Mitral prosthetic size predictor in minimally invasive mitral valve replacement

Area of Science:

• Cardiovascular Surgery
• Medical Imaging
• Biomedical Engineering

Background:

• Minimally invasive mitral valve replacement is increasingly common globally.
• Annular rupture and patient-prosthetic mismatch (PPM) remain significant challenges, particularly in Asian patients.
• Predictive models are needed to optimize prosthesis selection and mitigate these risks.

Purpose of the Study:

• To evaluate the efficacy of mitral valve diameters measured via TTE and CT scans in predicting the appropriate mitral prosthesis size.
• To develop a predictive model for mitral prosthesis selection to minimize PPM and annular rupture.

Main Methods:

• A cohort of 96 patients undergoing minimally invasive mitral valve replacement between January 2018 and December 2019 was analyzed.
• Pearson's correlation coefficient and scatter plots assessed the association between imaging measurements and prosthesis size.
• Univariable linear regression was employed to construct the predictive model.

Main Results:

• The strongest correlations for predicting prosthesis size were mean TTE diameter (r=0.702), mean CT annulus diameter (r=0.679), and area-derived CT diameter (r=0.665).
• Predictive models showed higher correlation for tissue valves compared to mechanical valves.
• Developed tissue valve size predictor models demonstrated strong predictive capabilities (r values ranging from 0.730 to 0.756).

Conclusions:

• Mitral prosthesis size can be accurately predicted using mitral diameters obtained from TTE and CT scans.
• The predictive models, with overall correlation coefficients from 0.665 (CT) to 0.702 (TTE), are effective for prosthesis selection.
• These models demonstrated superior performance when applied to bioprosthetic valves.