StrainNet: Improved Myocardial Strain Analysis of Cine MRI by Deep Learning from DENSE.

Purpose: To develop a three-dimensional (two dimensions + time) convolutional neural network trained with displacement encoding with stimulated echoes (DENSE) data for displacement and strain analysis of cine MRI. Materials and Methods: In this retrospective multicenter study, a deep learning model (StrainNet) was developed to predict intramyocardial displacement from contour motion. Patients with various heart diseases and healthy controls underwent cardiac MRI examinations with DENSE between August 2008 and January 2022. Network training inputs were a time series of myocardial contours from DENSE magnitude images, and ground truth data were DENSE displacement measurements. Model performance was evaluated using pixelwise end-point error (EPE). For testing, StrainNet was applied to contour motion from cine MRI. Global and segmental circumferential strain (Ecc) derived from commercial feature tracking (FT), StrainNet, and DENSE (reference) were compared using intraclass correlation coefficients (ICCs), Pearson correlations, Bland-Altman analyses, paired t tests, and linear mixed-effects models. Results: The study included 161 patients (110 men; mean age, 61 years ± 14 [SD]), 99 healthy adults (44 men; mean age, 35 years ± 15), and 45 healthy children and adolescents (21 males; mean age, 12 years ± 3). StrainNet showed good agreement with DENSE for intramyocardial displacement, with an average EPE of 0.75 mm ± 0.35. The ICCs between StrainNet and DENSE and FT and DENSE were 0.87 and 0.72, respectively, for global Ecc and 0.75 and 0.48, respectively, for segmental Ecc. Bland-Altman analysis showed that StrainNet had better agreement than FT with DENSE for global and segmental Ecc. Conclusion: StrainNet outperformed FT for global and segmental Ecc analysis of cine MRI.Keywords: Image Postprocessing, MR Imaging, Cardiac, Heart, Pediatrics, Technical Aspects, Technology Assessment, Strain, Deep Learning, DENSE Supplemental material is available for this article. © RSNA, 2023.

Clinical characteristics and outcomes of patients with severe left ventricular dysfunction undergoing cardiac MRI viability assessment prior to revascularization.

Coronary artery bypass grafting improves survival in patients with ischemic cardiomyopathy, however, these patients are at high risk for morbidity and mortality. The role of viability testing to guide revascularization in these patients is unclear. Cardiac magnetic resonance imaging (CMR) has not been studied adequately in this population despite being considered a reference standard for infarct imaging. We performed a multicenter retrospective analysis of patients (n = 154) with severe left ventricular systolic dysfunction [ejection fraction (EF) < 35%] on CMR who underwent CMR viability assessment prior to consideration for revascularization. Using the AHA16-segment model, percent total myocardial viability was determined depending on the degree of transmural scar thickness. Patients with or without revascularization had similar clinical characteristics and were prescribed similar medical therapy. Overall, 43% of patients (n = 66) experienced an adverse event during the median 3 years follow up. For the composite outcome (death, myocardial infarction, heart failure hospitalization, stroke, ventricular tachycardia) patients receiving revascularization were less likely to experience an adverse event compared to those without revascularization (HR 0.53, 95% CI 0.33-0.86, p = 0.01). Patients with > 50% viability on CMR had a 47% reduction in composite events when undergoing revascularization opposed to medical therapy alone (HR 0.53, p = 0.02) whereas patients with a viability < 50% were 2.7 times more likely to experience an adverse event (p = 0.01). CMR viability assessment may be an important tool in the shared decision-making process when considering revascularization options in patients with severe ischemic cardiomyopathy.

A comparison of both DENSE and feature tracking techniques with tagging for the cardiovascular magnetic resonance assessment of myocardial strain.

BACKGROUND: Myocardial strain is increasingly recognized as an important assessment for myocardial function. In addition, it also improves outcome prediction. However, there is lack of standardization in strain evaluation by cardiovascular magnetic resonance (CMR). In this study we compared strain values using multiple techniques and multiple vendor products. METHODS: Prospectively recruited patients with cardiomyopathy of diverse etiology (N = 77) and healthy controls (N = 10) underwent CMR on a 1.5 T scanner. Tagging, displacement encoding with stimulated echoes (DENSE) and balanced stead state free precession cine imaging were acquired on all subjects. A single matched mid left ventricular (LV) short axis plane was used for the comparisons of peak circumferential (Ecc) and radial strain (Err) and a 4-chamber view for longitudinal strain (Ell). Tagging images were analyzed using harmonic phase (HARP) and displacement encoding with stimulated echoes (DENSE) images using a proprietary program. Feature tracking (FT) was evaluated using 3 commercially available software from Tomtec Imaging Systems, Cardiac Image Modeller (CIM), and Circle Cardiovascular Imaging. Tagging data were used as reference. Statistic analyses were performed using paired t-test, intraclass correlation coefficient (ICC), Bland Altman limits of agreement and coefficient of variations. RESULTS: Average LV ejection fraction was 50% (range 32 to 62%). Regional LV wall motion abnormalities were present in 48% of the analyzed planes. The average Ecc was - 13 ± 4%, - 13 ± 4%, - 16 ± 6%, - 10 ± 3% and - 14 ± 4% for tagging, DENSE, Tomtec, CIM and Circle, respectively, with the best agreement seen in DENSE and Circle with tagging. The Err was highly varied with poor agreement across the techniques, 32 ± 24%, 40 ± 28%, 47 ± 26%, 64 ± 33% and 23 ± 9% for tagging, DENSE, Tomtec, CIM and Circle, respectively. The average Ell was - 14 ± 4%, - 8 ± 3%, - 13 ± 5%, - 11 ± 3% and - 12 ± 4% for tagging, DENSE, Tomtec, CIM and Circle, respectively with the best agreement seen in Tomtec and Circle with tagging. In the intra- and inter-observer agreement analysis the reproducibility of each technique was good except for Err by HARP. CONCLUSIONS: Small but important differences are evident in Ecc and Ell comparisons among vendors while large differences are seen in Err assessment. Our findings suggest that CMR strain values are technique and vendor dependent. Hence, it is essential to develop reference standard from each technique and analytical product for clinical use, and to sequentially compare patient data using the same software.