Fatemi, Mostafa

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.

B‐mode ultrasound imaging guidance of cannulas can be compromised by noise, artifacts, and echogenicity that is not distinctive from that of surrounding anatomy. We have modified a venovenous extracorporeal membrane oxygenation cannula by embedding piezoelectric crystals into each of its 3 blood flow ports. Each vibrating crystal acoustically interacts with a Doppler imaging signal and produces an instantaneous color marker. The aim of this study was to compare identification of the extracorporeal membrane oxygenation cannula ports by B‐mode imaging versus the color Doppler marker. Unlike B‐mode imaging, the color Doppler marker identified the corresponding port even in highly challenging closed‐chest scans in anesthetized pigs. The method could improve guidance accuracy of cannulas by ultrasound scans.

Abstract Kelvin–Voigt fractional derivative (KVFD) model parameters have been used to describe viscoelastic properties of soft tissues. However, translating model parameters into a concise set of intrinsic mechanical properties related to tissue composition and structure remains challenging. This paper begins by exploring these relationships using a biphasic emulsion materials with known composition. Mechanical properties are measured by analyzing data from two indentation techniques—ramp-stress relaxation and load-unload hysteresis tests. Material composition is predictably correlated with viscoelastic model parameters. Model parameters estimated from the tests reveal that elastic modulus E 0 closely approximates the shear modulus for pure gelatin. Fractional-order parameter α and time constant τ vary monotonically with the volume fraction of the material’s fluid component. α characterizes medium fluidity and the rate of energy dissipation, and τ is a viscous time constant. Numerical simulations suggest that the viscous coefficient η is proportional to the energy lost during quasi-static force-displacement cycles, E A . The slope of E A versus η is determined by α and the applied indentation ramp time T r . Experimental measurements from phantom and ex vivo liver data show close agreement with theoretical predictions of the η − E A relation. The relative error is less than 20% for emulsions 22% for liver. We find that KVFD model parameters form a concise features space for biphasic medium characterization that described time-varying mechanical properties.

Vibro-acoustography has gained interest in the recent years as a new modality for medical imaging. This method is based on low-frequency vibrations induced in the object by the radiation force of ultrasound. This paper focuses on potential applications of vibro-acoustography in breast imaging, including detection of microcalcifications, detection of arterial calcifications, and soft tissue imaging. In addition, we will briefly discuss our recent results of in vivo breast vibro-acoustography. Future developments and potential impact of vibro-acoustography in breast imaging are also discussed.

This study concerns the development and preliminary experimental verification of a topological sensitivity–based platform for the material characterization of tissue anomalies exposed by vibroacoustography-type imaging techniques. Vibroacoustography (VA) is a high-resolution imaging method that has been applied to the detection of pathological changes in soft tissues. Although the data provided by this method is related to the mechanical properties of tissue, the viscoelastic parameters of the object cannot be estimated by this imaging method itself. Topological sensitivity (TS) method is a data processing methodology that can be used to estimate the viscoelastic parameters of an object from vibration data. In this study, the concept of topological sensitivity is applied to interpret the vibroacoustography measurements for the purpose of lesion characterization. In the proposed approach, the topological sensitivity function, which signifies the variation of a given cost functional when an infinitesimal inclusion with trial material parameters is placed at the location of a point force, is formulated in terms of the adjoint field. The effectiveness of the resulting formula as a material indicator for lesion characterization is demonstrated by estimating the relative elastic parameters of a well-controlled neoprene sphere embedded in a tissue-mimicking phantom specimen.