PURPOSE: Adenosine stress first pass cardiac magnetic resonance imaging (CMRI) is a rapidly evolving tool in the diagnosis of ischemic heart disease (IHD). The rest and stress first pass myocardial perfusion data may be interpreted using commercially available software for calculation of time intensity curves in order to generate a numeric value of the segmental or whole heart myocardial perfusion reserve index (MPRI). The objective of this study was to determine the inter- and intra-observer reliability of the data generated by standard commercially available software. METHODS: Data from 20 adenosine stress CMRI (1.5 T) studies were analyzed using commercially available CAAS MRV 3.3 software (Pie Medical Imaging B.V., Netherlands) for calculation of the MPRI. The stress CMRI was performed using a standardized protocol in 20 women including 10 women with angina and the absence of obstructive CAD and 10 healthy volunteers. MPRI calculation was made in a standardized manner on separate occasions by two independent observers. A single observer repeated the calculation of MPRI three months later, without reference to the prior data. Basal, mid, and apical segments, for the whole myocardium, sub-endocardium, and sub-epicardium were analyzed. Intra-class correlation coefficients (ICC), repeatability coefficients (RC), and coefficients of variation (CoV) were determined. RESULTS: The MPRI results by repeated software measurements were highly correlated, with potentially important variations in measurement observed. The myocardial inter-observer ICC was 0.80 (95% CI, 0.57, 0.92) with a CoV of 7.5%, and intra-observer ICC was 0.89 (95% CI, 0.77, 0.95) with a CoV of 3.6%. The mid-ventricular level MPRI was most reproducible, with intra-observer ICC at 0.91 (95% CI, 0.77, 0.97); intra-observer measurement was more reproducible than inter-observer measurement. CONCLUSIONS: There is variation in measurement of MPRI observed in post processing of perfusion data when using a standardized approach and commercially available software. This has implications in the interpretation of data obtained for clinical and research purposes.
PURPOSE:Adenosine stress first pass cardiac magnetic resonance imaging (CMRI) is a rapidly evolving tool in the diagnosis of ischemic heart disease (IHD). The rest and stress first pass myocardial perfusion data may be interpreted using commercially available software for calculation of time intensity curves in order to generate a numeric value of the segmental or whole heart myocardial perfusion reserve index (MPRI). The objective of this study was to determine the inter- and intra-observer reliability of the data generated by standard commercially available software. METHODS: Data from 20 adenosine stress CMRI (1.5 T) studies were analyzed using commercially available CAAS MRV 3.3 software (Pie Medical Imaging B.V., Netherlands) for calculation of the MPRI. The stress CMRI was performed using a standardized protocol in 20 women including 10 women with angina and the absence of obstructive CAD and 10 healthy volunteers. MPRI calculation was made in a standardized manner on separate occasions by two independent observers. A single observer repeated the calculation of MPRI three months later, without reference to the prior data. Basal, mid, and apical segments, for the whole myocardium, sub-endocardium, and sub-epicardium were analyzed. Intra-class correlation coefficients (ICC), repeatability coefficients (RC), and coefficients of variation (CoV) were determined. RESULTS: The MPRI results by repeated software measurements were highly correlated, with potentially important variations in measurement observed. The myocardial inter-observer ICC was 0.80 (95% CI, 0.57, 0.92) with a CoV of 7.5%, and intra-observer ICC was 0.89 (95% CI, 0.77, 0.95) with a CoV of 3.6%. The mid-ventricular level MPRI was most reproducible, with intra-observer ICC at 0.91 (95% CI, 0.77, 0.97); intra-observer measurement was more reproducible than inter-observer measurement. CONCLUSIONS: There is variation in measurement of MPRI observed in post processing of perfusion data when using a standardized approach and commercially available software. This has implications in the interpretation of data obtained for clinical and research purposes.
Entities:
Keywords:
Cardiac magnetic resonance; myocardial perfusion reserve; reproducibility
Authors: Manuel D Cerqueira; Neil J Weissman; Vasken Dilsizian; Alice K Jacobs; Sanjiv Kaul; Warren K Laskey; Dudley J Pennell; John A Rumberger; Thomas Ryan; Mario S Verani Journal: Circulation Date: 2002-01-29 Impact factor: 29.690
Authors: Igor Klem; John F Heitner; Dipan J Shah; Michael H Sketch; Victor Behar; Jonathan Weinsaft; Peter Cawley; Michele Parker; Michael Elliott; Robert M Judd; Raymond J Kim Journal: J Am Coll Cardiol Date: 2006-03-27 Impact factor: 24.094
Authors: Janet Wei; Puja K Mehta; B Delia Johnson; Bruce Samuels; Saibal Kar; R David Anderson; Babak Azarbal; John Petersen; Barry Sharaf; Eileen Handberg; Chrisandra Shufelt; Kamlesh Kothawade; George Sopko; Amir Lerman; Leslee Shaw; Sheryl F Kelsey; Carl J Pepine; C Noel Bairey Merz Journal: JACC Cardiovasc Interv Date: 2012-06 Impact factor: 11.195
Authors: Piotr J Slomka; Erick Alexanderson; Rodrigo Jácome; Moises Jiménez; Edgar Romero; Aloha Meave; Ludovic Le Meunier; Magnus Dalhbom; Daniel S Berman; Guido Germano; Heinrich Schelbert Journal: J Nucl Med Date: 2012-01-06 Impact factor: 10.057
Authors: Jonathan R Panting; Peter D Gatehouse; Guang-Zhong Yang; Frank Grothues; David N Firmin; Peter Collins; Dudley J Pennell Journal: N Engl J Med Date: 2002-06-20 Impact factor: 91.245
Authors: Sharon Chih; Peter S Macdonald; Michael P Feneley; Matthew Law; Robert M Graham; Jane A McCrohon Journal: J Cardiovasc Magn Reson Date: 2010-07-21 Impact factor: 5.364
Authors: Mark Doyle; Gerald M Pohost; C Noel Bairey Merz; Leslee J Shaw; George Sopko; William J Rogers; Barry L Sharaf; Carl J Pepine; Diane A Vido-Thompson; Geetha Rayarao; Lindsey Tauxe; Sheryl F Kelsey; Douglas Mc Nair; Robert W Biederman Journal: Cardiovasc Diagn Ther Date: 2013-12
Authors: Michael D Nelson; Lidia S Szczepaniak; Janet Wei; Afsaneh Haftabaradaren; Meghan Bharadwaj; Behzad Sharif; Puja Mehta; Xiao Zhang; Louise E Thomson; Daniel S Berman; Debiao Li; C Noel Bairey Merz Journal: Circ Cardiovasc Imaging Date: 2014-03-14 Impact factor: 7.792
Authors: Mark Doyle; Gerald M Pohost; C Noel Bairey Merz; Leslee J Shaw; George Sopko; William J Rogers; Barry L Sharaf; Carl J Pepine; Diane V Thompson; Geetha Rayarao; Lindsey Tauxe; Sheryl F Kelsey; Robert W W Biederman Journal: Cardiovasc Diagn Ther Date: 2016-10
Authors: May Bakir; Janet Wei; Michael D Nelson; Puja K Mehta; Afsaneh Haftbaradaran; Erika Jones; Edward Gill; Behzad Sharif; Piotr J Slomka; Debiao Li; Chrisandra L Shufelt; Margo Minissian; Daniel S Berman; C Noel Bairey Merz; Louise E J Thomson Journal: Cardiovasc Diagn Ther Date: 2016-02
Authors: Cecil A Rambarat; Islam Y Elgendy; Eileen M Handberg; C Noel Bairey Merz; Janet Wei; Margo B Minissian; Michael D Nelson; Louise E J Thomson; Daniel S Berman; Leslee J Shaw; Galen Cook-Wiens; Carl J Pepine Journal: Int J Cardiol Date: 2018-09-26 Impact factor: 4.039
Authors: C Noel Bairey Merz; Eileen M Handberg; Chrisandra L Shufelt; Puja K Mehta; Margo B Minissian; Janet Wei; Louise E J Thomson; Daniel S Berman; Leslee J Shaw; John W Petersen; Garrett H Brown; R David Anderson; Jonathan J Shuster; Galen Cook-Wiens; André Rogatko; Carl J Pepine Journal: Eur Heart J Date: 2015-11-27 Impact factor: 35.855