Literature DB >> 33778661

Artificial Intelligence in Cardiovascular Imaging for Risk Stratification in Coronary Artery Disease.

Andrew Lin1, Márton Kolossváry1, Manish Motwani1, Ivana Išgum1, Pál Maurovich-Horvat1, Piotr J Slomka1, Damini Dey1.   

Abstract

Artificial intelligence (AI) describes the use of computational techniques to perform tasks that normally require human cognition. Machine learning and deep learning are subfields of AI that are increasingly being applied to cardiovascular imaging for risk stratification. Deep learning algorithms can accurately quantify prognostic biomarkers from image data. Additionally, conventional or AI-based imaging parameters can be combined with clinical data using machine learning models for individualized risk prediction. The aim of this review is to provide a comprehensive review of state-of-the-art AI applications across various noninvasive imaging modalities (coronary artery calcium scoring CT, coronary CT angiography, and nuclear myocardial perfusion imaging) for the quantification of cardiovascular risk in coronary artery disease. © RSNA, 2021. 2021 by the Radiological Society of North America, Inc.

Entities:  

Year:  2021        PMID: 33778661      PMCID: PMC7978004          DOI: 10.1148/ryct.2021200512

Source DB:  PubMed          Journal:  Radiol Cardiothorac Imaging        ISSN: 2638-6135


  55 in total

1.  Integrated prediction of lesion-specific ischaemia from quantitative coronary CT angiography using machine learning: a multicentre study.

Authors:  Damini Dey; Sara Gaur; Kristian A Ovrehus; Piotr J Slomka; Julian Betancur; Markus Goeller; Michaela M Hell; Heidi Gransar; Daniel S Berman; Stephan Achenbach; Hans Erik Botker; Jesper Moller Jensen; Jens Flensted Lassen; Bjarne Linde Norgaard
Journal:  Eur Radiol       Date:  2018-01-19       Impact factor: 5.315

2.  Coronary risk stratification, discrimination, and reclassification improvement based on quantification of subclinical coronary atherosclerosis: the Heinz Nixdorf Recall study.

Authors:  Raimund Erbel; Stefan Möhlenkamp; Susanne Moebus; Axel Schmermund; Nils Lehmann; Andreas Stang; Nico Dragano; Dietrich Grönemeyer; Rainer Seibel; Hagen Kälsch; Martina Bröcker-Preuss; Klaus Mann; Johannes Siegrist; Karl-Heinz Jöckel
Journal:  J Am Coll Cardiol       Date:  2010-10-19       Impact factor: 24.094

3.  Coronary artery disease: improved reproducibility of calcium scoring with an electron-beam CT volumetric method.

Authors:  T Q Callister; B Cooil; S P Raya; N J Lippolis; D J Russo; P Raggi
Journal:  Radiology       Date:  1998-09       Impact factor: 11.105

Review 4.  Machine Learning in Medicine.

Authors:  Rahul C Deo
Journal:  Circulation       Date:  2015-11-17       Impact factor: 29.690

5.  Long-term prognosis associated with coronary calcification: observations from a registry of 25,253 patients.

Authors:  Matthew J Budoff; Leslee J Shaw; Sandy T Liu; Steven R Weinstein; Tristen P Mosler; Philip H Tseng; Ferdinand R Flores; Tracy Q Callister; Paolo Raggi; Daniel S Berman
Journal:  J Am Coll Cardiol       Date:  2007-04-20       Impact factor: 24.094

6.  Comparison of novel risk markers for improvement in cardiovascular risk assessment in intermediate-risk individuals.

Authors:  Joseph Yeboah; Robyn L McClelland; Tamar S Polonsky; Gregory L Burke; Christopher T Sibley; Daniel O'Leary; Jeffery J Carr; David C Goff; Philip Greenland; David M Herrington
Journal:  JAMA       Date:  2012-08-22       Impact factor: 56.272

Review 7.  A guide to deep learning in healthcare.

Authors:  Andre Esteva; Alexandre Robicquet; Bharath Ramsundar; Volodymyr Kuleshov; Mark DePristo; Katherine Chou; Claire Cui; Greg Corrado; Sebastian Thrun; Jeff Dean
Journal:  Nat Med       Date:  2019-01-07       Impact factor: 53.440

8.  Fully Automated CT Quantification of Epicardial Adipose Tissue by Deep Learning: A Multicenter Study.

Authors:  Frederic Commandeur; Markus Goeller; Aryabod Razipour; Sebastien Cadet; Michaela M Hell; Jacek Kwiecinski; Xi Chen; Hyuk-Jae Chang; Mohamed Marwan; Stephan Achenbach; Daniel S Berman; Piotr J Slomka; Balaji K Tamarappoo; Damini Dey
Journal:  Radiol Artif Intell       Date:  2019-11-27

9.  Deep Learning for Automatic Calcium Scoring in CT: Validation Using Multiple Cardiac CT and Chest CT Protocols.

Authors:  Sanne G M van Velzen; Nikolas Lessmann; Birgitta K Velthuis; Ingrid E M Bank; Desiree H J G van den Bongard; Tim Leiner; Pim A de Jong; Wouter B Veldhuis; Adolfo Correa; James G Terry; John Jeffrey Carr; Max A Viergever; Helena M Verkooijen; Ivana Išgum
Journal:  Radiology       Date:  2020-02-11       Impact factor: 29.146

10.  Low-Attenuation Noncalcified Plaque on Coronary Computed Tomography Angiography Predicts Myocardial Infarction: Results From the Multicenter SCOT-HEART Trial (Scottish Computed Tomography of the HEART).

Authors:  Marc R Dweck; Damini Dey; Michelle C Williams; Jacek Kwiecinski; Mhairi Doris; Priscilla McElhinney; Michelle S D'Souza; Sebastien Cadet; Philip D Adamson; Alastair J Moss; Shirjel Alam; Amanda Hunter; Anoop S V Shah; Nicholas L Mills; Tania Pawade; Chengjia Wang; Jonathan Weir McCall; Michael Bonnici-Mallia; Christopher Murrills; Giles Roditi; Edwin J R van Beek; Leslee J Shaw; Edward D Nicol; Daniel S Berman; Piotr J Slomka; David E Newby
Journal:  Circulation       Date:  2020-03-16       Impact factor: 29.690

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  7 in total

1.  Handling missing values in machine learning to predict patient-specific risk of adverse cardiac events: Insights from REFINE SPECT registry.

Authors:  Richard Rios; Robert J H Miller; Nipun Manral; Tali Sharir; Andrew J Einstein; Mathews B Fish; Terrence D Ruddy; Philipp A Kaufmann; Albert J Sinusas; Edward J Miller; Timothy M Bateman; Sharmila Dorbala; Marcelo Di Carli; Serge D Van Kriekinge; Paul B Kavanagh; Tejas Parekh; Joanna X Liang; Damini Dey; Daniel S Berman; Piotr J Slomka
Journal:  Comput Biol Med       Date:  2022-03-25       Impact factor: 6.698

2.  Application of Table Tennis Ball Trajectory and Rotation-Oriented Prediction Algorithm Using Artificial Intelligence.

Authors:  Qiang Liu; Hairong Ding
Journal:  Front Neurorobot       Date:  2022-05-11       Impact factor: 3.493

3.  The Predictive Value of the Perivascular Adipose Tissue CT Fat Attenuation Index for Coronary In-stent Restenosis.

Authors:  Bin Qin; Zhengjun Li; Hao Zhou; Yongkang Liu; Huiming Wu; Zhongqiu Wang
Journal:  Front Cardiovasc Med       Date:  2022-04-26

Review 4.  Cardiac Computed Tomography Radiomics for the Non-Invasive Assessment of Coronary Inflammation.

Authors:  Kevin Cheng; Andrew Lin; Jeremy Yuvaraj; Stephen J Nicholls; Dennis T L Wong
Journal:  Cells       Date:  2021-04-12       Impact factor: 6.600

5.  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

6.  Use of artificial intelligence to assess the risk of coronary artery disease without additional (non-invasive) testing: validation in a low-risk to intermediate-risk outpatient clinic cohort.

Authors:  Casper G M J Eurlings; Sema Bektas; Sandra Sanders-van Wijk; Andrew Tsirkin; Vasily Vasilchenko; Steven J R Meex; Michael Failer; Caroline Oehri; Peter Ruff; Michael J Zellweger; Hans-Peter Brunner-La Rocca
Journal:  BMJ Open       Date:  2022-09-26       Impact factor: 3.006

7.  Comparing the Prognostic Value of Stress Myocardial Perfusion Imaging by Conventional and Cadmium-Zinc Telluride Single-Photon Emission Computed Tomography through a Machine Learning Approach.

Authors:  Valeria Cantoni; Roberta Green; Carlo Ricciardi; Roberta Assante; Leandro Donisi; Emilia Zampella; Giuseppe Cesarelli; Carmela Nappi; Vincenzo Sannino; Valeria Gaudieri; Teresa Mannarino; Andrea Genova; Giovanni De Simini; Alessia Giordano; Adriana D'Antonio; Wanda Acampa; Mario Petretta; Alberto Cuocolo
Journal:  Comput Math Methods Med       Date:  2021-10-16       Impact factor: 2.238

  7 in total

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