scholarly journals The Evaluation of Posterior Cingulate Gyrus by Diffusion Tensor Imaging in Alzheimer’s Disease Patients Compared with Normal Control Subjects

2019 ◽  
Vol 71 (2) ◽  
pp. 117-122
Author(s):  
Orasa Chawalparit
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Diffusion Tensor Imaging ◽  
Normal Control ◽  
Diffusion Tensor ◽  
Cingulate Gyrus ◽  
Posterior Cingulate ◽  
Posterior Cingulate Gyrus ◽  
Control Subjects

scholarly journals Biochemical Assessment of Precuneus and Posterior Cingulate Gyrus in the Context of Brain Aging and Alzheimer’s Disease

PLoS ONE ◽  
2014 ◽  
Vol 9 (8) ◽  
pp. e105784 ◽  
Author(s):  
Chera L. Maarouf ◽  
Tyler A. Kokjohn ◽  
Douglas G. Walker ◽  
Charisse M. Whiteside ◽  
Walter M. Kalback ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Brain Aging ◽  
Cingulate Gyrus ◽  
Posterior Cingulate ◽  
Posterior Cingulate Gyrus ◽  
Biochemical Assessment

scholarly journals Reduced Cortical Thickness in the Posterior Cingulate Gyrus is Characteristic of Both Typical and Atypical Alzheimer's Disease

2010 ◽  
Vol 20 (2) ◽  
pp. 587-598 ◽  
Author(s):  
Manja Lehmann ◽  
Jonathan D. Rohrer ◽  
Matthew J. Clarkson ◽  
Gerard R. Ridgway ◽  
Rachael I. Scahill ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cortical Thickness ◽  
Cingulate Gyrus ◽  
Posterior Cingulate ◽  
Posterior Cingulate Gyrus ◽  
Atypical Alzheimer’S Disease

scholarly journals Correlation between hippocampal volumes and proton magnetic resonance spectroscopy of the posterior cingulate gyrus and hippocampi in Alzheimer's disease

2010 ◽  
Vol 4 (2) ◽  
pp. 109-113
Author(s):  
Eun Joo Park ◽  
Katarina P. Lyra ◽  
Hae Won Lee ◽  
Paulo Caramelli ◽  
Maria C. G. Otaduy ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Hippocampal Volume ◽  
Resonance Spectroscopy ◽  
Cingulate Gyrus ◽  
Proton Spectroscopy ◽  
1H Mrs ◽  
Posterior Cingulate ◽  
Posterior Cingulate Gyrus ◽  
Single Voxel

Abstract Prior studies have reported hippocampal volume loss, decrease in N-Acetylaspartate (NAA) concentration and increased myo-inositol (mI) concentration in patients with Alzheimer's disease (AD). The purpose of this study was to evaluate hippocampal volumes of AD patients and their correlation with metabolic changes detected by proton spectroscopy (1H MRS) of hippocampal formations and the posterior cingulate region. Materials and Methods: 22 patients with probable AD (18 mild, 4 moderate) and 14 elderly controls without cognitive symptoms, were enrolled in the study. Hippocampal volumetric measurements, single-voxel 1H MRS of the posterior cingulate region and of hippocampal formations were obtained. The following metabolite ratios were evaluated: NAA/Cr, mI/Cr, mI/NAA. Statistical analysis was performed to detect differences and correlations between these parameters in patients and controls. Results: The hippocampal volume of patients and controls did not differ significantly. The results of 1H MRS differed significantly between patients and controls in the hippocampal formations (mI/Cr, mI/NAA) and posterior cingulate region (NAA/Cr, mI/Cr, mI/NAA). The best predictor of AD diagnosis was NAA/Cr in the posterior cingulate region, having a sensitivity of 0.899 and specificity of 0.800. There was no correlation between hippocampal volumes and the results of 1H MRS in patients with AD. Conclusions: The results of 1H MRS differed significantly between patients and controls in hippocampal formations and the posterior cingulate region, with NAA/Cr proving to be the best predictor for AD. No correlation between hippocampal volumes and the results of 1H MRS in patients with AD was observed.

scholarly journals Synaptic Change in the Posterior Cingulate Gyrus in the Progression of Alzheimer's Disease

2014 ◽  
Vol 43 (3) ◽  
pp. 1073-1090 ◽  
Author(s):  
Stephen W. Scheff ◽  
Douglas A. Price ◽  
Mubeen A. Ansari ◽  
Kelly N. Roberts ◽  
Frederick A. Schmitt ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cingulate Gyrus ◽  
Posterior Cingulate ◽  
Posterior Cingulate Gyrus ◽  
Synaptic Change

scholarly journals Machine Learning for the Classification of Alzheimer’s Disease and Its Prodromal Stage Using Brain Diffusion Tensor Imaging Data: A Systematic Review

Processes ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1071
Author(s):  
Lucia Billeci ◽  
Asia Badolato ◽  
Lorenzo Bachi ◽  
Alessandro Tonacci
Keyword(s):  
Machine Learning ◽  
Systematic Review ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Diffusion Tensor Imaging ◽  
Magnetic Resonance ◽  
Diffusion Tensor ◽  
Classification Problem ◽  
Computer Algorithms ◽  
Imaging Data

Alzheimer’s disease is notoriously the most common cause of dementia in the elderly, affecting an increasing number of people. Although widespread, its causes and progression modalities are complex and still not fully understood. Through neuroimaging techniques, such as diffusion Magnetic Resonance (MR), more sophisticated and specific studies of the disease can be performed, offering a valuable tool for both its diagnosis and early detection. However, processing large quantities of medical images is not an easy task, and researchers have turned their attention towards machine learning, a set of computer algorithms that automatically adapt their output towards the intended goal. In this paper, a systematic review of recent machine learning applications on diffusion tensor imaging studies of Alzheimer’s disease is presented, highlighting the fundamental aspects of each work and reporting their performance score. A few examined studies also include mild cognitive impairment in the classification problem, while others combine diffusion data with other sources, like structural magnetic resonance imaging (MRI) (multimodal analysis). The findings of the retrieved works suggest a promising role for machine learning in evaluating effective classification features, like fractional anisotropy, and in possibly performing on different image modalities with higher accuracy.

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