PURPOSE: To assess the reproducibility of Harmonic Phase (HARP) analysis of myocardial MR tagged images acquired in the Multi-Center Study of Atherosclerosis (MESA). METHODS: Using the HARP method, three independent observers performed two separate quantitative strain analyses of myocardial cine MR-tagging images blindly in 24 participants. The images were obtained in four different centers and analyzed at a single core lab. Each study comprised 3 short-axis slices subdivided in 12 segments (24 x 3 x 12 = 864 segments), each with three layers. Normal strains (circumferential [Ecc] and radial [Err]), principal strains (Lambda1, Lambda2), and the angle alpha (between Ecc-Lambda2) were calculated. Intraclass correlation coefficient (R) for peak systolic strains, and all pooled systolic and diastolic strain data were used to determine inter- and intraobserver agreement. Two observers also visually graded study quality. R values were related to the image quality in different myocardial regions and layers. RESULTS: Overall, HARP yielded an excellent inter- and intraobserver agreement for peak systolic strain data (for Ecc, R = 0.84 and 0.89, respectively) and all systolic pooled data (for Ecc, interobserver R = 0.82, intraobserver R = 0.69-0.76). Both inter and intraobserver agreement were lower for diastolic pooled data (R = 0.69 and 0.58-0.62, respectively). There was a direct relationship between image quality and performance of the HARP analysis, with increasing inter- and intraobserver R values in studies with longer tag persistence. Both inter- and intraobserver agreement were better in the anterior and septal myocardial regions, and in the midwall layer. The intraobserver agreement was similar among the three observers. CONCLUSION: Employing the HARP method for quantitative strain analysis of myocardial MR tagged images provides a high inter- and intraobserver agreement. These good results are obtained in case of good to excellent MR image quality.
PURPOSE: To assess the reproducibility of Harmonic Phase (HARP) analysis of myocardial MR tagged images acquired in the Multi-Center Study of Atherosclerosis (MESA). METHODS: Using the HARP method, three independent observers performed two separate quantitative strain analyses of myocardial cine MR-tagging images blindly in 24 participants. The images were obtained in four different centers and analyzed at a single core lab. Each study comprised 3 short-axis slices subdivided in 12 segments (24 x 3 x 12 = 864 segments), each with three layers. Normal strains (circumferential [Ecc] and radial [Err]), principal strains (Lambda1, Lambda2), and the angle alpha (between Ecc-Lambda2) were calculated. Intraclass correlation coefficient (R) for peak systolic strains, and all pooled systolic and diastolic strain data were used to determine inter- and intraobserver agreement. Two observers also visually graded study quality. R values were related to the image quality in different myocardial regions and layers. RESULTS: Overall, HARP yielded an excellent inter- and intraobserver agreement for peak systolic strain data (for Ecc, R = 0.84 and 0.89, respectively) and all systolic pooled data (for Ecc, interobserver R = 0.82, intraobserver R = 0.69-0.76). Both inter and intraobserver agreement were lower for diastolic pooled data (R = 0.69 and 0.58-0.62, respectively). There was a direct relationship between image quality and performance of the HARP analysis, with increasing inter- and intraobserver R values in studies with longer tag persistence. Both inter- and intraobserver agreement were better in the anterior and septal myocardial regions, and in the midwall layer. The intraobserver agreement was similar among the three observers. CONCLUSION: Employing the HARP method for quantitative strain analysis of myocardial MR tagged images provides a high inter- and intraobserver agreement. These good results are obtained in case of good to excellent MR image quality.
Authors: W Gregory Hundley; David A Bluemke; J Paul Finn; Scott D Flamm; Mark A Fogel; Matthias G Friedrich; Vincent B Ho; Michael Jerosch-Herold; Christopher M Kramer; Warren J Manning; Manesh Patel; Gerald M Pohost; Arthur E Stillman; Richard D White; Pamela K Woodard Journal: Circulation Date: 2010-05-17 Impact factor: 29.690
Authors: W Gregory Hundley; David A Bluemke; J Paul Finn; Scott D Flamm; Mark A Fogel; Matthias G Friedrich; Vincent B Ho; Michael Jerosch-Herold; Christopher M Kramer; Warren J Manning; Manesh Patel; Gerald M Pohost; Arthur E Stillman; Richard D White; Pamela K Woodard Journal: J Am Coll Cardiol Date: 2010-06-08 Impact factor: 24.094
Authors: Iris K Rüssel; Jeroen van Dijk; Sebastiaan A Kleijn; Tjeerd Germans; Gerjan de Roest; J Tim Marcus; Otto Kamp; Marco J W Götte; Albert C van Rossum Journal: Int J Cardiovasc Imaging Date: 2008-07-17 Impact factor: 2.357
Authors: Yoshiaki Ohyama; Bharath Ambale-Venkatesh; Chikara Noda; Atul R Chugh; Gisela Teixido-Tura; Jang-Young Kim; Sirisha Donekal; Kihei Yoneyama; Ola Gjesdal; Alban Redheuil; Chia-Ying Liu; Tetsuya Nakamura; Colin O Wu; W Gregory Hundley; David A Bluemke; Joao A C Lima Journal: Circ Cardiovasc Imaging Date: 2016-07 Impact factor: 7.792
Authors: Eui-Young Choi; Raymond T Yan; Veronica R S Fernandes; Anders Opdahl; Antoinette S Gomes; Andre L C Almeida; Colin O Wu; Kiang Liu; Jeffrey J Carr; Robyn L McClelland; David A Bluemke; Joao A C Lima Journal: Am Heart J Date: 2012-07-07 Impact factor: 4.749
Authors: Sirisha Donekal; Bharath A Venkatesh; Yuan Chang Liu; Chia-Ying Liu; Kihei Yoneyama; Colin O Wu; Marcelo Nacif; Antoinette S Gomes; W Gregory Hundley; David A Bluemke; Joao A C Lima Journal: Circ Cardiovasc Imaging Date: 2014-02-18 Impact factor: 7.792
Authors: Yijen L Wu; Qing Ye; Danielle F Eytan; Li Liu; Bedda L Rosario; T Kevin Hitchens; Fang-Cheng Yeh; Nico Rooijen van; Chien Ho Journal: Circ Cardiovasc Imaging Date: 2013-10-04 Impact factor: 7.792