Ghavami, Siavash

Vibrational characteristics of the bone are directly dependent on bone’s physical properties. In this paper, a vibrational method for bone evaluation is introduced. We propose a new type of quantitative vibro-acoustic method based on acoustic radiation force of ultrasound for bone characterization in patients with fracture. In this method, we excite the clavicle and ulna by an ultrasound radiation force (URF) pulse. The URF pulse induces vibrations in the bone, resulting in an acoustic wave that is measured by a hydrophone placed on the skin. The resulting acoustic signals were used for wave velocity estimation based on cross-correlation technique. To further separate different vibration characteristics, we adopt a variational mode decomposition (VMD) technique to decompose the received signal into an ensemble of band-limited intrinsic mode functions, which allows analyzing the acoustic signals in terms of their constitutive components. We conducted a prospective study that included a total of 15 patients, 12 with clavicle fractures and 3 with ulna fractures. The contralateral intact bones were used as control. Statistical analysis demonstrated that fracture bones can be differentiated from intact bone with a detection probability of 80%. Also, we introduce a “healing factor” that quantifies the progress of healing in clavicle bones. Statistical analysis showed that healing factor can track the progress of healing in clavicle in 80% of fractures.

We present a full-wave inversion approach with total variation regularization for elastography. The proposed method is based on the minimization of an error in constitutive equations functional augmented with a least squares data misfit term referred to as MECE for “modified error in constitutive equations.” The main theme of this paper is to demonstrate several key strengths of the proposed method on experimental data. In addition, some illustrative examples are provided where the proposed method is compared with a common shear wave elastography (SWE) approach. To this end, ultrasonically tracked displacement data from an acoustic radiation force (ARF) pulse are used in different phantoms including phantom with layered inclusion and triangle inclusion. The results indicate that the MECE approach can produce accurate shear modulus reconstructions in comparison with SWE, especially around the sharp edges in the layered and triangle inclusions. We compare shear modulus reconstruction using MECE and SWE with original inclusion shapes using two-dimensional normalized zero mean cross correlation, edge preservation index and dice coefficient similarity index. [Work supported by NIH Grant R01 CA174723.]

Vibrational characteristics of bone are directly dependent on its physical properties. In this study, a vibrational method for bone evaluation is introduced. We propose a new type of quantitative vibro-acoustic method based on the acoustic radiation force of ultrasound for bone characterization in persons with fracture. Using this method, we excited the clavicle or ulna by an ultrasound radiation force pulse which induces vibrations in the bone, resulting in an acoustic wave that is measured by a hydrophone placed on the skin. The acoustic signals were used for wave velocity estimation based on a cross-correlation technique. To further separate different vibration characteristics, we adopted a variational mode decomposition technique to decompose the received signal into an ensemble of band-limited intrinsic mode functions, allowing analysis of the acoustic signals by their constitutive components. This prospective study included 15 patients: 12 with clavicle fractures and three with ulna fractures. Contralateral intact bones were used as controls. Statistical analysis demonstrated that fractured bones can be differentiated from intact ones with a detection probability of 80%. Additionally, we introduce a “healing factor” to quantify the bone healing progress which successfully tracked the progress of healing in 80% of the clavicle fractures in the study.

Vascular networks can provide invaluable information about tumor angiogenesis. Ultrafast Doppler imaging enables ultrasound to image microvessels by applying tissue clutter filtering methods on the spatio-temporal data obtained from plane-wave imaging. However, the resultant vessel images suffer from background noise that degrades image quality and restricts vessel visibilities. In this paper, we addressed microvessel visualization and the associated noise problem in the power Doppler images with the goal of achieving enhanced vessel-background separation. We proposed a combination of patch-based non-local mean filtering and top-hat morphological filtering to improve vessel outline and background noise suppression. We tested the proposed method on a flow phantom, as well as in vivo breast lesions, thyroid nodules, and pathologic liver from human subjects. The proposed non-local-based framework provided a remarkable gain of more than 15 dB, on average, in terms of contrast-to-noise and signal-to-noise ratios. In addition to improving visualization of microvessels, the proposed method provided high quality images suitable for microvessel morphology quantification that may be used for diagnostic applications.

We hypothesize that pattern of microvasculature in the thyroid nodules can be a biomarker of thyroid cancer. In this study, morphological features of microvasculature networks are assessed as potential biomarkers for differentiation of benign, suspicious and malignant thyroid nodules. This prospective study included n = 81 patients, with a total of 61 benign, 12 suspicious and 8 malignant nodules verfied by pathology and cytology findings. Thyroid nodules were first identified using conventional B-mode ultrasound. A sequence of raw ultrasound data were acquired from each nodule site in two perpendicular planes at ~600 frames/sec. Power Doppler image of the microvasculature was formed using singular value decomposition clutter removal filtering. Gross images were further processed using a combination of morphology and Hessian-based vessel enhancement filtering. Background-free images of the microvasculature networks were segmented (vessels segment length >385μm and diameter >90μm) for morphological analysis. Using a Bayesian framework, measures of vessels density, diameter and tortuosity were tested for significant differences in the three groups. Among all measures, the probability of vessel diameter >600μm in benign cases was significantly higher than that in malignant cases with the p-value <0.01 using Wilcoxon-Rank-Sum test, suggesting reliable cancer detection performance of the proposed method. [Acknowledgment: NIH Grant EB17213.]

As shown in a recent study, estimation of the magnitude of the acoustic radiation force (ARF) in isotropic tissue-like solids is the key to measuring a third-order nonlinear modulus of elasticity (C)—responsible for coupling the shear and volumetric constitutive responses of a material. Due to experimental limitations, a direct measurement of the ARF in tissue is however difficult. To overcome this problem, we deploy 3D elastodynamic finite element (EFE) simulations of the ARF experiment in tissue-mimicking phantoms to estimate (i) the “background” shear modulus from the phase of the induced shear waves; (ii) the ARF magnitude from the shear wave amplitude, and (iii) the modulus C from the knowledge of the ARF. In this way, by interpreting the ARF-generated shear waves through the prism of 3D-EFE simulations, we facilitate local estimation of the nonlinear C modulus with spatial resolution equaling the size of the focal region. We call this method the C-Elastography (CE). In this study, the CE technique is applied to gelatin phantoms containing an agar-based inclusion. The profiles of the C-modulus in phantoms tested demonstrate good correlation with the phantom geometry, showing marked (and sharp) C-contrast at push points acting on the inclusion. [Acknowledgment: NIH-Grant EB23113.]

Early detection of osteopenia and osteoporosis is critical in identifying at-risk groups and manage necessary therapy. In this paper, a new noninvasive and quantitative vibro-acoustic method is proposed for detection of osteoporosis and osteopenia. In this method, we excite the bone by an ultrasound radiation force (URF) pulse. The URF pulse induces a vibration in the bone, resulting an acoustic wave that is received by a hydrophone placed on the skin. This prospective study included n = 23 volunteers. The number of volunteers with osteopenia and osteoporosis were 7, 6, respectively, and the number of volunteers with normal bone was 10. URF excitations were applied at four equi-distance points on the bone. The resulting acoustic signals were used for wave velocity estimation based on cross-correlation technique. In general, the hydrophone signal may be modeled as a superposition of different modes of bone vibration. Based on this model, we used variational mode decomposition (VMD) as an efficient technique to decompose the received signal into an ensemble of band-limited intrinsic mode functions. Statistical analysis demonstrates that osteopenia and osteoporosis bones can be differentiated from normal bone with p< 0.001 using Wilcoxon rank-sum test on estimated velocity of the modes with maximum power.