P1393 Intervendor difference in global and regional 2D speckle tracking strain. comparison against cMR tagging. (17th January 2020)

• Record Type: Journal Article
• Authors: Tamakloe, T; Langet, H; Amzulescu, M A; Saloux, E; Manrique, A; Pouleur, A C; Vancraeynest, D; Pasquet, A; Vanoverschelde, J L; Gerber, B L M
• Is Part Of: European heart journal. Volume 21(2020)Supplement 1
• Publication Date: 2020-01-17
• Subjects: Cardiovascular system -- Imaging -- Periodicals; Heart -- Imaging -- Periodicals; 616.10754
• DOI: 10.1093/ehjci/jez319.826
• Languages: English
• ISSNs: 2047-2404

Abstract

Abstract: Funding Acknowledgements: Fondation de Recherche Scientifique Belge FRSM PDR 19488731 BACKGROUND: 2D-speckle-tracking (ST) echocardiography is currently widely used for estimation of global (G) and regional myocardial deformation. In previous works, we showed good correlation between global longitudinal (LS) and circumferential strain (CS) from one 2DST vendor with cMR-Tagging, however with significant bias between both methods. Also, we found poorer agreement between 2DST and cMR-Tagging on regional basis. However it is unknown how 2DST from other vendors would comparte to cMR tagging. PURPOSE: To asssess vendor differences in global and regional strain assessment and compare 1) the agreement of 2 different 2DST softwares for global and regional LS and CS among each other and against cMR-Tagging as reference; and 2) the accuracy of both softwares to detect infarcted segments. METHODS: 100 subjects with different cardiac disease (among which 31 with chronic infarct) underwent 2DST and tagging and LGE cMR on the same day. Global and regional CS (16 AHA segments) and LS (18 AHA segments) was computed using 2 different ST vendor softwares and compared to cMR-Tagging with HARP. Accuracy of regional 2D-ST by both vendors to detect infarcted segments (ie >75% transmurality of late gadolinium) was compared using ROC analysis. RESULTS: Global LS (ICC = 0.87) and CS 2DST (ICC = 0.83, p < 0.001) agreed well between both vendors, but GCS values of vendor2 were significantly greater than that of vendor 1. Also we fond good correlation between ST of both vendors and cMR-Tagging for GLS (ICC = 0.80 and ICC = 0.69 for vendor 1 and 2 respectively) and GCS (ICC = 0.64 and ICC = 0.50 for vendor 1 and 2 respectively). Bias for GLS (-4.6 ± 2.9% and -6.1 ± 3.8% for vendor 1 and 2 respectively) vs cMR-Tagging was similar, however GCS of vendor 2 had higher bias vs cMR-Tagging (-16.0 ± 8.5%) than vendor 1 (-5.1 ± 5.8%). Agreement for regional strains is shown in the figure below. Overall, regional LS and CS agreed adequately among both vendors. Agreement of regional LS and CS vs cMR-tagging was slightly better for vendor 1, with less bias than for vendor 2, and disagreement was similarly located (ie agreement with cMR-Tagging for LS in inferolateral inferior and inferoseptal basal segments). The predictive accuracy of regional CS and LS for detecting segments with infarct was higher for vendor 2 (AUC 0.76 and 0.68) than for vendor 1 (AUC 0.70 and 0.63) . CONCLUSION: GLS agreed well among both vendors and with cMR-Tagging, confirming the universal validity of this measurement. However vendor 2 provided significantly greater GCS values and had higher bias against cMR-Tagging than vendor 1. On regional basis CS and LS agreed moderately well among both vendors, however vendor 2 agreed less with cMR-Tagging than vendor 1, but astoundingly had higher diagnostic accuracy for detecting infarct. Overall this findings call for further efforts in standardization of 2DST CS and regional strain.