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从标记磁共振成像中计算出的心肌应变的多个空间尺度:估算 CRT 患者的心脏生物标志物。

Myocardial strain computed at multiple spatial scales from tagged magnetic resonance imaging: Estimating cardiac biomarkers for CRT patients.

机构信息

Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom; Biomedical Image Analysis Group, Imperial College London,London, United Kingdom.

Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom; Mirada Medical Ltd., Oxford Centre for Innovation, Oxford, United Kingdom.

出版信息

Med Image Anal. 2018 Jan;43:169-185. doi: 10.1016/j.media.2017.10.004. Epub 2017 Oct 31.

Abstract

Abnormal cardiac motion can indicate different forms of disease, which can manifest at different spatial scales in the myocardium. Many studies have sought to characterise particular motion abnormalities associated with specific diseases, and to utilise motion information to improve diagnoses. However, the importance of spatial scale in the analysis of cardiac deformation has not been extensively investigated. We build on recent work on the analysis of myocardial strains at different spatial scales using a cardiac motion atlas to find the optimal scales for estimating different cardiac biomarkers. We apply a multi-scale strain analysis to a 43 patient cohort of cardiac resynchronisation therapy (CRT) patients using tagged magnetic resonance imaging data for (1) predicting response to CRT, (2) identifying septal flash, (3) estimating QRS duration, and (4) identifying the presence of ischaemia. A repeated, stratified cross-validation is used to demonstrate the importance of spatial scale in our analysis, revealing different optimal spatial scales for the estimation of different biomarkers.

摘要

异常的心脏运动可以指示不同形式的疾病,这些疾病可以在心肌的不同空间尺度上表现出来。许多研究都试图描述与特定疾病相关的特定运动异常,并利用运动信息来改善诊断。然而,在心脏变形分析中,空间尺度的重要性尚未得到广泛研究。我们基于最近在不同空间尺度上分析心肌应变的工作,使用心脏运动图谱来寻找估计不同心脏生物标志物的最佳尺度。我们使用标记的磁共振成像数据对 43 名心脏再同步治疗(CRT)患者进行了多尺度应变分析,用于(1)预测 CRT 的反应,(2)识别室间隔闪光,(3)估计 QRS 持续时间,以及(4)识别缺血的存在。重复的分层交叉验证证明了空间尺度在我们的分析中的重要性,揭示了不同的最佳空间尺度用于估计不同的生物标志物。

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