医学
射血分数
危险系数
置信区间
核医学
体表面积
磁共振成像
心脏病学
心脏磁共振成像
单变量分析
内科学
心力衰竭
放射科
多元分析
作者
Hanna J Tadros,Tam Doan,Amol Pednekar,Prakash Masand,J.A. Spinner,Tobias R. Schlingmann,Ricardo H. Pignatelli,Cory V. Noel,J. P. D. Wilkinson
出处
期刊:European Journal of Echocardiography
[Oxford University Press]
日期:2022-11-28
卷期号:24 (5): 598-606
标识
DOI:10.1093/ehjci/jeac226
摘要
Abstract Aims We set out to design a reliable, semi-automated, and quantitative imaging tool using cardiac magnetic resonance (CMR) imaging that captures LV trabeculations in relation to the morphologic endocardial and epicardial surface, or perimeter-derived ratios, and assess its diagnostic and prognostic utility. Methods and results We queried our institutional database between January 2008 and December 2018. Non-compacted (NC)-to-compacted (C) (NC/C) myocardium ratios were calculated and our tool was used to calculate fractal dimension (FD), total mass ratio (TMR), and composite surface ratios (SRcomp). NC/C, FD, TMR, and SRcomp were assessed in relation to LVNC diagnosis and outcomes. Univariate hazard ratios with cut-offs were performed using clinically significant variables to find ‘at-risk’ patients and imaging parameters were compared in ‘at-risk’ patients missed by Petersen Index (PI). Ninety-six patients were included. The average time to complete the semi-automated measurements was 3.90 min (SEM: 0.06). TMR, SRcomp, and NC/C were negatively correlated with LV ejection fraction (LVEF) and positively correlated with indexed LV end-systolic volumes (iLVESVs), with TMR showing the strongest correlation with LVEF (−0.287; P = 0.005) and SRcomp with iLVESV (0.260; P = 0.011). We found 29 ‘at-risk’ patients who were classified as non-LVNC by PI and hence, were missed. When compared with non-LVNC and ‘low-risk’ patients, only SRcomp differentiated between both groups (1.91 SEM 0.03 vs. 1.80 SEM 0.03; P = 0.019). Conclusion This method of semi-automatic calculation of SRcomp captured changes in at-risk patients missed by standard methods, was strongly correlated with LVEF and LV systolic volumes and may better capture outcome events.
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