Subcortical nuclei in Alzheimer’s disease: a volumetric and diffusion kurtosis imaging study

2018 ◽  
Vol 59 (11) ◽  
pp. 1365-1371 ◽  
Author(s):  
Ming-Liang Wang ◽  
Xiao-Er Wei ◽  
Jian-Liang Fu ◽  
Wei Li ◽  
Meng-Meng Yu ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Mmse Score ◽  
Mean Diffusivity ◽  
Volume Reduction ◽  
Diffusion Kurtosis Imaging ◽  
Left Hippocampus ◽  
Subcortical Nuclei ◽  
Diffusion Kurtosis ◽  
And Diffusion

Background Previous studies revealed that subcortical nuclei were harmed in the process of Alzheimer’s disease (AD). Purpose To investigate the volumetric and diffusion kurtosis imaging (DKI) parameter changes of subcortical nuclei in AD and their relationship with cognitive function. Materials and Methods A total of 17 mild AD patients, 15 moderate to severe AD patients, and 16 controls underwent neuropsychological tests and magnetic resonance imaging (MRI) scans. Volume, mean kurtosis (MK), mean diffusivity (MD), and fractional anisotropy (FA) were measured in hippocampus, thalamus, caudate, putamen, pallidum, and amygdala. MRI parameters were compared. Correlation analysis was performed between subcortical nuclei volume, DKI parameters, and MMSE score. Results Significant volume reduction was seen in the left hippocampus in mild AD, and the bilateral hippocampus, thalamus, putamen, left caudate, and right amygdala in moderate to severe AD ( P < 0.05). Increased MD values were observed in the left hippocampus, left amygdala, and right caudate in mild AD, and the bilateral hippocampus and right amygdala in moderate to severe AD ( P < 0.05). Decreased MK values were observed only in the bilateral hippocampus in moderate to severe AD ( P < 0.05). No group significances were found in FA value. MMSE score was positively correlated with the volume of the bilateral hippocampus, thalamus, and putamen, and MK value of the left hippocampus ( P < 0.05). A negative correlation was found with the MD value of the bilateral hippocampus and left amygdala ( P < 0.05). Conclusion Mild AD mainly has microscopic subcortical changes revealed by increased MD value, and moderate to severe AD mainly has macroscopic subcortical changes revealed by volume reduction. MK is more sensitive in severe AD than mild AD.

O2-03-06: DIFFUSION KURTOSIS IMAGING: A BIOMARKER FOR EARLY DIAGNOSIS OF ALZHEIMER'S DISEASE?

2014 ◽  
Vol 10 ◽  
pp. P169-P170
Author(s):  
Hanne Struyfs ◽  
Wim Van Hecke ◽  
Sylvie Slaets ◽  
Stefan Van der Mussele ◽  
Maya De Belder ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Diagnosis ◽  
Diffusion Kurtosis Imaging ◽  
Diffusion Kurtosis

scholarly journals Diffusion kurtosis imaging to detect amyloidosis in an APP/PS1 mouse model for Alzheimer's disease

2013 ◽  
Vol 69 (4) ◽  
pp. 1115-1121 ◽  
Author(s):  
Greetje Vanhoutte ◽  
Sandra Pereson ◽  
Rafael Delgado y Palacios ◽  
Pieter-Jan Guns ◽  
Bob Asselbergh ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Mouse Model ◽  
Diffusion Kurtosis Imaging ◽  
Diffusion Kurtosis

The diagnostic accuracy of intravoxel incoherent motion and diffusion kurtosis imaging in the differentiation of malignant and benign soft-tissue masses: which is better?

2021 ◽  
pp. 028418512110175
Author(s):  
Yajie Liu ◽  
Zhenzhen Yin ◽  
Xiangwen Li ◽  
Yu Zhang ◽  
Yuan Yuan ◽  
...  
Keyword(s):  
Soft Tissue ◽  
Mean Diffusivity ◽  
Intravoxel Incoherent Motion ◽  
Diffusion Kurtosis Imaging ◽  
Conventional Mri ◽  
Mri Features ◽  
Soft Tissue Masses ◽  
Mri Sequences ◽  
Diffusion Kurtosis ◽  
And Diffusion

Background It is difficult for conventional magnetic resonance imaging (MRI) to distinguish benign soft-tissue masses (STMs) from malignant masses. Purpose To quantitatively compare the diagnostic value of intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) in STMs. Material and Methods The data from 58 patients with STMs were retrospectively analyzed. The GE Discovery 3.0-T MRI scanner was used to acquire conventional MRI sequences, IVIM, and DKI images. The chi-square test, independent sample t-test, and Mann–Whitney U tests were used to compare the differences between conventional MRI features, IVIM, and DKI parameters (Dslow, Dfast, f, mean kurtosis [MK], and mean diffusivity [MD]) between the benign and malignant groups. Receiver-operating characteristic (ROC) curve analysis was also performed. Results Tumor size and depth are statistically different in STTs. Dslow, MK, and MD values in the malignant groups are significantly lower than the benign groups ( P < 0.05). However, Dfast and f values are not statistically different between the two groups. The area under the curve (AUC) of Dslow value (0.859) is higher than MD (0.765) and MK (0.676) values for identifying benign and malignant STMs. The Dslow value showed the best specificity (82.93%). The sensitivity and specificity of IVIM and DKI parameters are higher than that of conventional MRI sequences. Conclusion IVIM and DKI can be used to distinguish between benign and malignant STMs, with Dslow as the most meaningful parameter.

The diagnostic value of T2 map, diffusion tensor imaging, and diffusion kurtosis imaging in differentiating dermatomyositis from muscular dystrophy

2021 ◽  
pp. 028418512199900
Author(s):  
Jun Ran ◽  
Bin Dai ◽  
Chanyuan Liu ◽  
Huayue Zhang ◽  
Yitong Li ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Muscular Dystrophy ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Diagnostic Value ◽  
Thigh Muscle ◽  
Diffusion Kurtosis Imaging ◽  
T2 Map ◽  
Diffusion Kurtosis ◽  
And Diffusion

Background Dermatomyositis (DM) and muscular dystrophy are clinically difficult to differentiate. Purpose To confirm the feasibility and assess the accuracy of conventional magnetic resonance imaging (MRI), T2 map, diffusion tensor imaging (DTI), and diffusion kurtosis imaging (DKI) in the differentiation of DM from muscular dystrophy. Material and Methods Forty-two patients with DM proven by diagnostic criteria were enrolled in the study along with 23 patients with muscular dystrophy. Conventional MR, T2 map, DTI, and DKI images were obtained in the thigh musculature for all patients. Intramuscular T2 value, apparent diffusion coefficient (ADC), fractional anisotropy (FA), mean diffusivity (MD), and mean kurtosis (MK) values were compared between the patients with DM and muscular dystrophy. Student’s t-tests and receiver operating characteristic (ROC) curve analyses were performed for all parameters. P values < 0.05 were considered statistically significant. Results The intramuscular T2, ADC, FA, MD, and MK values within muscles were statistically significantly different between the DM and muscular dystrophy groups ( P<0.01). The MK value was statistically significantly different between the groups in comparison with T2 and FA value. As a supplement to conventional MRI, the parameters of MD and MK differentiated DM and muscular dystrophy may be valuable. The optimal cut-off value of ADC and MD values (with respective AUC, sensitivity, and specificity) between DM and muscular dystrophy were 1.698 ×10−3mm2/s (0.723, 54.1%, and 78.1%) and 1.80 ×10−3mm2/s (61.9% and 70.2%), respectively. Conclusion Thigh muscle ADC and MD parameters may be useful in differentiating patients with DM from those with muscular dystrophy.

scholarly journals Multimodal Hippocampal Subfield Grading For Alzheimer’s Disease Classification

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Kilian Hett ◽  
◽  
Vinh-Thong Ta ◽  
Gwenaëlle Catheline ◽  
Thomas Tourdias ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Mean Diffusivity ◽  
Disease Classification ◽  
Hippocampal Subfields ◽  
Microstructural Alterations ◽  
Current Classification ◽  
Magnetic Resonance Imaging Mri ◽  
And Diffusion ◽  
New Framework

Abstract Numerous studies have proposed biomarkers based on magnetic resonance imaging (MRI) to detect and predict the risk of evolution toward Alzheimer’s disease (AD). Most of these methods have focused on the hippocampus, which is known to be one of the earliest structures impacted by the disease. To date, patch-based grading approaches provide among the best biomarkers based on the hippocampus. However, this structure is complex and is divided into different subfields, not equally impacted by AD. Former in-vivo imaging studies mainly investigated structural alterations of these subfields using volumetric measurements and microstructural modifications with mean diffusivity measurements. The aim of our work is to improve the current classification performances based on the hippocampus with a new multimodal patch-based framework combining structural and diffusivity MRI. The combination of these two MRI modalities enables the capture of subtle structural and microstructural alterations. Moreover, we propose to study the efficiency of this new framework applied to the hippocampal subfields. To this end, we compare the classification accuracy provided by the different hippocampal subfields using volume, mean diffusivity, and our novel multimodal patch-based grading framework combining structural and diffusion MRI. The experiments conducted in this work show that our new multimodal patch-based method applied to the whole hippocampus provides the most discriminating biomarker for advanced AD detection while our new framework applied into subiculum obtains the best results for AD prediction, improving by two percentage points the accuracy compared to the whole hippocampus.

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