Right ventricular mass measurement by electron beam computed tomography. Validation with autopsy data

Estimation of right ventricular mass by two-dimensional echocardiography

BACKGROUND

This report describes two original echocardiographic approaches to measure right ventricular (RV) mass (RVM).

METHODS

In the bullet formula (5/24 pi D1 D2 L), where D1 and D2 are short axes and L the log axis, the RVM is obtained by subtracting the cavity volume from the RV total volume and subsequently multiplying the difference by myocardium density. The second method uses 3 endocardium segments measured at: (1) short axis plane of the aortic valve and left atrium (b1); (2) short axis plane at the midpoint between the tricuspid valve annulus and the apex (b2); and (3) 4-chamber view (h). Those segment lengths are applying in the formula A = [(b1 + b2)/2] x h. The result is multiplied by the wall thickness and by myocardium density.

RESULTS

Both formulas were primarily tested in 30 mongrel dogs and have shown good correlation with the true mass ( r = 0.869 with the segments formula and r = 0.819 with the bullet formula). The same method was used in 20 human patients before heart transplant with similar results ( r = 0.810 with the segments formula and r = 0.836 with the bullet formula).

CONCLUSIONS

The RVM can be satisfactorily estimated by 2-dimensional echocardiography. The linear regression between the calculated mass (using the smoothest and thinner myocardium thickness) and the actual mass may provide the correction factor for the RVM calculation. Two echocardiographic methods were used to measure right ventricular mass. One of them used a bullet formula variant (5/24 pi D1 D2 L). The second method used 3 endocardium segments measured in 3 2-dimensional echocardiographic planes (short axis of aortic valve and left ventricle, and 4-chamber view), and applied in the formula A = [(b1 + b2)/2] x h. Both formulas have shown good correlation with the true mass in 30 mongrel dogs ( r = 0.869 with the segments formula and r = 0.819 with the bullet formula) and in 20 human patients before heart transplant ( r = 0.810 and r = 0.836, respectively).

Accurate Quantification of Right Ventricular Mass at MR Imaging by Using Cine True Fast Imaging with Steady-State Precession: Study in Dogs

PURPOSE

To assess the accuracy of cine magnetic resonance (MR) imaging with a segmented true fast imaging with steady-state precession (FISP) technique for right ventricular (RV) mass quantification.

MATERIALS AND METHODS

Fourteen dogs were imaged with a 1.5-T clinical MR imaging unit by using an electrocardiographically gated true FISP sequence. Contiguous segmented k-space cine images were acquired from the base of the RV to the apex during suspended respiration (repetition time msec/echo time msec, 3.2/1.6; section thickness, 5 mm; in-plane resolution, 1.0 x 1.3 mm2). After imaging, each dog was sacrificed, and the RV free wall was isolated and weighed. Each MR imaging data set was analyzed twice by each of two independent observers who were blinded to the results of RV mass measurement at autopsy, and the mass measurements at MR imaging were compared with the autopsy results by using linear regression and Bland-Altman analysis.

RESULTS

RV mass measurements calculated by using the true FISP cine MR images were nearly identical to those at autopsy (R = 0.82, standard error of the estimate = 1.7 g, P >.05), with a mean difference between the autopsy and MR imaging measurements of 0.3 g +/- 1.7 (1.9% +/- 8.2) (P >.05). Inter- and intraobserver variations were small, with a mean interobserver variability of -0.1 g +/- 2.3 and a mean intraobserver variability of 0.2 g +/- 1.6 at every-section analysis.

CONCLUSION

In this animal model, true FISP cine MR imaging enabled accurate quantification of RV mass.

Wavelet transform filtering and nonlinear anisotropic diffusion assessed for signal reconstruction performance on multidimensional biomedical data

Computer tomography (CT) techniques are the most widely applicable noninvasive methods for obtaining two- and three-dimensional insights into biological objects. They comprise CT for medical applications, as well as electron tomography used for investigating macromolecular and cellular specimens. Recent advances in the recording schemes improve the speed and resolution frontiers and provide new insights into structural organizations of different objects. However, many data sets suffer from a poor signal-to-noise ratio, which severely hinders the application of methods for automated data analysis, such as feature extraction, segmentation, and visualization. We propose the multidimensional implementation of two powerful signal reconstruction techniques, namely invariant wavelet filtering and nonlinear anisotropic diffusion. We establish quantitative measures to assess the signal reconstruction performance on synthetic data and biomedical images. The appropriate multidimensional implementations of wavelet and diffusion techniques allow for a superior performance over conventional noise-reduction methods. We derive the conditions for the choice between wavelet and diffusion techniques with respect to an optimal signal reconstruction performance. Results of applying the proposed methods in two very different imaging domains-molecular biology and clinical research-are provided.

Comparison of electron beam computed tomography scanning and magnetic resonance imaging quantification of right ventricular mass: validation with autopsy weights

RATIONALE AND OBJECTIVES

We compared, in the same human hearts, the ability of magnetic resonance (MR) imaging and electron beam computed tomography (CT) scanning to accurately quantify the free wall and septal components of right ventricular (RV) mass.

METHODS

Eleven hearts extracted at autopsy were subjected to MR imaging and electron beam CT scanning in short-axis projections. Regression analyses of mass determinations obtained by manual planimetry MR imaging and electron beam CT scanning and autopsy weights were performed.

RESULTS

RV free wall mass by both MR imaging (53.4 +/- 19.1 g) and electron beam CT scanning (53.9 +/- 20.4 g) correlated well with autopsy weight (57.7 +/- 20.2 g). Regression analysis showed a strong correlation for MR imaging (r = .88, slope = .88, standard error the estimate [SEE] = 7.2 g, p < .001) and electron beam CT scanning (r = .95, slope = .95, SEE = 6.6 g, p < .001). RV septal mass by MR imaging (10.8 +/- 3.5 g) and electron beam CT scanning (7.1 +/- 2.4 g) correlated less well with the autopsy weight (12.5 +/- 6.5 g). Regression analysis showed a fair correlation for MR imaging (r = .45, slope = .83, SEE = 2.05 g, p = .001) and a poor correlation for electron beam CT scanning (r = .46, slope = .17, SEE = 2.25 g, p = .57).

CONCLUSION

Both MR imaging and electron beam CT scanning accurately predict RV free wall mass but have difficulty predicting the septal component. Because the septal component constitutes only a small proportion of the total RV mass, determinations of RV mass should be based solely on the free wall component.