most common dementias of neurodegenerative origin: Alzheimer's disease, vascular dementia, dementia with Lewy bodies, variants of frontotemporal dementia, progressive supranuclear palsy, variants of multiple system atrophy, Parkinson dementia, and corticobasal degeneration.

CONCLUSION

Today the role of MRI is no longer limited to ruling out underlying causes of cognitive deterioration. MRI can show patterns of atrophy with a predictive value for certain dementias which, although not specific or unique to each disease, can help to confirm diagnostic suspicion or to identify certain processes. For this reason, it is important for radiologists to know the characteristic findings of the most common dementias.

Discrimination and conversion prediction of mild cognitive impairment using convolutional neural networks

Background

Recently, studies have demonstrated that machine learning techniques, particularly cutting-edge deep learning technology, have achieved significant progression on the classification of Alzheimer's disease (AD) and its prodromal phase, mild cognitive impairment (MCI). Moreover, accurate prediction of the progress and the conversion risk from MCI to probable AD has been of great importance in clinical application.

Methods

In this study, the baseline MR images and follow-up information during 3 years of 150 normal controls (NC), 150 patients with stable MCI (sMCI) and 157 converted MCI (cMCI) were collected from the Alzheimer's Disease Neuroimaging Initiative (ADNI). The deep convolutional neural networks (CNNs) were adopted to distinguish different stages of MCI from the NC group, and predict the conversion time from MCI to AD. Two CNN architectures including GoogleNet and CaffeNet were explored and evaluated in multiple classifications and estimations of conversion risk using transfer learning from pre-trained ImageNet (via fine-tuning) and five-fold cross-validation. A novel data augmentation approach using random views aggregation was applied to generate abundant image patches from the original MR scans.

Results

The GoogleNet acquired accuracies with 97.58%, 67.33% and 84.71% in three-way discrimination among the NC, sMCI and cMCI groups respectively, whereas the CaffeNet obtained promising accuracies of 98.71%, 72.04% and 92.35% in the NC, sMCI and cMCI classifications. Furthermore, the accuracy measures of conversion risk of patients with cMCI ranged from 71.25% to 83.25% in different time points using GoogleNet, whereas the CaffeNet achieved remarkable accuracy measures from 95.42% to 97.01% in conversion risk prediction.

Conclusions

The experimental results demonstrated that the proposed methods had prominent capability in classification among the 3 groups such as sMCI, cMCI and NC, and exhibited significant ability in conversion risk prediction of patients with MCI.

Current understanding of magnetic resonance imaging biomarkers and memory in Alzheimer's disease

Alzheimer's disease (AD) is caused by a cascade of changes to brain integrity. Neuroimaging biomarkers are important in diagnosis and monitoring the effects of interventions. As memory impairments are among the first symptoms of AD, the relationship between imaging findings and memory deficits is important in biomarker research. The most established magnetic resonance imaging (MRI) finding is hippocampal atrophy, which is related to memory decline and currently used as a diagnostic criterion for AD. While the medial temporal lobes are impacted early by the spread of neurofibrillary tangles, other networks and regional changes can be found quite early in the progression. Atrophy in several frontal and parietal regions, cortical thinning, and white matter alterations correlate with memory deficits in early AD. Changes in activation and connectivity have been detected by functional MRI (fMRI). Task-based fMRI studies have revealed medial temporal lobe hypoactivation, parietal hyperactivation, and frontal hyperactivation in AD during memory tasks, and activation patterns of these regions are also altered in preclinical and prodromal AD. Resting state fMRI has revealed alterations in default mode network activity related to memory in early AD. These studies are limited in part due to the historic inclusion of patients who had suspected AD but likely did not have the disorder. Modern biomarkers allow for more diagnostic certainty, allowing better understanding of neuroimaging markers in true AD, even in the preclinical stage. Larger patient cohorts, comparison of candidate imaging biomarkers to more established biomarkers, and inclusion of more detailed neuropsychological batteries to assess multiple aspects of memory are needed to better understand the memory deficit in AD and help develop new biomarkers. This article reviews MRI findings related to episodic memory impairments in AD and introduces a new study with multimodal imaging and comprehensive neuropsychiatric evaluation to overcome current limitations.