Literature DB >> 21427481

Evaluation of the effect of myocardial segmentation errors on myocardial blood flow estimates from DCE-MRI.

J Biglands1, D Magee, R Boyle, A Larghat, S Plein, A Radjenović.   

Abstract

Quantitative analysis of cardiac dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) perfusion datasets is dependent on the drawing (manually or automatically) of myocardial contours. The required accuracy of these contours for myocardial blood flow (MBF) estimation is not well understood. This study investigates the relationship between myocardial contour errors and MBF errors. Myocardial contours were manually drawn on DCE-MRI perfusion datasets of healthy volunteers imaged in systole. Systematic and random contour errors were simulated using spline curves and the resulting errors in MBF were calculated. The degree of contour error was also evaluated by two recognized segmentation metrics. We derived contour error tolerances in terms of the maximum deviation (MD) a contour could deviate radially from the 'true' contour expressed as a fraction of each volunteer's mean myocardial width (MW). Significant MBF errors were avoided by setting tolerances of MD ≤ 0.4 MW, when considering the whole myocardium, MD ≤ 0.3 MW, when considering six radial segments, and MD ≤ 0.2 MW for further subdivision into endo- and epicardial regions, with the exception of the anteroseptal region, which required greater accuracy. None of the considered segmentation metrics correlated with MBF error; thus, both segmentation metrics and MBF errors should be used to evaluate contouring algorithms.

Entities:  

Mesh:

Substances:

Year:  2011        PMID: 21427481     DOI: 10.1088/0031-9155/56/8/007

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  12 in total

1.  Interstudy repeatability of self-gated quantitative myocardial perfusion MRI.

Authors:  Devavrat Likhite; Promporn Suksaranjit; Ganesh Adluru; Nan Hu; Cindy Weng; Eugene Kholmovski; Chris McGann; Brent Wilson; Edward DiBella
Journal:  J Magn Reson Imaging       Date:  2015-12-13       Impact factor: 4.813

2.  Comparison of the Diagnostic Performance of Four Quantitative Myocardial Perfusion Estimation Methods Used in Cardiac MR Imaging: CE-MARC Substudy.

Authors:  John D Biglands; Derek R Magee; Steven P Sourbron; Sven Plein; John P Greenwood; Aleksandra Radjenovic
Journal:  Radiology       Date:  2014-12-18       Impact factor: 11.105

3.  Measurement of myocardial blood flow by cardiovascular magnetic resonance perfusion: comparison of distributed parameter and Fermi models with single and dual bolus.

Authors:  Giorgos Papanastasiou; Michelle C Williams; Lucy E Kershaw; Marc R Dweck; Shirjel Alam; Saeed Mirsadraee; Martin Connell; Calum Gray; Tom MacGillivray; David E Newby; Scott Ik Semple
Journal:  J Cardiovasc Magn Reson       Date:  2015-02-17       Impact factor: 5.364

4.  Evaluation of an automated method for arterial input function detection for first-pass myocardial perfusion cardiovascular magnetic resonance.

Authors:  Matthew Jacobs; Mitchel Benovoy; Lin-Ching Chang; Andrew E Arai; Li-Yueh Hsu
Journal:  J Cardiovasc Magn Reson       Date:  2016-04-08       Impact factor: 5.364

5.  Voxel-wise quantification of myocardial blood flow with cardiovascular magnetic resonance: effect of variations in methodology and validation with positron emission tomography.

Authors:  Christopher A Miller; Josephine H Naish; Mark P Ainslie; Christine Tonge; Deborah Tout; Parthiban Arumugam; Anita Banerji; Robin M Egdell; David Clark; Peter Weale; Christopher D Steadman; Gerry P McCann; Simon G Ray; Geoffrey J M Parker; Matthias Schmitt
Journal:  J Cardiovasc Magn Reson       Date:  2014-01-24       Impact factor: 5.364

6.  Multiparametric cardiovascular magnetic resonance surveillance of acute cardiac allograft rejection and characterisation of transplantation-associated myocardial injury: a pilot study.

Authors:  Christopher A Miller; Josephine H Naish; Steven M Shaw; Nizar Yonan; Simon G Williams; David Clark; Paul W Bishop; Mark P Ainslie; Alex Borg; Glyn Coutts; Geoffrey J M Parker; Simon G Ray; Matthias Schmitt
Journal:  J Cardiovasc Magn Reson       Date:  2014-07-20       Impact factor: 5.364

7.  Patient-specific coronary blood supply territories for quantitative perfusion analysis.

Authors:  Constantine Zakkaroff; John D Biglands; John P Greenwood; Sven Plein; Roger D Boyle; Aleksandra Radjenovic; Derek R Magee
Journal:  Comput Methods Biomech Biomed Eng Imaging Vis       Date:  2016-07-13

8.  A comparison of cardiovascular magnetic resonance and single photon emission computed tomography (SPECT) perfusion imaging in left main stem or equivalent coronary artery disease: a CE-MARC substudy.

Authors:  James R J Foley; Ananth Kidambi; John D Biglands; Neil Maredia; Catherine J Dickinson; Sven Plein; John P Greenwood
Journal:  J Cardiovasc Magn Reson       Date:  2017-11-06       Impact factor: 5.364

9.  Fibroblast growth factor-23 is associated with imaging markers of diabetic cardiomyopathy and anti-diabetic therapeutics.

Authors:  Martin H Sørensen; Annemie S Bojer; Niklas R Jørgensen; David A Broadbent; Sven Plein; Per L Madsen; Peter Gæde
Journal:  Cardiovasc Diabetol       Date:  2020-09-30       Impact factor: 9.951

10.  Myocardial blood flow quantification from MRI by deconvolution using an exponential approximation basis.

Authors:  Gilion Hautvast; Amedeo Chiribiri; Niloufar Zarinabad; Andreas Schuster; Marcel Breeuwer; Eike Nagel
Journal:  IEEE Trans Biomed Eng       Date:  2012-05-03       Impact factor: 4.538

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.