Quantitative Characterization of Tissue Microstructure in Concentrated Cell Pellet Biophantoms Based on the Structure Factor Model

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 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.

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.

RESULTS

All stated requirements have been met in the developed POC device. The high-frequency transducer is housed in a custom, 3D-printed, pen-like holder that allows for easy measurements of the anterior sclera. Custom software provides a simple interface for data acquisition, real-time data display and secure data storage. Exposimetry measurements of the US pressure field indicate device compliance with United States Food and Drug Administration limits for ophthalmic US. In vivo measurements on a volunteer suggest the RF data SNR and acquisition consistency are suitable for quantitative analysis.

CONCLUSIONS

A fully functioning POC device using high-frequency US has been created for evaluating the microstructure of the anterior sclera. Planned studies using the POC device to scan the eyes of myopia patients will help clarify how the anterior sclera microstructure may be affected by myopia. If effective, this portable, inexpensive and user-friendly system could be an important part of routine eye examinations.

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. QUS methods were applied to estimate parameters derived from the backscatter coefficient (BSC) and statistics of the envelope-detected RF signal. QUS parameters were used to train classifiers based on linear discriminant analysis (LDA) and support vector machines (SVMs). Two BSC-based parameters, scatterer diameter and acoustic concentration, were the most effective for accurately detecting metastatic LNs, with both LDA and SVMs achieving areas under the receiver operating characteristic (AUROC) curve ≥0.94. A strategy of classifying LNs based on the echo frame with the highest cancer probability improved performance to 88% specificity at 100% sensitivity (AUROC = 0.99). These results provide encouraging evidence that QUS applied at clinical frequencies may be effective at accurately identifying metastatic LNs in vivo, helping in diagnosis while reducing unnecessary biopsies and surgical treatments.

Extracting Quantitative Ultrasonic Parameters from the Backscatter Coefficient

The ultrasonic backscatter coefficient (BSC) is a fundamental quantitative ultrasound (QUS) parameter that contains rich information about the underlying tissue. Deriving parameters from the BSC is essential for fully utilizing the information contained in BSC for tissue characterization. In this chapter, we review two primary approaches for extracting parameters from the BSC versus frequency curve: the model-based approach and the model-free approach, focusing on the model-based approach, where a scattering model is fit to the observed BSC to yield model parameters. For this approach, we will attempt to unite commonly used models under a coherent theoretical framework. We will focus on the underlying assumptions and conditions for various BSC models. Computer code is provided to facilitate the use of some of the models. The strengths and weaknesses of various models are also discussed.

Ultrasound Scattering From Cell-Pellet Biophantoms and Ex Vivo Tumors Provides Insight Into the Cellular Structure Involved in Scattering

The histologically identifiable cellular structure(s) involved in ultrasonic scattering is(are) yet to be uniquely identified. The study quantifies six possible cellular scattering parameters, namely, cell and nucleus radii and their respective cell and nucleus volume fractions as well as a combination of cell and nucleus radii and their volume fraction. The six cellular parameters are each derived from four cell lines (4T1, JC, LMTK, and MAT) and two tissue types (cell-pellet biophantom and ex vivo tumor). Optical histology and quantitative ultrasound (QUS), both independent approaches, are used to yield these cellular parameters. QUS scatterer parameters are experimentally determined using two ultrasonic scattering models: the spherical Gaussian model (GM) and the structure factor model (SFM) to yield insight about scattering from nuclei only and cells only. GM is a classical ultrasonic scattering model to evaluate QUS parameters and is well adapted for diluted media. SFM is adapted for dense media to estimate reasonably well scatterer parameters of cellular structures from ex vivo tissue. Nucleus and cell radii and volume fractions are measured optically from histology. They were used as inputs to calculate BSC for scattering from cells, nuclei, and both cells and nuclei. The QUS-derived scatterers (radii and volume fractions) distributions were then compared to the optical histology scatterer parameters derived from these calculated BSCs. The results suggest scattering from cells only (LMTK and MAT) or both cells and nuclei (4T1 and JC) for cell-pellet biophantoms and scattering from nuclei only for tumors.

Quantifying scattering from dense media using two-dimensional impedance maps

A better understanding of ultrasound scattering in a three-dimensional (3D) medium can provide more accurate methods for ultrasound tissue characterization. The possibility of using two-dimensional impedance maps (2DZMs) based on correlation coefficients has shown promise in the case of isotropic and sparse medium [Luchies and Oelze, J. Acoust. Soc. Am. 139, 1557-1564 (2016)]. The present study investigates the use of 2DZMs in order to quantify 3D scatterer properties of dense media from two-dimensional (2D) histological slices. Two 2DZM approaches were studied: one based on the correlation coefficient and the other based on the 2D Fourier transform of 2DZMs. Both 2DZM approaches consist in estimating the backscatter coefficient (BSC) from several 2DZMs, and then the resulting BSC was fit to the theoretical polydisperse structure factor model to yield 3D scatterer properties. Simulation studies were performed to evaluate the ability of both 2DZM approaches to quantify scattering of a 3D medium containing randomly distributed polydisperse spheres or monodisperse ellipsoids. Experimental studies were also performed using the histology photomicrographs obtained from HT29 cell pellet phantoms. Results demonstrate that the 2DZM Fourier transform-based approach was more suitable than the correlation coefficient-based approach for estimating scatterer properties when using a small number of 2DZMs.

Improved evaluation of backscatter characteristics of soft tissue using high-frequency annular array

Clinical ultrasound is widely used for quantitative diagnosis. To clarify the relationship between anatomical and acoustic properties, high resolution imaging using high-frequency ultrasound (HFU) is required. However, when tissue properties are evaluated using HFU, the depth of field (DOF) is limited. To overcome this problem, an annular array transducer, which has a simple structure and produces high-quality images, is applied to HFU measurement. In previous phantom experiments, we demonstrated that the HFU annular array extends the DOF compared to that of a single-element transducer for quantitative ultrasound (QUS) analysis. Here, we extend that work by applying QUS methods to an ex vivo rat liver. The present study demonstrates that an annular array extends the region and improves the resolution for tissue characterization for an excised healthy rat liver. Amplitude envelope statistics and spectral-based analysis are used as QUS methods.

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.

Quantitative assessment of media concentration using the Homodyned K distribution

The Homodyned K distribution has been used successfully as a tool in the ultrasound characterization of sparse media, where the scatterer clustering parameter α accurately discriminates between media with different numbers of scatterers per resolution cell. However, as the number of scatterers increases and the corresponding amplitude statistics become Rician, the reliability of the α estimates decreases rapidly. In the present study, we assess the usefulness of α for the characterization of both sparse and concentrated media, using simulated independent and identically distributed (i.i.d.) samples from Homodyned K distributions, ultrasound images of media with up to 68 scatterers per resolution cell and ultrasound signals acquired from particle phantoms with up to 101 scatterers per resolution cell. All parameter estimates are obtained using the XU estimator (Destrempes et al., 2013). Results suggest that the parameter α can be used to distinguish between media with up to 40 scatterers per resolution cell at 22 MHz, provided that parameter estimation can be performed on very large sample sizes (i.e., >10,000 i.i.d. samples).

Probing the Cellular Size Distribution in Cell Samples Undergoing Cell Death

A polydisperse scattering model adapted for concentrated medium, namely the polydisperse structure factor model, was examined to explain the backscatter coefficients (BSCs) measured from packed cell samples undergoing cell death. Cell samples were scanned using high-frequency ultrasound in the 10-42 MHz bandwidth. A parameter estimation procedure was proposed to estimate the volume fraction and the relative impedance contrast that could explain the changes in BSC pattern by considering the actual change in cellular size distribution. Quantitative ultrasound parameters were estimated and related to the percentage of dead cells determined by flow cytometry. The standard deviation of scatterer size distribution extracted from the polydisperse structure factor model and the spectral intercept were found to be strongly correlated to the percentage of dead cells (r² = 0.79 and r² = 0.72, respectively). This study contributes to the understanding of ultrasonic scattering from cells undergoing cell death toward the monitoring of cancer therapy.

Quantitative Ultrasound in Ex Vivo Fibrotic Rabbit Livers

Liver fibrosis is the common result of chronic liver disease. Diagnosis and grading liver fibrosis for patient management is mainly based on blood tests and hepatic puncture-biopsy, which is particularly invasive. Quantitative ultrasound (QUS) techniques provide insight into tissue microstructure and are based on the frequency-based analysis of the signals from biologic tissues. This study aims to quantify how spectral-based QUS parameters change with fibrosis grade. The changes in QUS parameters of healthy and fibrotic rabbit liver samples were investigated and were compared with the changes in liver stiffness, using shear wave elastography. Overall, the acoustic concentration was found to decrease with increasing fibrosis grade, and the effective scatterer size was found to be higher in fibrotic livers when compared with normal liver. The result of this study indicates that the combination of three QUS parameters (stiffness, effective scatterer size and acoustic concentration) provides the best classification performance, especially for classifying healthy and fibrotic livers.

High-Frequency Quantitative Ultrasound for Imaging Prostate Cancer Using a Novel Micro-Ultrasound Scanner

Currently, biopsies guided by transrectal ultrasound (TRUS) are the only method for definitive diagnosis of prostate cancer. Studies by our group suggest that quantitative ultrasound (QUS) could provide a more sensitive means of targeting biopsies and directing focal treatments to cancer-suspicious regions in the prostate. Previous studies have utilized ultrasound signals at typical clinical frequencies, i.e., in the 6-MHz range. In the present study, a 29-MHz, TRUS, micro-ultrasound system and transducer (ExactVu micro-ultrasound, Exact Imaging, Markham, Canada) was used to acquire radio frequency data from 163 patients immediately before 12-core biopsy procedures, comprising 1956 cores. These retrospective data are a subset of data acquired in an ongoing, multisite, 2000-patient, randomized, clinical trial (clinicaltrials.gov NCT02079025). Spectrum-based QUS estimates of effective scatter diameter (ESD), effective acoustic concentration (EAC), midband (M), intercept (I) and slope (S) as well as envelope statistics employing a Nakagami distribution were used to train linear discriminant classifiers (LDCs) and support vector machines (SVMs). Classifier performance was assessed using area-under-the-curve (AUC) values obtained from receiver operating characteristic (ROC) analyses with 10-fold cross validation. A combination of ESD and EAC parameters resulted in an AUC value of 0.77 using a LDC. When Nakagami-µ or prostate-specific antigen (PSA) values were added as features, the AUC value increased to 0.79. SVM produced an AUC value of 0.77, using a combination of envelope and spectral QUS estimates. The best classification produced an AUC value of 0.81 using an LDC when combining envelope statistics, PSA, ESD and EAC. In a previous study, B-mode-based scoring and evaluation using the PRI-MUS protocol produced a maximal AUC value of 0.74 for higher Gleason-score values (GS >7) when read by an expert. Our initial results with AUC values of 0.81 are very encouraging for developing a new, predominantly user-independent, prostate-cancer, risk-assessing tool.

A Method for Stereological Determination of the Structure Function From Histological Sections of Isotropic Scattering Media

The frequency-dependent ultrasonic backscatter coefficient (BSC) from tissues, a fundamental parameter estimated by quantitative ultrasound (QUS) techniques, contains microstructure information useful for tissue characterization. To extract the microstructure information from the BSC, the tissue under investigation is often modeled as a collection of discrete scatterers embedded in a homogeneous background. From a discrete scatterer point of view, the BSC is dependent on not only the properties of individual scatterers relative to the background but also the scatterer spatial arrangement [described by the structure function (SF)]. Recently, the 2-D SF was computed from histological tissue sections, and was shown to be related to the volumetric SF extracted from QUS measurements. In this paper, a stereological method is proposed to extract the volumetric (3-D) SF from 2-D histological tissue sections. Simulations and experimental cell pellet biophantom studies were conducted to evaluate the proposed method. Simulation results verified the proposed method. Experimental results showed that the volumetric SF extracted using the proposed method had a significantly better agreement with the QUS-extracted SF than did the 2-D SF extracted in the previous study. The proposed stereological approach provides a useful tool for predicting the SF from histology.

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

Quantitative ultrasound techniques based on the backscatter coefficient (BSC) have been commonly used to characterize red blood cell (RBC) aggregation. Specifically, a scattering model is fitted to measured BSC and estimated parameters can provide a meaningful description of the RBC aggregates' structure (i.e., aggregate size and compactness). In most cases, scattering models assumed monodisperse RBC aggregates. This study proposes the Effective Medium Theory combined with the polydisperse Structure Factor Model (EMTSFM) to incorporate the polydispersity of aggregate size. From the measured BSC, this model allows estimating three structural parameters: the mean radius of the aggregate size distribution, the width of the distribution, and the compactness of the aggregates. Two successive experiments were conducted: a first experiment on blood sheared in a Couette flow device coupled with an ultrasonic probe, and a second experiment, on the same blood sample, sheared in a plane-plane rheometer coupled to a light microscope. Results demonstrated that the polydisperse EMTSFM provided the best fit to the BSC data when compared to the classical monodisperse models for the higher levels of aggregation at hematocrits between 10% and 40%. Fitting the polydisperse model yielded aggregate size distributions that were consistent with direct light microscope observations at low hematocrits.

Effects of Signal Saturation on QUS Parameter Estimates Based on High-Frequency-Ultrasound Signals Acquired From Isolated Cancerous Lymph Nodes

Choosing an appropriate dynamic range (DR) for acquiring radio frequency (RF) data from a high-frequency-ultrasound (HFU) system is challenging because signals can vary greatly in amplitude as a result of focusing and attenuation effects. In addition, quantitative ultrasound (QUS) results are altered by saturated data. In this paper, the effects of saturation on QUS estimates of effective scatterer diameter (ESD) and effective acoustic concentration (EAC) were quantified using simulated and experimental RF data. Experimental data were acquired from 69 dissected human lymph nodes using a single-element transducer with a 26-MHz center frequency. Artificially saturated signals ( x_c) were produced by thresholding the original unsaturated RF echo signals. Saturation severity was expressed using a quantity called saturate-signal-to-noise ratio (SSNR). Results indicated that saturation has little effect on ESD estimates. However, EAC estimates decreased significantly with decreasing SSNR. An EAC correction algorithm exploiting a linear relationship between EAC values over a range of SSNR values and l¹ -norm of x_c (i.e., the sum of absolute values of the true RF echo signal) is developed. The maximal errors in EAC estimates resulting from saturation were -8.05, -3.59, and -0.93 dB/mm³ with the RF echo signals thresholded to keep 5, 6, and 7-bit from the original 8-bit DR, respectively. The EAC correction algorithm reduced maximal errors to -3.71, -0.89, and -0.26 dB/mm³ when signals were thresholded at 5, 6, and 7-bit, respectively.

High frequency ultrasound imaging and simulations of sea urchin oocytes

High frequency ultrasound backscatter signals from sea urchin oocytes were measured using a 40 MHz transducer and compared to numerical simulations. The Faran scattering model was used to calculate the ultrasound scattered from single oocytes in suspension. The urchin oocytes are non-nucleated with uniform size and biomechanical properties; the backscatter from each cell is similar and easy to simulate, unlike typical nucleated mammalian cells. The time domain signal measured from single oocytes in suspension showed two distinct peaks, and the power spectrum was periodic with minima spaced approximately 10 MHz apart. Good agreement to the Faran scattering model was observed. Measurements from tightly packed oocyte cell pellets showed similar periodic features in the power spectra, which was a result of the uniform size and consistent biomechanical properties of the cells. Numerical simulations that calculated the ultrasound scattered from individual oocytes within a three dimensional volume showed good agreement to the measured signals and B-scan images. A cepstral analysis of the signal was used to calculate the size of the cells, which was 78.7 μm (measured) and 81.4 μm (simulated). This work supports the single scattering approximation, where ultrasound is discretely scattered from single cells within a bulk homogeneous sample, and that multiple scattering has a negligible effect. This technique can be applied towards understanding the complex scattering behaviour from heterogeneous tissues.

High-Frequency Quantitative Ultrasound Spectroscopy of Excised Canine Livers and Mouse Tumors Using the Structure Factor Model

Three scattering models were examined for characterizing ex vivo canine livers and HT29 mouse tumors in the 10-38- and the 15-42-MHz frequency bandwidth, respectively. The spherical Gaussian model (SGM) and the fluid sphere model (FSM) that were examined are suitable for dealing with sparse media, whereas the structure factor model (SFM) is adapted for characterizing concentrated media. For the canine livers, the scatterer radius and the acoustic concentration estimated with the three models were similar and matched well the nuclear structures obtained from histological analysis (with relative errors less than 7%). These results show that the livers could be considered as a diluted medium and that the nuclei in liver could be a dominant source of scattering. For the homogeneous mouse tumors, containing mostly viable HT29 cells, scatterer radius and volume fraction estimated with the SFM showed good agreement with the whole cell structures obtained from histological analysis (with relative errors less than 15%), whereas the sparse models (the SGM and the FSM) gave no consistent quantitative ultrasound parameters. This suggests that the viable HT29 cell areas have densely packed cellular content and that the whole HT29 cell could be responsible for scattering. For the heterogeneous tumors, the hyperechogenic zones observed in the B-mode images were linked to the presence of small necrotic areas surrounded by viable HT29 cells. Comparison between sparse and concentrated models shows that these hyperechogenic zones could be considered as a concentrated medium.