Elastography: history, principles, and technique comparison.

Elastography is a relatively new imaging technology that creates images of tissue stiffness. It can be thought of an extension of the ancient technique of palpation but it gives better spatial localization information and is less subjective. Two main types of elastography are currently in use, strain elastography where the tissue displacement in response to gentle pressure is used to compute and image tissue strain, and shear wave elastography where the speed of shear waves traversing tissue is measured and used to create an image of tissue stiffness. Each method has advantages and disadvantages but generally strain imaging is excellent for focal lesions and shear wave imaging, being more quantitative, is best for diffuse organ diseases. Strain imaging requires additional training in acquisition technique to obtain high quality images. Pitfalls to avoid and tips for good images are provided. Improvements in strain imaging are focused on better quality indicators and better methods for quantification. Improvements in shear wave imaging will be higher frame rates, greater accuracy in focal lesions, and making results more comparable between different ultrasound systems. Both methods will continue to improve and will provide ever more powerful new tools for diagnosis of diffuse and focal diseases.

Texture quantified from ultrasound Nakagami parametric images is diagnostically relevant for breast tumor characterization.

Purpose: We evaluate texture quantified from ultrasound Nakagami parametric images for non-invasive characterization of breast tumors, as Nakagami images can more faithfully represent intrinsic tumor characteristics than standard B-mode images. Approach: Parametric images were formed using sliding windows applied to ultrasound envelope data. To analyze the trade-off between spatial resolution and stability of estimated Nakagami parameters for texture quantification, two different window sizes were used for image formation: (i) the standard square window with sides equal to three times the pulse length of incident ultrasound, and (ii) a smaller square window with sides equal to exactly the pulse length. Texture was quantified from two different regions of interest (ROIs) consisting of the tumor core and a 5 mm surrounding margin. A total of 186 texture features were analyzed for each ROI, and feature selection was used to identify the most relevant feature sets for breast tumor characterization. Results: Texture quantified from parametric images formed using the two different windows did not outperform each other by a significant margin. However, when the mean pixel value within the tumor region of the parametric images was incorporated with the texture features, texture quantified from the tumor core and surrounding margin of images formed using the standard square window thoroughly outperformed other considerations for breast lesion characterization. The highest performing set of texture and mean value features yielded a significant AUC of 0.94, along with sensitivity of 90.38% and specificity of 89.58%. Conclusions: We establish that texture quantified from ultrasound Nakagami parametric images are diagnostically relevant and may be used to characterize breast lesions effectively.

Ultrasound classification of breast masses using a comprehensive Nakagami imaging and machine learning framework.

In this study we investigate the potential of parametric images formed from ultrasound B-mode scans using the Nakagami distribution for non-invasive classification of breast lesions and characterization of breast tissue. Through a sliding window technique, we generated seven types of Nakagami images for each patient scan in our dataset using basic and as well as derived parameters of the Nakagami distribution. To determine the suitable window size for image generation, we conducted an empirical analysis using 4 windows, which includes 3 column windows of lengths 0.1875 mm, 0.45 mm and 0.75 mm and widths of 0.002 mm, along with the standard square window with sides equal to three times the pulse length of incident ultrasound. From the parametric image sets generated using each window, we extracted a total of 72 features that consisted of morphometric, elemental and hybrid features. To our knowledge no other literature has conducted such a comprehensive analysis of Nakagami parametric images for the classification of breast lesions. Feature selection was performed to find the most useful subset of features from each of the parametric image sets for the classification of breast cancer. Analyzing the classification accuracy and Area under the Receiver Operating Characteristic (ROC) Curve (AUC) of the selected feature subsets, we determined that the selected features acquired from Nakagami parametric images generated using a column window of length 0.75 mm provides the best results for characterization of breast lesions. This optimal feature set provided a classification accuracy of 93.08%, an AUC of 0.9712, a False Negative Rate (FNR) of 0%, and a very low False Positive Rate (FPR) of 8.65%. Our results indicate that the high accuracy of such a procedure may assist in the diagnosis of breast cancer by helping to reduce false positive diagnoses.

Evaluation of Fluence Correction Algorithms in Multispectral Photoacoustic Imaging.

Multispectral photoacoustic imaging (MPAI) is a promising emerging diagnostic technology, but fluence artifacts can degrade device performance. Our goal was to develop well-validated phantom-based test methods for evaluating and comparing MPAI fluence correction algorithms, including a heuristic diffusion approximation, Monte Carlo simulations, and an algorithm we developed based on novel application of the diffusion dipole model (DDM). Phantoms simulated a range of breast-mimicking optical properties and contained channels filled with chromophore solutions (ink, hemoglobin, or copper sulfate) or connected to a previously developed blood flow circuit providing tunable oxygen saturation (SO2). The DDM algorithm achieved similar spectral recovery and SO2 measurement accuracy to Monte Carlo-based corrections with lower computational cost, potentially providing an accurate, real-time correction approach. Algorithms were sensitive to optical property uncertainty, but error was minimized by matching phantom albedo. The developed test methods may provide a foundation for standardized assessment of MPAI fluence correction algorithm performance.

Multidomain computational modeling of photoacoustic imaging: verification, validation, and image quality prediction.

As photoacoustic imaging (PAI) technology matures, computational modeling will increasingly represent a critical tool for facilitating clinical translation through predictive simulation of real-world performance under a wide range of device and biological conditions. While modeling currently offers a rapid, inexpensive tool for device development and prediction of fundamental image quality metrics (e.g., spatial resolution and contrast ratio), rigorous verification and validation will be required of models used to provide regulatory-grade data that effectively complements and/or replaces in vivo testing. To address methods for establishing model credibility, we developed an integrated computational model of PAI by coupling a previously developed three-dimensional Monte Carlo model of tissue light transport with a two-dimensional (2D) acoustic wave propagation model implemented in the well-known k-Wave toolbox. We then evaluated ability of the model to predict basic image quality metrics by applying standardized verification and validation principles for computational models. The model was verified against published simulation data and validated against phantom experiments using a custom PAI system. Furthermore, we used the model to conduct a parametric study of optical and acoustic design parameters. Results suggest that computationally economical 2D acoustic models can adequately predict spatial resolution, but metrics such as signal-to-noise ratio and penetration depth were difficult to replicate due to challenges in modeling strong clutter observed in experimental images. Parametric studies provided quantitative insight into complex relationships between transducer characteristics and image quality as well as optimal selection of optical beam geometry to ensure adequate image uniformity. Multidomain PAI simulation tools provide high-quality tools to aid device development and prediction of real-world performance, but further work is needed to improve model fidelity, especially in reproducing image noise and clutter.

Photoacoustic oximetry imaging performance evaluation using dynamic blood flow phantoms with tunable oxygen saturation.

Multispectral photoacoustic oximetry imaging (MPOI) is an emerging hybrid modality that enables the spatial mapping of blood oxygen saturation (SO2) to depths of several centimeters. To facilitate MPOI device development and clinical translation, well-validated performance test methods and improved quantitative understanding of physical processes and best practices are needed. We developed a breast-mimicking blood flow phantom with tunable SO2 and used this phantom to evaluate a custom MPOI system. Results provide quantitative evaluation of the impact of phantom medium properties (Intralipid versus polyvinyl chloride plastisol) and device design parameters (different transducers) on SO2 measurement accuracy, especially depth-dependent performance degradation due to fluence artifacts. This approach may guide development of standardized test methods for evaluating MPOI devices.

Breast tumor classification using axial shear strain elastography: a feasibility study.

Recently, the feasibility of visualizing the characteristics of bonding at an inclusion-background boundary using axial-shear strain elastography was demonstrated. In this paper, we report a feasibility study on the utility of the axial-shear strain elastograms in the classification of in vivo breast tumor as being benign or malignant. The study was performed using data sets obtained from 15 benign and 15 malignant cases that were biopsy proven. A total of three independent observers were trained, and their services were utilized for the study. A total of 9 cases were used as training set and the remaining cases were used as testing set. The feature from the axial-shear strain elastogram, namely, the area of the axial-shear region, was extracted by the observers. The observers also outlined the tumor area on the corresponding sonogram, which was used to normalize the area of the axial-shear strain region. There are several observations that can be drawn from the results. First, the result indicates that the observers consistently ( approximately 82% of the cases) noticed the characteristic pattern of the axial-shear strain distribution data as predicted in the previous simulation studies, i.e. alternating regions of positive and negative axial-shear strain values around the tumor-background interface. Second, the analysis of the result suggests that in approximately 57% of the cases in which the observers did not visualize tumor in the sonogram, the elastograms helped them to locate the tumor. Finally, the analysis of the result suggests that for the discriminant feature value of 0.46, the number of unnecessary biopsies could be reduced by 56.3% without compromising on sensitivity and on negative predictive value (NPV). Based on the results in this study, feature values greater than 0.75 appear to be indicative of malignancy, while values less than 0.46 to be indicative of benignity. Feature values between 0.46 and 0.75 may result in an overlap between benign and malignant cases.

Visualization of bonding at an inclusion boundary using axial-shear strain elastography: a feasibility study.

Ultrasound elastography produces strain images of compliant tissues under quasi-static compression. In axial-shear strain elastography, the local axial-shear strain resulting from application of quasi-static axial compression to an inhomogeneous material is imaged. The overall hypothesis of this work is that the pattern of axial-shear strain distribution around the inclusion/background interface is completely determined by the bonding at the interface after normalization for inclusion size and applied strain levels, and that it is feasible to extract certain features from the axial-shear strain elastograms to quantify this pattern. The mechanical model used in this study consisted of a single stiff circular inclusion embedded in a homogeneous softer background. First, we performed a parametric study using finite-element analysis (FEA) (no ultrasound involved) to identify possible features that quantify the pattern of axial-shear strain distribution around an inclusion/background interface. Next, the ability to extract these features from axial-shear strain elastograms, estimated from simulated pre- and post-compression noisy RF data, was investigated. Further, the feasibility of extracting these features from in vivo breast data of benign and malignant tumors was also investigated. It is shown using the FEA study that the pattern of axial-shear strain distribution is determined by the degree of bonding at the inclusion/background interface. The results suggest the feasibility of using normalized features that capture the region of positive and negative axial-shear strain area to quantify the pattern of the axial-shear strain distribution. The simulation results showed that it was feasible to extract the features, as identified in the FEA study, from axial-shear strain elastograms. However, an effort must be made to obtain axial-shear strain elastograms with the highest signal-to-noise ratio (SNR(asse)) possible, without compromising the resolution. The in vivo results demonstrated the feasibility of producing and extracting features from the axial-shear strain elastograms from breast data. Furthermore, the in vivo axial-shear strain elastograms suggest an additional feature not identified in the simulations that may potentially be used for distinguishing benign from malignant tumors-the proximity of the axial-shear strain regions to the inclusion/background interface identified in the sonogram.

The feasibility of using poroelastographic techniques for distinguishing between normal and lymphedematous tissues in vivo.

Lymphedema is a common condition involving an abnormal accumulation of lymphatic fluid in the interstitial space that causes swelling, most often in the arm(s) and leg(s). Lymphedema is a significant lifelong concern that can be congenital or develop following cancer treatment or cancer metastasis. Common methods of evaluation of lymphedema are mostly qualitative making it difficult to reliably assess the severity of the disease, a key factor in choosing the appropriate treatment. In this paper, we investigate the feasibility of using novel elastographic techniques to differentiate between lymphedematous and normal tissues. This study represents the first step of a larger study aimed at investigating the combined use of elastographic and sonographic techniques for the detection and staging of lymphedema. In this preliminary study, poroelastographic images were generated from the leg (8) and arm (4) subcutis of five normal volunteers and seven volunteers having lymphedema, and the results were compared using statistical analyses. The preliminary results reported in this paper suggest that it may be feasible to perform poroelastography in different lymphedematous tissues in vivo and that poroelastography techniques may be of help in differentiating between normal and lymphedematous tissues.

Phantom-based image quality test methods for photoacoustic imaging systems.

As photoacoustic imaging (PAI) technologies advance and applications arise, there is increasing need for standardized approaches to provide objective, quantitative performance assessment at various stages of the product development and clinical translation process. We have developed a set of performance test methods for PAI systems based on breast-mimicking tissue phantoms containing embedded inclusions. Performance standards for mature imaging modalities [magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound] were used to guide selection of critical PAI image quality characteristics and experimental methods. Specifically, the tests were designed to address axial, lateral, and elevational spatial resolution, signal uniformity, penetration depth, sensitivity, spatial measurement accuracy, and PAI-ultrasound coregistration. As an initial demonstration of the utility of these test methods, we characterized the performance of a modular, bimodal PAI-ultrasound system using four clinical ultrasound transducers with varying design specifications. Results helped to inform optimization of acquisition and data processing procedures while providing quantitative elucidation of transducer-dependent differences in image quality. Comparison of solid, tissue-mimicking polymer phantoms with those based on Intralipid indicated the superiority of the former approach in simulating real-world conditions for PAI. This work provides a critical foundation for the establishment of well-validated test methods that will facilitate the maturation of PAI as a medical imaging technology.

Two-layer heterogeneous breast phantom for photoacoustic imaging.

Photoacoustic tomography (PAT) is emerging as a potentially important aid for breast cancer detection. Well-validated tissue-simulating phantoms are needed for objective, quantitative, and physically realistic testing for system development. Prior reported PAT phantoms with homogenous structures do not incorporate the irregular layered structure of breast tissue. To assess the impact of this simplification, we design and construct two-layer breast phantoms incorporating vessel-simulating inclusions and realistic undulations at the fat/fibroglandular tissue interface. The phantoms are composed of custom poly(vinyl chloride) plastisol formulations mimicking the acoustic properties of two breast tissue types and tissue-relevant similar optical properties. Resulting PAT images demonstrate that in tissue with acoustic heterogeneity, lateral size of imaging targets is sensitive to the choice of sound speed in image reconstruction. The undulating boundary can further degrade a target's lateral size due to sound speed variation in tissue and refraction of sound waves at the interface. The extent of this degradation is also influenced by the geometric relationship between an absorber and the boundary. Results indicate that homogeneous phantom matrixes may underestimate the degradation of PAT image quality in breast tissue, whereas heterogeneous phantoms can provide more realistic testing through improved reproduction of spatial variations in physical properties.

Biologically relevant photoacoustic imaging phantoms with tunable optical and acoustic properties.

Established medical imaging technologies such as magnetic resonance imaging and computed tomography rely on well-validated tissue-simulating phantoms for standardized testing of device image quality. The availability of high-quality phantoms for optical-acoustic diagnostics such as photoacoustic tomography (PAT) will facilitate standardization and clinical translation of these emerging approaches. Materials used in prior PAT phantoms do not provide a suitable combination of long-term stability and realistic acoustic and optical properties. Therefore, we have investigated the use of custom polyvinyl chloride plastisol (PVCP) formulations for imaging phantoms and identified a dual-plasticizer approach that provides biologically relevant ranges of relevant properties. Speed of sound and acoustic attenuation were determined over a frequency range of 4 to 9 MHz and optical absorption and scattering over a wavelength range of 400 to 1100 nm. We present characterization of several PVCP formulations, including one designed to mimic breast tissue. This material is used to construct a phantom comprised of an array of cylindrical, hemoglobin-filled inclusions for evaluation of penetration depth. Measurements with a custom near-infrared PAT imager provide quantitative and qualitative comparisons of phantom and tissue images. Results indicate that our PVCP material is uniquely suitable for PAT system image quality evaluation and may provide a practical tool for device validation and intercomparison.

Comparison of windowing effects on elastography images: Simulation, phantom and in vivo studies.

In this paper, we have evaluated the use of smooth windows for ultrasound elastography. In ultrasound elastography, local tissue strain is estimated using operations such as cross-correlation on local segments of RF data. In this process, local data segments are selected by multiplying the RF data by a rectangular window. Such data truncation causes non-ideal spectral behavior, which can be mitigated by using smooth windows. Accordingly, we hypothesize that the use of smooth windows may improve the elastographic signal-to-noise ratio (SNRe) and contrast-to-noise ratio (CNRe) of strain images. The effects of using smooth windows have not been fully characterized for time-domain strain estimators. Thus, we have compared the elastographic performance of rectangular, Hanning, Gaussian, and Chebyshev windows used in conjunction with cross-correlation based algorithm and adaptive stretching algorithm using finite element method (FEM) simulation, experimental phantom, and in vivo data. Smooth windows are found to improve the SNRe by up to 3.94 for FEM data and by up to 1.76 for phantom data which represent 76% and 60.52% improvements, respectively. CNRe improves by up to 12.23 for FEM simulated data and by up to 4.28 for phantom data which represent 213.07% and 248.2% improvements, respectively. Mean structural similarity (MSSIM) was used for assessing the image perceptual quality and smooth windows improved it by up to 0.22 (85.98% improvement) for simulated data. We have evaluated these parameters at 1-6% applied strains for the experimental phantom and at 1%, 2%, 4%, 6%, 8%, and 12% applied strains for FEM simulation. We observed a maximum deterioration in axial resolution of 0.375 mm (which is on the order of the wavelength, 0.3mm) due to smooth windows. "Salt-and-pepper" noise from false-peak errors has also been reduced. Smooth windows increased the lesion-to-background contrast (by increasing the CNRe by 213.07%) of a low contrast lesion (10-dB). For the in vivo cases, use of smooth windows resulted in better depiction of lesions, which is important for lesion classification. In this work, we have used an ATL Ultramark 9 scanner with an L10-5 (7.5 MHz) probe for the phantom experiment and a Sonix SP500 scanner with an L14-5/38 probe (10 MHz) for in vivo data collection.

Tissue displacements during acupuncture using ultrasound elastography techniques.

Acupuncture needle manipulation has been previously shown to result in measurable changes in connective tissue architecture in animal experiments. In this study, we used a novel in vivo ultrasound (US)-based technique to quantify tissue displacement during acupuncture manipulation in humans. B-scan ultrasonic imaging was performed on the thighs of 12 human subjects at different stages of needle motion, including varying amounts of rotation, downward and upward movement performed with a computer-controlled acupuncture needling instrument. Tissue displacements, estimated using cross-correlation techniques, provided successful mapping and quantitative analysis of spatial and temporal tissue behavior during acupuncture needle manipulation. Increasing amounts of rotation had a significant linear effect on tissue displacement during downward and upward needle motion, as well as on rebound tissue displacement after downward needle movement. In addition to being a valuable tool for studies of acupuncture's mechanism of action, this technique may have applications to other types of needling including biopsies.

Elastography: Imaging the elastic properties of soft tissues with ultrasound.

Elastography is a method that can ultimately generate several new kinds of images, called elastograms. As such, all the properties of elastograms are different from the familiar properties of sonograms. While sonograms convey information related to the local acoustic backscatter energy from tissue components, elastograms relate to its local strains, Young's moduli or Poisson's ratios. In general, these elasticity parameters are not directly correlated with sonographic parameters, i.e. elastography conveys new information about internal tissue structure and behavior under load that is not otherwise obtainable. In this paper we summarize our work in the field of elastography over the past decade. We present some relevant background material from the field of biomechanics. We then discuss the basic principles and limitations that are involved in the production of elastograms of biological tissues. Results from biological tissues in vitro and in vivo are shown to demonstrate this point. We conclude with some observations regarding the potential of elastography for medical diagnosis.

Elastography: current status, future prospects, and making it work for you.

Elastography has emerged as a useful adjunct tool for ultrasound diagnosis. Elastograms are images of tissue stiffness and may be in color, grayscale, or a combination of the two. The first and most common application of elastography is for the diagnosis of breast lesions where studies have shown an area under the receiver operating characteristic curve of 0.88 to 0.95 for distinguishing cancer from benign lesions. The technique is also useful for the diagnosis of complex cysts, although different scanners may vary in how they display such lesions. Recent advances in elastography include quantification using strain ratios, acoustic radiation force impulse imaging, and shear wave velocity estimation. These are useful not only for characterizing focal masses but also for diagnosing diffuse organ diseases such as liver cirrhosis. Other near term potential applications for elastography include characterization of thyroid nodules and lymph node evaluation for metastatic disease. Prostate cancer detection is also a potential application, but obtaining high-quality elastograms may be difficult. This area is evolving. Other promising applications include atheromatous plaque and arterial wall evaluation, venous thrombus evaluation, graft rejection, and monitoring of tumor ablation therapy. When contemplating the acquisition of a system with elastography in this rapidly evolving field, a clear picture of the manufacturer's plans for future upgrades (including quantification) should be obtained.

Ultrasonic multi-feature analysis procedure for computer-aided diagnosis of solid breast lesions.

We have developed quantitative descriptors to provide an objective means of noninvasive identification of cancerous breast lesions. These descriptors include quantitative acoustic features assessed using spectrum analysis of ultrasonic radiofrequency (rf) echo signals and morphometric properties related to lesion shape. Acoustic features include measures of echogenicity, heterogeneity and shadowing, computed by generating spectral-parameter images of the lesion and surrounding tissue. Spectral-parameter values are derived from rf echo signals at each pixel using a sliding-window Fourier analysis. We derive quantitative acoustic features from spectral-parameter maps of the lesion and adjacent areas. We quantify morphometric features by geometric and fractal analysis of traced lesion boundaries. Initial results on biopsy-proven cases show that although a single parameter cannot reliably discriminate cancerous from noncancerous breast lesions, multi-feature analysis provides excellent discrimination for this data set. We have processed data for 130 biopsy-proven patients, acquired during routine ultrasonic examinations at three clinical sites and produced an area under the receiver-operating-characteristics (ROC) curve of 0.947 +/- 0.045. Among the quantitative descriptors, lesion-margin definition, spiculation and border irregularity are the most useful; some additional morphometric features (such as border irregularity) also are particularly effective in lesion classification. Our findings are consistent with many of the BI-RADS (Breast Imaging Reporting and Data System) breast-lesion-classification criteria in use today.

AN OVERVIEW OF ELASTOGRAPHY - AN EMERGING BRANCH OF MEDICAL IMAGING.

From times immemorial manual palpation served as a source of information on the state of soft tissues and allowed detection of various diseases accompanied by changes in tissue elasticity. During the last two decades, the ancient art of palpation gained new life due to numerous emerging elasticity imaging (EI) methods. Areas of applications of EI in medical diagnostics and treatment monitoring are steadily expanding. Elasticity imaging methods are emerging as commercial applications, a true testament to the progress and importance of the field.In this paper we present a brief history and theoretical basis of EI, describe various techniques of EI and, analyze their advantages and limitations, and overview main clinical applications. We present a classification of elasticity measurement and imaging techniques based on the methods used for generating a stress in the tissue (external mechanical force, internal ultrasound radiation force, or an internal endogenous force), and measurement of the tissue response. The measurement method can be performed using differing physical principles including magnetic resonance imaging (MRI), ultrasound imaging, X-ray imaging, optical and acoustic signals.Until recently, EI was largely a research method used by a few select institutions having the special equipment needed to perform the studies. Since 2005 however, increasing numbers of mainstream manufacturers have added EI to their ultrasound systems so that today the majority of manufacturers offer some sort of Elastography or tissue stiffness imaging on their clinical systems. Now it is safe to say that some sort of elasticity imaging may be performed on virtually all types of focal and diffuse disease. Most of the new applications are still in the early stages of research, but a few are becoming common applications in clinical practice.

Axial-shear strain elastography for breast lesion classification: further results from in vivo data.

The purpose of this work was to investigate the potential of the normalized axial-shear strain area (NASSA) feature, derived from axial-shear strain elastograms (ASSE), for breast lesion classification of fibroadenoma and cancer. This study consisted of previously acquired in vivo digital radiofrequency data of breast lesions. A total of 33 biopsy-proven malignant tumors and 30 fibroadenoma cases were included in the study, which involved three observers blinded to the original BIRADS-ultrasound scores. The observers outlined the lesions on the sonograms. The ASSEs were segmented and color-overlaid on the sonograms, and the NASSA feature from the ASSE was computed semi-automatically. Receiver operating characteristic (ROC) curves were then generated and the area under the curve (AUC) was calculated for each observer performance. A logistic regression classifier was built to compare the improvement in the AUC when using BIRADS scores plus NASSA values as opposed to BIRADS scores alone. BIRADS score ROC had an AUC of 0.89 (95% CI = 0.81 to 0.97). In comparison, the average of the AUC for all the three observers using ASSE feature alone was 0.84. However, the AUC increased to 0.94 (average of 3 observers) when BIRADS score and ASSE feature were combined. The results demonstrate that the NASSA feature derived from ASSE has the potential to improve BIRADS breast lesion classification of fibroadenoma and malignant tumors.