Ultrasonic backscatter coefficient quantitative estimates from Chinese hamster ovary cell pellet biophantoms

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.

Discovering new 3D bioprinting applications: Analyzing the case of optical tissue phantoms

Optical tissue phantoms enable to mimic the optical properties of biological tissues for biomedical device calibration, new equipment validation, and clinical training for the detection, and treatment of diseases. Unfortunately, current methods for their development present some problems, such as a lack of repeatability in their optical properties. Where the use of three-dimensional (3D) printing or 3D bioprinting could address these issues. This paper aims to evaluate the use of this technology in the development of optical tissue phantoms. A competitive technology intelligence methodology was applied by analyzing Scopus, Web of Science, and patents from January 1, 2000, to July 31, 2018. The main trends regarding methods, materials, and uses, as well as predominant countries, institutions, and journals, were determined. The results revealed that, while 3D printing is already employed (in total, 108 scientific papers and 18 patent families were identified), 3D bioprinting is not yet applied for optical tissue phantoms. Nevertheless, it is expected to have significant growth. This research gives biomedical scientists a new window of opportunity for exploring the use of 3D bioprinting in a new area that may support testing of new equipment and development of techniques for the diagnosis and treatment of diseases.

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.

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.

Structure Function Estimated From Histological Tissue Sections

Ultrasonic scattering is determined by not only the properties of individual scatterers but also the correlation among scatterer positions. The role of scatterer spatial correlation is significant for dense medium, but has not been fully understood. The effect of scatterer spatial correlation may be modeled by the structure function as a frequency-dependent factor in the backscatter coefficient (BSC) expression. The structure function has been previously estimated from the BSC data. The aim of this study is to estimate the structure function from histology to test if the acoustically estimated structure function is indeed caused by the scatterer spatial distribution. Hematoxylin and eosin stained histological sections from dense cell pellet biophantoms were digitized. The scatterer positions were determined manually from the histological images. The structure function was calculated from the extracted scatterer positions. The structure function obtained from histology showed reasonable agreement in the shape but not in the amplitude, compared with the structure function previously estimated from the backscattered data. Fitting a polydisperse structure function model to the histologically estimated structure function yielded relatively accurate cell radius estimates ([Formula: see text]). Furthermore, two types of mouse tumors that have similar cell size and shape but distinct cell spatial distributions were studied, where the backscattered data were shown to be related to the cell spatial distribution through the structure function estimated from histology. In conclusion, the agreement between acoustically estimated and histologically estimated structure functions suggests that the acoustically estimated structure function is related to the scatterer spatial distribution.

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

Quantitative ultrasound (QUS) methods based on the backscatter coefficient (BSC) are typically model-based. The BSC is estimated from experiments and is fit to a model. The fit parameters are often termed QUS estimates and are used to characterize the scattering properties of the tissue under investigation. Nevertheless, for physical interpretation of QUS estimates to be accurate, the scattering model chosen must also be accurate. The goal of this work was to investigate the use of the structure factor model (SFM) to take into account coherent scattering from high volume fractions of scatterers. The study focuses on comparing the performance of two sparse models (fluid-filled sphere and Gaussian) and one concentrated model (SFM) to estimate QUS parameters from simulations and cell pellet biophantoms with a range of scatterer volume fractions. Results demonstrated the superiority of the SFM for all investigated volume fractions (i.e., from 0.006 to 0.30). In particular, the sparse models underestimated scatterer size and overestimated acoustic concentration when the volume fraction was greater than 0.12. In addition, the SFM has the ability to provide the volume fraction and the relative impedance contrast (instead of only the acoustic concentration provided by the sparse models), which could have a great benefit for tissue characterization. This study demonstrates that the SFM could prove to be an invaluable tool for QUS and could help to more accurately characterize tissue from ultrasound measurements.

Experimental application of ultrafast imaging to spectral tissue characterization

Ultrasound ultrafast imaging (UI) allows acquisition of thousands of frames per second with a sustained image quality at any depth in the field of view. Therefore, it would be ideally suited to obtain good statistical sampling of fast-moving tissues using spectral-based techniques to derive the backscatter coefficient (BSC) and associated quantitative parameters. In UI, an image is formed by insonifying the medium with plane waves steered at different angles, beamforming them and compounding the resulting radiofrequency images. We aimed at validating, experimentally, the effect of these beamforming protocols on the BSC, under both isotropic and anisotropic conditions. Using UI techniques with a linear array transducer (5-14 MHz), we estimated the BSCs of tissue-mimicking phantoms and flowing porcine blood at depths up to 35 mm with a frame rate reaching 514 Hz. UI-based data were compared with those obtained using single-element transducers and conventional focusing imaging. Results revealed that UI compounded images can produce valid estimates of BSCs and effective scatterer size (errors less than 2.2 ± 0.8 and 0.26 ± 0.2 dB for blood and phantom experiments, respectively). This work also describes the use of pre-compounded UI images (i.e., steered images) to assess the angular dependency of circulating red blood cells. We have concluded that UI data sets can be used for BSC spectral tissue analysis and anisotropy characterization.

Structure function for high-concentration biophantoms of polydisperse scatterer sizes

Ultrasonic backscattering coefficient (BSC) has been used extensively to characterize tissue. In most cases, sparse scatterer concentrations are assumed. However, many types of tissues have dense scattering media. This study addresses the problem of dense media scattering by taking into account the correlation among scatterers using the structure functions. The effect of scatterer polydispersity on the structure functions is investigated. Structure function models based on polydisperse scatterers are theoretically developed and experimentally evaluated against the structure functions obtained from cell pellet biophantoms. The biophantoms were constructed by placing live cells of known concentration in coagulation media to form a clot. The BSCs of the biophantoms were estimated using single-element transducers over the frequency range from 11 to 105 MHz. Experimental structure functions were obtained by comparing the BSCs of two cell concentrations. The structure functions predicted by the models agreed with the experimental structure functions. Fitting the models yielded cell radius estimates that were consistent with direct light microscope measures. The results demonstrate the role of scatterer position correlation on dense media scattering, and the significance of scatterer polydispersity on structure functions. This work may lead to more accurate modeling of ultrasonic scattering in dense medium for improved tissue characterization.

Structure factor model for understanding the measured backscatter coefficients from concentrated cell pellet biophantoms

Ultrasonic backscatter coefficient (BSC) measurements were performed on K562 cell pellet biophantoms with cell concentrations ranging from 0.006 to 0.30 in the 10-42 MHz frequency bandwidth. Three scattering models, namely, the fluid-filled sphere model (FFSM), the particle model (PM), and the structure factor model (SFM), were compared for modeling the scattering from an ensemble of concentrated cells. A parameter estimation procedure was developed in order to estimate the scatterer size and relative impedance contrast that could explain the measured BSCs from all the studied cell concentrations. This procedure was applied to the BSC data from K562 cell pellet biophantoms in the 10-42 MHz frequency bandwidth and to the BSC data from Chinese hamster ovary cell pellet biophantoms in the 26-105 MHz frequency bandwidth given in Han, Abuhabsah, Blue, Sarwate, and O'Brien [J. Acoust. Soc. Am. 130, 4139-4147 (2011)]. The data fitting quality and the scatterer size estimates show that the SFM was more suitable than the PM and the FFSM for modeling the responses from concentrated cell pellet biophantoms.

Quantitative ultrasound from single cells to biophantoms to tumors

There is no underestimating the importance of modern imaging to the improved detection and management of diseases such as cancer. Ultrasound offers a cost-effective and safe modern imaging modality. A quantitative approach, termed quantitative ultrasound (QUS), offers the capability to examine the anatomic microstructure of tissue, hence opening up opportunities to quantify/diagnose such microstructure. One approach to improve specificity with QUS techniques, a model-based approach, is to develop ultrasonic scattering models that match the anatomic geometry of the tissue type under investigation. To do so, an approach from simple (individual cells) to moderate complexity (groupings of cells imbedded in a supportive structure) to significant complexity (actual tissue/tumors) has merit, especially if the degrees of complexity are with the same cell type. Therefore, an approach for improved imaging capabilities with quantitative ultrasound is that from single cells to biophantoms to tumors, and is discussed herein.

The measurement of ultrasound backscattering from cell pellet biophantoms and tumors ex vivo

Simple scattering media fit scattering model theories much better than more complex scattering media. Tissue is much more complex as an acoustic scattering media and to date there has not been an adequate scattering model that fits it well. Previous studies evaluated the scattering characteristics of simple media (grouping of cells at various number densities) and fit them to the concentric spheres scattering model theory. This study is to increase the complexity of the media to provide insight into the acoustic scattering characteristics of tissue, and specifically two tumor types. Complementing the data from the tumors is 100% volume fraction cell pellets of the same cell lines. Cell pellets and ex vivo tumors are scanned using high-frequency single-element transducers (9-105 MHz), and the attenuation and backscatter coefficient (BSC) are estimated. BSC comparisons are made between cell pellets and tumors. The results show that the 4T1 (ATCC #CRL-2539) cell pellets and tumors have similar BSC characteristics, whereas the MAT (ATCC #CRL-1666) cell pellets and tumors have significantly different BSC characteristics. Factors that yield such differences are explored. Also, the fluid-filled sphere and the concentric spheres models are evaluated against the BSC characteristics, demonstrating that further work is required.

Experimental assessment of four ultrasound scattering models for characterizing concentrated tissue-mimicking phantoms

Tissue-mimicking phantoms with high scatterer concentrations were examined using quantitative ultrasound techniques based on four scattering models: The Gaussian model (GM), the Faran model (FM), the structure factor model (SFM), and the particle model (PM). Experiments were conducted using 10- and 17.5-MHz focused transducers on tissue-mimicking phantoms with scatterer concentrations ranging from 1% to 25%. Theoretical backscatter coefficients (BSCs) were first compared with the experimentally measured BSCs in the forward problem framework. The measured BSC versus scatterer concentration relationship was predicted satisfactorily by the SFM and the PM. The FM and the PM overestimated the BSC magnitude at actual concentrations greater than 2.5% and 10%, respectively. The SFM was the model that better matched the BSC magnitude at all the scatterer concentrations tested. Second, the four scattering models were compared in the inverse problem framework to estimate the scatterer size and concentration from the experimentally measured BSCs. The FM did not predict the concentration accurately at actual concentrations greater than 12.5%. The SFM and PM need to be associated with another quantitative parameter to differentiate between low and high concentrations. In that case, the SFM predicted the concentration satisfactorily with relative errors below 38% at actual concentrations ranging from 10% to 25%.

Quantitative ultrasound estimates from populations of scatterers with continuous size distributions: effects of the size estimator algorithm

Quantitative ultrasonic techniques using backscatter coefficients (BSCs) may fail to produce physically meaningful estimates of effective scatterer diameter (ESD) when the analysis media contains scatterers of different sizes. In this work, three different estimator algorithms were used to produce estimates of ESD. The performance of the three estimators was compared over different frequency bands using simulations and experiments with physical phantoms. All estimators produced ESD estimates by comparing the estimated BSCs with a scattering model based on the backscattering cross section of a single spherical fluid scatterer. The first estimator consisted of minimizing the average square deviation of the logarithmically compressed ratio between the estimated BSCs and the scattering model. The second and third estimators consisted of minimizing the mean square error between the estimated BSCs and a linear transformation of the scattering model with and without considering an intercept, respectively. Simulations were conducted over several analysis bandwidths between 1 and 40 MHz from populations of scatterers with either a uniform size distribution or a distribution based on the inverse cubic of the size. Diameters of the distributions ranged between [25, 100], [25, 50], [50, 100], and [50, 75] μm. Experimental results were obtained from two gelatin phantoms containing cross-linked dextran gel spheres ranging in diameter from 28 to 130 μm and 70 to 130 μm, respectively, and 5-, 7.5-, 10-, and 13-MHz focused transducers. Significant differences in the performances of the ESD estimator algorithms as a function of the analysis frequency were observed. Specifically, the third estimator exhibited potential to produce physically meaningful ESD estimates even for large ka values when using a single-size scattering model if sufficient analysis bandwidth was available.

Ultrasonic backscatter coefficient quantitative estimates from high-concentration Chinese Hamster Ovary cell pellet biophantoms

Previous work estimated the ultrasonic backscatter coefficient (BSC) from low-concentration (volume density <3%) Chinese Hamster Ovary (CHO, 6.7-μm cell radius) cell pellets. This study extends the work to higher cell concentrations (volume densities: 9.6% to 63%). At low concentration, BSC magnitude is proportional to the cell concentration and BSC frequency dependency is independent of cell concentration. At high cell concentration, BSC magnitude is not proportional to cell concentration and BSC frequency dependency is dependent on cell concentration. This transition occurs when the volume density reaches between 10% and 30%. Under high cell concentration conditions, the BSC magnitude increases slower than proportionally with the number density at low frequencies (ka<1), as observed by others. However, what is new is that the BSC magnitude can increase either slower or faster than proportionally with number density at high frequencies (ka>1). The concentric sphere model least squares estimates show a decrease in estimated cell radius with number density, suggesting that the concentric spheres model is becoming less applicable as concentration increases because the estimated cell radius becomes smaller than that measured. The critical volume density, starting from when the model becomes less applicable, is estimated to be between 10% and 30% cell volume density.