Automated Frame-by-Frame Endocardial Border Detection from Cardiac Magnetic Resonance Images for Quantitative Assessment of Left Ventricular Function: Validation and Clinical Feasibility
Automated Frame-by-Frame Endocardial Border Detection from Cardiac Magnetic Resonance Images for Quantitative Assessment of Left Ventricular Function: Validation and Clinical Feasibility
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DOI：
10.1002/jmri.21681
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发表时间：
2009-03-01
影响因子：
4.4
通讯作者：
Mor-Avi, Victor
中科院分区：
文献类型：
--
作者：
Corsi, Cristiana;Veronesi, Federico;Mor-Avi, Victor
目的：为了开发一种基于图像噪声分布的技术，用于从整个心动周期的心脏磁共振（CMR）图像中自动检测心内膜边界，验证它。并测试其临床utility.Materials和方法：在36例患者中获得的图像进行了分析，使用自定义软件，以获得整个心动周期的左心室（LV）容积，收缩末期和舒张末期LV容积。射血分数（EF）针对手动追踪的endoembryos边界的验证包括LV体积、切片面积和边界位置的技术间比较。结果：14例左室功能正常，12例左室收缩功能不全，10例左室舒张功能不全患者的左室功能动态自动分析时间< 15 min。技术间比较导致高相关性（r > 0.96）、小偏倚（体积：-6 mL; EF：4.6%）和窄一致性限（体积：17.6 mL; EF：9.2%）。我们发现显着的组间差异在多个定量指标的收缩和舒张function.Conclusion：快速，自动化，动态检测LV endoform边界是可行的，并允许准确的定量LV的大小和功能，这是潜在的临床有用的收缩和舒张功能障碍的客观评估。
Purpose: To develop a technique based on image noise distribution for automated endocardial border detection from cardiac magnetic resonance (CMR) images throughout the cardiac cycle, validate it. and test its clinical utility.Materials and Methods: Images obtained in 36 patients were analyzed using custom software to obtain left ventricular (LV) volume throughout the cardiac cycle, end-systolic and end-diastolic LV volumes. and ejection fraction (EF). Validation against manually-traced endocardial boundaries included intertechnique comparisons of LV volumes, slice areas, and border positions. Then, the clinical feasibility of the dynamic automated analysis of LV function was tested in 14 patients with normal LV function, 12 patients with systolic dysfunction, and 10 patients with diastolic dysfunction.Results: Analysis time for one cardiac cycle was < 15 minutes. Intertechnique comparisons resulted in high correlation (r > 0.96), small biases (volumes: -6 mL: EF: 4.6%) and narrow limits of agreement (volumes: 17.6 mL; EF: 9.2%). We found significant intergroup differences in multiple quantitative indices of systolic and diastolic function.Conclusion: Fast, automated, dynamic detection of LV endocardial boundaries is feasible and allows accurate quantification of LV size and function, which is potentially clinically useful for objective assessment of systolic and diastolic dysfunction.