Lukáš Opatřil, Mary Luz Mojica-Pisciotti, Roman Panovský, Jan Máchal, Tomáš Holeček, Věra Feitová, Július Godava, Hana Poloczková, Vladimír Kincl, Jan Krejčí
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引用次数: 0
Abstract
Background: Recent-onset dilated cardiomyopathy (RODCM), defined as new DCM with heart failure (HF) symptoms appearing within six months, is a less documented form of HF. This study aims to evaluate pulmonary circulation imaging biomarkers (PCIB) obtained by cardiovascular magnetic resonance (CMR) in patients with RODCM to assess their association with pulmonary hypertension, systolic and diastolic function, and clinical improvement.
Methods: Ninety RODCM patients with baseline and one-year follow-up CMR, clinical examination, and transthoracic echocardiography were retrospectively included. Twenty-six were excluded following a myocarditis diagnosis confirmed by endomyocardial biopsy (EMB). PCIB (pulmonary transit time (PTT), corrected PTT (PTTc), pulmonary transit beats (PTB), and pulmonary blood volume index (PBVI)) were assessed using a first-pass perfusion CMR sequence. Pulmonary hypertension, diastolic, and systolic function were assessed. Correlations between PCIB and echocardiographic changes were analyzed. Patients were classified as responders/non-responders based on left ventricular ejection fraction (LVEF) improvement.
Results: From baseline to follow-up, LVEF increased (25% to 40%), while EDD (65 mm to 61 mm), sPAP (24.2 mmHg to 20.0 mmHg), and E/e' ratio (13 to 9) significantly reduced. Thirty-three patients were labeled as responders. PTT, PTTc, and PTB correlated with ΔE/e', diastolic function improvement, and ΔsPAP. PBVI correlated with ΔsPAP. PTB correlated with ΔNYHA class. The PCIB could not predict whether a patient would be a responder.
Conclusions: This study focused on PCIB as outcome predictors in patients with RODCM with EMB-excluded myocarditis. Our findings show that PTB and PTTc correlated with ΔE/e', diastolic function improvement, and ΔsPAP, while PTB additionally correlated with ΔNYHA class.
期刊介绍:
BMC Medical Imaging is an open access journal publishing original peer-reviewed research articles in the development, evaluation, and use of imaging techniques and image processing tools to diagnose and manage disease.