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Estimation of right ventricular mass by two-dimensional echocardiography
Sergio C Pontes1, Jorge E Assef, Rodrigo B M Barretto
1Section of Cardiovascular Diagnostic Methods, Instituto Dante Pazzanese de Cardiologia, São Paulo, Brazil. scponte@attglobal.net
Summary
Two novel echocardiographic methods accurately estimate right ventricular mass (RVM). These techniques showed strong correlations with true RVM in both canine and human subjects, offering a reliable non-invasive measurement approach.
Area of Science:
- Cardiology
- Medical Imaging
- Biomedical Engineering
Background:
- Accurate measurement of right ventricular mass (RVM) is crucial for assessing cardiac health.
- Existing methods for RVM assessment may be invasive or less precise.
- Echocardiography offers a non-invasive imaging modality with potential for RVM quantification.
Purpose of the Study:
- To introduce and validate two novel 2-dimensional echocardiographic methods for measuring right ventricular mass (RVM).
- To assess the accuracy and correlation of these echocardiographic methods against true RVM in animal and human subjects.
Main Methods:
- Developed a 'bullet formula' variant (5/24 pi D1 D2 L) utilizing short and long axes for RVM calculation.
- Introduced a second method using three endocardial segment lengths (b1, b2, h) applied in a specific formula (A = [(b1 + b2)/2] x h).
- Both methods involved multiplying calculated volumes/areas by myocardium density and wall thickness.
Main Results:
- The segment-based formula showed high correlation (r=0.869) with true RVM in dogs.
- The bullet formula also demonstrated good correlation (r=0.819) with true RVM in dogs.
- Similar high correlations were observed in human patients awaiting heart transplant (r=0.810 for segments, r=0.836 for bullet formula).
Conclusions:
- Two-dimensional echocardiography can satisfactorily estimate right ventricular mass (RVM).
- The developed echocardiographic methods provide a reliable means for RVM quantification.
- Linear regression analysis may yield correction factors for improved RVM calculation accuracy.