Hhm Erik Korsten

On the physical and stochastic representation of an indicator dilution curve as a gamma variate

The analysis of intravascular indicator dynamics is important for cardiovascular diagnostics as well as for the assessment of tissue perfusion, aimed at the detection of ischemic regions or cancer hypervascularization. To this end, indicator dilution curves are measured after the intravenous injection of an indicator bolus and fitted by parametric models for the estimation of the hemodynamic parameters of interest. Based on heuristic reasoning, the dilution process is often modeled by a gamma variate. In this paper, we provide both a physical and stochastic interpretation of the gamma variate model. The accuracy of the model is compared with the local density random walk model, a known model based on physics principles. Dilution curves were measured by contrast ultrasonography both in vitro and in vivo (20 patients). Blood volume measurements were used to test the accuracy and clinical relevance of the estimated parameters. Both models provided accurate curve fits and volume estimates. In conclusion, the proposed interpretations of the gamma variate model describe physics aspects of the dilution process and lead to a better understanding of the observed parameters, increasing the value and credibility of the model, and possibly expanding its diagnostic applications.

Quantification of Regional Left Ventricular Dyssynchrony by Magnetic Resonance Imaging

Cardiac resynchronization therapy is an established treatment in patients with symptomatic heart failure and intraventricular conduction delay. Electrical dyssynchrony is typically adopted to represent myocardial activation dyssynchrony, which should be compensated by cardiac resynchronization therapy. One third of the patients, however, does not respond to the therapy. Therefore, imaging modalities aimed at the mechanical dyssynchrony estimation have been recently proposed to improve patient selection criteria. This paper presents a novel fully automated method for regional mechanical left ventricular dyssynchrony quantification in short-axis magnetic resonance imaging. The endocardial movement is described by time-displacement curves with respect to an automatically determined reference point. Different methods are proposed for time-displacement curve analysis aimed at the regional contraction timing estimation. These methods were evaluated in two groups of subjects with (nine patients) and without (six patients) left bundle branch block. The contraction timing standard deviation showed a significant increase for left bundle branch block patients with all the methods. A novel method based on phase spectrum analysis may be however preferred due to a better specificity (99.7%) and sensitivity (99.0%). In conclusion, this method provides a valuable prognostic indicator for heart failure patients with dyssynchronous ventricular contraction and it opens new possibilities for regional timing analysis.

Intra-thoracic blood volume measurement by contrast magnetic resonance imaging

The intra‐thoracic blood volume (ITBV) is a cardiovascular parameter related to the cardiac preload and left ventricular function. Its assessment is, therefore, important for diagnosis and follow‐up of several cardiovascular dysfunctions. Nowadays, the ITBV can be accurately measured only by invasive indicator dilution techniques, which require a double catheterization of the patient. In this study, a novel technique is presented for ITBV assessment by dynamic magnetic resonance imaging after intravenous injection of a small bolus of gadolinium chelate. The dose was chosen on the basis of in vitro calibration. The bolus first pass is detected from a simultaneous dynamic image series of the right and left ventricles. Two indicator dilution curves are derived and used to inspect the transpulmonary dilution system. Various mathematical models for the interpretation of the measured indicator dilution curves are compared. The ITBV is assessed as the product of the transpulmonary mean transit time of the indicator and the cardiac output, obtained by phase contrast magnetic resonance angiography. In vitro measurements showed a correlation coefficient larger than 0.99 and preliminary tests with volunteers proved the feasibility of the method, opening new possibilities for noninvasive quantitative cardiovascular diagnostics. Magn Reson Med 61:344–353, 2009.

Modeling of ultrasound propagation through contrast agents

In the past years many advances have been made in the detection of ultrasound contrast agents (UCA) by exploiting their nonlinear behavior. However, little attention has been paid to the nonlinear distortion of ultrasound (US) waves propagating through contrast media. The aim of this study is to model the nonlinear propagation of low pressure US waves through contrast media. The Burgers’ equation (approximated to the second order) is used to model the nonlinear US propagation. In addition, the results are compared to a numerical approximation of forward scattering, combining the linear-wave and modified Rayleigh-Plesset Noltingk Neppiras and Poritsky (RPNNP) equations. Measurements are performed for the model validation. Using a single element transducer, a Hanning-windowed 20 cycle US pulse was transmitted through water. An acoustically transparent tube (22 mm diameter) was positioned in the transducer focus containing different UCA concentrations up to 0.2%. All measurements were performed with an US mechanical index of 0.1 to prevent bubble collapse. The adopted frequency range was 0.5 to 3.5 MHz, which is around the UCA resonance frequency. The waves were measured by a hydrophone placed in line with the transducer. For low concentrations of UCA, the propagation of US waves can be described using the Burgers’ equation. For higher concentrations and frequencies close to the UCA resonance frequency a phase shift arises in the measurements which can be predicted by combining the modified RPNNP and the linear-wave equations.

Prostate cancer localization by contrast-ultrasound diffusion imaging

Prostate cancer is the form of cancer with the highest incidence in men. The invasiveness or low specificity of available diagnostics hampers a timely use of efficient focal therapies. New imaging techniques are therefore needed for an early prostate cancer localization. We propose a new ultrasound imaging method for prostate cancer localization based on quantification of the (intravascular) local diffusion of ultrasound contrast agents. Local diffusion is expected to correlate better than perfusion with cancer microvascular growth and, therefore, aggressiveness. Local diffusion is estimated by transrectal ultrasound imaging of an ultrasound contrast-agent bolus passing through the prostate circulation after a peripheral intravenous injection. A time-intensity curve (TIC) is measured at each pixel by acoustic quantification. The measured TICs are fitted by a modified Local Density Random Walk model, a solution of the convective diffusion equation that provides a physical representation of the diffusion process. The obtained parametric diffusion images were compared with the histology results after radical prostatectomy. The resulting receiver operating characteristics (curve area = 0.91) were superior to those obtained by estimation of perfusion related parameters. Although extensive validation is necessary, contrast ultrasound diffusion imaging is a promising method, with potential to assess cancer aggressiveness.

System modeling and identification in indicator dilution method for assessment of ejection fraction and pulmonary blood volume

Clinically relevant cardiovascular parameters, such as pulmonary blood volume (PBV) and ejection fraction (EF), can be assessed through indicator dilution techniques. Among these techniques, which are typically invasive due to the need for central catheterization, contrast ultrasonography provides a new emerging minimally invasive option. PBV and EF are then measured by a dilution system identification algorithm after detection of multiple dilution curves by an ultrasound scanner. In this paper, dilution systems are represented by parametric models. Since the measured indicator dilution curves (IDCs) are corrupted by measurement artifacts and outliers, the use of conventional least square error (LSE) estimator for estimating system parameters is not optimal. Different estimators are therefore proposed for estimating the system parameters. Comparison of these estimators with the LSE estimator in assessing EF and PBV is performed on simulated, in vitro and patient data. The results show that the proposed total least absolute deviation estimator (TLAD) outperforms other estimators. The measured IDCs are highly corrupted by noise, which affect the estimation of EF and PBV. Therefore, a two stage denoising method capable of removing outliers is also proposed for removing noise in IDCs.

Automatic blood pool identification in contrast ultrasound using principal component analysis

Several cardiovascular parameters of clinical interest can be assessed by indicator dilution techniques. Ultrasound contrast agents have been proposed as non-invasive indicator, showing promising results for blood volume estimation. However, the definition of an optimal region of interest for quantification of the indicator remains a critical step in the procedure, usually performed manually. In this work we present an automatic method to extract indicator dilution curves. Dimensionality reduction is achieved by principal component analysis followed by clustering to identify the different regions of interest. The method is evaluated on in vitro and in vivo datasets, compared to manually defined regions. The average difference was -3.47% ± 3.58% for in vitro volume estimates and the error was 1.29% ± 2.54% for trans-pulmonary mean transit time estimation. The new method allows kinetic parameter estimates in close agreement with those obtained manually; therefore it is a promising alternative for indicator dilution curve extraction.