A Study on the Effects of Depth-Dependent Power Loss on Speckle Statistics Estimation.

Characterization of the interference patterns observed in B-mode images (i.e., speckle statistics) is a valuable tool in tissue characterization.

A Systematized Review of Quantitative Ultrasound Based on First-Order Speckle Statistics.

Since the late 1970s, the speckle interference patterns ubiquitous in pulse-echo ultrasound images have been used to characterize subresolution tissue structures. During this time, new models, estimation methods, and processing techniques have proliferated, offering a wealth of recommendations for the task of tissue characterization. A literature review was performed to draw attention to these various methods and to critically track assumptions and gaps in knowledge.

Simulation of ultrasonic scattering from scatterer size distributions using Field II.

Quantitative analysis of radio frequency (RF) signals obtained from ultrasound scanners can yield objective parameters that are gaining clinical relevance as imaging biomarkers. These include the backscatter coefficient (BSC) and the effective scatterer diameter (ESD). Biomarker validation is typically performed in phantoms which do not provide the flexibility of systematic variation of scattering properties.

Homodyned K-Distribution Parameter Estimation in Quantitative Ultrasound: Autoencoder and Bayesian Neural Network Approaches.

Quantitative ultrasound (QUS) analyzes the ultrasound (US) backscattered data to find the properties of scatterers that correlate with the tissue microstructure. Statistics of the envelope of the backscattered radio frequency (RF) data can be utilized to estimate several QUS parameters. Different distributions have been proposed to model envelope data.

The Future Is Beyond Bright: The Evolving Role of Quantitative US for Fatty Liver Disease.

Nonalcoholic fatty liver disease (NAFLD) is a common cause of morbidity and mortality. Nonfocal liver biopsy is the historical reference standard for evaluating NAFLD, but it is limited by invasiveness, high cost, and sampling error. Imaging methods are ideally situated to provide quantifiable results and rule out other anatomic diseases of the liver.

Physics-Inspired Regularized Pulse-Echo Quantitative Ultrasound: Efficient Optimization With ADMM.

Pulse-echo quantitative ultrasound (PEQUS), which estimates the quantitative properties of tissue microstructure, entails estimating the average attenuation and the backscatter coefficient (BSC). Growing recent research has focused on the regularized estimation of these parameters. Herein, we make two contributions to this field: first, we consider the physics of the average attenuation and backscattering to devise regularization terms accordingly.

Recent Advances in Attenuation Estimation.

This chapter reviews some of the recent advances in the estimation of the local and the total attenuation, with an emphasis on reducing the bias and variance of the estimates. A special focus is put on describing the effect of power spectrum estimation on bias and variance, the introduction of regularization strategies, as well as on eliminating the need to use reference phantoms for compensating for system dependent effects.

Inter- and Intra-Operator Variability of Regularized Backscatter Quantitative Ultrasound for the Characterization of Breast Masses.

Objectives: Here we report on the intra- and inter-operator variability of the backscatter coefficient (BSC) estimated with a new low-variance quantitative ultrasound (QUS) approach applied to breast lesions in vivo.

Methods: Radiofrequency (RF) echo signals were acquired from 29 BIRADS 4 and 5 breast lesions in 2 sequential cohorts following 2 imaging protocols: cohort 1) radial and antiradial views, and cohort 2) short- and long-axis views. Protocol 2 was implemented after retraining and discussion on how to improve reproducibility.

A Geometric Model of Ultrasound Backscatter to Describe Microstructural Anisotropy of Tissue.

Methods to assess ultrasound backscatter anisotropy from clinical array transducers have recently been developed. However, they do not provide information about the anisotropy of microstructural features of the specimens. This work develops a simple geometric model, referred to as the , of backscatter coefficient anisotropy.

Multiscale Label-Free Imaging of Fibrillar Collagen in the Tumor Microenvironment.

With recent advances in cancer therapeutics, there is a great need for improved imaging methods for characterizing cancer onset and progression in a quantitative and actionable way. Collagen, the most abundant extracellular matrix protein in the tumor microenvironment (and the body in general), plays a multifaceted role, both hindering and promoting cancer invasion and progression. Collagen deposition can defend the tumor with immunosuppressive effects, while aligned collagen fiber structures can enable tumor cell migration, aiding invasion and metastasis.

Pulse-Echo Quantitative US Biomarkers for Liver Steatosis: Toward Technical Standardization.

Excessive liver fat (steatosis) is now the most common cause of chronic liver disease worldwide and is an independent risk factor for cirrhosis and associated complications. Accurate and clinically useful diagnosis, risk stratification, prognostication, and therapy monitoring require accurate and reliable biomarker measurement at acceptable cost. This article describes a joint effort by the American Institute of Ultrasound in Medicine (AIUM) and the RSNA Quantitative Imaging Biomarkers Alliance (QIBA) to develop standards for clinical and technical validation of quantitative biomarkers for liver steatosis.

Deep Estimation of Speckle Statistics Parametric Images.

Quantitative Ultrasound (QUS) provides important information about the tissue properties. QUS parametric image can be formed by dividing the envelope data into small overlapping patches and computing different speckle statistics such as parameters of the Nakagami and Homodyned K-distributions (HK-distribution). The calculated QUS parametric images can be erroneous since only a few independent samples are available inside the patches.

Robust Scatterer Number Density Segmentation of Ultrasound Images.

Quantitative ultrasound (QUS) aims to reveal information about the tissue microstructure using backscattered echo signals from clinical scanners. Among different QUS parameters, scatterer number density is an important property that can affect the estimation of other QUS parameters. Scatterer number density can be classified into high or low scatterer densities.

Shear wave dispersion as a potential biomarker for cervical remodeling during pregnancy: evidence from a non-human primate model.

Shear wave dispersion (variation of phase velocity with frequency) occurs in tissues with layered and anisotropic microstructure and viscous components, such as the uterine cervix. This phenomenon, mostly overlooked in previous applications of cervical Shear Wave Elasticity Imaging (SWEI) for preterm birth risk assessment, is expected to change drastically during pregnancy due to cervical remodeling. Here we demonstrate the potential of SWEI-based descriptors of dispersion as potential biomarkers for cervical remodeling during pregnancy.

Ultrasound Scatterer Density Classification Using Convolutional Neural Networks and Patch Statistics.

Quantitative ultrasound (QUS) can reveal crucial information on tissue properties, such as scatterer density. If the scatterer density per resolution cell is above or below 10, the tissue is considered as fully developed speckle (FDS) or underdeveloped speckle (UDS), respectively. Conventionally, the scatterer density has been classified using estimated statistical parameters of the amplitude of backscattered echoes.

Analytic Global Regularized Backscatter Quantitative Ultrasound.

Although a variety of techniques have been developed to reduce the appearance of B-mode speckle, quantitative ultrasound (QUS) aims at extracting the hidden properties of the tissue. Herein, we propose two novel techniques to accurately and precisely estimate two important QUS parameters, namely, the average attenuation coefficient and the backscatter coefficient. Both the techniques optimize a cost function that incorporates data and continuity constraint terms, which we call AnaLytical Global rEgularized BackscatteR quAntitative ultrasound (ALGEBRA).

A Pilot Study on Scatterer Density Classification of Ultrasound Images Using Deep Neural Networks.

Quantitative ultrasound estimates different intrinsic tissue properties, which can be used for tissue characterization. Among different tissue properties, the effective number of scatterers per resolution cell is an important parameter, which can be estimated by the echo envelope. Assuming the signal is stationary and coherent, if the number of scatterers per resolution cell is above approximately 10, envelope signal is considered to be fully developed speckle (FDS) and otherwise they are from low scatterer number density (LSND).

Regularized Estimation of Effective Scatterer Size and Acoustic Concentration Quantitative Ultrasound Parameters Using Dynamic Programming.

The objective of quantitative ultrasound (QUS) is to characterize tissue microstructure by parametrizing backscattered radiofrequency (RF) signals from clinical ultrasound scanners. Herein, we develop a novel technique based on dynamic programming (DP) to simultaneously estimate the acoustic attenuation, the effective scatterer size (ESS), and the acoustic concentration (AC) from ultrasound backscattered power spectra. This is achieved through two different approaches: (1) using a Gaussian form factor (GFF) and (2) using a general form factor (gFF) that is more flexible than the Gaussian form factor but involves estimating more parameters.

Optimization of Ultrasound Backscatter Spectroscopy to Assess Neurotoxic Effects of Anesthesia in the Newborn Non-human Primate Brain.

Studies in animal models have revealed that long exposures to anesthetics can induce apoptosis in the newborn and young developing brain. These effects have not been confirmed in humans because of the lack of a non-invasive, practical in vivo imaging tool with the ability to detect these changes. Following the successful use of ultrasound backscatter spectroscopy (UBS) to monitor in vivo cell death in breast tumors, we aimed to use UBS to assess the neurotoxicity of the anesthetic sevoflurane (SEVO) in a non-human primate (NHP) model.

Quantitative assessment of cervical softening during pregnancy with shear wave elasticity imaging: an longitudinal study.

We report here the results of a longitudinal study of cervix stiffness during pregnancy. Thirty women, ages ranging from 19 to 37 years, were scanned with ultrasound at five time points beginning at their normal first-trimester screening (8-13 weeks) through term pregnancy (nominally 40 week) using a clinical ultrasound imaging system modified with a special ultrasound transducer and system software. The system estimated the shear wave speed (its square proportional to the shear modulus under idealized conditions) in the cervix.

Personalized Breast Cancer Treatments Using Artificial Intelligence in Radiomics and Pathomics.

Progress in computing power and advances in medical imaging over recent decades have culminated in new opportunities for artificial intelligence (AI), computer vision, and using radiomics to facilitate clinical decision-making. These opportunities are growing in medical specialties, such as radiology, pathology, and oncology. As medical imaging and pathology are becoming increasingly digitized, it is recently recognized that harnessing data from digital images can yield parameters that reflect the underlying biology and physiology of various malignancies.

A Quantitative Ultrasound-Based Multi-Parameter Classifier for Breast Masses.

This manuscript reports preliminary results obtained by combining estimates of two or three (among seven) quantitative ultrasound (QUS) parameters in a model-free, multi-parameter classifier to differentiate breast carcinomas from fibroadenomas (the most common benign solid tumor). Forty-three patients scheduled for core biopsy of a suspicious breast mass were recruited. Radiofrequency echo signal data were acquired using clinical breast ultrasound systems equipped with linear array transducers.