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Association of Coronary Artery Calcium Detected by Routine Ungated CT Imaging With Cardiovascular Outcomes
CONCLUSIONS: Incidental CAC ≥100 was associated with an increased risk of all-cause death and adverse cardiovascular outcomes, beyond traditional risk factors. DL-CAC from routine non-ECG-gated CTs identifies patients at increased cardiovascular risk and holds promise as a tool for opportunistic screening to facilitate earlier intervention.PMID:37704309 | DOI:10.1016/j.jacc.2023.06.040
Source: Atherosclerosis - September 13, 2023 Category: Cardiology Authors: Allison W Peng Ramzi Dudum Sneha S Jain David J Maron Bhavik N Patel Nishith Khandwala David Eng Akshay S Chaudhari Alexander T Sandhu Fatima Rodriguez Source Type: research

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

Stroke risk study based on deep learning-based magnetic resonance imaging carotid plaque automatic segmentation algorithm
CONCLUSION: The evaluations in this work have demonstrated that this methodology produces acceptable results for classifying magnetic resonance imaging (MRI) data.PMID:36910524 | PMC:PMC9998982 | DOI:10.3389/fcvm.2023.1101765
Source: Atherosclerosis - March 13, 2023 Category: Cardiology Authors: Ya-Fang Chen Zhen-Jie Chen You-Yu Lin Zhi-Qiang Lin Chun-Nuan Chen Mei-Li Yang Jin-Yin Zhang Yuan-Zhe Li Yi Wang Yin-Hui Huang Source Type: research

Deep-Learning for Epicardial Adipose Tissue Assessment With Computed  Tomography: Implications for Cardiovascular Risk Prediction
CONCLUSIONS: Automated assessment of EAT volume is possible in CCTA, including in patients who are technically challenging; it forms a powerful marker of metabolically unhealthy visceral obesity, which could be used for cardiovascular risk stratification.PMID:36881425 | DOI:10.1016/j.jcmg.2022.11.018
Source: Atherosclerosis - March 7, 2023 Category: Cardiology Authors: Henry W West Muhammad Siddique Michelle C Williams Lucrezia Volpe Ria Desai Maria Lyasheva Sheena Thomas Katerina Dangas Christos P Kotanidis Pete Tomlins Ciara Mahon Attila Kardos David Adlam John Graby Jonathan C L Rodrigues Cheerag Shirodaria John Dean Source Type: research

Ischemic stroke subtyping method combining convolutional neural network and radiomics
CONCLUSION: The experimental results show that the proposed method can effectively predict the subtype of IS and has potential to assist doctors in making timely and accurate diagnoses of IS patients.PMID:36591693 | DOI:10.3233/XST-221284
Source: Atherosclerosis - January 2, 2023 Category: Cardiology Authors: Yang Chen Yiwen He Zhuoyun Jiang Yuanzhong Xie Shengdong Nie Source Type: research

New strategy for clinical etiologic diagnosis of acute ischemic stroke and blood biomarker discovery based on machine learning
RSC Adv. 2022 May 16;12(23):14716-14723. doi: 10.1039/d2ra02022j. eCollection 2022 May 12.ABSTRACTAcute ischemic stroke (AIS) is a syndrome characterized by high morbidity, prevalence, mortality, recurrence and disability. The longer the delay before proper treatment of a stroke, the greater the likelihood of brain damage and disability. Computed tomography and nuclear magnetic resonance are the primary choices for fast diagnosis of AIS in the early stage, which can provide certain information about infarction location and degree, and even the vascular distribution of lesions responsible for strokes. However, this is quite...
Source: Atherosclerosis - June 15, 2022 Category: Cardiology Authors: Jin Zhang Ting Yuan Sixi Wei Zhanhui Feng Boyan Li Hai Huang Source Type: research

Radiomics versus Conventional Assessment to Identify Symptomatic Participants at Carotid Computed Tomography Angiography
CONCLUSION: Radiomics-based ML analysis improves the discriminatory power of carotid CTA in the identification of recent ischemic symptoms in patients with carotid artery atherosclerosis.PMID:35259744 | DOI:10.1159/000522058
Source: Atherosclerosis - March 8, 2022 Category: Cardiology Authors: Zheng Dong ChangSheng Zhou HongXia Li JiaQian Shi Jia Liu QuanHui Liu XiaoQin Su FanDong Zhang XiaoQing Cheng GuangMing Lu Source Type: research