Publications by authors named "Richard G Lopata"

Background: Exercise stress echocardiography is clinically used to assess cardiovascular diseases. For accurate cardiac evaluation, a stable field-of-view is required. However, transducer orientation and position are difficult to preserve.

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Assessment of microvasculature and tissue perfusion can provide diagnostic information on local or systemic diseases. Photoacoustic (PA) imaging has strong clinical potential because of its sensitivity to hemoglobin. We used a hand-held PA probe with integrated diode lasers and examined its feasibility and validity in the detection of increasing blood volume and (sub) dermal vascularization.

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Photoacoustic imaging (PAI) may have the ability to reveal the composition and the anatomical structure of carotid plaques, which determines its mechanical properties and vulnerability. We used PAI and plane wave ultrasound (PUS) imaging to obtain three-dimensional (3-D) images of endarterectomy samples ex vivo and compared the results with histology to investigate the potential of PAI-based identification of intraplaque hemorrhage. Seven carotid plaque samples were obtained from patients undergoing carotid endarterectomy and imaged with a fully integrated hand-held photoacoustic (PA) probe, consisting of a pulsed diode laser ( t pulse = 130 ?? ns , E pulse = 1 ?? mJ , ? = 808 ?? nm ) and a linear array transducer ( f c = 7.

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When applying models to patient-specific situations, the impact of model input uncertainty on the model output uncertainty has to be assessed. Proper uncertainty quantification (UQ) and sensitivity analysis (SA) techniques are indispensable for this purpose. An efficient approach for UQ and SA is the generalized polynomial chaos expansion (gPCE) method, where model response is expanded into a finite series of polynomials that depend on the model input (i.

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Abdominal aortic aneurysms (AAAs) are local dilations of the aorta which can lead to a fatal hemorrhage when ruptured. Wall stress analysis of AAAs has been widely reported in literature to predict the risk of rupture. Usually, the complete AAA geometry including the aortic bifurcation is obtained by computed tomography (CT).

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Knowledge of the intrinsic material properties of healthy and diseased arterial tissue components is of great importance in diagnostics. This study describes an in vitro comparison of 13 porcine carotid arteries using inflation testing combined with functional ultrasound and bi-axial tensile testing. The measured tissue behavior was described using both a linear, but geometrically non-linear, one-parameter (neo-Hookean) model and a two-parameter non-linear (Demiray) model.

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Objective: Abdominal aortic aneurysms (AAAs) are local dilations that can lead to a fatal hemorrhage when ruptured. Wall stress analysis of AAAs is a novel tool that has proven high potential to improve risk stratification. Currently, wall stress analysis of AAAs is based on computed tomography (CT) and magnetic resonance imaging; however, three-dimensional (3D) ultrasound (US) has great advantages over CT and magnetic resonance imaging in terms of costs, speed, and lack of radiation.

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Ultrasound imaging can be used to estimate the morphology as well as the motion and deformation of tissues. If the interrogated tissue is actively deforming, this deformation is directly related to its function and quantification of this deformation is normally referred as 'strain imaging'. Tissue can also be deformed by applying an internal or external force and the resulting, induced deformation is a function of the mechanical tissue characteristics.

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Vascular elastography techniques are promising tools for mechanical characterization of diseased arteries. These techniques are usually validated with simulations or phantoms or by comparing results with histology or other imaging modalities. In the study described here, vascular elastography was applied to porcine aortas in vitro during inflation testing (n = 10) and results were compared with those of standard bi-axial tensile testing, a technique that directly measures the force applied to the tissue.

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To improve our understanding of the mechanical behavior of human atherosclerotic plaque tissue, fully 3-D geometrical, morphological and dynamical information is essential. For this purpose, four-dimensional (3-D+t) strain imaging using an ultrasound tomography approach (echo-computed tomography) was performed in carotid arteries in vitro. The method was applied to a carotid phantom (CPh), a porcine carotid artery (PC) and human carotid atherosclerotic plaque samples (HC, n = 5).

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In this study, an experimental framework is described that allows pressurization of intact, human atherosclerotic carotid samples (inflation testing), in combination with ultrasound imaging. Eight fresh human carotid endarterectomy samples were successfully pressurized and tested. About 36 2-D (+t) ultrasound datasets were acquired by rotating the vessel in 10° steps (Echo-CT), from which both 3-D geometry and 3-D strain data were obtained.

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For automated segmentation of 3-D echocardiographic images, incorporation of temporal information may be helpful. In this study, optimal settings for calculation of temporal cross-correlations between subsequent time frames were determined, to obtain the maximum cross-correlation (MCC) values that provided the best contrast between blood and cardiac tissue over the entire cardiac cycle. Both contrast and boundary gradient quality measures were assessed to optimize MCC values with respect to signal choice (radiofrequency or envelope data) and axial window size.

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To improve diagnosis and understanding of the risk of rupture of atherosclerotic plaque, new strategies to realistically determine mechanical properties of atherosclerotic plaque need to be developed. In this study, an in vitro experimental method is proposed for accurate 3-D assessment of (diseased) vessel geometry using ultrasound. The method was applied to a vascular phantom, a healthy porcine carotid artery and human carotid endarterectomy specimens (n = 6).

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Soft tissue displacements during minimally invasive surgical procedures may cause target motion and subsequent misplacement of the surgical tool. A technique is presented to predict target displacements using a combination of ultrasound elastography and finite element (FE) modeling. A cubic gelatin/agar phantom with stiff targets was manufactured to obtain pre- and post-loading ultrasound radio frequency (RF) data from a linear array transducer.

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In this study, a new radio-frequency (RF)-based, three-dimensional (3-D) strain imaging technique is introduced and applied to 3-D full volume ultrasound data of the heart of healthy children. Continuing advances in performance of transducers for 3-D ultrasound imaging have boosted research on 3-D strain imaging. In general, speckle tracking techniques are used for strain imaging.

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Clinical diagnosis of heart disease might be substantially supported by automated segmentation of the endocardial surface in three-dimensional (3-D) echographic images. Because of the poor echogenicity contrast between blood and myocardial tissue in some regions and the inherent speckle noise, automated analysis of these images is challenging. A priori knowledge on the shape of the heart cannot always be relied on, e.

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Strain is considered to be a useful indicator of atherosclerotic plaque vulnerability. This study introduces an alternative for a recently introduced strain imaging method that combined beam steered ultrasound acquisitions to construct radial strain images of transverse cross-sections of superficial arteries. In that study, axial strains were projected in the radial direction.

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In this study, a multidimensional strain estimation method using biplane ultrasound is presented to assess local relative deformation (i.e., local strain) in three orthogonal directions in skeletal muscles during induced and voluntary contractions.

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The goal of this study was to investigate the applicability of conventional 2-D displacement and strain imaging techniques to phased array radiofrequency (RF) data. Furthermore, the possible advantages of aligning and stretching techniques for the reduction of decorrelation artefacts was examined. Data from both realistic simulations and phantoms were used in this study.

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In this study, the performances of one-dimensional and two-dimensional least-squares strain estimators (LSQSE) are compared. Furthermore, the effects of kernel size are examined using simulated raw frequency data of a widely-adapted hard lesion/soft tissue model. The performances of both methods are assessed in terms of root-mean-squared errors (RMSE), elastographic signal-to-noise ratio (SNRe) and contrast-to-noise ratio (CNRe).

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In elastography, several methods for 2-D strain imaging have been introduced, based on both raw frequency (RF) data and speckle-tracking. Although the precision and lesion detectability of axial strain imaging in terms of elastographic signal-to-noise ratio (SNRe) and elastographic contrast-to-noise ratio (CNRe) have been reported extensively, analysis of lateral precision is still lacking. In this paper, the performance of different 2-D correlation RF- and envelope-based strain estimation methods was evaluated using simulation data and phantom experiments.

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Reconstruction of a cleft lip leads inevitably to scar tissue formation. Scar tissue within the restored oral orbicular muscle might be assessed by quantification of the local contractility of this muscle. Furthermore, information about the contraction capability of the oral orbicular muscle is crucial for planning the revision surgery of an individual patient.

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Stroke and myocardial infarction are initiated by rupturing vulnerable atherosclerotic plaques. With noninvasive ultrasound elastography, these plaques might be detected in carotid arteries. However, since the ultrasound beam is generally not aligned with the radial direction in which the artery pulsates, radial and circumferential strains need to be derived from axial and lateral data.

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Semi-automatic segmentation of the myocardium in 3D echographic images may substantially support clinical diagnosis of heart disease. Particularly in children with congenital heart disease, segmentation should be based on the echo features solely since a priori knowledge on the shape of the heart cannot be used. Segmentation of echocardiographic images is challenging because of the poor echogenicity contrast between blood and the myocardium in some regions and the inherent speckle noise from randomly backscattered echoes.

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