Quantification of regional myocardial perfusion using semiautomated translation-free analysis of contrast-enhanced power modulation images

Semi-automated analysis of dynamic changes in myocardial contrast from real-time three-dimensional echocardiographic images as a basis for volumetric quantification of myocardial perfusion

AIMS

Despite the potential of real-time three-dimensional (3D) echocardiography (RT3DE) to assess myocardial perfusion, there is no quantification method available for perfusion analysis from RT3DE images. Such method would require 3D regions of interest (ROI) to be defined and adjusted frame-by-frame to compensate for cardiac translation and deformation. Our aims were to develop and test a technique for automated identification of 3D myocardial ROI suitable for translation-free quantification of myocardial videointensity over time, MVI(t), from contrast-enhanced RT3DE images.

METHODS AND RESULTS

Twelve transthoracic RT3DE (Philips) data sets obtained in pigs during transition from no contrast to steady-state enhancement (Definity) were analysed using custom software. Analysis included: (i) semi-automated detection of left ventricular endo- and epicardial surfaces using level-set techniques in one frame to define a 3D myocardial ROI, (ii) rigid 3D registration to reduce translation and rotation, (iii) elastic 3D registration to compensate for deformation, and (iv) quantification of MVI(t) in the 3D ROI from the registered and non-registered data sets to assess the effectiveness of registration. For each MVI(t) curve we computed % variability during steady-state enhancement (100 x SD/mean) and goodness of fit (r2) to the indicator dilution equation MVI(t) = A[1-exp(-betat)]. Analysis of myocardial contrast throughout contrast inflow was feasible in all data sets. Three-dimensional registration improved MVI(t) curves in terms of both % variability (2.8 +/- 1.8 to 1.5 +/- 0.9%; P < 0.05) and goodness of fit (r2 from 0.79 +/- 0.2 to 0.90 +/- 0.1; P < 0.05).

CONCLUSION

This is the first study to describe a new technique for semi-automated volumetric quantification of myocardial contrast from RT3DE images that includes registration and thus provides the basis for 3D measurement of myocardial perfusion.

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.

Automated Interpretation of Regional Left Ventricular Wall Motion from Cardiac Magnetic Resonance Images

Magnetic resonance (MR) diagnosis of regional left ventricular (LV) dysfunction relies on visual interpretation of cine images that suffers from wide inter-observer variability, especially when performed by readers not specifically trained in the assessment of LV wall motion. Quantitative analysis tools, though widely available, are rarely used because they provide large amounts of detailed information, the interpretation of which requires additional time-consuming processing. We tested the feasibility of fast automated interpretation of regional LV function using computer analysis of this wall motion information.

METHODS

Dynamic, ECG-gated, steady-state free precession short-axis images were obtained in 6-10 slices in 28 subjects (10 normal volunteers; 18 patients). Images were reviewed by an expert cardiologist who provided "gold standard" grades (normal, abnormal) for regional wall motion and, independently, by four radiologists. Same images were then analyzed using custom software. Regional fractional area changes computed in normal volunteers were used to obtain the optimal segment- and slice-specific threshold values for automated classification of regional wall motion for each patient. The levels of agreement with the "gold standard" grades were compared between the radiologists and the automated interpretation.

RESULTS

While the visual interpretation required 2-5 minute per patient, the automated interpretation required < 1 sec, after endocardial border detection was complete. The automated interpretation resulted in higher sensitivity, specificity, and accuracy (84%, 77%, 79%, respectively) than the radiologists' grades (80%, 76%, 77%, respectively) and eliminated the high interobserver variability.

CONCLUSION

Once the endocardial boundaries are defined, computer analysis of the regional wall motion information allows accurate, fully automated, immediate, objective and experience-independent interpretation of regional LV function.

A New Method of Color Doppler Perfusion Measurement via Dynamic Sonographic Signal Quantification in Renal Parenchyma

OBJECTIVE

Perfusion quantification of tissues is an important goal to evaluate the state of blood supply of an organ. We developed a method to quantify tissue perfusion via color Doppler signal quantification from sonographic videos and applied this to describe renal parenchymal perfusion in healthy kidneys.

METHOD

Color Doppler sonographic videos of renal perfusion from both kidneys of 87 healthy children (age 2 weeks to 16 years) were recorded under defined conditions. Perfusion data (color hue, color area) were measured in a standardized region of interest automatically. Signal intensity was calculated as whole ROIs (regions of interest) mean flow velocity (cm/s) encoded by color Doppler signals during one full heart cycle.

RESULTS

Normal signal intensity values are: 1.86 cm/s in the region encompassing central 50% of the renal cortex and 0.56 cm/s in the peripheral 50% of the renal cortex. These differences are significant. Signal intensity of both kidneys did not differ.

CONCLUSION

Signal intensity of cortical tissue in healthy kidneys was quantified noninvasively from color Doppler signal data in an easily accomplishable manner with new measurement software. Normal values for this technique have been calculated. Possible further applications might be all situations, where perfusion changes could be expected like inflammation, renal insufficiency, vascular diseases and tumors.