Int J Cardiovasc Imaging. 2023 Sep 8. doi: 10.1007/s10554-023-02930-x. Online ahead of print.
ABSTRACT
The evaluation of cardiac magnetic resonance feature tracking may have great diagnostic value in hypertrophic cardiomyopathy and hypertensive heart disease. Exploring the diagnostic and clinical research value of cardiac magnetic resonance feature tracks in evaluation of myocardium deformation in patients with subclinical hypertrophic cardiomyopathy(SHCM)and subclinical hypertensive heart disease(SHHD). Cardiovascular Magnetic Resonance (CMR) scans were performed on a 1.5 T MR scanner in 33 patients with SHCM, 31 patients with SHHD, and 27 controls(NS). The CMR image post-processing software was used to analyze the characteristics of routine cardiac function, different global and regional myocardial strain in each group. Analysis of variance (ANOVA) was used to compare age, blood pressure, heart rate, routine cardiac function, body mass index (BMI), as well as the strain between different segments within each of the three groups. Once a significant difference was detected, a least significant difference (LSD) comparison would be performed. The diagnostic efficacy of different parameters in differentiating SHHD from SHCM was evaluated through receiver operating characteristic (ROC) curve analysis, and the best cut-off value was determined. There was no statistical difference among three groups (P>0.05) in routine cardiac function while significant statistical differences were found in the global myocardial strain parameters and the peak strain parameters of some segments (especially basal segments) (P < 0.05). The global radial peak strain (GRPS) was most effective (AUC = 0.885, 95% CI: 0.085-0.971, P<0.001) with a sensitivity and specificity of 84% and 88% at a cut-off value of 40.105, contributing to distinguishing SHCM from SHHD group. Cardiac magnetic resonance feature tracking could detect left ventricular deformation in patients with SHCM and SHHD group. The abnormality of strain has important research value for subclinical diagnosis and clinical evaluation.
PMID:37682417 | DOI:10.1007/s10554-023-02930-x
