Hippocampal and amygdalar morphological abnormalities in Alzheimer’s disease based on three Chinese MRI datasets

2021 ◽  
Vol 18 ◽  
Author(s):  
Yuanyuan Wei ◽  
Nianwei Huang ◽  
Yong Liu ◽  
Xi Zhang ◽  
Silun Wang ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Shape Analysis ◽  
Early Stage ◽  
Disease Status ◽  
Brain Structures ◽  
Statistical Shape Analysis ◽  
Social Significance ◽  
Statistical Shape ◽  
Shape Characteristics

Background: Early detection of Alzheimer’s disease (AD) and its early stage, the mild cognitive impairment (MCI), has important scientific, clinical and social significance. Magnetic resonance imaging (MRI) based statistical shape analysis provides an opportunity to detect regional structural abnormalities of brain structures caused by AD and MCI. Objective: In this work, we aimed to employ a well-established statistical shape analysis pipeline, in the framework of large deformation diffeomorphic metric mapping, to identify and quantify the regional shape abnormalities of the bilateral hippocampus and amygdala at different prodromal stages of AD, using three Chinese MRI datasets collected from different domestic hospitals. Methods: We analyzed the region-specific shape abnormalities at different stages of the neuropathology of AD by comparing the localized shape characteristics of the bilateral hippocampi and amygdalas between healthy controls and two disease groups (MCI and AD). In addition to group comparison analyses, we also investigated the association between the shape characteristics and the Mini Mental State Examination (MMSE) of each structure of interest in the disease group (MCI and AD combined) as well as the discriminative power of different morphometric biomarkers. Results: We found the strongest disease pathology (regional atrophy) at the subiculum and CA1 subregions of the hippocampus and the basolateral, basomedial as well as centromedial subregions of the amygdala. Furthermore, the shape characteristics of the hippocampal and amygdalar subregions exhibiting the strongest AD related atrophy were found to have the most significant positive associations with the MMSE. Employing the shape deformation marker of the hippocampus or the amygdala for automated MCI or AD detection yielded a significant accuracy boost over the corresponding volume measurement. Conclusion: Our results suggested that the amygdalar and hippocampal morphometrics, especially those of shape morphometrics, can be used as auxiliary indicators for monitoring the disease status of an AD patient.

Deformation-based Statistical Shape Analysis of the Corpus Callosum in Mild Cognitive Impairment and Alzheimer’s Disease

2018 ◽  
Vol 15 (12) ◽  
pp. 1151-1160 ◽  
Author(s):  
Zihan Jiang ◽  
Huilin Yang ◽  
Xiaoying Tang
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Corpus Callosum ◽  
Shape Analysis ◽  
Disease Assessment ◽  
Statistical Shape Analysis ◽  
Superior Part ◽  
Statistical Shape

Objective: In this study, we investigated the influence that the pathology of Alzheimer’s disease (AD) exerts upon the corpus callosum (CC) using a total of 325 mild cognitive impairment (MCI) subjects, 155 AD subjects, and 185 healthy control (HC) subjects. Method: Regionally-specific morphological CC abnormalities, as induced by AD, were quantified using a large deformation diffeomorphic metric curve mapping based statistical shape analysis pipeline. We also quantified the association between the CC shape phenotype and two cognitive measures; the Mini Mental State Examination (MMSE) and the Alzheimer’s Disease Assessment Scale-Cognitive Behavior Section (ADAS-cog). To identify AD-relevant areas, CC was sub-divided into three subregions; the genu, body, and splenium (gCC, bCC, and sCC). Results: We observed significant shape compressions in AD relative to that in HC, mainly concentrated on the superior part of CC, across all three sub-regions. The HC-vs-MCI shape abnormalities were also concentrated on the superior part, but mainly occurred on bCC and sCC. The significant MCI-vs-AD shape differences, however, were only detected in part of sCC. In the shape-cognition association, significant negative correlations to ADAS-cog were detected for shape deformations at regions belonging to gCC and sCC and significant positive correlations to MMSE at regions mainly belonging to sCC. Conclusion: Our results suggest that the callosal shape deformation patterns, especially those of sCC, linked tightly to the cognitive decline in AD, and are potentially a powerful biomarker for monitoring the progression of AD.

scholarly journals A Review of Oxidative Stress Products and Related Genes in Early Alzheimer’s Disease

2021 ◽  
pp. 1-25
Author(s):  
Federica Cioffi ◽  
Rayan Hassan Ibrahim Adam ◽  
Ruchi Bansal ◽  
Kerensa Broersen
Keyword(s):  
Oxidative Stress ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Molecular Mechanisms ◽  
Early Stage ◽  
Disease Status ◽  
Diagnostic Value ◽  
Oxidation Products ◽  
Protein Levels ◽  
Stress Levels

Oxidative stress is associated with the progression of Alzheimer’s disease (AD). Reactive oxygen species can modify lipids, DNA, RNA, and proteins in the brain. The products of their peroxidation and oxidation are readily detectable at incipient stages of disease. Based on these oxidation products, various biomarker-based strategies have been developed to identify oxidative stress levels in AD. Known oxidative stress-related biomarkers include lipid peroxidation products F2-isoprostanes, as well as malondialdehyde and 4-hydroxynonenal which both conjugate to specific amino acids to modify proteins, and DNA or RNA oxidation products 8-hydroxy-2’-deoxyguanosine (8-OHdG) and 8-hydroxyguanosine (8-OHG), respectively. The inducible enzyme heme oxygenase type 1 (HO-1) is found to be upregulated in response to oxidative stress-related events in the AD brain. While these global biomarkers for oxidative stress are associated with early-stage AD, they generally poorly differentiate from other neurodegenerative disorders that also coincide with oxidative stress. Redox proteomics approaches provided specificity of oxidative stress-associated biomarkers to AD pathology by the identification of oxidatively damaged pathology-specific proteins. In this review, we discuss the potential combined diagnostic value of these reported biomarkers in the context of AD and discuss eight oxidative stress-related mRNA biomarkers in AD that we newly identified using a transcriptomics approach. We review these genes in the context of their reported involvement in oxidative stress regulation and specificity for AD. Further research is warranted to establish the protein levels and their functionalities as well as the molecular mechanisms by which these potential biomarkers are involved in regulation of oxidative stress levels and their potential for determination of oxidative stress and disease status of AD patients.

scholarly journals Framework for the Statistical Shape Analysis of Brain Structures using SPHARM-PDM

2006 ◽  
Author(s):  
Martin Styner ◽  
Ipek Oguz ◽  
Shun Xu ◽  
Christian Brechbuehler ◽  
Dimitrios Pantazis ◽  
...  
Keyword(s):  
Shape Analysis ◽  
Morphological Changes ◽  
Multiple Comparisons ◽  
Brain Structures ◽  
Statistical Shape Analysis ◽  
Brain Morphometry ◽  
Triangulated Surfaces ◽  
Statistical Shape ◽  
Spherical Topology ◽  
Binary Segmentation

Shape analysis has become of increasing interest to the neuroimaging community due to its potential to precisely locate morphological changes between healthy and pathological structures. This manuscript presents a comprehensive set of tools for the computation of 3D structural statistical shape analysis. It has been applied in several studies on brain morphometry, but can potentially be employed in other 3D shape problems. Its main limitations is the necessity of spherical topology.The input of the proposed shape analysis is a set of binary segmentation of a single brain structure, such as the hippocampus or caudate. These segmentations are converted into a corresponding spherical harmonic description (SPHARM), which is then sampled into a triangulated surfaces (SPHARM-PDM). After alignment, differences between groups of surfaces are computed using the Hotelling T^2 T2 two sample metric. Statistical p-values, both raw and corrected for multiple comparisons, result in significance maps. Additional visualization of the group tests are provided via mean difference magnitude and vector maps, as well as maps of the group covariance information.The correction for multiple comparisons is performed via two separate methods that each have a distinct view of the problem. The first one aims to control the family-wise error rate (FWER) or false-positives via the extrema histogram of non-parametric permutations. The second method controls the false discovery rate and results in a less conservative estimate of the false-negatives. New NITRC page for binary distribution

scholarly journals Cats and Apples: Semantic Fluency Performance for Living Things Identifies Patients with Very Early Alzheimer’s Disease

2020 ◽  
Author(s):  
Sabine Krumm ◽  
Manfred Berres ◽  
Sasa L Kivisaari ◽  
Andreas U Monsch ◽  
Julia Reinhardt ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Stage ◽  
Memory Performance ◽  
Area Under The Curve ◽  
Disease Status ◽  
Semantic Fluency ◽  
Operating Characteristics ◽  
Living Things ◽  
Early Alzheimer’S Disease

Abstract Objective: Reduced semantic memory performance is a known neuropsychological marker of very early Alzheimer’s disease (AD), but the task format that best predicts disease status is an open question. The present study aimed to identify the semantic fluency task and measure that best discriminates early-stage AD patients (PATs) from cognitively healthy controls. Method: Semantic fluency performance for animals, fruits, tools, and vehicles was assessed in 70 early-stage AD PATs and 67 cognitively healthy participants. Logistic regressions and receiver operating characteristics were calculated for five total score semantic fluency measures. Results: Compared with all other measures, living things (i.e., total correct animals + total correct fruits) achieved highest z-statistics, highest area under the curve and smallest difference between the upper and lower 95% confidence intervals. Conclusion: Living things total correct is a powerful tool to detect the earliest signs of incipient AD.

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