Effective Acoustic Concentration Research Articles

In Vivo Validation of an In Situ Calibration Bead as a Reference for Backscatter Coefficient Calculation

ObjectiveThe study described here was aimed at assessing the capability of quantitative ultrasound (QUS) based on the backscatter coefficient (BSC) for classifying disease states, such as breast cancer response to neoadjuvant chemotherapy and quantification of fatty liver disease. We evaluated the effectiveness of an in situ titanium (Ti) bead as a reference target in calibrating the system and mitigating attenuation and transmission loss effects on BSC estimation. MethodsTraditional BSC estimation methods require external references for calibration, which do not account for ultrasound attenuation or transmission losses through tissues. To address this issue, we used an in situ Ti bead as a reference target, because it can be used to calibrate the system and mitigate the attenuation and transmission loss effects on estimation of the BSC. The capabilities of the in situ calibration approach were assessed by quantifying consistency of BSC estimates from rabbit mammary tumors (N = 21). Specifically, mammary tumors were grown in rabbits and when a tumor reached ≥1 cm in size, a 2 mm Ti bead was implanted in the tumor as a radiological marker and a calibration source for ultrasound. Three days later, the tumors were scanned with an L-14/5 38 array transducer connected to a SonixOne scanner with and without a slab of pork belly placed on top of the tumors. The pork belly acted as an additional source of attenuation and transmission loss. QUS parameters, specifically effective scatterer diameter (ESD) and effective acoustic concentration (EAC), were calculated using calibration spectra from both an external reference phantom and the Ti bead. ResultsFor ESD estimation, the 95% confidence interval between measurements with and without the pork belly layer was 6.0, 27.4 using the in situ bead and 114, 135.1 with the external reference phantom. For EAC estimation, the 95% confidence intervals were –8.1, 0.5 for the bead and –41.5, –32.2 for the phantom. These results indicate that the in situ bead method has reduced bias in QUS estimates because of intervening tissue losses. ConclusionThe use of an in situ Ti bead as a radiological marker not only serves its traditional role but also effectively acts as a calibration target for QUS methods. This approach accounts for attenuation and transmission losses in tissue, resulting in more accurate QUS estimates and offering a promising method for enhanced disease state classification in clinical settings.

Machine learning-enabled quantitative ultrasound techniques for tissue differentiation

PurposeQuantitative ultrasound (QUS) infers properties about tissue microstructure from backscattered radio-frequency ultrasound data. This paper describes how to implement the most practical QUS parameters using an ultrasound research system for tissue differentiation.MethodsThis study first validated chicken liver and gizzard muscle as suitable acoustic phantoms for human brain and brain tumour tissues via measurement of the speed of sound and acoustic attenuation. A total of thirteen QUS parameters were estimated from twelve samples, each using data obtained with a transducer with a frequency of 5–11 MHz. Spectral parameters, i.e., effective scatterer diameter and acoustic concentration, were calculated from the backscattered power spectrum of the tissue, and echo envelope statistics were estimated by modelling the scattering inside the tissue as a homodyned K-distribution, yielding the scatterer clustering parameter α and the structure parameter κ. Standard deviation and higher-order moments were calculated from the echogenicity value assigned in conventional B-mode images.ResultsThe k-nearest neighbours algorithm was used to combine those parameters, which achieved 94.5% accuracy and 0.933 F1-score.ConclusionWe were able to generate classification parametric images in near-real-time speed as a potential diagnostic tool in the operating room for the possible use for human brain tissue characterisation.

In Vivo Quantitative Ultrasound on Dermis and Hypodermis for Classifying Lymphedema Severity in Humans.

This study investigated the ability of in vivo quantitative ultrasound (QUS) assessment to evaluate lymphedema severity compared with the gold standard method, the International Society of Lymphology (ISL) stage. Ultrasonic measurements were made around the middle thigh (n=150). Radiofrequency data were acquired using a clinical scanner and 8-MHz linear probe. Envelope statistical analysis was performed using constant false alarm rate processing and homodyned K (HK) distribution. The attenuation coefficient was calculated using the spectral log-difference technique. The backscatter coefficient (BSC) was obtained by the reference phantom method with attenuation compensation according to the attenuation coefficients in the dermis and hypodermis, and then effective scatterer diameter (ESD) and effective acoustic concentration (EAC) were estimated with a Gaussian model. Receiver operating characteristic curves of QUS parameters were obtained using a linear regression model. A single QUS parameter with high area under the curve (AUC) differed between the dermis (ESD and EAC) and hypodermis (HK) parameters. The combinations with ESD and EAC in the dermis, HK parameters in the hypodermis and typical features (dermal thickness and echogenic regions in the hypodermis) improved classification performance between ISL stages 0 and ≥I (AUC=0.90 with sensitivity of 75% and specificity of 91%) in comparison with ESD and EAC in the dermis (AUC=0.82) and HK parameters in the hypodermis (AUC=0.82). In vivo QUS assessment by BSC and envelope statistical analyses can be valuable for non-invasively classifying an extremely early stage of lymphedema, such as ISL stage I, and following its progression.

Regularized Estimation of Effective Scatterer Size and Acoustic Concentration Quantitative Ultrasound Parameters Using Dynamic Programming.

The objective of quantitative ultrasound (QUS) is to characterize tissue microstructure by parametrizing backscattered radiofrequency (RF) signals from clinical ultrasound scanners. Herein, we develop a novel technique based on dynamic programming (DP) to simultaneously estimate the acoustic attenuation, the effective scatterer size (ESS), and the acoustic concentration (AC) from ultrasound backscattered power spectra. This is achieved through two different approaches: (1) using a Gaussian form factor (GFF) and (2) using a general form factor (gFF) that is more flexible than the Gaussian form factor but involves estimating more parameters. Both DP methods are compared to an adaptation of a previously proposed least-squares (LSQ) method. Simulation results show that in the GFF approach, the variance of DP is on average 88%, 75% and 32% lower than that of LSQ for the three estimated QUS parameters. The gFF approach also yields similar improvements.

High-frequency ultrasonic backscatter coefficient analysis considering microscopic acoustic and histopathological properties of lymphedema dermis

We studied the effect of acoustic and histopathological features on the ultrasound backscatter properties of lymphedema (LE) dermis. Experimental effective scatterer diameter (ESD) and effective acoustic concentration (EAC) were calculated from a backscatter coefficient using the reflector method for backscattered signals. Predicted parameters were also analyzed using two-dimensional Fourier transforms of the acoustic impedance and histopathological distributions. Backscattered signals were obtained from ex vivo human tissues negative (n = 5) and positive (n = 5) for LE using a laboratory-made scanner with a 14 MHz transducer. Acoustic impedance was analyzed using scanning acoustic microscopy with a 68 MHz transducer, and histopathological features, such as fiber number density and thickness, were assessed with digital histopathology. Both experimental and predicted EACs showed differences (in the range 25.7%–102%) between negative and positive LE. Although the mean and standard deviation of the acoustic impedance were related to the difference in EACs, the ESD and histopathological features were the same regardless of the presence of LE.

Frequency dependence of attenuation and backscatter coefficient of ex vivo human lymphedema dermis.

Radio-frequency (RF) signals from the most dominant scatterer in a dermis, i.e., collagen fibers, are collected as backscattered signals. We aim to confirm the frequency dependence of the spatial distribution of features in ultrasound images, as well as the attenuation coefficient (AC) and backscatter coefficient (BSC) of skin tissue without [LE (-)] and with lymphedema [LE (+)]. Measurement samples (n = 13) were excised from human skin tissue with LE (-) and middle severity LE (+). A laboratory-made scanner and single-element concave transducers (range 9-47MHz) were used to measure RF data. A localized AC was computed from the normalized power spectrum using the linear least squares technique. The reflector method and compensation technique of the attenuation of tissue were applied to calculate the BSC. In addition, effective scatterer diameter (ESD), effective acoustic concentration (EAC), and integrated BSC (IBS) were calculated from the BSC as the benchmark to differentiate LE (-) and LE (+) tissues. High-frequency ultrasound displayed different echogenicity and texture compared between LE (-) and LE (+) in all transducers. The AC for LE (-) (0.22dB/mm/MHz) and LE (+) (0.29dB/mm/MHz) was comparable. BSC in LE (-) and LE (+) increased linearly with each transducer. The difference of intercept of the BSC between LE (-) and LE (+) indicated that both EAC and IBS of LE (+) were higher than that of LE (-). In contrast, ESD correlated with the slope of the BSC demonstrated the same tendency for both LE (-) and LE (+). These tendencies appeared for each transducer independent of the frequency bandwidth. Frequency independence of AC and BSC in LE (-) and LE (+) was confirmed. Several 9- to 19-MHz ultrasound beams are sufficient for BSC analysis to discriminate LE (-) and LE (+) in terms of the penetration depth of the ultrasound.

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 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.

Detection and imaging of prostate cancer using acoustic radiation force impulse imaging and quantitative ultrasound

Transrectal ultrasound (TRUS) imaging is routinely performed to guide core-needle biopsies for the definitive diagnosis of prostate cancer (PCa). Needles are rigidly attached to the transducer and randomly sample the prostate yielding a high rate of false negative determinations. This study investigated the combined use of acoustic radiation force impulse imaging (ARFI) and quantitative ultrasound (QUS) to detect cancerous lesions in the prostate during TRUS imaging. Three-dimensional (3D) RF data from 12 PCA patients scheduled for radical prostatectomy were acquired over the full gland volume during ARFI data acquisition and used to obtain effective scatterer size (ESS), effective acoustic concentration (ESC), nakagami shape (µ), and nakagami scale (Ω) parameters. In each three-dimensional dataset, healthy and cancerous regions were obtained by manual segmentation using whole-mount histology slides. Linear discriminant and ROC methods were used to quantify the performance of ARFI displacements and QUS estimates at detecting PCa. Results for ARFI displacement and µ alone yielded an area under the ROC (AUC) curve of 0.84 and 0.69, respectively. The AUC value increased to 0.86 when µ and ARFI displacement were linearly combined. These results suggest that QUS and ARFI methods are sensitive to tissue properties affected by PCA. The proposed methods pave the way for novel real-time imaging of PCA during TRUS imaging. [Work supported in part by NIH Grants EB026233 and CA142824 and DOD PRCP Grant W81XWH-16-1-0653.]

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.

Quantitative-ultrasound-based prostate-cancer imaging by means of a novel micro-ultrasound scanner

Currently, transrectal ultrasound (TRUS) guided biopsy is the only method for definitive diagnosis of prostate cancer. Our current study used a high-frequency (i.e., 29-MHz), transrectal, micro-ultrasound system (ExactVu™ micro-ultrasound, Exact Imaging) to acquire RF data from 163 patients immediately before needle firing during 12-core biopsy examinations. Quantitative ultrasound (QUS) estimates of effective scatter diameter (ESD), effective acoustic concentration (EAC), midband (M), intercept (I), and slope (S) were calculated. Additional QUS estimates were derived including envelope statistics employing a Nakagami distribution and the envelope signal-to-noise ratio (ESNR). Estimate values were used to train linear-discriminant classifiers and performance was assessed using area-under-the-curve (AUC) values obtained from receiver operating characteristic (ROC) analyses based on 10-fold cross validation. A combination of ESS- and EAC-related parameters produced an AUC value of 0.75. When ESNR or PSA value was added as a feature, the AUC increased significantly to 0.77 or 0.78, respectively. The best classifier performance was obtained by combining envelope statistics, PSA, ESD, and EAC, which produced an AUC of 0.80. Our initial results with AUC values of 0.80 are very encouraging for developing a new tool for prostate-cancer biopsy guidance and treatment.

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 ( xc) 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 xc (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.

Abstract 889: A comparison between quantitative ultrasound and histology in heterogeneous tumor structure

Abstract Background: To investigate how QUS (Quantitative Ultrasound) maps reflect regional variations in heterogeneous tumor microstructure, we compared like-regions of QUS effective scatterer diameter (ESD, μm) and effective acoustic concentration (EAC, dB/cm) maps to whole-slice, virtual histology sections stained for vascular, cellular and other microstructural features. Methods: An ectopic model of murine colorectal carcinoma (CT26) was implanted in 7 mice (BALB/c). US radiofrequency data were acquired for the longitudinal plane of tumors in vivo (SSI, Aixplorer, SL15-4 probe, research mode) on days 6 and 14 after start of therapy with an anti-angiogenic (AA: n = 3) or placebo (P: n = 4). The AA used is Pazopanib, an oral tyrosine kinase inhibitor of VEGF receptors 1/-2/-3, platelet-derived growth factor receptors (PDGFR) -alfa/-beta, and c-KIT. A daily dose of 2 mg of AA, diluted in 100µl of solution, was administered per os. Average backscattered power spectra were calculated (FFT, 512 pts, Rectangular gated RF), normalized with respect to a reference phantom and corrected for attenuation (0.4 dB/cm/MHz). ESD and EAC were mapped (2 x 2 mm blocks, with 75% axial and lateral overlap). Tumors were excised and marked to conserve orientation and approximate position relative to US imaging plane. Whole-slice, histological sections were prepared with fluorescent immunohistochemical markers at D6 and D14 for invasive assessment of cell nuclei, apoptosis and vascular endothelium. The Number of Nuclei (NU), the % area of Apoptosis (AP) and % area of Vascular (VA) marker were calculated with image analysis processing for each 333µm by 333µm region of histological sections. QUS and histological maps of each tumor were manually segmented and coregistered using an affine registration method so that matched regions could be compared. Results: The absolute value of the non-parametric Spearman correlation coefficient (RS) was computed separately for each mouse to study the correlation between histological parameters and QUS parameters. Two mice of the AA group showed a moderate correlation (0.4<=RS<0.6) between NU and EAC. Only one mouse in the P group showed strong correlation (0.6<=RS) for [AP vs. ESD], [AP vs. EAC], [VA vs. ESD] and [VA vs. EAC]. The other tumors (1 from AA group and 3 from P group) showed poor correlation (RS<0,4). Additional data is available from 14 other mice (7 from AA group and 7 from P group) and will be analyzed to more fully investigate correlation between the QUS parameters and the histological parameters. Conclusions: This original technique to compare QUS parameter maps and whole slice histology analysis shows a promising evolution for this non-invasive imaging technique. Complete results on 21 mice will be presented in April. Citation Format: Jerome Griffon, Delphine Le Guillou-Buffello, Oumeima Laifa, Alexandre Dizeux, Micheal Oelze, Lori Bridal, Michele Lamuraglia. A comparison between quantitative ultrasound and histology in heterogeneous tumor structure [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 889. doi:10.1158/1538-7445.AM2017-889

Comparison of quantitative ultrasound parameters from two approaches on in vivo human fatty liver

Two different quantitative ultrasound (QUS) processing strategies are evaluated and compared. The first method estimates the Lizzi-Feleppa (LF) parameters from the linear fit of the normalized power spectrum, and yields the slope, the intercept, and the midband. The QUS approach relies on the attenuation and BSC versus frequency, and yields the mean attenuation and BSC. By using the spherical Gaussian model, the effective scatterer diameter (ESD) and acoustic concentration (EAC) are estimated from the BSC. The goal of this study is to compare the LF and QUS parameters to determine how they are correlated and to verify their correlation with ESD and EAC. To do this, RF data were acquired using a Siemens S3000 from 20 patient livers (suspected of Non-Alcoholic Fatty Liver Diseases (NAFLD)) and from these spectra, the LF and QUS parameters were estimated. The liver fat fraction for each patient was estimated using MRI, and ranged from 0.03 to 0.3. The results show that LF slope is correlated to ESD (R2 = 0.75), LF midband to EAC (R2 = 0.70), and LF intercept to ESD and EAC. A very high correlation between LF midband and the mean BSC is observed (R2 = 1.00), along with the fat fraction (R2 = 0.63). [Support: NIH R01DK106419.]

Quantitative Ultrasound for Monitoring High-Intensity Focused Ultrasound Treatment In Vivo.

The success of any minimally invasive treatment procedure can be enhanced significantly if combined with a robust noninvasive imaging modality that can monitor therapy in real time. Quantitative ultrasound (QUS) imaging has been widely investigated for monitoring various treatment responses such as chemotherapy, radiation, and thermal therapy. Previously, we demonstrated the feasibility of using spectral-based QUS parameters to monitor high-intensity focused ultrasound (HIFU) treatment of in situ tumors in euthanized rats [Ultrasonic Imaging 36(4), 239-255, 2014]. In the present study, we examined the use of spectral-based QUS parameters to monitor HIFU treatment of in vivo rat mammary adenocarcinoma tumors (MAT) where significant tissue motion was present. HIFU was applied to tumors in rats using a single-element transducer. During the off part of the HIFU duty cycle, ultrasound backscatter was recorded from the tumors using a linear array co-aligned with the HIFU focus. A total of 10 rats were treated with HIFU in this study with an additional sham-treated rat. Spectral parameters from the backscatter coefficient, i.e., effective scatterer diameter (ESD) and effective acoustic concentration (EAC), were estimated. The changes of each parameter during treatment were compared with a temperature profile recorded by a fine-needle thermocouple inserted into the tumor a few millimeters behind the focus of the HIFU transducer. The mean ESD changed from 121 ±6 to [Formula: see text], and the EAC changed from 33 ±2 to [Formula: see text] during HIFU exposure as the temperature increased on average from 38.7 ±1.0 (°)C to 64.2 ±2.7 (°)C. The changes in ESD and EAC were linearly correlated with the changes in tissue temperature during the treatment. When HIFU was turned off, the ESD increased from 81 ±8 to [Formula: see text] and the EAC dropped from 46 ±3 to 36±2 dB/cm(3) as the temperature decreased from 64.2 ±2.7 (°)C to 45 ±2.7 (°)C. QUS was demonstrated in vivo to track temperature elevations caused by HIFU exposure.

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.

The Best of Quantitative Ultrasound

The objective of these studies was to demonstrate that quantitative ultrasound (QUS) techniques could be used to improve diagnostic ultrasound imaging. Specifically, QUS techniques were applied to improving detection of breast and thyroid cancer, early detection of preterm birth, quantification of fatty liver and thermometry. QUS techniques were employed that utilized parameterization of the frequency-dependent backscatter coefficient, the attenuation coefficient and/or envelope statistics. The backscatter coefficient was parameterized through the effective scatterer diameter (ESD) and the effective acoustic concentration (EAC). Backscattered ultrasound data were acquired from tissue samples using clinical ultrasound scanners providing the RF signal and from laboratory systems utilizing single-element focused transducers. The data spanned frequency ranges from 2 to 50 MHz. Combinations of the ESD, EAC and envelope statistics were successful in differentiating malignant from benign tumors in rodent models of breast cancer. Similarly, the ESD combined with envelope statistics provided differentiation of malignant from benign nodules in mouse models of thyroid cancer. Cervical attenuation was an early predictor of preterm birth in rat models and in humans. Attenuation and the slope and magnitude of the backscatter coefficient were observed to predict the degree of fatty liver in mouse models and in humans. The EAC was observed to track temperature when using thermal therapies in different tissues. QUS techniques have continued to mature and have demonstrated new sources of contrast leading to improved diagnostic capabilities and the ability to monitor and assess therapy.

Backscatter coefficient estimation using tapers with gaps

When using the backscatter coefficient (BSC) to estimate quantitative ultrasound (QUS) parameters such as the effective scatterer diameter (ESD) and the effective acoustic concentration (EAC), it is necessary to assume that the interrogated medium contains diffuse scatterers. Structures that invalidate this assumption can significantly affect the estimated BSC parameters in terms of increased bias and variance and decrease performance when classifying disease. In this work, a method was developed to mitigate the effects of non-diffuse echoes, while preserving as much signal as possible for obtaining diffuse scatterer property estimates. Specially designed tapers with gaps that avoid signal truncation were utilized for this purpose. Experiments from physical phantoms were used to evaluate the effectiveness of the proposed BSC estimation methods. The mean squared error (MSE) for BSC between measured and theoretical had an average value of approximately 1.0 and 0.2 when using a Hanning taper and PR taper, respectively, with six gaps. The BSC error due to amplitude bias was smallest for PR tapers with time-bandwidth product Nω = 1. The BSC error due to shape bias was smallest for PR tapers with Nω = 4. These results suggest using different taper types for estimating ESD versus EAC.

Backscatter coefficient estimation using tapers with gaps.

When using the backscatter coefficient (BSC) to estimate quantitative ultrasound parameters such as the effective scatterer diameter (ESD) and the effective acoustic concentration (EAC), it is necessary to assume that the interrogated medium contains diffuse scatterers. Structures that invalidate this assumption can affect the estimated BSC parameters in terms of increased bias and variance and decrease performance when classifying disease. In this work, a method was developed to mitigate the effects of echoes from structures that invalidate the assumption of diffuse scattering, while preserving as much signal as possible for obtaining diffuse scatterer property estimates. Backscattered signal sections that contained nondiffuse signals were identified and a windowing technique was used to provide BSC estimates for diffuse echoes only. Experiments from physical phantoms were used to evaluate the effectiveness of the proposed BSC estimation methods. Tradeoffs associated with effective mitigation of specular scatterers and bias and variance introduced into the estimates were quantified. Analysis of the results suggested that discrete prolate spheroidal (PR) tapers with gaps provided the best performance for minimizing BSC error. Specifically, the mean square error for BSC between measured and theoretical had an average value of approximately 1.0 and 0.2 when using a Hanning taper and PR taper respectively, with six gaps. The BSC error due to amplitude bias was smallest for PR (Nω = 1) tapers. The BSC error due to shape bias was smallest for PR (Nω = 4) tapers. These results suggest using different taper types for estimating ESD versus EAC.

Quantitative Ultrasound Imaging for Monitoring In Situ High-Intensity Focused Ultrasound Exposure

Quantitative ultrasound (QUS) imaging is hypothesized to map temperature elevations induced in tissue with high spatial and temporal resolution. To test this hypothesis, QUS techniques were examined to monitor high-intensity focused ultrasound (HIFU) exposure of tissue. In situ experiments were conducted on mammary adenocarcinoma tumors grown in rats and lesions were formed using a HIFU system. A thermocouple was inserted into the tumor to provide estimates of temperature at one location. Backscattered time-domain waveforms from the tissue during exposure were recorded using a clinical ultrasonic imaging system. Backscatter coefficients were estimated using a reference phantom technique. Two parameters were estimated from the backscatter coefficient (effective scatterer diameter (ESD) and effective acoustic concentration (EAC). The changes in the average parameters in the regions corresponding to the HIFU focus over time were correlated to the temperature readings from the thermocouple. The changes in the EAC parameter were consistently correlated to temperature during both heating and cooling of the tumors. The changes in the ESD did not have a consistent trend with temperature. The mean ESD and EAC before exposure were 120 ± 16 μm and 32 ± 3 dB/cm3, respectively, and changed to 144 ± 9 μm and 51 ± 7 dB/cm3, respectively, just before the last HIFU pulse was delivered to the tissue. After the tissue cooled down to 37 °C, the mean ESD and EAC were 126 ± 8 μm and 35 ± 4 dB/cm3, respectively. Peak temperature in the range of 50-60 °C was recorded by a thermocouple placed just behind the tumor. These results suggest that QUS techniques have the potential to be used for non-invasive monitoring of HIFU exposure.