Literature DB >> 25948160

Semi-automated echocardiographic quantification of right ventricular size and function.

Diego Medvedofsky1, Karima Addetia, Jamie Hamilton, Javier Leon Jimenez, Roberto M Lang, Victor Mor-Avi.   

Abstract

Although parameters of right ventricular (RV) size and function are clinically important, echocardiographic assessment of this chamber is complex. Existing quantitative approaches rely on manual measurements performed on different images, and are thus time-consuming. Consequently, in clinical practice, qualitative assessment is usually used instead. We tested a new approach for automated measurements of RV size and function using speckle tracking by comparing them to the conventional manual methodology. Transthoracic images were obtained in 149 patients with a wide range of RV size and function, and were analyzed by an expert using conventional techniques to obtain RV end-diastolic and end-systolic areas, fractional area change, dimensions (basal and mid-cavity diameters and length), tricuspid annular plane systolic excursion and peak systolic velocity. Same parameters were obtained using the semi-automated software (Epsilon Imaging), which requires tracing of the RV endocardial boundary in a single frame in the RV focused view. Fifteen patients were excluded due to image quality (90% feasibility). Time required for the automated analysis was approximately 30 s per patient, compared to 4 min for conventional analysis. The parameters obtained with the semi-automated approach were in good agreement with manual measurements: r-values 0.79-0.95 for RV size and 0.70-0.74 for function indices and biases of 2-22% of the mean measured values, which were comparable to the intrinsic variability of the conventional technique. In conclusion, the semi-automated technique is feasible, fast and provides quantitative parameters of RV size and function, which are comparable to conventional measurements.

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Year:  2015        PMID: 25948160     DOI: 10.1007/s10554-015-0672-4

Source DB:  PubMed          Journal:  Int J Cardiovasc Imaging        ISSN: 1569-5794            Impact factor:   2.357


  45 in total

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Review 3.  Artificial intelligence in cardiovascular imaging: state of the art and implications for the imaging cardiologist.

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