Feature-Tracking Strain Parameters Differ Between Highly Accelerated and Conventional Acquisitions

Abstract

Background: Cardiac magnetic resonance imaging protocols have been adapted to fit the needs for faster, more efficient acquisitions, resulting in the development of highly accelerated, compressed sensing-based (CS) sequences. The aim of this study was to evaluate intersoftware and interacquisition differences for postprocessing software applied to both CS and conventional cine sequences. Materials and Methods: A total of 106 individuals (66 healthy volunteers, 40 patients with dilated cardiomyopathy, 51% female, 38±17 y) underwent cardiac magnetic resonance at 3T with retrospectively gated conventional cine and CS sequences. Postprocessing was performed using 2 commercially available software solutions and 1 research prototype from 3 different developers. The agreement of clinical and feature-tracking strain parameters between software solutions and acquisition types was assessed by Bland-Altmann analyses and intraclass correlation coefficients. Differences between softwares and acquisitions were assessed using Kruskal-Wallis analysis of variances. In addition, receiver operating characteristic curve-derived cutoffs were used to evaluate whether sequence-specific cutoffs influence disease classification. Results: There were significant intersoftware (P<0.002 for all except LV end-diastolic volume per body surface area) and interacquisition differences (P<0.02 for all except end-diastolic volume per body surface area from Neosoft, left ventricular mass per body surface area from cvi42 and TrufiStrain and global circumferential strain from Neosoft). However, the intraclass correlation coefficients between acquisitions were strong-to-excellent for all parameters (all ≥0.81). In comparing individual softwares to a pooled mean, Bland-Altmann analyses revealed smaller magnitudes of bias for cine acquisition than for CS acquisition. In addition, the application of conventional cutoffs to CS measurements did not result in the false reclassification of patients. Conclusion: Significantly lower magnitudes of strain and volumetric parameters were observed in retrospectively gated CS acquisitions, despite strong-to-excellent agreement amongst software solutions and acquisition types. It remains important to be aware of the acquisition type in the context of follow-up examinations, where different cutoffs might lead to misclassifications.