Relation of ultrasonic tissue characterization with integrated backscatter to contractile reserve in patients with chronic coronary artery disease

The diastolic function to cyclic variation of myocardial ultrasonic backscatter relation: the influence of parameterized diastolic filling (PDF) formalism determined chamber properties

Myocardial tissue characterization represents an extension of currently available echocardiographic imaging. The systematic variation of backscattered energy during the cardiac cycle (the "cyclic variation" of backscatter) has been employed to characterize cardiac function in a wide range of investigations. However, the mechanisms responsible for observed cyclic variation remain incompletely understood. As a step toward determining the features of cardiac structure and function that are responsible for the observed cyclic variation, the present study makes use of a kinematic approach of diastolic function quantitation to identify diastolic function determinants that influence the magnitude and timing of cyclic variation. Echocardiographic measurements of 32 subjects provided data for determination of the cyclic variation of backscatter to diastolic function relation characterized in terms of E-wave determined, kinematic model-based parameters of chamber stiffness, viscosity/relaxation and load. The normalized time delay of cyclic variation appears to be related to the relative viscoelasticity of the chamber and predictive of the kinematic filling dynamics as determined using the parameterized diastolic filling formalism (with r-values ranging from .44 to .59). The magnitude of cyclic variation does not appear to be strongly related to the kinematic parameters.

Bayesian parameter estimation for characterizing the cyclic variation of echocardiographic backscatter to assess the hearts of asymptomatic type 2 diabetes mellitus subjects

Previous studies have shown that effective quantification of the cyclic variation of myocardial ultrasonic backscatter over the heart cycle might provide a non-invasive technique for identifying the early onset of cardiac abnormalities. These studies have demonstrated the potential for measurements of the magnitude and time delay of cyclic variation for identifying early onset of disease. The goal of this study was to extend this approach by extracting additional parameters characterizing the cyclic variation in an effort to better assess subtle changes in myocardial properties in asymptomatic subjects with type 2 diabetes. Echocardiographic images were obtained on a total of 43 age-matched normal control subjects and 100 type 2 diabetics. Cyclic variation data were generated by measuring the average level of ultrasonic backscatter over the heart cycle within a region of interest placed in the posterior wall of the left ventricle. Cyclic variation waveforms were modeled as piecewise linear functions, and quantified using a novel Bayesian parameter estimation method. Magnitude, rise time and slew rate parameters were extracted from models of the data. The ability of each of these parameters to distinguish between normal and type 2 diabetic subjects, and between subjects grouped by glycated hemoglobin (HbA1c) was compared. Results suggest a significant improvement in using measurements of the rise time and slew rate parameters of cyclic variation to differentiate (P < 0.001) the hearts of patients segregated based on widely employed indices of diabetic control compared to differentiation based on the magnitude of cyclic variation.

Improving the reproducibility of the cyclic variation of myocardial backscatter

The goal of myocardial tissue characterization is to augment information provided by two- and three-dimensional echocardiographic imaging, Doppler blood flow and speckle- or Doppler-derived tissue motion. Tissue characterization based on the systematic variation ofbackscattered ultrasound during the cardiac cycle ('cyclic variation') appears to be effective in characterizing both focal and diffuse myocardial pathologies. Unfortunately, comparison ofresults from different laboratories is difficult because of a lack of consistency among the several reported methods of analyzing the cyclic variation data. The goals of the present work are to present an improved method of analysis and to demonstrate that apparent disagreements are attributable primarily to the distinct approaches employed by different investigators. The improved automated method for determining the magnitude of cyclic variation utilizes binomial smoothing and an average deviation method and was validated using data acquired from 23 patients. This method illustrates a systematic means for resolving differences between laboratories. This resolution facilitates future comparisons between the cyclic variation of myocardial backscatter and measurements derived, for example, from strain-related approaches.

Quantitative analysis of the magnitude and time delay of cyclic variation of myocardial backscatter from asymptomatic type 2 diabetes mellitus subjects

Early detection of diabetic patients at high risk for developing diabetic cardiomyopathy may permit effective intervention. The goal of this work is to determine whether measurements of the magnitude and time delay of cyclic variation of myocardial backscatter, individually and in combination, can be used to discriminate between subgroups of individuals including normal controls and asymptomatic type 2 diabetes subjects. Two-dimensional parasternal long-axis echocardiographic images of 104 type 2 diabetic patients and 44 normal volunteers were acquired. Cyclic variation data were produced by measuring the mean myocardial backscatter level within a region-of-interest in the posterior wall, and characterized in terms of the magnitude and normalized time delay. The cyclic variation parameters were analyzed using Bayes classification and a nonparametric estimate of the area under the receiver operating characteristic (ROC) curve to illustrate the relative effectiveness of using one or two features to segregate subgroups of individuals. The subjects were grouped based on glycated hemoglobin (HbA1c), the homeostasis model assessment for insulin resistance (HOMA-IR) and the ratio of triglyceride to high-density lipoprotein cholesterol (TG/HDL-C). Analyses comparing the cyclic variation measurements of subjects in the highest and lowest quartiles of HbA1c, HOMA-IR and TG/HDL-C showed substantial differences in the mean magnitude and normalized time delay of cyclic variation. Results show that analyses of the cyclic variation of backscatter in young asymptomatic type 2 diabetics may be an early indicator for the development of diabetic cardiomyopathy.

Relationship between myocardial ultrasonic integrated backscatter and mitochondria of the myocardium in dogs

OBJECTIVE

This study aimed to explore the relationship between integrated backscatter (IBS) and mitochondria in arrested myocardium.

METHODS

Twelve open-chest dogs were randomly divided into two groups: one group with cardiac arrest in systole and the other with cardiac arrest in diastole. IBS images at parasternal papillary muscle short-axis view were stored at different time frames (0, 30, and 60 min after cardiac arrest). The values of ultrasonic IBS were obtained using the acoustic densitometry technique. After ultrasound examination, tissue samples of corresponding times were harvested and observed under the transmission electron microscope. The microscopic images were analyzed using a computer imaging analysis system to obtain the stereological parameters of mitochondria. The correlation between IBS and the stereological parameters was analyzed.

RESULTS

After cardiac arrest, swollen mitochondria with electron-lucent matrix could be observed in some myofibers following the progression of time. The alteration of IBS correlated well with that of mitochondrial stereological parameters, such as volume density (Vv), surface density (Sv), average volume (v), average surface area (s), and specific surface (Rsv, ratio between surface and volume).

CONCLUSION

Mitochondria might be an important scatterer in the myocardium for IBS.