Literature DB >> 23662778

Cardiovascular magnetic resonance: deeper insights through bioengineering.

A A Young1, J L Prince.   

Abstract

Heart disease is the main cause of morbidity and mortality worldwide, with coronary artery disease, diabetes, and obesity being major contributing factors. Cardiovascular magnetic resonance (CMR) can provide a wealth of quantitative information on the performance of the heart, without risk to the patient. Quantitative analyses of these data can substantially augment the diagnostic quality of CMR examinations and can lead to more effective characterization of disease and quantification of treatment benefit. This review provides an overview of the current state of the art in CMR with particular regard to the quantification of motion, both microscopic and macroscopic, and the application of bioengineering analysis for the evaluation of cardiac mechanics. We discuss the current clinical practice and the likely advances in the next 5-10 years, as well as the ways in which clinical examinations can be augmented by bioengineering analysis of strain, compliance, and stress.

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Year:  2013        PMID: 23662778     DOI: 10.1146/annurev-bioeng-071812-152346

Source DB:  PubMed          Journal:  Annu Rev Biomed Eng        ISSN: 1523-9829            Impact factor:   9.590


  7 in total

1.  A Meshfree Representation for Cardiac Medical Image Computing.

Authors:  Heye Zhang; Zhifan Gao; Lin Xu; Xingjian Yu; Ken C L Wong; Huafeng Liu; Ling Zhuang; Pengcheng Shi
Journal:  IEEE J Transl Eng Health Med       Date:  2018-01-18       Impact factor: 3.316

2.  Accurate high-resolution measurements of 3-D tissue dynamics with registration-enhanced displacement encoded MRI.

Authors:  Arnold D Gomez; Samer S Merchant; Edward W Hsu
Journal:  IEEE Trans Med Imaging       Date:  2014-03-14       Impact factor: 10.048

Review 3.  Challenges of cardiac image analysis in large-scale population-based studies.

Authors:  Pau Medrano-Gracia; Brett R Cowan; Avan Suinesiaputra; Alistair A Young
Journal:  Curr Cardiol Rep       Date:  2015-03       Impact factor: 2.931

Review 4.  Lagrangian postprocessing of computational hemodynamics.

Authors:  Shawn C Shadden; Amirhossein Arzani
Journal:  Ann Biomed Eng       Date:  2014-07-25       Impact factor: 3.934

5.  Atlas-based quantification of cardiac remodeling due to myocardial infarction.

Authors:  Xingyu Zhang; Brett R Cowan; David A Bluemke; J Paul Finn; Carissa G Fonseca; Alan H Kadish; Daniel C Lee; Joao A C Lima; Avan Suinesiaputra; Alistair A Young; Pau Medrano-Gracia
Journal:  PLoS One       Date:  2014-10-31       Impact factor: 3.240

Review 6.  Multimodality Imaging for Left Ventricular Hypertrophy Severity Grading: A Methodological Review.

Authors:  Maaike Alkema; Ernest Spitzer; Osama I I Soliman; Christian Loewe
Journal:  J Cardiovasc Ultrasound       Date:  2016-12-28

7.  Fully Automated Myocardial Strain Estimation from Cardiovascular MRI-tagged Images Using a Deep Learning Framework in the UK Biobank.

Authors:  Edward Ferdian; Avan Suinesiaputra; Kenneth Fung; Nay Aung; Elena Lukaschuk; Ahmet Barutcu; Edd Maclean; Jose Paiva; Stefan K Piechnik; Stefan Neubauer; Steffen E Petersen; Alistair A Young
Journal:  Radiol Cardiothorac Imaging       Date:  2020-02-27
  7 in total

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