Alzheimer's disease diagnosis on structural MR images using circular harmonic functions descriptors on hippocampus and posterior cingulate cortex

Ahmed, Olfa Ben; Mizotin, Maxim M.; Benois-Pineau, Jenny; Allard, Michèle; Catheline, Gwénaëlle; Amar, Chokri Ben

doi:10.1016/j.compmedimag.2015.04.007

Cited by 92 publications

(59 citation statements)

References 58 publications

(92 reference statements)

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“…The dominant role of the histopathological changes of hippocampus in AD has been widely acknowledged [40] and there has been studies suggesting the diagnostic significance of MR-based hippocampal volumetry [41, 42]. According to our results, A allele of rs3781836 showed protective inclination on hippocampus at baseline and A allele of rs11218350 and rs3824968 showed protective trend on hippocampus in two-year follow-up study.…”

Section: Discussionsupporting

confidence: 61%

Impact of SORL1 genetic variations on MRI markers in non-demented elders

Yin

Tan

et al. 2016

Oncotarget

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The sorting protein-related receptor 1 (SORL1 or LR11) gene has been verified to play an important role in the pathologic process of β-amyloid (Aβ) formation and trafficking in Alzheimer's Disease (AD) by plenty of cytological and molecular biological studies. But there were few studies investigated the association of SORL1 gene and neurodegeneration features from a rather macroscopic perspective. In the present study, we explored the effect of SORL1 genotypes on AD-related brain atrophy. We recruited 812 individuals with both baseline and two-year follow-up information from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database and applied multiple linear regression models to examine the association between eight single nucleotide polymorphisms (SNPs) and neuroimaging phenotypes. Finally, four SNPs (rs11219350, rs2298813, rs3781836, rs3824968) showed trend of association with the volume of hippocampus and parahippocampal gyrus but failed to survive the false discovery rate (FDR) correction. Only rs1784933 and rs753780 showed significant association with right parahippocampal gyrus. According to our findings, SORL1 variations influence the atrophy of specific AD-related brain structures, which suggested the potential role of SORL1 in the neurodegeneration of cognitive related regions.

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Section: Discussionsupporting

confidence: 61%

Impact of SORL1 genetic variations on MRI markers in non-demented elders

Yin

Tan

et al. 2016

Oncotarget

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“…rs-fcMRI is one of the most popular functional neuroimaging techniques and is used to infer functional connectivity between different regions of the brain (Zhang & Raichle, 2010). As one of the most important seeds, the posterior cingulate cortex (PCC) has been studied as it applies to different clinical diseases, including Alzheimer's disease and depression (Ben Ahmed et al, 2015). rs-fcMRI is useful for exploring network interruptions in different clinical disorders including Alzheimer's disease (Greicius, Srivastava, Reiss, & Menon, 2004), attention-deficit disorder (Tian et al, 2006) and depression (Sheline et al, 2009).…”

mentioning

confidence: 99%

“…In particular, the seed-based approach has been more widely used. As one of the most important seeds, the posterior cingulate cortex (PCC) has been studied as it applies to different clinical diseases, including Alzheimer's disease and depression (Ben Ahmed et al, 2015). Previous studies using rs-fcMRI have indicated aberrant activity in fronto-subcortical and limbic networks (Koolschijn, Van Haren, Lensvelt-Mulders, Hulshoff Pol, & Kahn, 2009;Sexton, Mackay, & Ebmeier, 2009) that contain parts of the cognitive control regions such as the dorsolateral prefrontal cortex (dlPFC) and PCC.…”

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confidence: 99%

Impairment of the executive function in breast cancer patients receiving chemotherapy treatment: a functional MRI study

et al. 2016

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The aim of this study is to investigate chemotherapy-induced alterations in the functional framework of the brain, and probe the relationship between these changes and executive function impairments in breast cancer patients. Thirty-three breast cancer patients (BC) after receiving chemotherapy and 31 matched healthy controls (HC) were enrolled in this study. All participants received resting-state functional connectivity magnetic resonance imaging (rs-fcMRI) and neuropsychological background tests. The lower functional connectivity of the posterior cingulate cortex (PCC) was found in the left postcentral gyrus, left precentral gyrus, right superior temporal gyrus, right cingulate gyrus and right middle frontal gyrus. A significant negative correlation was found between the response time on the Trail Making Tests and the functional connectivity strength between the PCC and right middle frontal and right cingulate gyri in breast cancer patients. In addition, the strength of the functional connectivity between the PCC and right middle frontal gyrus had a negative correlation with the response times on the Stroop Interference Test in breast cancer patients. This study demonstrated that BC patients after receiving chemotherapy have abnormal functional connectivity. These findings suggest that functional connectivity changes might play an important role in chemotherapy-induced executive function impairments in breast cancer patients.

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“…In this paper, the proposed methodology experimented using MATLAB (version 2016) with 3.0 GHz Intel i5 processor. For determining the efficiency of proposed methodology, the performance of proposed methodology was compared with the existing methodologies (Partial Least Squares (PLS) + Principal Component Analysis (PCA) + SVM [16], Circular Harmonic Functions (CHFs) descriptors + Posterior Cingulate Cortex (PCC) [17], and fusion of volume [18]) on a reputed dataset ADNI. The performance of the proposed methodology is determined in terms of accuracy, specificity, sensitivity, and f-score.…”

Section: Resultsmentioning

confidence: 99%

“…Compared to this existing work, the proposed work achieved maximum sensitivity of 100%, specificity of 90% and accuracy of 90% that was slightly higher than the existing work. [17] utilized pattern recognition and visual indexing framework for classifying three Alzheimer classes of subjects: normal, Alzheimer disease and MCI. In this research paper, CHFs was used for extracting the local features from PCC and hippocampus in every slice in all three-brain projection.…”

Section: Comparative Analysismentioning

confidence: 99%

Relieff Feature Selection Based Alzheimer Disease Classification Using Hybrid Features and Support Vector Machine in Magnetic Resonance Imaging

Suresha¹,

Parthasarathi²

2019

IJCET

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Alzheimer disease is a form of dementia that results in memory-related problems in human beings. An accurate detection and classification of Alzheimer disease and its stages plays a crucial role in human health monitoring system. In this research paper, Alzheimer disease classification was assessed by Alzheimer's disease Neuro-Imaging Initiative (ADNI) dataset. After performing histogram equalization and skull removal of the collected brain images, segmentation was carried-out using Fuzzy C-Means (FCM) for segmenting the white matter, Cerebro-Spinal Fluid (CSF), and grey matter from the pre-processed brain images. Then, hybrid feature extraction (Histogram of Oriented Gradients (HOG), Local Binary Patterns (LBP), and Gray-Level Co-Occurrence Matrix (GLCM)) was performed for extracting the feature values from the segmented brain images. After hybrid feature extraction, reliefF feature selection was used for selecting the optimal feature subsets or to reject the irrelevant feature vectors. Then, the selected optimal feature vectors were given as the input to a supervised classifier Support Vector Machine (SVM) to classify three Alzheimer classes of subjects; those are normal, Alzheimer disease and Mild Cognitive Impairment (MCI). The experimental outcome showed that the proposed methodology performed effectively by means of sensitivity, accuracy, specificity, and f-score. The proposed methodology enhanced the classification accuracy up to 2-20% compared to the existing methodologies.

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Alzheimer's disease diagnosis on structural MR images using circular harmonic functions descriptors on hippocampus and posterior cingulate cortex

Cited by 92 publications

References 58 publications

Impact of SORL1 genetic variations on MRI markers in non-demented elders

Impact of SORL1 genetic variations on MRI markers in non-demented elders

Impairment of the executive function in breast cancer patients receiving chemotherapy treatment: a functional MRI study

Relieff Feature Selection Based Alzheimer Disease Classification Using Hybrid Features and Support Vector Machine in Magnetic Resonance Imaging

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