Feasibility of Backscattering Coefficient Evaluation of Soft Tissue Using High-Frequency Annular Array Probe.

The objective of this work is to address the need for versatile and effective tissue characterization in abdominal ultrasound diagnosis using a simpler system. We evaluated the backscattering coefficient (BSC) of several tissue-mimicking phantoms utilizing three different ultrasonic probes: a single-element transducer, a linear array probe for clinical use, and a laboratory-made annular array probe. The single-element transducer, commonly used in developing fundamental BSC evaluation methods, served as a benchmark.

Biomechanical changes occur in myopic choroidal stroma and mirror those in the adjacent sclera.

Retina-derived growth signals relayed from the choroid to the sclera cause remodeling of the extracellular scleral matrix, resulting in myopic ocular elongation. However, to the best of our knowledge, no studies have assessed changes in choroidal stromal biomechanical properties during myopia progression. Here we utilized 7 µm-resolution scanning acoustic microscopy (SAM) to assess biomechanical properties (bulk modulus (K) and mass density (rho)) of choroidal stroma from guinea pig eyes with form-deprivation (FD) induced myopia.

In-vivo high-frequency quantitative ultrasound-derived parameters of the anterior sclera correlated with level of myopia and presence of staphyloma.

Background: A high-frequency point-of-care (POC) ultrasound instrument was used to evaluate the microstructural and biomechanical properties of the anterior sclera in vivo using parameters computed from quantitative ultrasound (QUS) methods.

Methods: In this cross-sectional study, both eyes of 85 enrolled patients were scanned with the POC instrument and ultrasound data were processed to obtain QUS parameters. Pearson correlation and multi-linear regression were used to identify relationships between QUS parameters and refractive error (RE) or axial length.

Relationship between transmission/reception conditions of high-frequency plane wave compounding and evaluation accuracy of extended amplitude envelope statistics.

The double-Nakagami (DN) model provides a method for analyzing the amplitude envelope statistics of quantitative ultrasound (QUS). In this study, the relationship between the sound field characteristics and the robustness of QUS evaluation was evaluated using five HF linear array probes and tissue-mimicking phantoms. Compound plane-wave imaging (CPWI) was used to acquire echo data.

Machine Independence of Ultrasound-Based Quantification of Vitreous Echodensities.

Purpose: Quantitative ultrasound (QUS) provides objective indices of Vision Degrading Myodesopsia (VDM) that correlate with contrast sensitivity (CS). To date, QUS methods were only tested on a single ultrasound machine. Here, we evaluate whether QUS measurements are machine independent.

Advanced Topics in Quantitative Acoustic Microscopy.

Quantitative acoustic microscopy (QAM) reconstructs two-dimensional (2D) maps of the acoustic properties of thin tissue sections. Using ultrahigh frequency transducers (≥ 100 MHz), unstained, micron-thick tissue sections affixed to glass are raster scanned to collect radiofrequency (RF) echo data and generate parametric maps with resolution approximately equal to the ultrasound wavelength. 2D maps of speed of sound, mass density, acoustic impedance, bulk modulus, and acoustic attenuation provide unique and quantitative information that is complementary to typical optical microscopy modalities.

High-frequency ultrasound point-of-care device to quantify myopia-induced microstructural changes in the anterior sclera.

Purpose: To develop a point-of-care (POC) device using high-frequency ultrasound (US) for evaluating microstructural changes in the anterior sclera associated with myopia.

Methods: The proposed POC device must satisfy four primary requirements for effective clinical use: the measurement component is handheld; the software must be simple and provide real-time feedback; patient safety and health data security requirements set forth by relevant governing bodies must be satisfied and the measurement data must have sufficient signal-to-noise ratio (SNR) and repeatability. Radiofrequency (RF) echo data acquired by the POC device will be processed using our quantitative US methods to characterise tissue microstructure and biomechanical properties.

RECURRENT FLOATERS AFTER LIMITED VITRECTOMY FOR VISION DEGRADING MYODESOPSIA.

Purpose: Limited vitrectomy improves vision degrading myodesopsia, but the incidence of recurrent floaters postoperatively is not known. We studied patients with recurrent central floaters using ultrasonography and contrast sensitivity (CS) testing to characterize this subgroup and identify the clinical profile of patients at risk of recurrent floaters.

Methods: A total of 286 eyes (203 patients, 60.

Classification of Metastatic Lymph Nodes In Vivo Using Quantitative Ultrasound at Clinical Frequencies.

Quantitative ultrasound (QUS) methods characterizing the backscattered echo signal have been of use in assessing tissue microstructure. High-frequency (30 MHz) QUS methods have been successful in detecting metastases in surgically excised lymph nodes (LNs), but limited evidence exists regarding the efficacy of QUS for evaluating LNs in vivo at clinical frequencies (2-10 MHz). In this study, a clinical scanner and 10-MHz linear probe were used to collect radiofrequency (RF) echo data of LNs in vivo from 19 cancer patients.

Biomechanical changes in myopic sclera correlate with underlying changes in microstructure.

Myopia alters the microstructural and biomechanical properties of the posterior sclera, which is characterized as a layered structure with potentially different inter-layer collagen fibril characteristics. Scanning acoustic microscopy (SAM) has been used to investigate how the micron-scale bulk mechanical properties of the posterior sclera are affected by myopia. Other investigators have employed second harmonic generation (SHG) imaging to characterize the collagen microstructure of tissues.

A data-driven approach to characterizing nonlinear elastic behavior of soft materials.

The Autoprogressive (AutoP) method is a data-driven inverse method that leverages finite element analysis (FEA) and machine learning (ML) techniques to build constitutive relationships from measured force and displacement data. Previous applications of AutoP in tissue-like media have focused on linear elastic mechanical behavior as the target object is infinitesimally compressed. In this study, we extended the application of AutoP in characterizing nonlinear elastic mechanical behavior as the target object undergoes finite compressive deformation.

Experimental Validation of Perfusion Imaging With HOSVD Clutter Filters.

Novel pulsed-Doppler methods for perfusion imaging are validated using dialysis cartridges as perfusion phantoms. Techniques that were demonstrated qualitatively at 24 MHz, in vivo, are here examined quantitatively at 5 and 12.5 MHz using phantoms with the blood-mimicking fluid flow within cellulose microfibers.

Physics-guided machine learning for 3-D quantitative quasi-static elasticity imaging.

We present a 3D extension of the Autoprogressive Method (AutoP) for quantitative quasi-static ultrasonic elastography (QUSE) based on sparse sampling of force-displacement measurements. Compared to current model-based inverse methods, our approach requires neither geometric nor constitutive model assumptions. We build upon our previous report for 2D QUSE and demonstrate the feasibility of recovering the 3D linear-elastic material property distribution of gelatin phantoms under compressive loads.

Data-Driven Elasticity Imaging Using Cartesian Neural Network Constitutive Models and the Autoprogressive Method.

Quasi-static elasticity imaging techniques rely on model-based mathematical inverse methods to estimate mechanical parameters from force-displacement measurements. These techniques introduce simplifying assumptions that preclude exploration of unknown mechanical properties with potential diagnostic value. We previously reported a data-driven approach to elasticity imaging using artificial neural networks (NNs) that circumvents limitations associated with model-based inverse methods.

An information-based machine learning approach to elasticity imaging.

An information-based technique is described for applications in mechanical property imaging of soft biological media under quasi-static loads. We adapted the Autoprogressive method that was originally developed for civil engineering applications for this purpose. The Autoprogressive method is a computational technique that combines knowledge of object shape and a sparse distribution of force and displacement measurements with finite-element analyses and artificial neural networks to estimate a complete set of stress and strain vectors.

Prediction and suppression of HIFU-induced vessel rupture using passive cavitation detection in an ex vivo model.

Background: Occlusion of blood vessels using high-intensity focused ultrasound (HIFU) is a potential treatment for arteriovenous malformations and other neurovascular disorders. However, attempting HIFU-induced vessel occlusion can also cause vessel rupture, resulting in hemorrhage. Possible rupture mechanisms include mechanical effects of acoustic cavitation and heating of the vessel wall.

Relations between acoustic cavitation and skin resistance during intermediate- and high-frequency sonophoresis.

Enhanced skin permeability is known to be achieved during sonophoresis due to ultrasound-induced cavitation. However, the mechanistic role of cavitation during sonophoresis has been extensively investigated only for low-frequency (LFS, <100 kHz) applications. Here, mechanisms of permeability-enhancing stable and inertial cavitation were investigated by passively monitoring subharmonic and broadband emissions arising from cavitation isolated within or external to porcine skin in vitro during intermediate- (IFS, 100-700 kHz) and high-frequency sonophoresis (HFS, >1 MHz).