1,721,022 research outputs found
Fully Automated Assessment of Left Ventricular Volumes, Function and Mass from Cardiac MRI
No full textThe importance of quantification of left ventricular (LV) size, function and mass is increasingly recognized through growing evidence about the prognostic value of these indices and their diagnostic role in patient follow-up during therapy. However, quantitative evaluation from cardiac magnetic resonance (CMR) images relies on manual tracing of LV endo- and epicardial boundaries, which is subjective and time-consuming. Our goal was to develop a fully automated technique for the detection of these boundaries to assess LV volumes, ejection fraction (EF) and mass. Our automated approach consists of: 1) identification of the LV cavity based on detection of moving and circular structures in short-axis views; 2) endocardial detection using a region-based probabilistic level set model to allow volume measurements throughout the cardiac cycle; 3) epicardium detection at end-diastole based on an edge-based level set model to allow LV mass measurement. This approach was tested in 10 patients by comparing automatically derived LV volumes, EF and mass using manual tracing as a reference. Automated detection of the endo- and epicardial boundaries took <;5 minutes per patient on a standard PC. The detected boundaries were in good agreement with manual tracing. As a result, LV volumes, EF and mass showed good inter-technique concordance, reflected by minimal biases and narrow limits of agreement. The proposed technique allows fully automated, fast and accurate measurements of LV volumes, EF and mass from CMR images, which may address the growing clinical need for quantitative assessment
Quantitative analysis of myocardial perfusion and regional left ventricular function from contrast-enhanced power modulation images
No full textObjective selection of short-axis slices for automated quantification of left ventricular size and function by cardiovascular magnetic resonance
No full textBackground: Quantification of left ventricular (LV) volume from cardiovascular magnetic resonance images relies on subjective and often challenging selection of short-axis (SAX) slices. We hypothesized that this could be solved by defining mitral annular (MA) plane and apex in long-axis (LAX) views, which could be combined with automated LV volume analysis that does not rely on manual tracing of the endocardial border. Methods: SAX images from 50 subjects were analyzed using custom software. LV apex and insertion points of the mitral leaflets were marked on LAX views and used to approximate MA plane. End-systolic and end-diastolic LV volumes (ESV, EDV) were measured while including only slices or their parts located between MA plane and LV apex. Endocardial borders were automatically detected using our previously validated algorithm and also manually traced to obtain reference values. Results: Selection of anatomic landmarks in LAX views allowed automated measurement of LV volumes without the need for subjective slice selection. Intertechnique comparisons resulted in high correlations (EDV: r. = 0.95; ESV: r. = 0.96) and small biases (1 and 9 ml). Combined three-dimensional displays of LAX and SAX views with the MA plane showed that in 7/10 worst cases, intertechnique discordance was due to incorrect manual tracing at LV base that erroneously included part of atrial cavity in LV volume or excluded part of LV cavity, i.e., incorrect reference values. Conclusion: Defining the MA plane and apex in the LAX views obviates the need for subjective slice selection and eliminates errors in LV volume measurements
Fully automated assessment of left ventricular volumes, function and mass from cardiac MRI
No full textThe importance of quantification of left ventricular (LV) size, function and mass is increasingly recognized through growing evidence about the prognostic value of these indices and their diagnostic role in patient follow-up during therapy. However, quantitative evaluation from cardiac magnetic resonance (CMR) images relies on manual tracing of LV endo-and epicardial boundaries, which is subjective and time-consuming. Our goal was to develop a fully automated technique for the detection of these boundaries to assess LV volumes, ejection fraction (EF) and mass. Our automated approach consists of 1) identification of the LV cavity based on detection of moving and circular structures in short-axis views; 2) endocardial detection using a region-based probabilistic level set model to allow volume measurements throughout the cardiac cycle; 3) epicardium detection at end-diastole based on an edge-based level set model to allow L V mass measurement. This approach was tested in 10 patients by comparing automatically derived L V volumes, EF and mass using manual tracing as a reference. Automated detection of the endo-and epicardial boundaries took <5 minutes per patient on a standard Pc. The detected boundaries were in good agreement with manual tracing. As a result, L V volumes, EF and mass showed good intertechnique concordance, reflected by minimal biases and narrow limits of agreement. The proposed technique allows fully automated, fast and accurate measurements of L V volumes, EF and mass from CMR images, which may address the growing clinical need for quantitative assessment
A novel software tool to semi-automatically characterize tricuspid valve function and shape using trans-thoracic 3D echocardiography
No full text
Quantification of regional myocardial perfusion using automated translation-free analysis of contrast-enhanced power modulation images
No full textSemi-automatic tracking for mitral annulus dynamic analysis using real-time 3D echocardiography
No full textVolumetric quantification of global and regional left ventricular function from real-time three-dimensional echocardiographic images
No full textBackground—Real-time 3D echocardiographic (RT3DE) data sets contain dynamic volumetric information on cardiac function. However, quantification of left ventricular (LV) function from 3D echocardiographic data is performed on cut-planes extracted from the 3D data sets and thus does not fully exploit the volumetric information. Accordingly, we developed a volumetric analysis technique aimed at quantification of global and regional LV function.
Methods and Results—RT3DE images obtained in 30 patients (Philips 7500) were analyzed by use of custom software based on the level-set approach for semiautomated detection of LV endocardial surface throughout the cardiac cycle, from which global and regional LV volume (LVV)–time and wall motion (WM)–time curves were obtained. The study design included 3 protocols. In protocol 1, time curves obtained in 16 patients were compared point-by-point with MRI data (linear regression and Bland-Altman analyses). Global LVV correlated highly with MRI (r=0.98; y=0.99x+2.3) with minimal bias (1.4 mL) and narrow limits of agreement (±20 mL). WM correlated highly only in basal and midventricular segments (r=0.88; y=0.85x+0.7). In protocol 2, we tested the ability of this technique to differentiate populations with known differences in LV function by studying 9 patients with dilated cardiomyopathy and 9 normal subjects. All calculated indices of global and regional systolic and diastolic LV function were significantly different between the groups. In protocol 3, we tested the feasibility of automated detection of regional WM abnormalities in 11 patients. In each segment, abnormality was detected when regional shortening fraction was below a threshold obtained in normal subjects. The automated detection agreed with expert interpretation of 2D WM in 86% of segments.
Conclusions—Volumetric analysis of RT3DE data is clinically feasible and allows fast, semiautomated, dynamic measurement of LVV and automated detection of regional WM abnormalities
Automated quantification of regional myocardial perfusion by analysis of contrast-enhanced echocardiographic images
No full textWinner Rosanna Degani Young Investigator Awar
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