Estimation of polydispersity in aggregating red blood cells by quantitative ultrasound backscatter analysis

Effects of Size Polydispersity and Dense Media on Quantitative Ultrasound Estimates

Quantitative ultrasound (QUS) techniques based on the backscatter coefficient (BSC) aim to characterize the scattering properties of biological tissues. A scattering model is fit to the measured BSC, and the fitted QUS parameters can provide local tissue microstructure, namely, scatterer size and acoustic concentration. However, these techniques may fail to provide a correct description of tissue microstructure when the medium is polydisperse and/or dense. The objective of this study is to investigate the effects of scatterer size polydispersity in sparse or dense media on the QUS estimates. Four scattering models (i.e., the monodisperse and polydisperse sparse models, and the monodisperse and polydisperse concentrated models based on the structure factor) are compared to assess their accuracy and reliability in quantifying the QUS estimates. Simulations are conducted with different scatterer size distributions for sparse, moderately dense, and dense media (volume fractions of 1%, 20%, and 73%, respectively). The QUS parameters are estimated by using model-based inverse methods at different center frequencies between 8 and 50 MHz. Experimental data are also analyzed using colon adenocarcinoma HT29 cell pellet biophantoms to further validate the results obtained from simulations at the volume fraction of 73%. Our findings reveal that the choice of scattering model has a significant impact on the accuracy of QUS estimates. For sufficiently high frequencies and dense media, the polydisperse concentrated model outperforms the other models and enables more accurate quantification. Furthermore, our results contribute to advancing our understanding of the complexities associated with scatterer size polydispersity and dense media in spectral-based QUS techniques.

Quantitative evaluation of rat sciatic nerve degeneration using high-frequency ultrasound

In this study, we evaluated the utility of using high-frequency ultrasound to non-invasively track the degenerative process in a rat model of peripheral nerve injury. Primary analyses explored spatial and temporal changes in quantitative backscatter coefficient (BSC) spectrum-based outcomes and B-mode textural outcomes, using gray level co-occurrence matrices (GLCMs), during the progressive transition from acute to chronic injury. As secondary analyses, correlations among GLCM and BSC spectrum-based parameters were evaluated, and immunohistochemistry were used to suggest a structural basis for ultrasound outcomes. Both mean BSC spectrum-based and mean GLCM-based measures exhibited significant spatial differences across presurgical and 1-month/2-month time points, distal stumps enclosed proximity to the injury site being particularly affected. The two sets of parameters sensitively detected peripheral nerve degeneration at 1-month and 2-month post-injury, with area under the receiver operating charactersitic curve > 0.8 for most parameters. The results also indicated that the many BSC spectrum-based and GLCM-based parameters significantly correlate with each other, and suggested a common structural basis for a diverse set of quantitative ultrasound parameters. The findings of this study suggest that BSC spectrum-based and GLCM-based analysis are promising non-invasive techniques for diagnosing peripheral nerve degeneration.

Quantitative ultrasound techniques for assessing thermal ablation: Measurement of the backscatter coefficient from ex vivo human liver

BACKGROUND

Understanding the changes occurring in biological tissue during thermal ablation is at the heart of many current challenges in both therapy and medical imaging research.

PURPOSE

The objective of this work is to quantitatively interpret the scattering response of human liver samples, before and after thermal ablation. We report acoustic measurements performed involving n = 21 human liver samples. Thermal ablation is achieved at temperatures between 45 and 80°C and quantification of the irreversible changes in acoustic attenuation and Backscattering Coefficient (BSC) is reported, with a particular attention to the latter.

METHODS

Both attenuation coefficient and BSCs were measured in the frequency range from 10 to 52 MHz. Scans were performed before heating and after cooling down. Attenuation coefficients were calculated using spectral difference method and BSC estimated using the reference phantom method.

RESULTS

Strong increases of attenuation coefficients and BSCs with heating temperature were observed. Quantitative ultrasonic parameters obtained with the polydisperse structure factor model (poly-SFM)are compared to histological observations and seen to be close to hepatocyte mean diameter (HMD).

CONCLUSIONS

The results presented in this study provide a description of the impact of thermal ablation in human liver tissue on acoustic attenuation and the BSC. For the first time, quantitative agreement between the Effective Scatterer Diameter (ESD) estimated from BSC and HMD was shown, highlighting the important role of cellular network in the scattering response of the medium. This core result is an important step toward the determination of the nature of scattering sources in biological tissues.

Influence of storage and buffer composition on the mechanical behavior of flowing red blood cells

On-chip study of blood flow has emerged as a powerful tool to assess the contribution of each component of blood to its overall function. Blood has indeed many functions, from gas and nutrient transport to immune response and thermal regulation. Red blood cells play a central role therein, in particular through their specific mechanical properties, which directly influence pressure regulation, oxygen perfusion, or platelet and white cell segregation toward endothelial walls. As the bloom of in-vitro studies has led to the apparition of various storage and sample preparation protocols, we address the question of the robustness of the results involving cell mechanical behavior against this diversity. The effects of three conservation media (EDTA, citrate, and glucose-albumin-sodium-phosphate) and storage time on the red blood cell mechanical behavior are assessed under different flow conditions: cell deformability by ektacytometry, shape recovery of cells flowing out of a microfluidic constriction, and cell-flipping dynamics under shear flow. The impact of buffer solutions (phosphate-buffered saline and density-matched suspension using iodixanol/Optiprep) are also studied by investigating individual cell-flipping dynamics, relative viscosity of cell suspensions, and cell structuration under Poiseuille flow. Our results reveal that storing blood samples up to 7 days after withdrawal and suspending them in adequate density-matched buffer solutions has, in most experiments, a moderate effect on the overall mechanical response, with a possible rapid evolution in the first 3 days after sample collection.

Repeatability, Reproducibility and Sources of Variability in the Assessment of Backscatter Coefficient and Texture Parameters from High-Frequency Ultrasound Acquisitions in Human Median Nerve

Ultrasound (US) is an increasingly prevalent and effective diagnostic modality for neuromuscular imaging. Gray-scale B-mode imaging has been the dominant US approach to evaluating nerves qualitatively or making morphometric measurements of nerves, providing important insights into pathological changes for conditions such as carpal tunnel syndrome. Among more recent ultrasound strategies, high-frequency ultrasound (often defined as >15 MHz for clinical applications), quantitative ultrasound and image textural analysis offer promising enhancements for improved and more objective approaches to nerve imaging. In this study, we evaluated the repeatability and reproducibility of backscatter coefficient (BSC) and imaging texture features extracted by gray-level co-occurrence matrices (GLCMs) in homogeneous tissue-mimicking reference phantoms and in median nerves in the wrists of healthy participants. We also investigated several practical sources of variability in the assessment of quantitative parameters, including influences of operators, and participant-to-participant variability. Overall, BSC- and GLCM-based outcomes are highly repeatable and reproducible after operator training, based on measurement of descriptive statistics, repeatability coefficient (RC) and reproducibility coefficient recommended by Quantitative Imaging Biomarker Alliance (QIBA RDC). GLCM parameters appear more reproducible and repeatable than BSC-based parameters in healthy participants in vivo. However, such variability noted here must be compared with the value ranges and variability of the results in pathological nerves, including median nerves afflicted by trauma, overuse syndromes such as carpal tunnel syndrome and after surgical repair.

Classification of red blood cell aggregation using empirical wavelet transform analysis of ultrasonic radiofrequency echo signals

Grading red blood cell (RBC) aggregation is important for the early diagnosis and prevention of related diseases such as ischemic cardio-cerebrovascular disease, type II diabetes, deep vein thrombosis, and sickle cell disease. In this study, a machine learning technique based on an adaptive analysis of ultrasonic radiofrequency (RF) echo signals in blood is proposed, and its feasibility for classifying RBC aggregation is explored. Using an adaptive empirical wavelet transform (EWT) analysis, the ultrasonic RF signals are decomposed into a series of empirical mode functions (EMFs); then, dominant empirical mode functions (DEMFs) are selected from the series. Six statistical characteristics, including the mean, variance, median, kurtosis, root mean square (RMS), and skewness are calculated for the locally normalized DEMFs, aiming to form primary feature vectors. Random forest (RDF) and support vector machine (SVM) classifiers are trained with the given feature vectors to obtain prediction models for RBC classification. Ultrasonic RF echo signals are acquired from five groups of six types of porcine blood samples with average numbers of aggregated RBCs of 1.04, 1.20, 1.83, 2.31, 2.72, and 4.28, respectively, to test the classification performance of the proposed method. The best subset with regard to the variance, kurtosis, and RMS is determined according to the maximum accuracy based on the RDF and SVM classifiers. The classification accuracies are 84.03 ± 3.13% for the RDF classifier, and 85.88 ± 2.99% for the SVM classifier. The mean classification accuracy of the SVM classifier is 1.85% better than that of the RDF classifier. In conclusion, the machine learning method is useful for the discrimination of varying degrees of RBC aggregation, and has potential for use in characterizing and monitoring the RBC aggregation in vessels.

Numerical investigations of anisotropic structures of red blood cell aggregates on ultrasonic backscattering

Although quantitative ultrasound techniques based on the parameterization of the backscatter coefficient (BSC) have been successfully applied to blood characterization, theoretical scattering models assume blood as an isotropic scattering medium. However, the red blood cell (RBC) aggregates form anisotropic structures such as rouleaux. The present study proposes an anisotropic formulation of the effective medium theory combined with the local monodisperse approximation (EMTLMA) that considers perfectly aligned prolate-shaped aggregates. Theoretical BSC predictions were first compared with computer simulations of BSCs in a forward problem framework. Computer simulations were conducted for perfectly aligned prolate-shaped aggregates and more complex configurations with partially aligned prolate-shaped aggregates for which the size and orientation of RBC aggregates were obtained from blood optical observations. The isotropic and anisotropic EMTLMA models were then compared in an inverse problem framework to estimate blindly the structural parameters of RBC aggregates from the simulated BSCs. When considering the isotropic EMTLMA, the use of averaged BSCs over different insonification directions significantly improves the estimation of aggregate structural parameters. Overall, the anisotropic EMTLMA was found to be superior to the isotropic EMTLMA in estimating the scatterer volume distribution. These results contribute to a better interpretation of scatterer size estimates for blood characterization.

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.

Ultrasonic backscattering and microstructure in sheared concentrated suspensions

Quantitative ultrasound techniques based on the parametrization of the backscatter coefficient (BSC) are used to characterize concentrated particle suspensions. Specifically, a scattering model is fit to the measured BSC and the fit parameters can provide local suspension properties. The scattering models generally assume an isotropic microstructure (i.e., spatial organization) of the scatterers, whereas the sheared concentrated suspensions can develop an anisotropic microstructure. This paper studied the influence of the shear-induced anisotropic microstructure of concentrated suspensions on the ultrasonic backscattering. Experiments were conducted on suspensions of polymethylmetacrylate spheres (5.8 μm in radius) sheared in a Couette flow device to obtain anisotropic microstructure and then mixed by hand to obtain isotropic microstructure. Experimental structure factors that are related to the spatial distribution of sphere positions were obtained by comparing the BSCs of one concentrated and one diluted suspension. Finally, Stokesian dynamics numerical simulations of sheared concentrated suspensions are used to determine the pair correlation function, which is linked to the Fourier transform of the structure factor. The experimental structure factors are found to be in good agreement with numerical simulations. The numerical simulation demonstrates that the angular-dependent BSCs and structure factors are caused by the shear-induced anisotropic microstructure within the suspension.