Multi-parametric approach to predict prosthetic valve size using CMR and clinical data: insights from SAVR

The purpose of this investigation was to characterize the CMR and clinical parameters that correlate to prosthetic valve size (PVS) determined at SAVR and develop a multi-parametric model to predict PVS. Sixty-two subjects were included. Linear/area measurements of the aortic annulus were performed...

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Bibliographic Details
Published in:The International Journal of Cardiovascular Imaging 2021-07, Vol.37 (7), p.2269-2276
Main Authors: Mordini, Federico E., Hynes, Conor F., Amdur, Richard L., Panting, Jeffrey, Emerson, Dominic A., Morrissette, Jason, Goheen-Thomas, Erin, Greenberg, Michael D., Trachiotis, Gregory D.
Format: Article
Language:English
Subjects:
Age
Aorta
Cardiac Imaging
Cardiology
Diameters
Diastole
Habitus
Imaging
Lesions
Mathematical models
Medicine
Medicine & Public Health
Model accuracy
Morphology
Original Paper
Parameters
Parametric statistics
Prediction models
Prostheses
Radiology
Systole
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Summary:The purpose of this investigation was to characterize the CMR and clinical parameters that correlate to prosthetic valve size (PVS) determined at SAVR and develop a multi-parametric model to predict PVS. Sixty-two subjects were included. Linear/area measurements of the aortic annulus were performed on cine CMR images in systole/diastole on long/short axis (SAX) views. Clinical parameters (age, habitus, valve lesion, valve morphology) were recorded. PVS determined intraoperatively was the reference value. Data were analyzed using Spearman correlation. A prediction model combining imaging and clinical parameters was generated. Imaging parameters had moderate to moderately strong correlation to PVS with the highest correlations from systolic SAX mean diameter (r = 0.73, p 
ISSN:1569-5794
1573-0743
1875-8312
DOI:10.1007/s10554-021-02203-5