Single pulse frequency compounding protocol for superharmonic imaging.

Second harmonic imaging is currently accepted as the standard in commercial echographic systems. A new imaging technique, coined as superharmonic imaging (SHI), combines the third till the fifth harmonics, arising during nonlinear sound propagation. It could further enhance the resolution and quality of echographic images. To meet the bandwidth requirement for SHI a dedicated phased array has been developed: a low frequency subarray, intended for transmission, interleaved with a high frequency subarray, used in reception. As the bandwidth of the elements is limited, the spectral gaps in between the harmonics cause multiple (ghost) reflection artifacts. A dual-pulse frequency compounding method aims at suppressing those artifacts at a price of a reduced frame rate. In this study we explore a possibility of performing frequency compounding within a single transmission. The traditional frequency compounding method suppresses the ripples by consecutively emitting two short Gaussian bursts with a slightly different center frequency. In the newly proposed method, the transmit aperture is divided into two parts: the first half is used to send a pulse at the lower center frequency, while the other half simultaneously transmits at a slightly higher center frequency. The suitability of the protocol for medical imaging applications in terms of the steering capabilities was performed in a simulation study with INCS and the hydrophone measurements. Moreover, an experimental study was carried out to find the optimal parameters for the clinical imaging protocol. The latter was subsequently used to obtain the images of a tissue mimicking phantom containing strongly reflecting wires. Additionally, the images of a human heart in the parasternal projection were acquired. The scanning aperture with the developed protocol amounts to approximately 90°, which is sufficient to capture the cardiac structures in the standard anatomical projections. The theoretically estimated and experimentally measured grating lobe levels are equal to -28.3 dB and -35.9 dB, respectively. A considerable improvement in the axial resolution of the SHI component (0.73 mm) at -6 dB in comparison with the third harmonic (2.23 mm) was observed. A similar comparison in terms of the lateral resolution slightly favored the superharmonic component by 0.2 mm. Additionally, the images of the tissue mimicking phantom exhibited the absence of the multiple reflection artifacts. The in-vivo acquisition allows one to clearly observe the dynamic of the mitral valve leaflets. The new method is equally effective in eliminating the ripple artifacts associated with SHI as the dual-pulse technique, while the full frame rate is maintained.

Automated analysis of three-dimensional stress echocardiography.

Real-time three-dimensional (3D) ultrasound imaging has been proposed as an alternative for two-dimensional stress echocardiography for assessing myocardial dysfunction and underlying coronary artery disease. Analysis of 3D stress echocardiography is no simple task and requires considerable expertise. In this paper, we propose methods for automated analysis, which may provide a more objective and accurate diagnosis. Expert knowledge is incorporated via statistical modelling of patient data. Methods for identifying anatomical views, detecting endocardial borders, and classification of wall motion are described and shown to provide favourable results. We also present software developed especially for analysis of 3D stress echocardiography in clinical practice. Interobserver agreement in wall motion scoring is better using the dedicated software (96%) than commercially available software not dedicated for this purpose (79%). The developed tools may provide useful quantitative and objective parameters to assist the clinical expert in the diagnosis of left ventricular function.

A study of coronary artery rotational motion with dense scale-space optical flow in intravascular ultrasound.

This paper describes a novel method for estimating tissue motion in two-dimensional intravascular ultrasound (IVUS) images of a coronary artery. It is based on the classical Lukas-Kanade (LK) algorithm for optical flow (OF). The OF vector field quantifies the amount of misalignment between two consecutive frames in a sequence of images. From the theoretical standpoint, two fundamental improvements are proposed in this paper. First, using a simplified representation of the vessel wall as a medium with randomly distributed scatterers, it was shown that the OF equation satisfies the integral brightness conservation law. Second, a scale-space embedding for the OF equation was derived under the assumption of spatial consistency in IVUS acquisitions. The spatial coherence is equivalent to a locally affine motion model. The latter effectively captures and appropriately describes a complex deformation pattern of the coronary vessel wall under the varying physiological conditions (i.e. pulsatile blood pressure). The accuracy of OF tracking was estimated on the tissue-mimicking phantoms subjected to the controlled amount of angular deviation. Moreover, the performance of the classical LK and proposed approach was compared using the simulated IVUS images with an atherosclerotic lesion. The experimental results showed robust and reliable performance of up to 5 degrees of rotation, which is within the plausible range of circumferential displacement of the coronary arteries. Subsequently, the algorithm was used to analyze vessel wall motion in 18 IVUS pullbacks from 16 patients. The in vivo experiments revealed that the motion of coronary arteries is primarily determined by the cardiac contraction.

Optimizing the automatic segmentation of the left ventricle in magnetic resonance images.

Automatic segmentation of the left ventricular (LV) myocardial borders in cardiovascular MR (CMR) images allows a significant speed-up of the procedure of quantifying LV function, and improves its reproducibility. The automated boundary delineation is usually based on a set of parameters that define the algorithms. Since the automatic segmentation algorithms are usually sensitive to the image quality and frequently depend heavily on the acquisition protocol, optimizing the parameters of the algorithm for such different protocols may be necessary to obtain optimal results. In other words, using a default set of parameters may be far from optimal for different scanners or protocols. For the MASS-software, for example, this means that a total of 14 parameters need to be optimized. This optimization is a difficult and labor-intensive process. To be able to more consistently and rapidly tune the parameters, an automated optimization system would be extremely desirable. In this paper we propose such an approach, which is based on genetic algorithms (GAs). The GA is an unsupervised iterative tool that generates new sets of parameters and converges toward an optimal set. We implemented and compared two different types of the genetic algorithms: a simple GA (SGA) and a steady state GA (2SGA). The difference between these two algorithms lies in the characteristics of the generated populations: "nonoverlapping populations" and "overlapping populations," respectively "nonoverlapping" population means that the two populations are disjoint, and "overlapping" means that the best parameters found in the previous generation are included in the present population. The performance of both algorithms was evaluated on twenty routinely obtained short-axis examinations (eleven examinations acquired with a steady-state free precession pulse sequence, and nine examinations with a gradient echo pulse sequence). The optimal parameters obtained with the GAs were used for the LV myocardial border delineation. Finally, the automatically outlined contours were compared to the gold standard--manually drawn contours by experts. The result of the comparison was expressed as a degree of similarity after a processing time of less than 72 h to a 59.5% of degree of similarity for SGA and a 66.7% of degree of similarity for 2SGA. In conclusion, genetic algorithms are very suitable to automatically tune the parameters of a border detection algorithm. Based on our data, the 2SGA was more suitable than the SGA method. This approach can be generalized to other optimization problems in medical image processing.

Accuracy of short-axis cardiac MRI automatically derived from scout acquisitions in free-breathing and breath-holding modes.

To qualitatively assess the accuracy of automated cardiovascular magnetic resonance planning procedures devised from scout acquisitions in free-breathing and breath-holding modes, to quantitatively evaluate the accuracy of the derived left ventricular volumes, mass and function and compare these parameters with the ones obtained from the manually planned acquisitions. Ten healthy volunteers underwent cardiovascular MR (CMR) acquisitions for ventricular function assessment. Short-axis data sets of the left ventricle (LV) were manually planned and generated twice in an automatic fashion. Automated planning parameters were derived from gated scout acquisitions in free-breathing and breath-holding modes. End-diastolic volume (EDV), end-systolic volume (ESV), ejection fraction (EF), and left ventricular mass (LVM) were measured. The agreement between the manual and automatic planning methods, as well as the variability of the aforementioned measurements were assessed. The differences between two automated planning methods were also compared. The mean differences between the manual and automated CMR planning derived from gated scouts in free-breathing mode were 8.05 ml (EDV), 1.84 ml (ESV), 0.69% (EF), and 4.72 g (LVM). The comparison between manual and automated CMR planning derived from gated scouts in breath-holding mode yielded the following differences: 4.22 ml (EDV), 0.34 ml (ESV), 0.3% (EF), and -0.72 mg (LVM). The variability coefficients were 3.72 and 3.66 (EDV), 5.6 and 8.19 (ESV), 3.46 and 4.31 (EF), 6.49 and 5.20 (LVM) for the automated CMR planning methods derived from scouts in free-breathing and breath-holding modes, respectively. Automated CMR planning methods can provide accurate measurements of LV dimensions in normal subjects, and therefore may be utilized in the clinical environment to provide a cost-effective solution for functional assessment of the human cardiovascular system.

Mitral valve regurgitation: accurate blood flow quantification with MRI.

BACKGROUND: The quantification of transvalvular blood flow through the mitral valve (MV) and regurgitant flow in particular is difficult with echocardiography, which is the method of choice to diagnose patients selected for valve repair or replacement. With magnetic resonance imaging, information on the intraventricular blood flow can be obtained. Several scanning techniques have attempted to assess the regurgitant flow. These techniques either do not directly assess the complete flow through the MV, or they do not measure the flow at the location of the valve. AIM: To investigate the accuracy of a novel method using three-directional velocity-encoded MRI to acquire the transvalvular blood flow directly from the intraventricular blood flow field, also representing the regurgitant flow during systole. METHODS: Ten volunteers without cardiac valvular disease were recruited. The transvalvular MV flow volume was measured with three-directional velocity-encoded MRI (3-dir MV flow). RESULTS: The transvalvular flow measurements correlate very well with the flow measured in the aorta (rp=0.92, p<0.01). The small differences (mean -5±7 ml) are insignificant (p=0.06) and demonstrate the high accuracy of the new method. Intra- and inter-observer studies showed non-significant mean differences of 0.9±5.1 ml and 1.3±5.6 ml, respectively, thereby proving the high reproducibility. CONCLUSION: Three-directional velocity-encoded MRI is a patient-friendly and easy-to-use method suitable for quantifying the regurgitant MV flow in clinical practice.

Validation of the coupling of magnetic resonance imaging velocity measurements with computational fluid dynamics in a U bend.

Magnetic resonance imaging (MRI) can be used in vivo in combination with computational fluid dynamics (CFD) to derive velocity profiles in space and time and accordingly, pressure drop and wall shear stress distribution in natural or artificial vessel segments. These hemodynamic data are difficult or impossible to acquire directly in vivo. Therefore, research has been performed combining MRI and CFD for flow simulations in flow phantoms, such as bends or anastomoses, and even in human vessels such as the aorta, the carotid, and the abdominal bifurcation. There is, however, no unanimity concerning the use of MRI velocity measurements as input for the inflow boundary condition of a CFD simulation. In this study, different input possibilities for the inflow boundary conditions are compared. MRI measurements of steady and pulsatile flow were performed on a U bend phantom, representing the aorta geometry. PAMFLOW (ESI Software, Krimpen aan den Ussel, The Netherlands), an industrial CFD software package, was used to solve the Navier-Stokes equations for incompressible flow. Three main parameters were found to influence the choice of an inflow boundary condition type. First, the flow rate through a vessel should be exact, since it proves to be a determining factor for the accuracy of the velocity profile. The other decisive parameters are the physiology of the flow profile and the required computer processing unit time. Our comparative study indicates that the best way to handle an inflow boundary condition is to use the velocities measured by MRI at the inflow plane as being fixed velocities. However, before using these MRI velocity data, they first should be corrected for the partial volume effect by filtering and second scaled in order to obtain the correct flow rate. This implies that a reliable flow rate measurement absolutely is needed for CFD calculations based on MRI velocity measurements.