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A semi-automatic method for left ventricle volume estimate: an in vivo validation studyThis study aims to the validation of the left ventricular (LV) volume estimates obtained by processing volumetric data utilizing a segmentation model based on level set technique. The validation has been performed by comparing real-time volumetric echo data (RT3DE) and magnetic resonance (MRI) data. A validation protocol has been defined. The validation protocol was applied to twenty-four estimates (range 61-467 ml) obtained from normal and pathologic subjects, which underwent both RT3DE and MRI. A statistical analysis was performed on each estimate and on clinical parameters as stroke volume (SV) and ejection fraction (EF). Assuming MRI estimates (x) as a reference, an excellent correlation was found with volume measured by utilizing the segmentation procedure (y) (y=0.89x + 13.78, r=0.98). The mean error on SV was 8 ml and the mean error on EF was 2%. This study demonstrated that the segmentation technique is reliably applicable on human hearts in clinical practice.
Document ID
20040087439
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
Authors
Corsi, C.
(University of Bologna Bologna, Italy)
Lamberti, C.
Sarti, A.
Saracino, G.
Shiota, T.
Thomas, J. D.
Date Acquired
August 21, 2013
Publication Date
January 1, 2001
Publication Information
Publication: Computers in cardiology
Volume: 28
ISSN: 0276-6574
Subject Category
Life Sciences (General)
Report/Patent Number
ISSN: 0276-6574
Distribution Limits
Public
Copyright
Other
Keywords
NASA Discipline Cardiopulmonary
Validation Studies
Non-NASA Center
NASA Program Biomedical Research and Countermeasures
Magnetic Resonance Imaging/methods/statistics & numerical data
Ventricular Dysfunction, Left/diagnosis/physiopathology/ultrasonography
Ventricular Function, Left/physiology
Heart Ventricles/ultrasonography
Echocardiography, Three-Dimensional/methods/statistics & numerical data
Reproducibility of Results
Linear Models
Image Processing, Computer-Assisted
Stroke Volume/physiology
Comparative Study
Human
Regression Analysis

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