Dataset Information

Computed tomography of amyloid plaques in a mouse model of Alzheimer's disease using diffraction enhanced imaging.

ABSTRACT: Our understanding of early development in Alzheimer's disease (AD) is clouded by the scale at which the disease progresses; amyloid beta (Abeta) plaques, a hallmark feature of AD, are small (approximately 50 microm) and low contrast in diagnostic clinical imaging techniques. Diffraction enhanced imaging (DEI), a phase contrast x-ray imaging technique, has greater soft tissue contrast than conventional radiography and generates higher resolution images than magnetic resonance microimaging. Thus, in this proof of principle study, DEI in micro-CT mode was performed on the brains of AD-model mice to determine if DEI can visualize Abeta plaques. Results revealed small nodules in the cortex and hippocampus of the brain. Histology confirmed that the features seen in the DEI images of the brain were Abeta plaques. Several anatomical structures, including hippocampal subregions and white matter tracks, were also observed. Thus, DEI has strong promise in early diagnosis of AD, as well as general studies of the mouse brain.

SUBMITTER: Connor DM

PROVIDER: S-EPMC4652842 | biostudies-literature | 2009 Jul

REPOSITORIES: biostudies-literature

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Computed tomography of amyloid plaques in a mouse model of Alzheimer's disease using diffraction enhanced imaging.

Connor Dean M DM Benveniste Helene H Dilmanian F Avraham FA Kritzer Mary F MF Miller Lisa M LM Zhong Zhong Z

NeuroImage 20090319 4

Our understanding of early development in Alzheimer's disease (AD) is clouded by the scale at which the disease progresses; amyloid beta (Abeta) plaques, a hallmark feature of AD, are small (approximately 50 microm) and low contrast in diagnostic clinical imaging techniques. Diffraction enhanced imaging (DEI), a phase contrast x-ray imaging technique, has greater soft tissue contrast than conventional radiography and generates higher resolution images than magnetic resonance microimaging. Thus, ...[more]

PMID: 19303447

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Project description:BackgroundExtracranial atherosclerosis is one of the major causes of stroke. Carotid computed tomography angiography (CTA) is a widely used imaging modality that allows detailed assessments of plaque characteristics. This study aimed to develop and test radiomics models of carotid plaques and perivascular adipose tissue (PVAT) to distinguish symptomatic from asymptomatic plaques and compare the diagnostic value between radiomics models and traditional CTA model.MethodsA total of 144 patients with carotid plaques were divided into symptomatic and asymptomatic groups. The traditional CTA model was built by the traditional radiological features of carotid plaques measured on CTA images which were screened by univariate analysis and multivariable logistic regression. We extracted and screened radiomics features from carotid plaques and PVAT. Then, a support vector machine was used for building plaque and PVAT radiomics models, as well as a combined model using traditional CTA features and radiomics features. The diagnostic value between radiomics models and traditional CTA model was compared in identifying symptomatic carotid plaques by Delong method.ResultsThe area under curve (AUC) values of traditional CTA model were 0.624 and 0.624 for the training and validation groups, respectively. The plaque radiomics model and PVAT radiomics model achieved AUC values of 0.766, 0.740 and 0.759, 0.618 in the two groups, respectively. Meanwhile, the combined model of plaque and PVAT radiomics features and traditional CTA features had AUC values of 0.883 and 0.840 for the training and validation groups, respectively, and the receiver operating characteristic curves of combined model were significantly better than those of traditional CTA model in the training group (P<0.001) and validation group (P=0.029).ConclusionsThe combined model of the radiomics features of carotid plaques and PVAT and the traditional CTA features significantly contributes to identifying high-risk carotid plaques compared with traditional CTA model.

Dataset Information

Computed tomography of amyloid plaques in a mouse model of Alzheimer's disease using diffraction enhanced imaging.

Publications

Computed tomography of amyloid plaques in a mouse model of Alzheimer's disease using diffraction enhanced imaging.

Similar Datasets

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