Literature DB >> 22135141

Assessment of right ventricle volumes and function by cardiac MRI: quantification of the regional and global interobserver variability.

Laurent Bonnemains1, Damien Mandry, Pierre-Yves Marie, Emilien Micard, Bailiang Chen, Pierre-André Vuissoz.   

Abstract

Reproducibility of the manual assessment of right ventricle volumes by short-axis cine-MRI remains low and is often attributed to the difficulty in separating the right atrium from the ventricle. This study was designed to evaluate the regional interobserver variability of the right ventricle volume assessment to identify segmentation zones with the highest interobserver variability. Short-axis views of 90 right ventricles (30 hypertrophic, 30 dilated, and 30 normal) were acquired with 2D steady-state free precession sequences at 1.5 T and were manually segmented by two observers. The two segmentations were compared and the variations were quantified with a variation score based on the Hausdorff distance between the two segmentations and the interobserver 95% limits of concordance of the global volumes. The right ventricles were semiautomatically split into four subregions: apex, mid-ventricle, tricuspid zone, and infundibulum. These four subregions represented 11%, 34%, 36%, and 19% of the volume but, respectively, yielded variation scores of 8%, 16%, 42%, and 34%. The infundibulum yielded the highest interobserver regional variability although its variation score remained comparable to the tricuspid zone due to its lower volume. These results emphasize the importance of standardizing the segmentation of the infundibulum and the tricuspid zone to improve reproducibility.
Copyright © 2011 Wiley-Liss, Inc.

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Year:  2011        PMID: 22135141     DOI: 10.1002/mrm.23143

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  13 in total

1.  Preoperative right ventricular dysfunction is a strong predictor of 3 years survival after cardiac surgery.

Authors:  Jérôme Peyrou; Christophe Chauvel; Atul Pathak; Marc Simon; Patrick Dehant; Eric Abergel
Journal:  Clin Res Cardiol       Date:  2017-04-13       Impact factor: 5.460

2.  The prognostic value of right ventricular long axis strain in non-ischaemic dilated cardiomyopathies using standard cardiac magnetic resonance imaging.

Authors:  Nisha Arenja; Johannes H Riffel; Manuel Halder; Charly N Djiokou; Thomas Fritz; Florian Andre; Fabian Aus dem Siepen; Thomas Zelniker; Benjamin Meder; Elham Kayvanpour; Grigorios Korosoglou; Hugo A Katus; Sebastian J Buss
Journal:  Eur Radiol       Date:  2017-02-10       Impact factor: 5.315

3.  Surface-length index: a novel index for rapid detection of right ventricles with abnormal ejection fraction using cardiac MRI.

Authors:  Laurent Bonnemains; Damien Mandry; Anne Menini; Bertrand Stos; Jacques Felblinger; Pierre-Yves Marie; Pierre-Andre Vuissoz
Journal:  Eur Radiol       Date:  2013-05-09       Impact factor: 5.315

4.  Computerized segmentation of pulmonary nodules depicted in CT examinations using freehand sketches.

Authors:  Yongqian Qiang; Qiuping Wang; Guiping Xu; Hongxia Ma; Lei Deng; Lei Zhang; Jiantao Pu; Youmin Guo
Journal:  Med Phys       Date:  2014-04       Impact factor: 4.071

5.  Stylus/tablet user input device for MRI heart wall segmentation: efficiency and ease of use.

Authors:  Bedros Taslakian; Antonio Pires; Dan Halpern; James S Babb; Leon Axel
Journal:  Eur Radiol       Date:  2018-05-02       Impact factor: 5.315

6.  Correlated Regression Feature Learning for Automated Right Ventricle Segmentation.

Authors:  Jun Chen; Heye Zhang; Weiwei Zhang; Xiuquan Du; Yanping Zhang; Shuo Li
Journal:  IEEE J Transl Eng Health Med       Date:  2018-06-28       Impact factor: 3.316

7.  Assessment of right ventricular functional recovery after acute myocardial infarction by 2D speckle-tracking echocardiography.

Authors:  Olivier Huttin; Jérémie Lemarié; Marine Di Meglio; Nicolas Girerd; Damien Mandry; Frédéric Moulin; Simon Lemoine; Yves Juillière; Jacques Felblinger; Pierre-Yves Marie; Christine Selton-Suty
Journal:  Int J Cardiovasc Imaging       Date:  2015-01-06       Impact factor: 2.357

Review 8.  Methods for measuring right ventricular function and hemodynamic coupling with the pulmonary vasculature.

Authors:  Alessandro Bellofiore; Naomi C Chesler
Journal:  Ann Biomed Eng       Date:  2013-02-20       Impact factor: 3.934

9.  Clinical Performance and Role of Expert Supervision of Deep Learning for Cardiac Ventricular Volumetry: A Validation Study.

Authors:  Tara A Retson; Evan M Masutani; Daniel Golden; Albert Hsiao
Journal:  Radiol Artif Intell       Date:  2020-07-08

10.  Assessment of right ventricular function using cardiovascular magnetic resonance in patients with type 2 diabetes mellitus.

Authors:  Yongning Shang; Yulin Zhang; Weiling Leng; Xiaotian Lei; Liu Chen; Xiaoyue Zhou; Ziwen Liang; Jian Wang
Journal:  Quant Imaging Med Surg       Date:  2022-02
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