Rapid quantitative assessment of myocardial perfusion: spectral analysis of myocardial contrast echocardiographic images

Parametric detection and measurement of perfusion defects in attenuated contrast echocardiographic images

OBJECTIVE

Attenuation of radio frequency (RF) signals limits the use of contrast echocardiography. The harmonic-to-fundamental ratio (HFR) of the RF signals compensates for attenuation. We tested whether HFR analysis measures the left ventricular nonperfused area under simulated experimental attenuation.

METHODS

Radio frequency image data from short axis systolic projections were obtained from 11 open-chest dogs with left anterior descending or left circumflex coronary artery occlusion followed by left atrial bolus injection of a perflutren microbubble contrast agent. Clinical attenuation was simulated by calibrated silicone pads interposed between the epicardial surface and the transducer to induce mild (7-dB) and severe (14-dB) reduction of the backscattered RF signals. Harmonic-to-fundamental ratio values were calculated for each image pixel for 0-, 7-, and 14-dB attenuation conditions and reproducibly showed a "perfused area" and a "nonperfused area." A reference nonperfused area was obtained by manual delineation in high-quality contrast scans.

RESULTS

Correlations of the HFR-detected and manually outlined perfusion defect areas were R = 0.92 for 0 dB, R = 0.94 for 7 dB, and R = 0.90 for 14 dB; the mean difference was less than 0.36 cm(2) (negligible) in all 3 attenuation settings. Conclusions. Attenuation compensation by our HFR method allows precise measurement of myocardial perfusion defect areas in contrast scans with simulated high level of attenuation.

Parametric harmonic-to-fundamental ratio contrast echocardiography: a novel approach to identification and accurate measurement of left ventricular area under variable levels of ultrasound signal attenuation

OBJECTIVES

We introduced a harmonic-to-fundamental ratio (HFR) of the radiofrequency (RF) signals that reduces confounding effects of attenuation. We studied whether HFR analysis of RF signals received from contrast microbubbles allows accurate measurement of the left ventricular (LV) cavity area under varying levels of attenuation.

BACKGROUND

Attenuation is a fundamental problem in ultrasound imaging and limits the use of clinical echocardiography.

METHODS

RF data from short axis systolic and diastolic scans were obtained from 14 open-chest dogs following left-atrial bolus of Optison. Attenuation was induced by interposed silicone pads calibrated to induce 7dB or 14dB reductions of the backscattered RF signal. RF images were reconstructed from the RF signals, HFR values calculated for each image pixel for 0dB, 7dB and 14dB attenuation conditions, and LV area obtained by summation of "LV cavity pixels". A reference LV cavity area was obtained from endocardial border tracings in enhanced scans by experts.

RESULTS

Correlation of the HFR-defined and reference areas at systole was R=0.95, R=0.94, and R=0.91 for 0dB, 7dB and 14dB levels of attenuation, respectively, and at diastole was R=0.95 for 0dB, 7dB and 14dB levels of attenuation. The mean difference from both systolic and diastolic values was <1.45 cm(2) (i.e. negligible) in all attenuation settings.

CONCLUSION

Our novel HFR method supports precise measurement of the LV cavity area in contrast images with simulated high attenuation of ultrasound signals.

Three-Dimensional Echocardiographic Evaluation of Myocardial Perfusion

One of the most intriguing developments in ultrasound imaging of the heart was the use of contrast media to assess myocardial perfusion, which sparked tremendous interest and over the years generated a significant body of research. Although most published work has been based on the use of contrast for 2D perfusion imaging, there are a few recent studies aimed at exploring the idea of 3D assessment of myocardial perfusion, which has the potential to overcome many of the limitations of the 2D methodology. We provide a brief overview of the 2D work that provided the scientific basis for the emerging 3D methodology and discuss the unique features and promises as well as the challenges posed by this novel approach.

Spectral normalization for ultrasonic contrast microbubble detection

Ultrasonic contrast agents consisting of microbubbles are used to assess tissue perfusion. The microbubbles are highly reflective and nonlinear and thus produce harmonics that are stronger than those from tissues. However, the magnitude of harmonic signals resulting from a region with microbubbles also depends on the acoustic pressure of incident ultrasound and the attenuation of intervening tissues in the ultrasound path. Therefore, the harmonic magnitude, as used in traditional harmonic imaging, may not be a reliable indicator of the presence or absence of microbubbles, and hence, tissue perfusion. To compensate for these effects, we present two parameters defined as the ratio of the harmonic to the fundamental component (HFR) and the ratio of the harmonic to squared fundamental (HSFR). A simplified model is used to illustrate the usefulness of these two parameters. Experiments show that both parameters improve detection of microbubbles and that HSFR performs better than HFR.

Radio frequency dual-spectra analysis of regional myocardial perfusion: Comparison with harmonic densitometric method

Our objective was to compare harmonic-to-fundamental frequency ratio peak (HFRp) analysis with conventional harmonic gray-scale densitometric analysis on the basis of ability to eliminate heterogeneity in ultrasound signals. Broadband radio frequency and harmonic data were obtained by using intermittent short-axis scans in 10 open-chest pigs before and during infusion of contrast microbubbles. HFRp and gray-scale intensity values were measured in 6 segments of left ventricular myocardium. In baseline images, the influence of anisotropy on HFRp values was significantly less than that in gray-scale intensities. In perfusion assessment with subtraction, contrast heterogeneity in HFRp values was significantly smaller than that in gray-scale intensities. The increase in HFRp values after subtraction was significantly greater than that in gray-scale intensities in lateral (P <.001), posterior (P <.0001), and inferior (P <.01) myocardium. HFRp analysis can compensate for baseline myocardial anisotropy and regional contrast heterogeneity. With background subtraction, HFRp analysis allows better quantification of myocardial perfusion.