Cross-imaging system comparison of backscatter coefficient estimates from a tissue-mimicking material

Simulation of ultrasound backscatter coefficient measurement using the finite element method

Ultrasound backscatter coefficient (BSC) measurement is a method for assessing tissue morphology that can inform on pathologies such as cancer. The BSC measurement is, however, limited by the accuracy with which the investigator can normalise their results to account for frequency dependent effects of diffraction and attenuation whilst performing such measurements. We propose a simulation-based approach to investigate the potential sources of error in assessing the BSC. Presented is a tool for the 2D Finite Element (FE) simulation mimicking a BSC measurement using the planar reflector substitution method in reduced dimensionality. The results of this are verified against new derivations of BSC equations also in reduced dimensionality. These new derivations allow computation of BSC estimates based on the scattering from a 2D scattering area, a line reference reflector and a theoretical value for the BSC of a 2D distribution of scatterers. This 2D model was designed to generate lightweight simulations that allow rapid investigation of the factors associated with BSC measurement, allowing the investigator to generate large data sets in relatively short time scales. Under the conditions for an incoherent scattering medium, the simulations produced BSC estimates within 6% of the theoretical value calculated from the simulation domain, a result reproduced across a range of source f-numbers. This value of error compares well to both estimated errors from other simulation based approaches and to physical experiments. The mathematical and simulation models described here provide a theoretical and experimental framework for continued investigation into factors affecting the accuracy of BSC measurements.

Spectral-based Quantitative Ultrasound Imaging Processing Techniques: Comparisons of RF Versus IQ Approaches

Quantitative ultrasound (QUS) is an imaging technique which includes spectral-based parameterization. Typical spectral-based parameters include the backscatter coefficient (BSC) and attenuation coefficient slope (ACS). Traditionally, spectral-based QUS relies on the radio frequency (RF) signal to calculate the spectral-based parameters. Many clinical and research scanners only provide the in-phase and quadrature (IQ) signal. To acquire the RF data, the common approach is to convert IQ signal back into RF signal via mixing with a carrier frequency. In this study, we hypothesize that the performance, that is, accuracy and precision, of spectral-based parameters calculated directly from IQ data is as good as or better than using converted RF data. To test this hypothesis, estimation of the BSC and ACS using RF and IQ data from software, physical phantoms and in vivo rabbit data were analyzed and compared. The results indicated that there were only small differences in estimates of the BSC between when using the original RF, the IQ derived from the original RF and the RF reconverted from the IQ, that is, root mean square errors (RMSEs) were less than 0.04. Furthermore, the structural similarity index measure (SSIM) was calculated for ACS maps with a value greater than 0.96 for maps created using the original RF, IQ data and reconverted RF. On the other hand, the processing time using the IQ data compared to RF data were substantially less, that is, reduced by more than a factor of two. Therefore, this study confirms two things: (1) there is no need to convert IQ data back to RF data for conducting spectral-based QUS analysis, because the conversion from IQ back into RF data can introduce artifacts. (2) For the implementation of real-time QUS, there is an advantage to convert the original RF data into IQ data to conduct spectral-based QUS analysis because IQ data-based QUS can improve processing speed.

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. Computer simulations, such as those from the ultrasound simulator Field II, can allow more flexibility. However, Field II does not allow simulation of RF data from a distribution of scatterers with finite size. In this work, a simulation method is presented which builds upon previous work by including Faran theory models representative of distributions of scatterer size. These are systematically applied to RF data simulated in Field II. The method is validated by measuring the root mean square error of the estimated BSC and percent bias of the ESD and comparing to experimental results. The results indicate the method accurately simulates distributions of scatterer sizes and provides scattering similar to that seen in data from clinical scanners. Because Field II is widely used by the ultrasound community, this method can be adopted to aid in validation of quantitative ultrasound imaging biomarkers.

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. Each patient was scanned by at least 2 of 3 radiologists; each performed 3 acquisitions with transducer and patient repositioning in between acquisitions. BSC was estimated using a low-variance QUS approach based on regularization. Intra- and inter-operator variability of the intra-lesion median BSC was evaluated with a multifactorial ANOVA test (P-values) and the intraclass correlation coefficient (ICC).

RESULTS

Inter-operator variability was only significant in the first protocol (P < .007); ICCinter  = .77 (95% CI .71-.82), indicating good inter-operator agreement. In the second protocol, the inter-operator variability was not significant (P > .05) and agreement was excellent (ICCinter  = .92 [.89-.94]). In both protocols, the intra-operator variability was not significant.

CONCLUSIONS

Our findings demonstrate the need for standardizing image acquisition protocols for backscatter-based QUS to reduce inter-operator variability and ensure its successful translation to the characterization of suspicious breast masses.

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 secant model, of backscatter coefficient anisotropy. Specifically, we evaluate anisotropy of the frequency dependence of the backscatter coefficient parameterized in terms of effective scatterer size. We assess the model in phantoms with known scattering sources and in a skeletal muscle, a well-known anisotropic tissue. We demonstrate that the secant model can determine the orientation of the anisotropic scatterers, as well as accurately determining effective scatterer sizes, and it may classify isotropic versus anisotropic scatterers. The secant model may find utility in monitoring disease progression as well as characterizing normal tissue architectures.

Assessing engineered tissues and biomaterials using ultrasound imaging: In vitro and in vivo applications

Quantitative assessment of the structural, functional, and mechanical properties of engineered tissues and biomaterials is fundamental to their development for regenerative medicine applications. Ultrasound (US) imaging is a non-invasive, non-destructive, and cost-effective technique capable of longitudinal and quantitative monitoring of tissue structure and function across centimeter to sub-micron length scales. Here we present the fundamentals of US to contextualize its application for the assessment of biomaterials and engineered tissues, both in vivo and in vitro. We review key studies that demonstrate the versatility and broad capabilities of US for clinical and pre-clinical biomaterials research. Finally, we highlight emerging techniques that further extend the applications of US, including for ultrafast imaging of biomaterials and engineered tissues in vivo and functional monitoring of stem cells, organoids, and organ-on-a-chip systems in vitro.

Quantitative Ultrasound: Experimental Implementation

The backscatter coefficient is a fundamental property of tissues, much like the attenuation and sound speed. From the backscatter coefficient, different scatterer properties describing the underlying tissue can be used to characterize tissue state. Furthermore, because the backscatter coefficient is a fundamental property of a tissue, estimation of the backscatter coefficient should be able to be computed with system and operator independence. To accomplish system- and operator-independent estimates of the backscatter coefficient, a calibration spectrum must be obtained at the same system settings as the settings used to scan a tissue. In this chapter, we discuss three approaches to obtaining a calibration spectrum and compare the engineering tradeoffs associated with each approach. In addition, methods for reducing deterministic noise in the backscatter coefficient spectrum are considered and implementation of these techniques is discussed.

US Attenuation for Liver Fat Quantification: An AIUM-RSNA QIBA Pulse-Echo Quantitative Ultrasound Initiative

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide, with an estimated prevalence of up to 30% in the general population and higher in people with type 2 diabetes. The assessment of liver fat content is essential to help identify patients with or who are at risk for NAFLD and to follow their disease over time. The American Institute of Ultrasound in Medicine-RSNA Quantitative Imaging Biomarkers Alliance Pulse-Echo Quantitative Ultrasound Initiative was formed to help develop and standardize acquisition protocols and to better understand confounding factors of US-based fat quantification. The three quantitative US parameters explored by the initiative are attenuation, backscatter coefficient, and speed of sound. The purpose of this review is to present the current state of attenuation imaging for fat quantification and to provide expert opinion on examination performance and interpretation. US attenuation methods that need further study are outlined.

Quantitative ultrasound imaging of soft biological tissues: a primer for radiologists and medical physicists

Quantitative ultrasound (QUS) aims at quantifying interactions between ultrasound and biological tissues. QUS techniques extract fundamental physical properties of tissues based on interactions between ultrasound waves and tissue microstructure. These techniques provide quantitative information on sub-resolution properties that are not visible on grayscale (B-mode) imaging. Quantitative data may be represented either as a global measurement or as parametric maps overlaid on B-mode images. Recently, major ultrasound manufacturers have released speed of sound, attenuation, and backscatter packages for tissue characterization and imaging. Established and emerging clinical applications are currently limited and include liver fibrosis staging, liver steatosis grading, and breast cancer characterization. On the other hand, most biological tissues have been studied using experimental QUS methods, and quantitative datasets are available in the literature. This educational review addresses the general topic of biological soft tissue characterization using QUS, with a focus on disseminating technical concepts for clinicians and specialized QUS materials for medical physicists. Advanced but simplified technical descriptions are also provided in separate subsections identified as such. To understand QUS methods, this article reviews types of ultrasound waves, basic concepts of ultrasound wave propagation, ultrasound image formation, point spread function, constructive and destructive wave interferences, radiofrequency data processing, and a summary of different imaging modes. For each major QUS technique, topics include: concept, illustrations, clinical examples, pitfalls, and future directions.

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. Sixteen 2- to 7-day-old rhesus macaques were exposed for 5 h to SEVO. Ultrasound scanning was done with a phased array transducer on a clinical ultrasound scanner operated at 10 MHz. Data consisting of 10-15 frames of radiofrequency (RF) echo signals from coronal views of the thalamus were obtained 0.5 and 6.0 h after initiating exposure. The UBS parameter "effective scatterer size" (ESS) was estimated by fitting a scattering form factor (FF) model to the FF measured from RF echo signals. The approach involved analyzing the frequency dependence of the measured FF to characterize scattering sources and selecting the FF model based on a χ² goodness-of-fit criterion. To assess data quality, a rigorous acceptance criterion based on the analysis of prevalence of diffuse scattering (an assumption in the estimation of ESS) was established. ESS changes after exposure to SEVO were compared with changes in a control group of five primates for which ultrasound data were acquired at 0 and 10 min (no apoptosis expected). Over the entire data set, the average measured FF at 0.5 and 6.0 h monotonically decreased with frequency, justifying fitting a single FF over the analysis bandwidth. χ² values of a (inhomogeneous continuum) Gaussian FF model were one-fifth those of the discrete fluid sphere model, suggesting that a continuum scatterer model better represents ultrasound scattering in the young rhesus brain. After application of the data quality criterion, only 5 of 16 subjects from the apoptotic group and 5 of 5 subjects from the control group fulfilled the acceptance criteria. All subjects in the apoptotic group that passed the acceptance criterion exhibited a significant ESS reduction at 6.0 h. These changes (-6.4%, 95% Interquartile Range: -14.3% to -3.3%) were larger than those in the control group (-0.8%, 95% Interquartile Range: -2.0% to 1.5%]). Data with a low prevalence of diffuse scattering corresponded to possibly biased results. Thus, ESS has the potential to detect changes in brain microstructure related to anesthesia-induced apoptosis.

Quantitative Ultrasound Monitoring of Breast Tumour Response to Neoadjuvant Chemotherapy: Comparison of Results Among Clinical Scanners

Quantitative ultrasound (QUS) techniques have been demonstrated to detect cell death in vitro and in vivo. Recently, multi-feature classification models have been incorporated into QUS texture-feature analysis methods to increase further the sensitivity and specificity of detecting treatment response in locally advanced breast cancer patients. To effectively incorporate these analytic methods into clinical applications, QUS and texture-feature estimations should be independent of data acquisition systems. The study here investigated the consistencies of QUS and texture-feature estimation techniques relative to several factors. These included the ultrasound system properties, the effects of tissue heterogeneity and the effects of these factors on the monitoring of response to neoadjuvant chemotherapy. Specifically, tumour-response-detection performance based on QUS and texture parameters using two clinical ultrasound systems was compared. Observed variations in data between the systems were small and the results exhibited good agreement in tumour response predictions obtained from both ultrasound systems. The results obtained in this study suggest that tissue heterogeneity was a dominant feature in the parameters measured with the two different ultrasound systems; whereas differences in ultrasound system beam properties only exhibited a minor impact on texture features. The McNemar statistical test performed on tumour response prediction results from the two systems did not reveal significant differences. Overall, the results in this study demonstrate the potential to achieve reliable and consistent QUS and texture-based analyses across different ultrasound imaging platforms.

Gap-filling method for suppressing grating lobes in ultrasound imaging: Experimental study with deep-learning approach

Sparse arrays reduce the number of active channels that effectively increases the inter-element spacing. Large inter-element spacing results in grating lobe artifacts degrading the ultrasound image quality and reducing the contrast-to-noise ratio. A deep learning-based custom algorithm is proposed to estimate inactive channel data in periodic sparse arrays. The algorithm uses data from multiple active channels to estimate inactive channels. The estimated inactive channel data effectively reduces the inter-element spacing for beamforming, thus suppressing the grating lobes. Estimated inactive element channel data was combined with active element channel data resulting in a pseudo fully sampled array. The channel data was beamformed using a simple delay-and-sum method and compared with the sparse array and fully sampled array. The performance of the algorithm was validated using a wire target in a water tank, multi-purpose tissue-mimicking phantom, and in-vivo carotid data. Grating lobes suppression up to 15.25 dB was observed with an increase in contrast-to-noise (CNR) for the pseudo fully sampled array. Hypoechoic regions showed more improvement in CNR than hyperechoic regions. Root-mean-square error for unwrapped phase between fully sampled array and the pseudo fully sampled array was low, making the estimated data suitable for Doppler and elastography applications. Speckle pattern was also preserved; thus, the estimated data can also be used for quantitative ultrasound applications. The algorithm can improve the quality of sparse array images and has applications in small scale ultrasound devices and 2D arrays.

Estimation of Backscatter Coefficients Using an In Situ Calibration Source

The objective of this article is to demonstrate the feasibility of estimating the backscatter coefficient (BSC) using an in situ calibration source. Traditional methods of estimating the BSC in vivo using a reference phantom technique do not account for transmission losses due to intervening layers between the ultrasonic source and the tissue region to be interrogated, leading to increases in bias and variance of BSC-based estimates. To account for transmission losses, an in situ calibration approach is proposed. The in situ calibration technique employs a titanium sphere that is well-characterized ultrasonically, biocompatible, and embedded inside the sample. A set of experiments was conducted to evaluate the embedded titanium spheres as in situ calibration targets for BSC estimation. The first experiment quantified the backscattered signal strength from titanium spheres of three sizes: 0.5, 1, and 2 mm in diameter. The second set of experiments assessed the repeatability of BSC estimates from the titanium spheres and compared these BSCs to theory. The third set of experiments quantified the ability of the titanium bead to provide an in situ reference spectrum in the presence of a lossy layer on top of the sample. The final set of experiments quantified the ability of the bead to provide a calibration spectrum over multiple depths in the sample. All experiments were conducted using an L9-4/38 linear array connected to a SonixOne system. The strongest signal was observed from the 2-mm titanium bead with the signal-to-noise ratio (SNR) of 11.6 dB with respect to the background speckle. Using an analysis bandwidth of 2.5-5.5 MHz, the mean differences between the experimentally derived BSCs and BSCs derived from the Faran theory were 0.54 and 0.76 dB using the array and a single-element transducer, respectively. The BSCs estimated using the in situ calibration approach without the layer and with the layer and using the reference phantom approach with the layer were compared to the reference phantom approach without the layer present. The mean differences in BSCs were 0.15, 0.73, and -9.69 dB, respectively. The mean differences of the BSCs calculated from data blocks located at depths that were either 30 pulse lengths above or below the actual bead depth compared to the BSC calculated at bead depth were -1.55 and -1.48 dB, respectively. The results indicate that an in situ calibration target can account for overlaying tissue losses, thereby improving the robustness of BSC-based estimates.

Characterizing Fatty Liver in vivo in Rabbits, Using Quantitative Ultrasound

Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease and can often lead to fibrosis, cirrhosis, cancer and complete liver failure. Liver biopsy is the current standard of care to quantify hepatic steatosis, but it comes with increased patient risk and only samples a small portion of the liver. Imaging approaches to assess NAFLD include proton density fat fraction estimated via magnetic resonance imaging (MRI) and shear wave elastography. However, MRI is expensive and shear wave elastography is not proven to be sensitive to fat content of the liver (Kramer et al. 2016). On the other hand, ultrasonic attenuation and the backscatter coefficient (BSC) have been observed to be sensitive to levels of fat in the liver (Lin et al. 2015; Paige et al. 2017). In this study, we assessed the use of attenuation and the BSC to quantify hepatic steatosis in vivo in a rabbit model of fatty liver. Rabbits were maintained on a high-fat diet for 0, 1, 2, 3 or 6 wk, with 3 rabbits per diet group (total N = 15). An array transducer (L9-4) with a center frequency of 4.5 MHz connected to a SonixOne scanner was used to gather radio frequency (RF) backscattered data in vivo from rabbits. The RF signals were used to estimate an average attenuation and BSC for each rabbit. Two approaches were used to parameterize the BSC (i.e., the effective scatterer diameter and effective acoustic concentration using a spherical Gaussian model and a model-free approach using a principal component analysis [PCA]). The 2 major components of the PCA from the BSCs, which captured 96% of the variance of the transformed data, were used to generate input features to a support vector machine for classification. Rabbits were separated into two liver fat-level classes, such that approximately half of the rabbits were in the low-lipid class (≤9% lipid liver level) and half of the rabbits in the high-lipid class (>9% lipid liver level). The slope and the midband fit of the attenuation coefficient provided statistically significant differences (p value = 0.00014 and p value = 0.007, using a two-sample t test) between low and high-lipid fat classes. The proposed model-free and model-based parameterization of the BSC and attenuation coefficient parameters yielded classification accuracies of 84.11 %, 82.93 % and 78.91 % for differentiating low-lipid versus high-lipid classes, respectively. The results suggest that attenuation and BSC analysis can differentiate low-fat versus high-fat livers in a rabbit model of fatty liver disease.

Quantitative Ultrasound Parameters Based on the Backscattered Echo Power Signal as Biomarkers of Cervical Remodeling: A Longitudinal Study in the Pregnant Rhesus Macaque

Clinical prediction and especially prevention of abnormal birth timing, particularly pre-term, is poor. The cervix plays a key role in birth timing; it first serves as a rigid barrier to protect the developing fetus, then becomes the pathway to delivery of that fetus. Imaging biomarkers to define this remodeling process could provide insights to improve prediction of birth timing and elucidate novel targets for preventive therapies. Quantitative ultrasound (QUS) approaches that appear promising for this purpose include shear wave speed (SWS) estimation to quantify softness, as well as parameters based on backscattered power, such as the mean backscattered power difference (mBSPD) and specific attenuation coefficient (SAC), to quantify the organization of tissue microstructure. Invasive studies in rodents demonstrated that as pregnancy advances, cervical microstructure disorganizes as tissue softness and compliance increase. Our non-invasive studies in pregnant women and rhesus macaques suggested that QUS can detect these microstructural changes in vivo. Our previous study in the same cohort showed a progressive decline in SWS during pregnancy, consistent with increasing tissue softness, and we hypothesized that backscatter parameters would also decrease, consistent with increasing microstructural disorganization. In this study, we analyzed the mBSPD and SAC in the cervices of rhesus macaques (n = 18). We found that both mBSPD and SAC decreased throughout pregnancy (p < 0.001 for both parameters) and that the former appears to be a more reliable biomarker. In summary, biomarkers that can characterize tissue microstructural organization are promising for comprehensive characterization of cervical remodeling in pregnancy.

Quantitative ultrasound and apoptotic death in the neonatal primate brain

Apoptosis is triggered in the developing mammalian brain by sedative, anesthetic or antiepileptic drugs during late gestation and early life. Whether human children are vulnerable to this toxicity mechanism remains unknown, as there are no imaging techniques to capture it. Apoptosis is characterized by distinct structural features, which affect the way damaged tissue scatters ultrasound compared to healthy tissue. We evaluated whether apoptosis, triggered by the anesthetic sevoflurane in the brains of neonatal rhesus macaques, can be detected using quantitative ultrasound (QUS). Neonatal (n = 15) rhesus macaques underwent 5 h of sevoflurane anesthesia. QUS images were obtained through the sagittal suture at 0.5 and 6 h. Brains were collected at 8 h and examined immunohistochemically to analyze apoptotic neuronal and oligodendroglial death. Significant apoptosis was detected in white and gray matter throughout the brain, including the thalamus. We measured a change in the effective scatterer size (ESS), a QUS biomarker derived from ultrasound echo signals obtained with clinical scanners, after sevoflurane-anesthesia in the thalamus. Although initial inclusion of all measurements did not reveal a significant correlation, when outliers were excluded, the change in the ESS between the pre- and post-anesthesia measurements correlated strongly and proportionally with the severity of apoptotic death. We report for the first time in vivo changes in QUS parameters, which may reflect severity of apoptosis in the brains of infant nonhuman primates. These findings suggest that QUS may enable in vivo studies of apoptosis in the brains of human infants following exposure to anesthetics, antiepileptics and other brain injury mechanisms.

Review of quantitative multiscale imaging of breast cancer

Breast cancer is the most common cancer among women worldwide and ranks second in terms of overall cancer deaths. One of the difficulties associated with treating breast cancer is that it is a heterogeneous disease with variations in benign and pathologic tissue composition, which contributes to disease development, progression, and treatment response. Many of these phenotypes are uncharacterized and their presence is difficult to detect, in part due to the sparsity of methods to correlate information between the cellular microscale and the whole-breast macroscale. Quantitative multiscale imaging of the breast is an emerging field concerned with the development of imaging technology that can characterize anatomic, functional, and molecular information across different resolutions and fields of view. It involves a diverse collection of imaging modalities, which touch large sections of the breast imaging research community. Prospective studies have shown promising results, but there are several challenges, ranging from basic physics and engineering to data processing and quantification, that must be met to bring the field to maturity. This paper presents some of the challenges that investigators face, reviews currently used multiscale imaging methods for preclinical imaging, and discusses the potential of these methods for clinical breast imaging.

Quantifying Backscatter Anisotropy Using the Reference Phantom Method

Acoustic properties can be exploited to infer and evaluate tissue microstructure. However, common assumptions are that the medium of interest is homogeneous and isotropic, and that its underlying physical properties cause diffuse scattering. In this paper, we describe how we developed and tested novel parameters designed to address isotropy/anisotropy in backscattered echo signal power in complex biological tissues. Specifically, we explored isotropy/anisotropy in backscattered power in isotropic phantoms (spherical glass beads), an anisotropic phantom (dialysis phantom with rodlike fibers), and an in vivo human tissue with well-described anisotropy (bicep muscle). Our approach uses the reference phantom method to compensate for system transfer and diffraction losses when electronically beamsteering a linear array transducer. We define three parameters to quantify the presence and orientation of anisotropic scatterers, as well as address magnitude of anisotropy. We found that these parameters can detect and sense the degree of anisotropy in backscatter in both phantoms and bicep muscle. Bias of the summary anisotropy parameters, induced through a speed of sound mismatch of sample media and reference phantom, was less than 0.2 dB if the speed of sound was within ±20 m/s of the sample media. In summary, these new parameters may be useful for testing the assumption of isotropy as well as providing more detailed information about the underlying microstructural sources of backscatter in complex biological tissues.

Photoacoustic signal characterization of cancer treatment response: Correlation with changes in tumor oxygenation

Frequency analysis of the photoacoustic radiofrequency signals and oxygen saturation estimates were used to monitor the in-vivo response of a novel, thermosensitive liposome treatment. The liposome encapsulated doxorubicin (HaT-DOX) releasing it rapidly (<20 s) when the tumor was exposed to mild hyperthermia (43 °C). Photoacoustic imaging (VevoLAZR, 750/850 nm, 40 MHz) of EMT-6 breast cancer tumors was performed 30 min pre- and post-treatment and up to 7 days post-treatment (at 2/5/24 h timepoints). HaT-DOX-treatment responders exhibited on average a 22% drop in oxygen saturation 2 h post-treatment and a decrease (45% at 750 nm and 73% at 850 nm) in the slope of the normalized PA frequency spectra. The spectral slope parameter correlated with treatment-induced hemorrhaging which increased the optical absorber effective size via interstitial red blood cell leakage. Combining frequency analysis and oxygen saturation estimates differentiated treatment responders from non-responders/control animals by probing the treatment-induced structural changes of blood vessel.

In Vivo Estimation of Attenuation and Backscatter Coefficients From Human Thyroids

Fine-needle aspiration (FNA) remains the gold standard for the diagnosis of thyroid cancer. However, currently, a large number of FNA biopsies result in negative or undetermined diagnosis, which suggests that better noninvasive tools are needed for the clinical management of thyroid cancer. Spectral-based quantitative ultrasound (QUS) characterizations may offer a better diagnostic management as previously demonstrated in mouse cancer models ex vivo. As a first step toward understanding the potential of QUS markers for thyroid disease management, this paper deals with the spectral-based QUS estimation of healthy human thyroids in vivo. Twenty volunteers were inspected by a trained radiologist using two ultrasonic imaging systems, which allowed them to acquire radio-frequency data spanning the 3-16-MHz frequency range. Estimates of attenuation coefficient slope (ACS) using the spectral logarithmic difference method had an average value of [Formula: see text]) with a standard deviation of [Formula: see text]. Estimates of backscatter coefficient (BSC) using the reference-phantom method had an average value of [Formula: see text] over the useful frequency range. The intersubject variability when estimating BSCs was less than 1.5 dB over the analysis frequency range. Further, the effectiveness of three scattering models (i.e., fluid sphere, Gaussian, and exponential form factors) when fitting the experimentally estimated BSCs was assessed. The exponential form factor was found to provide the best overall goodness of fit ( R² = 0.917), followed by the Gaussian ( R² = 0.807) and the fluid-sphere models ( R² = 0.752). For all scattering models used in this study, average estimates of the effective scatterer diameter were between 44 and 56 μm. Overall, an excellent agreement in the estimated attenuation and BSCs with both scanners was exhibited.

Review of Quantitative Ultrasound: Envelope Statistics and Backscatter Coefficient Imaging and Contributions to Diagnostic Ultrasound

Conventional medical imaging technologies, including ultrasound, have continued to improve over the years. For example, in oncology, medical imaging is characterized by high sensitivity, i.e., the ability to detect anomalous tissue features, but the ability to classify these tissue features from images often lacks specificity. As a result, a large number of biopsies of tissues with suspicious image findings are performed each year with a vast majority of these biopsies resulting in a negative finding. To improve specificity of cancer imaging, quantitative imaging techniques can play an important role. Conventional ultrasound B-mode imaging is mainly qualitative in nature. However, quantitative ultrasound (QUS) imaging can provide specific numbers related to tissue features that can increase the specificity of image findings leading to improvements in diagnostic ultrasound. QUS imaging can encompass a wide variety of techniques including spectral-based parameterization, elastography, shear wave imaging, flow estimation, and envelope statistics. Currently, spectral-based parameterization and envelope statistics are not available on most conventional clinical ultrasound machines. However, in recent years, QUS techniques involving spectral-based parameterization and envelope statistics have demonstrated success in many applications, providing additional diagnostic capabilities. Spectral-based techniques include the estimation of the backscatter coefficient (BSC), estimation of attenuation, and estimation of scatterer properties such as the correlation length associated with an effective scatterer diameter (ESD) and the effective acoustic concentration (EAC) of scatterers. Envelope statistics include the estimation of the number density of scatterers and quantification of coherent to incoherent signals produced from the tissue. Challenges for clinical application include correctly accounting for attenuation effects and transmission losses and implementation of QUS on clinical devices. Successful clinical and preclinical applications demonstrating the ability of QUS to improve medical diagnostics include characterization of the myocardium during the cardiac cycle, cancer detection, classification of solid tumors and lymph nodes, detection and quantification of fatty liver disease, and monitoring and assessment of therapy.

Speed of sound in diseased liver observed by scanning acoustic microscopy with 80 MHz and 250 MHz

In this study, the speed of sound (SOS) of two types of rat livers (eight normal livers, four cirrhotic livers) was measured with a scanning acoustic microscope using two transducers, one of which had an 80-MHz and the other a 250-MHz center frequency. The 250-MHz transducer had a better spatial resolution adapted to studying fiber or hepatic parenchymal cells. In normal livers, averages of the SOS values were from 1598 to 1677 m/s at 80-MHz and from 1568 to 1668 m/s at 250-MHz. In the fiber tissue of cirrhotic livers, averages of the SOS values were from 1645 to 1658 m/s at 80-MHz and from 1610 to 1695 m/s at 250-MHz, while the SOS values in the other tissue of cirrhotic livers ranged from 1644 to 1709 m/s at 80-MHz and from 1641 to 1715 m/s at 250-MHz. In one liver, SOS in fiber tissue was larger than that of tissues without fiber while in others it was lower. The resulting two-dimensional SOS maps provide a unique quantitative insight of liver acoustic microstructures in a healthy liver and in a cirrhotic ones. This study would be helpful to understand the complex relationship between acoustic properties and liver disease including fiber tissue.

Beyond Cervical Length: A Pilot Study of Ultrasonic Attenuation for Early Detection of Preterm Birth Risk

The purpose of this study was to determine whether cervical ultrasonic attenuation could identify women at risk of spontaneous preterm birth. During pregnancy, women (n = 67) underwent from one to five transvaginal ultrasonic examinations to estimate cervical ultrasonic attenuation and cervical length. Ultrasonic data were obtained with a Zonare ultrasound system with a 5- to 9-MHz endovaginal transducer and processed offline. Cervical ultrasonic attenuation was lower at 17-21 wk of gestation in the SPTB group (1.02 dB/cm-MHz) than in the full-term birth groups (1.34 dB/cm-MHz) (p = 0.04). Cervical length was shorter (3.16 cm) at 22-26 wk in the SPTB group than in the women delivering full term (3.68 cm) (p = 0.004); cervical attenuation was not significantly different at this time point. These findings suggest that low attenuation may be an additional early cervical marker to identify women at risk for SPTB.

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.

Quantitative Ultrasound Comparison of MAT and 4T1 Mammary Tumors in Mice and Rats Across Multiple Imaging Systems

OBJECTIVES

Quantitative ultrasound estimates such as the frequency-dependent backscatter coefficient (BSC) have the potential to enhance noninvasive tissue characterization and to identify tumors better than traditional B-mode imaging. Thus, investigating system independence of BSC estimates from multiple imaging platforms is important for assessing their capabilities to detect tissue differences.

METHODS

Mouse and rat mammary tumor models, 4T1 and MAT, respectively, were used in a comparative experiment using 3 imaging systems (Siemens, Ultrasonix, and VisualSonics) with 5 different transducers covering a range of ultrasonic frequencies.

RESULTS

Functional analysis of variance of the MAT and 4T1 BSC-versus-frequency curves revealed statistically significant differences between the two tumor types. Variations also were found among results from different transducers, attributable to frequency range effects. At 3 to 8 MHz, tumor BSC functions using different systems showed no differences between tumor type, but at 10 to 20 MHz, there were differences between 4T1 and MAT tumors. Fitting an average spline model to the combined BSC estimates (3-22 MHz) demonstrated that the BSC differences between tumors increased with increasing frequency, with the greatest separation above 15 MHz. Confining the analysis to larger tumors resulted in better discrimination over a wider bandwidth.

CONCLUSIONS

Confining the comparison to higher ultrasonic frequencies or larger tumor sizes allowed for separation of BSC-versus-frequency curves from 4T1 and MAT tumors. These constraints ensure that a greater fraction of the backscattered signals originated from within the tumor, thus demonstrating that statistically significant tumor differences were detected.

The mechanical role of the cervix in pregnancy

Appropriate mechanical function of the uterine cervix is critical for maintaining a pregnancy to term so that the fetus can develop fully. At the end of pregnancy, however, the cervix must allow delivery, which requires it to markedly soften, shorten and dilate. There are multiple pathways to spontaneous preterm birth, the leading global cause of death in children less than 5 years old, but all culminate in premature cervical change, because that is the last step in the final common pathway to delivery. The mechanisms underlying premature cervical change in pregnancy are poorly understood, and therefore current clinical protocols to assess preterm birth risk are limited to surrogate markers of mechanical function, such as sonographically measured cervical length. This is what motivates us to study the cervix, for which we propose investigating clinical cervical function in parallel with a quantitative engineering evaluation of its structural function. We aspire to develop a common translational language, as well as generate a rigorous integrated clinical-engineering framework for assessing cervical mechanical function at the cellular to organ level. In this review, we embark on that challenge by describing the current landscape of clinical, biochemical, and engineering concepts associated with the mechanical function of the cervix during pregnancy. Our goal is to use this common platform to inspire novel approaches to delineate normal and abnormal cervical function in pregnancy.

Experimental evaluation of spectral-based quantitative ultrasound imaging using plane wave compounding

Quantitative ultrasound (QUS) based on backscatter coefficient (BSC) estimation has shown potential for tissue characterization. Beamforming using plane wave compounding has advantages for echographic, Doppler, and elastographic imaging; however, to date, plane wave compounding has not been experimentally evaluated for the purpose of BSC estimation. In this study, two BSC-derived parameters (i.e., the BSC midband fit and intercept) were estimated from experimental data obtained using compound plane wave beamforming. For comparison, QUS parameters were also estimated from data obtained using both fixed focus and dynamic receive beamforming. An ultrasound imaging system equipped with a 9-MHz center frequency, 64-element array was used to collect data up to a depth of 45 mm. Two gelatin phantoms with randomly distributed 20-μm inclusions with a homogeneous scatterer concentration and a two-region scatterer concentration were used for assessing the precision and lateral resolution of QUS imaging, respectively. The use of plane wave compounding resulted in accurate QUS estimation (i.e., bias in the BSC parameters of less than 2 dB) and relatively constant lateral resolution (i.e., BSC midband fit 10% to 90% rise distance ranging between 1.0 and 1.5 mm) throughout a 45 mm field of view. Although both fixed focus and dynamic receive beamforming provided the same performance around the focal depth, the reduction in SNR away from the focus resulted in a reduced field of view in the homogeneous phantom (i.e., only 28 mm). The lateral resolution also degraded away from the focus, with up to a 2-fold and 10-fold increase in the rise distance at 20 mm beyond the focal depth for dynamic receive and fixed focus beamforming, respectively. These results suggest that plane wave compounding has the potential to improve the performance of spectral-based quantitative ultrasound over other conventional beamforming strategies.

3-D high-frequency ultrasound backscatter analysis of human articular cartilage

High-frequency ultrasound is a promising method for non-invasive characterization of cartilage degeneration. Surface reflection and integrated spectral parameters are often used. In the work described here, human cartilage samples with varying degrees of degeneration were measured using a 40-MHz transducer. Backscatter signals originating from the superficial and transitional zones of cartilage were analyzed using amplitude, spectral and envelope statistical parameters and related to degenerative changes of the matrix given by the Mankin score. The results indicate an increased sensitivity of spectral slope and envelope statistical parameters to early matrix degeneration compared with conventional amplitude parameters. Furthermore, moderate correlations of chondrocyte number with backscatter amplitude and envelope statistics were observed, suggesting that at high frequencies, cells are one important scattering source in cartilage. An application of spectral and envelope statistical parameters to intra-articular ultrasound arthroscopy is conceivable and could improve the diagnostic potential of these examinations. Future studies are necessary to clarify the contributions of chondrocytes, extracellular matrix and collagen content to ultrasound backscatter to further improve the diagnostic potential of ultrasound for cartilage assessment.

Comparison of ultrasound attenuation and backscatter estimates in layered tissue-mimicking phantoms among three clinical scanners

Backscatter and attenuation coefficient estimates are needed in many quantitative ultrasound strategies. In clinical applications, these parameters may not be easily obtained because of variations in scattering by tissues overlying a region of interest (ROI). The goal of this study is to assess the accuracy of backscatter and attenuation estimates for regions distal to nonuniform layers of tissue-mimicking materials. In addition, this work compares results of these estimates for "layered" phantoms scanned using different clinical ultrasound machines. Two tissue-mimicking phantoms were constructed, each exhibiting depth-dependent variations in attenuation or backscatter. The phantoms were scanned with three ultrasound imaging systems, acquiring radio frequency echo data for offline analysis. The attenuation coefficient and the backscatter coefficient (BSC) for sections of the phantoms were estimated using the reference phantom method. Properties of each layer were also measured with laboratory techniques on test samples manufactured during the construction of the phantom. Estimates of the attenuation coefficient versus frequency slope, α(0), using backscatter data from the different systems agreed to within 0.24 dB/cm-MHz. Bias in the α(0) estimates varied with the location of the ROI. BSC estimates for phantom sections whose locations ranged from 0 to 7 cm from the transducer agreed among the different systems and with theoretical predictions, with a mean bias error of 1.01 dB over the used bandwidths. This study demonstrates that attenuation and BSCs can be accurately estimated in layered inhomogeneous media using pulse-echo data from clinical imaging systems.