Value of cardiac magnetic resonance feature tracking technology in the differential diagnosis of isolated left ventricular noncompaction and dilated cardiomyopathy.

BACKGROUND

This study explored the value of myocardial strain in the differential diagnosis of isolated left ventricular myocardial noncompaction (ILVNC) and dilated cardiomyopathy (DCM) using cardiac magnetic resonance (CMR) feature tracking technology.

METHODS

This retrospective analysis was performed on consecutive patients (25 with ILVNC, 30 with DCM, and 30 healthy controls) presenting to Shanxi Cardiovascular Hospital. All ILVNC patients met echocardiographic and CMR criteria for ventricular non-compaction. All patients with DCM met the 2016 American Heart Association and 2018 Chinese Medical Association Cardiovascular Branch diagnostic criteria. cvi42 software (Circle Cardiovascular Imaging) was used to measure radial, circumferential, and longitudinal strain (LS) globally and in segments of the left ventricle. Analysis of variance was used to compare strains among groups and among different segments within the same group. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic efficacy of different parameters in ILVNC and DCM.

RESULTS

Basal circumferential strain was lower in the DCM than in the ILVNC group (P=0.05). Both median and apical LS were lower in the ILVNC than in DCM group (P=0.02 and P=0.01, respectively). ROC curves showed that apical LS was the most effective in distinguishing ILVNC from DCM [area under the curve (AUC) =0.883; P<0.001; 95% CI: 0.850-0.977]. Comparing strains among different segments within the same group revealed that in DCM, the circumferential and LS of the apex were higher than those of the basal segment, which is consistent with the pattern in healthy controls; however, has no such regular pattern was seen in ILVNC.

CONCLUSIONS

Myocardial strain parameters are of considerable value in the differential diagnosis of ILVNC and DCM. Differences in patterns between ILVNC and DCM can be sensitively identified, providing more comprehensive information for early clinical diagnosis.