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基于应变-容积环半自动计算的经胸超声心动图舒张功能评估的新期望。

New expectations for diastolic function assessment in transthoracic echocardiography based on a semi-automated computing of strain-volume loops.

机构信息

Univ Rennes, CHU Rennes, Inserm, LTSI - UMR 1099, F-35000 Rennes, France.

出版信息

Eur Heart J Cardiovasc Imaging. 2020 Dec 1;21(12):1366-1371. doi: 10.1093/ehjci/jeaa123.

Abstract

AIMS

Early diagnosis of heart failure with preserved ejection fraction (HFpEF) by determination of diastolic dysfunction is challenging. Strain-volume loop (SVL) is a new tool to analyse left ventricular function. We propose a new semi-automated method to calculate SVL area and explore the added value of this index for diastolic function assessment.

METHOD AND RESULTS

Fifty patients (25 amyloidosis, 25 HFpEF) were included in the study and compared with 25 healthy control subjects. Left ventricular ejection fraction was preserved and similar between groups. Classical indices of diastolic function were pathological in HFpEF and amyloidosis groups with greater left atrial volume index, greater mitral average E/e' ratio, faster tricuspid regurgitation (P < 0.0001 compared with controls). SVL analysis demonstrated a significant difference of the global area between groups, with the smaller area in amyloidosis group, the greater in controls and a mid-range value in HFpEF group (37 vs. 120 vs. 72 mL.%, respectively, P < 0.0001). Applying a linear discriminant analysis (LDA) classifier, results show a mean area under the curve of 0.91 for the comparison between HFpEF and amyloidosis groups.

CONCLUSION

SVLs area is efficient to identify patients with a diastolic dysfunction. This new semi-automated tool is very promising for future development of automated diagnosis with machine-learning algorithms.

摘要

目的

通过确定舒张功能障碍来早期诊断射血分数保留的心力衰竭(HFpEF)具有挑战性。应变-容积环(SVL)是一种分析左心室功能的新工具。我们提出了一种新的半自动方法来计算 SVL 面积,并探讨该指数对舒张功能评估的附加价值。

方法和结果

本研究纳入了 50 名患者(25 名淀粉样变性,25 名 HFpEF),并与 25 名健康对照进行了比较。左心室射血分数在各组之间保持不变且相似。HFpEF 和淀粉样变性组的经典舒张功能指标存在病理学改变,左心房容积指数较大,二尖瓣平均 E/e' 比值较大,三尖瓣反流速度较快(与对照组相比,P<0.0001)。SVL 分析显示各组之间的整体面积存在显著差异,淀粉样变性组面积较小,对照组面积较大,HFpEF 组面积中等(分别为 37、120 和 72%,P<0.0001)。应用线性判别分析(LDA)分类器,结果表明 HFpEF 和淀粉样变性组之间的曲线下面积平均为 0.91。

结论

SVLs 面积可有效识别舒张功能障碍患者。这种新的半自动工具对于未来使用机器学习算法进行自动诊断具有很大的发展前景。

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