Modeling the thermo-acoustic effects of thermal-dependent speed of sound and acoustic absorption of biological tissues during focused ultrasound hyperthermia

Investigation of nonlinear photoacoustic microscopy using a low-cost infrared lamp

Nonlinear photoacoustic microscopy (PAM) is a novel approach to enhance contrast and resolution. In this study, a low-cost infrared (IR) lamp as a simple approach for nonlinear PAM is demonstrated. Numerical simulations are first performed to verify the nonlinear photoacoustic effect under steady heating for two cases: (a) Differentiation of absorbers with different Grüneisen coefficients; (b) enhancement of photoacoustic amplitude. Then, sets of experiments are conducted to experimentally demonstrate our proposed approach: (a) Longitudinal monitoring of photoacoustic A-line signals from two samples, porcine tissue ex vivo and hemoglobin and indocyanine green (ICG) solutions in tubes in vitro for demonstrating the above-mentioned two cases; (b) PAM imaging of hemoglobin and ICG solutions in tubes before and after IR lamp heating. Different signal change and amplitude enhancement are observed in different demonstrations, showing the efficacy of the proposed approach. By virtue of cost-effectiveness and decent performance, our work facilitates nonlinear PAM studies.

Multiphysics Analysis of Ultrasonic Shock Wave Lithotripsy and Side Effects on Surrounding Tissues

Background:

Today, the most common method for kidney stone therapy is extracorporeal shock wave lithotripsy. Current research is a numerical simulation of kidney stone fragmentation via ultrasonic shock waves. Most numerical studies in lithotripsy have been carried out using the elasticity or energy method and neglected the dissipation phenomenon. In the current study, it is solved by not only the linear acoustics equation, but also the Westervelt acoustics equation which nonlinearity and dissipation are involved.

Objective:

This study is to compare two methods for simulation of shock wave lithotripsy, clarifying the effect of shock wave profiles and stones’ material, and investigating side effects on surrounding tissues

Material and Methods:

Computational study is done using COMSOL Multiphysics, commercial software based on the finite element method. Nonlinear governing equations of acoustics, elasticity and bioheat-transfer are coupled and solved.

Results:

A decrease in the rise time of shock wave leads to increase the produced acoustic pressure and enlarge focus region. The shock wave damages kidney tissues in both linear and nonlinear simulation but the damage due to high temperature is very negligible compared to the High Intensity Focused Ultrasound (HIFU).

Conclusion:

Disaffiliation of wave nonlinearity causes a high incompatibility with reality. Stone’s material is an important factor, affecting the fragmentation

Modeling Focused-Ultrasound Response for Non-Invasive Treatment Using Machine Learning

The interactions between body tissues and a focused ultrasound beam can be evaluated using various numerical models. Among these, the Rayleigh-Sommerfeld and angular spectrum methods are considered to be the most effective in terms of accuracy. However, they are computationally expensive, which is one of the underlying issues of most computational models. Typically, evaluations using these models require a significant amount of time (hours to days) if realistic scenarios such as tissue inhomogeneity or non-linearity are considered. This study aims to address this issue by developing a rapid estimation model for ultrasound therapy using a machine learning algorithm. Several machine learning models were trained on a very-large dataset (19,227 simulations), and the performance of these models were evaluated with metrics such as Root Mean Squared Error (RMSE), R-squared (R²), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). The resulted random forest provides superior accuracy with an R² value of 0.997, an RMSE of 0.0123, an AIC of -82.56, and a BIC of -81.65 on an external test dataset. The results indicate the efficacy of the random forest-based model for the focused ultrasound response, and practical adoption of this approach will improve the therapeutic planning process by minimizing simulation time.

Basic concept and clinical applications of quantitative ultrasound (QUS) technologies

In the field of clinical ultrasound, the full digitalization of diagnostic equipment in the 2000s enabled the technological development of quantitative ultrasound (QUS), followed by multiple diagnostic technologies that have been put into practical use in recent years. In QUS, tissue characteristics are quantified and parameters are calculated by analyzing the radiofrequency (RF) echo signals returning to the transducer. However, the physical properties (and pathological level structure) of the biological tissues responsible for the imaging features and QUS parameters have not been sufficiently verified as there are various conditions for observing living tissue with ultrasound and inevitable discrepancies between theoretical and actual measurements. A major issue of QUS in clinical application is that the evaluation results depend on the acquisition conditions of the RF echo signal as the source of the image information, and also vary according to the model of the diagnostic device. In this paper, typical examples of QUS techniques for evaluating attenuation, speed of sound, amplitude envelope characteristics, and backscatter coefficient in living tissues are introduced. Exemplary basic research and clinical applications related to these technologies, and initiatives currently being undertaken to establish the QUS method as a true tissue characterization technology, are also discussed.