Literature DB >> 29734858

Current and future applications of CT coronary calcium assessment.

Christian Tesche1,2, Taylor M Duguay1, U Joseph Schoepf1,3, Marly van Assen1,4, Carlo N De Cecco1, Moritz H Albrecht1,5, Akos Varga-Szemes1, Richard R Bayer1,3, Ullrich Ebersberger1,2, John W Nance1, Christian Thilo6.   

Abstract

INTRODUCTION: Computed tomographic (CT) coronary artery calcium scoring (CAC) has been validated as a well-established screening method for cardiovascular risk stratification and treatment management that is used in addition to traditional risk factors. The purpose of this review is to present an update on current and future applications of CAC. Areas covered: The topic of CAC is summarized from its introduction to current application with focus on the validation and clinical integration including cardiovascular risk prediction and outcome, cost-effectiveness, impact on downstream medical testing, and the technical advances in scanner and software technology that are shaping the future of CAC. Furthermore, this review aims to provide guidance for the appropriate clinical use of CAC. Expert commentary: CAC is a well-established screening test in preventive care that is underused in daily clinical practice. The widespread clinical implementation of CAC will be decided by future technical advances in CT image acquisition, cost-effectiveness, and reimbursement status.

Keywords:  Computed tomography; coronary artery calcium scoring; outcome; radiation dose; risk prediction

Mesh:

Substances:

Year:  2018        PMID: 29734858     DOI: 10.1080/14779072.2018.1474347

Source DB:  PubMed          Journal:  Expert Rev Cardiovasc Ther        ISSN: 1477-9072


  4 in total

Review 1.  Artificial Intelligence in Coronary Computed Tomography Angiography: From Anatomy to Prognosis.

Authors:  Giuseppe Muscogiuri; Marly Van Assen; Christian Tesche; Carlo N De Cecco; Mattia Chiesa; Stefano Scafuri; Marco Guglielmo; Andrea Baggiano; Laura Fusini; Andrea I Guaricci; Mark G Rabbat; Gianluca Pontone
Journal:  Biomed Res Int       Date:  2020-12-16       Impact factor: 3.411

2.  Influence of deep learning image reconstruction and adaptive statistical iterative reconstruction-V on coronary artery calcium quantification.

Authors:  Yiran Wang; Hefeng Zhan; Jiameng Hou; Xueyan Ma; Wenjie Wu; Jie Liu; Jianbo Gao; Ying Guo; Yonggao Zhang
Journal:  Ann Transl Med       Date:  2021-12

Review 3.  Application of AI in cardiovascular multimodality imaging.

Authors:  Giuseppe Muscogiuri; Valentina Volpato; Riccardo Cau; Mattia Chiesa; Luca Saba; Marco Guglielmo; Alberto Senatieri; Gregorio Chierchia; Gianluca Pontone; Serena Dell'Aversana; U Joseph Schoepf; Mason G Andrews; Paolo Basile; Andrea Igoren Guaricci; Paolo Marra; Denisa Muraru; Luigi P Badano; Sandro Sironi
Journal:  Heliyon       Date:  2022-10-05

4.  Sinogram-Affirmed Iterative Reconstruction Negatively Impacts the Risk Category Based on Agatston Score: A Study Combining Coronary Calcium Score Measurement and Coronary CT Angiography.

Authors:  Wei Wang; Yan E Zhao; Li Qi; Chang Sheng Zhou; Meng Jie Lu; Jian Xin Yang; Long Jiang Zhang; Guang Ming Lu
Journal:  Biomed Res Int       Date:  2020-07-13       Impact factor: 3.411

  4 in total

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