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Attention-Based UNet Deep Learning Model for Plaque Segmentation in Carotid Ultrasound for Stroke Risk Stratification: An Artificial Intelligence Paradigm
This study proposes an attention-channel-based UNet deep learning (DL) model that identifies the carotid plaques in the internal carotid artery (ICA) and common carotid artery (CCA) images. Our experiments consist of 970 ICA images from the UK, 379 CCA images from diabetic Japanese patients, and 300 CCA images from post-menopausal women from Hong Kong. We combined both CCA images to form an integrated database of 679 images. A rotation transformation technique was applied to 679 CCA images, doubling the database for the experiments. The cross-validation K5 (80% training: 20% testing) protocol was applied for accuracy deter...
Source: Atherosclerosis - October 26, 2022 Category: Cardiology Authors: Pankaj K Jain Abhishek Dubey Luca Saba Narender N Khanna John R Laird Andrew Nicolaides Mostafa M Fouda Jasjit S Suri Neeraj Sharma Source Type: research

Evaluation of Large-Scale Proteomics for Prediction of Cardiovascular Events
CONCLUSIONS AND RELEVANCE: A protein risk score was significantly associated with ASCVD events in primary and secondary event populations. When added to clinical risk factors, the protein risk score and polygenic risk score both provided statistically significant but modest improvement in discrimination.PMID:37606673 | DOI:10.1001/jama.2023.13258
Source: Atherosclerosis - August 22, 2023 Category: Cardiology Authors: Hannes Helgason Thjodbjorg Eiriksdottir Magnus O Ulfarsson Abhishek Choudhary Sigrun H Lund Erna V Ivarsdottir Grimur Hjorleifsson Eldjarn Gudmundur Einarsson Egil Ferkingstad Kristjan H S Moore Narimon Honarpour Thomas Liu Huei Wang Thomas Hucko Marc S S Source Type: research

Distinguishing intracranial diabetes-related atherosclerotic plaques : A high-resolution MRI-based radiomics study
CONCLUSIONS: The use of radiomics features of intracranial plaques on hrMRI can effectively distinguish culprit plaques with diabetes as the primary pathological cause, which will provide new avenues of research into plaque formation and precise treatment.PMID:37044072 | DOI:10.1159/000530412
Source: Atherosclerosis - April 12, 2023 Category: Cardiology Authors: XiaoQing Cheng HongXia Li Jia Liu ChangSheng Zhou QuanHui Liu XingZhi Chen ChenCui Huang YingLe Li WuSheng Zhu GuangMing Lu Source Type: research

Development and validation of explainable machine-learning models for carotid atherosclerosis early screening
CONCLUSIONS: The ML models developed could provide good performance for CAS identification using routine health check-up indicators and could hopefully be applied in scenarios without ethnic and geographic heterogeneity for CAS prevention.PMID:37246225 | DOI:10.1186/s12967-023-04093-8
Source: Atherosclerosis - May 28, 2023 Category: Cardiology Authors: Ke Yun Tao He Shi Zhen Meihui Quan Xiaotao Yang Dongliang Man Shuang Zhang Wei Wang Xiaoxu Han Source Type: research