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Machine learning-based identification of symptomatic carotid atherosclerotic plaques with dual-energy computed tomography angiography
CONCLUSION: FF and NID can serve as useful imaging markers of symptomatic carotid plaques. This tree-based machine learning model incorporating both DECT and clinical features could potentially comprise a non-invasive method for identification of symptomatic carotid plaques to guide clinical treatment strategies.PMID:37290153 | DOI:10.1016/j.jstrokecerebrovasdis.2023.107209
Source: Atherosclerosis - June 8, 2023 Category: Cardiology Authors: Ling-Jie Wang Pei-Qing Zhai Li-Li Xue Cai-Yun Shi Qian Zhang Hua Zhang Source Type: research

CT Angiography Radiomics Combining Traditional Risk Factors to Predict Brain Arteriovenous Malformation Rupture: a Machine Learning, Multicenter Study
This study aimed to develop a machine learning model for predicting brain arteriovenous malformation (bAVM) rupture using a combination of traditional risk factors and radiomics features. This multicenter retrospective study enrolled 586 patients with unruptured bAVMs from 2010 to 2020. All patients were grouped into the hemorrhage (n = 368) and non-hemorrhage (n = 218) groups. The bAVM nidus were segmented on CT angiography images using Slicer software, and radiomic features were extracted using Pyradiomics. The dataset included a training set and an independent testing set. The machine learning model was developed on the...
Source: Translational Stroke Research - June 13, 2023 Category: Neurology Source Type: research

Computed tomography angiography-based radiomics model for predicting carotid atherosclerotic plaque vulnerability
This study aimed to identify radiomic features associated with the neovascularization of CAP and construct a prediction model for CAP vulnerability based on radiomic features. CTA data and clinical data of patients with CAPs who underwent CTA and CEUS between January 2018 and December 2021 in Beijing Hospital were retrospectively collected. The data were divided into a training cohort and a testing cohort using a 7:3 split. According to the examination of CEUS, CAPs were dichotomized into vulnerable and stable groups. 3D Slicer software was used to delineate the region of interest in CTA images, and the Pyradiomics package...
Source: Frontiers in Neurology - June 16, 2023 Category: Neurology Source Type: research

Computed tomography angiography-based radiomics model to identify high-risk carotid plaques
CONCLUSIONS: The 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.PMID:37711840 | PMC:PMC10498225 | DOI:10.21037/qims-23-158
Source: Atherosclerosis - September 15, 2023 Category: Cardiology Authors: Chao Chen Wei Tang Yong Chen Wenhan Xu Ningjun Yu Chao Liu Zenghui Li Zhao Tang Xiaoming Zhang Source Type: research

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