A Force-Matched Approach to Large-Strain Nonlinearity in Elasticity Imaging for Breast Lesion Characterization.

OBJECTIVE: Ultrasound elasticity imaging is a class of ultrasound techniques with applications that include the detection of malignancy in breast lesions. Although elasticity imaging traditionally assumes linear elasticity, the large strain elastic response of soft tissue is known to be nonlinear. This study evaluates the nonlinear response of breast lesions for the characterization of malignancy using force measurement and force-controlled compression during ultrasound imaging. METHODS: 54 patients were recruited for this study. A custom force-instrumented compression device was used to apply a controlled force during ultrasound imaging. Motion tracking derived strain was averaged over lesion or background ROIs and matched with compression force. The resulting force-matched strain was used for subsequent analysis and curve fitting. RESULTS: Greater median differences between malignant and benign lesions were observed at higher compressional forces (p-value < 0.05 for compressional forces of 2-6N). Of three candidate functions, a power law function produced the best fit to the force-matched strain. A statistically significant difference in the scaling parameter of the power function between malignant and benign lesions was observed (p-value = 0.025). CONCLUSIONS: We observed a greater separation in average lesion strain between malignant and benign lesions at large compression forces and demonstrated the characterization of this nonlinear effect using a power law model. Using this model, we were able to differentiate between malignant and benign breast lesions. SIGNIFICANCE: With further development, the proposed method to utilize the nonlinear elastic response of breast tissue has the potential for improving non-invasive lesion characterization for potential malignancy.

Delivering a Quantitative Imaging Agenda.

In a digital image, each voxel contains quantitative information dependent on the technique used to generate the image [...].

A Multimodal Phantom for Visualization and Assessment of Histotripsy Treatments on Ultrasound and X-Ray Imaging.

OBJECTIVE: Histotripsy is an emerging non-invasive, non-ionizing and non-thermal focal tumor therapy. Although histotripsy targeting is currently based on ultrasound (US), other imaging modalities such as cone-beam computed tomography (CBCT) have recently been proposed to enable the treatment of tumors not visible on ultrasound. The objective of this study was to develop and evaluate a multi-modality phantom to facilitate the assessment of histotripsy treatment zones on both US and CBCT imaging. METHODS: Fifteen red blood cell phantoms composed of alternating layers with and without barium were manufactured. Spherical 25-mm histotripsy treatments were performed, and treatment zone size and location were measured on CBCT and ultrasound. Sound speed, impedance and attenuation were measured for each layer type. RESULTS: The average ± standard deviation signed difference between measured treatment diameters was 0.29 ± 1.25 mm. The Euclidean distance between measured treatment centers was 1.68 ± 0.63 mm. The sound speed in the different layers ranged from 1491 to 1514 m/s and was within typically reported soft tissue ranges (1480-1560 m/s). In all phantoms, histotripsy resulted in sharply delineated treatment zones, allowing segmentation in both modalities. CONCLUSION: These phantoms will aid in the development and validation of X-ray-based histotripsy targeting techniques, which promise to expand the scope of treatable lesions beyond only those visible on ultrasound.

Multiparametric Data-driven Imaging Markers: Guidelines for Development, Application and Reporting of Model Outputs in Radiomics.

This paper is the fifth in a five-part series on statistical methodology for performance assessment of multi-parametric quantitative imaging biomarkers (mpQIBs) for radiomic analysis. Radiomics is the process of extracting visually imperceptible features from radiographic medical images using data-driven algorithms. We refer to the radiomic features as data-driven imaging markers (DIMs), which are quantitative measures discovered under a data-driven framework from images beyond visual recognition but evident as patterns of disease processes irrespective of whether or not ground truth exists for the true value of the DIM. This paper aims to set guidelines on how to build machine learning models using DIMs in radiomics and to apply and report them appropriately. We provide a list of recommendations, named RANDAM (an abbreviation of "Radiomic ANalysis and DAta Modeling"), for analysis, modeling, and reporting in a radiomic study to make machine learning analyses in radiomics more reproducible. RANDAM contains five main components to use in reporting radiomics studies: design, data preparation, data analysis and modeling, reporting, and material availability. Real case studies in lung cancer research are presented along with simulation studies to compare different feature selection methods and several validation strategies.

Repeatability of Linear and Nonlinear Elastic Modulus Maps From Repeat Scans in the Breast.

Compression elastography allows the precise measurement of large deformations of soft tissue in vivo. From an image sequence showing tissue undergoing large deformation, an inverse problem for both the linear and nonlinear elastic moduli distributions can be solved. As part of a larger clinical study to evaluate nonlinear elastic modulus maps (NEMs) in breast cancer, we evaluate the repeatability of linear and nonlinear modulus maps from repeat measurements. Within the cohort of subjects scanned to date, 20 had repeat scans. These repeated scans were processed to evaluate NEM repeatability. In vivo data were acquired by a custom-built, digitally controlled, uniaxial compression device with force feedback from the pressure-plate. RF-data were acquired using plane-wave imaging, at a frame-rate of 200 Hz, with a ramp-and-hold compressive force of 8N, applied at 8N/sec. A 2D block-matching algorithm was used to obtain sample-level displacement fields which were then tracked at subsample resolution using 2D cross correlation. Linear and nonlinear elasticity parameters in a modified Veronda-Westmann model of tissue elasticity were estimated using an iterative optimization method. For the repeated scans, B-mode images, strain images, and linear and nonlinear elastic modulus maps are measured and compared. Results indicate that when images are acquired in the same region of tissue and sufficiently high strain is used to recover nonlinearity parameters, then the reconstructed modulus maps are consistent.

Challenges of conducting quantitative ultrasound with a multimodal optical imaging system.

High-frequency quantitative ultrasound is a potential non-invasive source of imaging cell-tissue scale biomarkers for major diseases such as heart disease, cancer, and preterm birth. However, one of the barriers to developing such biomarkers is that it is labor-intensive to compare quantitative ultrasound images to optical images of the tissue structure. We have previously developed a multiscale imaging system that can obtain registered qualitative ultrasound and optical images, but there are further technical challenges to obtaining quantitative data: System-specific details of obtaining and processing data with Verasonics high-frequency transducers; the need for high-frequency reference phantoms; and off-axis clutter from imaging above a glass coverslip. This paper provides a characterization of the Verasonics ultrasound system with the 18.5 MHz L22-14v and 28.5 MHz L38-22v transducers, describes the construction of high-frequency reference phantoms, and details methods for reducing off-axis clutter. The paper features a demonstration multiscale image of a wild type mouse mammary gland that incorporates quantitative ultrasound with both transducers and second harmonic generation microscopy. These advances demonstrate a way to obtain, on a single system with a cohesive and integrated pipeline, quantitative ultrasound data that is correlated with optical imaging without the need for extensive sample preparation.

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.

3-D-Printed Registration Phantom for Combined Ultrasound and Optical Imaging of Biological Tissues.

Efforts to develop quantitative ultrasound biomarkers would benefit from comparisons between ultrasound data and higher-resolution images of the tissue microstructure, such as from optical microscopy. However, only a few studies have used these methods for multiscale imaging because it is difficult to register low-resolution (>100 µm) ultrasound images to high-resolution microscopy images. To address this need, we have designed a 3-D-printed registration phantom that is made of a hard fluorescent resin, fits into a glass-bottom dish and can be used to calculate a coordinate system transform between ultrasound and optical microscopy. We report the phantom design, a registration protocol and an example registration using 18.5-MHz ultrasound and second harmonic generation microscopy. We evaluate the registration precision, achieving standard deviations smaller than the ultrasound resolution across all axes, and illustrate on a mouse mammary gland that this method yields results superior to those of manual landmark registration.

Large-Strain 3-D in Vivo Breast Ultrasound Strain Elastography Using a Multi-compression Strategy and a Whole-Breast Scanning System.

Non-linear mechanical properties of breast tissue can be employed to diagnose and differentiate breast tumors. To obtain such non-linear mechanical properties, it is necessary to track tissue motion under large deformation. In this study, a multi-compression strategy was utilized to produce large tissue deformation, and a method to estimate 3-D motion of tissue under large deformation was introduced. Given multiple volumes of ultrasound data, the proposed method first estimates volume-to-volume incremental displacements using a 3-D region-growing motion-tracking method. Then, possible outliers among all incremental displacements are removed to avoid error accumulation. Once large displacement errors have been removed, all incremental displacements are registered together to obtain accumulated displacements under large tissue deformation (e.g., >10%). The proposed method was tested with one set of in vivo tumor-bearing ultrasound data acquired from a human subject. A total of 10 small-strain deformation steps were performed to obtain the final accumulated displacement field, in which the breast lesion and its surrounding were deformed by approximately 6% and 16%, respectively. The contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of the elasticity images obtained with the proposed method were all higher than those obtained with a 2-D tracking method. Furthermore, in three orthogonal views of accumulated axial strain images, the breast lesion was clearly visible with good correspondence between the axial strain and B-mode images.

A Quantitative Ultrasound-Based Multi-Parameter Classifier for Breast Masses.

This manuscript reports preliminary results obtained by combining estimates of two or three (among seven) quantitative ultrasound (QUS) parameters in a model-free, multi-parameter classifier to differentiate breast carcinomas from fibroadenomas (the most common benign solid tumor). Forty-three patients scheduled for core biopsy of a suspicious breast mass were recruited. Radiofrequency echo signal data were acquired using clinical breast ultrasound systems equipped with linear array transducers. The reference phantom method was used to obtain system-independent estimates of the specific attenuation (ATT), the average backscatter coefficients, the effective scatterer diameter (ESD) and an effective scatterer diameter heterogeneity index (ESDHI) over regions of interest within each mass. In addition, the envelope amplitude signal-to-noise ratio (SNR), the Nakagami shape parameter, m, and the maximum collapsed average (maxCA) of the generalized spectrum were also computed. Classification was performed using the minimum Mahalanobis distance to the centroids of the training classes and tested against biopsy results. Classification performance was evaluated with the area under the receiver operating characteristic (ROC) curve. The best performance with a two-parameter classifier used the ESD and ESDHI and resulted in an area under the ROC curve of 0.98 (95% confidence interval [CI]: 0.95-1.00). Classification performance improved with three parameters (ATT, ESD and ESDHI) yielding an area under the ROC curve of 0.999 (0.995-1.000). These results suggest that system-independent QUS parameters, when combined in a model-free classifier, are a promising tool to characterize breast tumors. A larger study is needed to further test this idea.

A 3-D Region-Growing Motion-Tracking Method for Ultrasound Elasticity Imaging.

A 3-D region-growing motion-tracking (RGMT) method for ultrasound elasticity imaging is described. This 3-D RGMT method first estimates the displacements at a sparse subset of points, called seeds; uses an objective measure to determine, among those seeds, which displacement estimates to trust; and then performs RGMT in three dimensions to estimate displacements for the remaining points in the field. During the growing process in three dimensions, the displacement estimate at one grid point is employed to guide the displacement estimation of its neighboring points using a 3-D small search region. To test this algorithm, volumetric ultrasound radiofrequency echo data were acquired from one phantom and five in vivo human breasts. Displacement estimates obtained with the 3-D RGMT method were compared with a published 2-D RGMT method via motion-compensated cross-correlation (MCCC) of pre- and post-deformation radiofrequency echo signals. For data from experiments with the phantom, the MCCC values in the entire tracking region of interest averaged approximately 0.95, and the contrast-to-noise ratios averaged 4.6 for both tracking methods. For all five patients, the average MCCC values within the region of interest obtained with the 3-D RGMT were consistently higher than those obtained with the 2-D RGMT method. These results indicate that the 3-D RGMT algorithm is able to track displacements with increased accuracy and generate higher-quality 3-D elasticity images than the 2-D RGMT method.

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.

Three-dimensional Ultrasound Elasticity Imaging on an Automated Breast Volume Scanning System.

Ultrasound elasticity imaging has demonstrated utility in breast imaging, but it is typically performed with handheld transducers and two-dimensional imaging. Two-dimensional (2D) elastography images tissue stiffness of only a plane and hence suffers from errors due to out-of-plane motion, whereas three-dimensional (3D) data acquisition and motion tracking can be used to track out-of-plane motion that is lost in 2D elastography systems. A commercially available automated breast volume scanning system that acquires 3D ultrasound data with precisely controlled elevational movement of the 1D array ultrasound transducer was employed in this study. A hybrid guided 3D motion-tracking algorithm was developed that first estimated the displacements in one plane using a modified quality-guided search method, and then performed an elevational guided-search for displacement estimation in adjacent planes. To assess the performance of the method, 3D radiofrequency echo data were acquired with this system from a phantom and from an in vivo human breast. For both experiments, the axial displacement fields were smooth and high cross-correlation coefficients were obtained in most of the tracking region. The motion-tracking performance of the new method was compared with a correlation-based exhaustive-search method. For all motion-tracking volume pairs, the average motion-compensated cross-correlation values obtained by the guided-search motion-tracking method were equivalent to those by the exhaustive-search method, and the computation time was about a factor of 10 lesser. Therefore, the proposed 3D ultrasound elasticity imaging method was a more efficient approach to produce a high quality of 3D ultrasound strain image.

Improving three-dimensional mechanical imaging of breast lesions with principal component analysis.

PURPOSE: Elastography has emerged as a new tool for detecting and diagnosing many types of diseases including breast cancer. To date, most clinical applications of elastography have utilized two-dimensional strain images. The goal of this paper is to present a new quasi-static elastography technique that yields shear modulus images in three dimensions. METHODS: An automated breast volume scanner was used to acquire ultrasound images of the breast as it was gently compressed. Cross-correlation between successive images was used to determine the displacement within the tissue. The resulting displacement field was filtered of all but compressive motion through principal component analysis. This displacement field was used to infer spatial distribution of shear modulus by solving a 3D elastic inverse problem. RESULTS: Three dimensional shear modulus images of benign breast lesions for two subjects were generated using the techniques described above. It was found that the lesions were visualized more clearly in images generated using the displacement data de-noised through the use of principal components. CONCLUSIONS: We have presented experimental and algorithmic techniques that lead to three-dimensional imaging of shear modulus using quasi-static elastography. This work demonstrates feasibility of this approach, and lays the foundation for images of other, more informative, mechanical parameters.

A GPU-Accelerated 3-D Coupled Subsample Estimation Algorithm for Volumetric Breast Strain Elastography.

Our primary objective of this paper was to extend a previously published 2-D coupled subsample tracking algorithm for 3-D speckle tracking in the framework of ultrasound breast strain elastography. In order to overcome heavy computational cost, we investigated the use of a graphic processing unit (GPU) to accelerate the 3-D coupled subsample speckle tracking method. The performance of the proposed GPU implementation was tested using a tissue-mimicking phantom and in vivo breast ultrasound data. The performance of this 3-D subsample tracking algorithm was compared with the conventional 3-D quadratic subsample estimation algorithm. On the basis of these evaluations, we concluded that the GPU implementation of this 3-D subsample estimation algorithm can provide high-quality strain data (i.e., high correlation between the predeformation and the motion-compensated postdeformation radio frequency echo data and high contrast-to-noise ratio strain images), as compared with the conventional 3-D quadratic subsample algorithm. Using the GPU implementation of the 3-D speckle tracking algorithm, volumetric strain data can be achieved relatively fast (approximately 20 s per volume [2.5 cm ×2.5 cm ×2.5 cm]).

Estimation of Shear Wave Speed in the Rhesus Macaques' Uterine Cervix.

Cervical softness is a critical parameter in pregnancy. Clinically, preterm birth is associated with premature cervical softening and postdates birth is associated with delayed cervical softening. In practice, the assessment of softness is subjective, based on digital examination. Fortunately, objective, quantitative techniques to assess softness, and other parameters associated with microstructural cervical change are emerging. One of these is shear wave speed (SWS) estimation. In principle, this allows objective characterization of stiffness because waves travel more slowly in softer tissue. We are studying SWS in humans and rhesus macaques, the latter in order to accelerate translation from bench to bedside. For the current study, we estimated SWS in ex vivo cervices of rhesus macaques, n=24 nulliparous (never given birth) and n=9 multiparous (delivered at least one baby). Misoprostol (a prostaglandin used to soften human cervices prior to gynecological procedures) was administered to 13 macaques prior to necropsy (nulliparous: 7; multiparous: 6). SWS measurements were made at predetermined locations from the distal to proximal end of the cervix on both the anterior and posterior cervix, with five repeat measures at each location. The intent was to explore macaque cervical microstructure, including biological and spatial variability, to elucidate the similarities and differences between the macaque and the human cervix in order to facilitate future in vivo studies. We found that SWS is dependent on location in the normal nonpregnant macaque cervix, as in the human cervix. Unlike the human cervix, we detected no difference between ripened and unripened rhesus macaque cervix samples, nor nulliparous versus multiparous samples, although we observed a trend toward stiffer tissue in nulliparous samples. We found rhesus macaque cervix to be much stiffer than human, which is important for technique refinement. These findings are useful for guiding study of cervical microstructure in both humans and macaques.

A Tactile Sensor for Ultrasound Imaging Systems.

Medical ultrasound systems are capable of monitoring a variety of health conditions while avoiding invasive procedures. However this function is complicated by ultrasound contrast of the tissue varying with contact pressure exerted by the probe. The knowledge of the contact pressure is beneficial for a variety of screening and diagnostic procedures involving ultrasound. This paper introduces a solid-state sensor array which measures the contact pressure distribution between the probe and the tissue marginally affecting the ultrasound imaging capabilities. The probe design utilizes the dielectrostriction mechanism which relates the change in dielectric properties of the sensing layer to deformation. The concept, structure, fabrication, and performance of this sensor array are discussed. The prototype device is highly tolerant to overloads (>1 MPa tested) and provides stress measurements in the range of 0.14 to 10 kPa. Its loss of ultrasound transmissivity is less 3dB at 9 MHz ultrasound frequency. This performance is satisfactory for clinical and biomedical research in ultrasound image formation and interpretation, however for commercial product, a higher ultrasound transmissivity is desired. Directions for improving the sensor ultrasound transparency and electrical performance are discussed. The sensor array described in this paper has been developed specifically for ultrasound diagnosis during breast cancer screening. However, the same sensing mechanism, similar configuration and sensor array structure can be applied to other applications involving ultrasound tools for medical diagnostics.

A coupled subsample displacement estimation method for ultrasound-based strain elastography.

Obtaining accurate displacement estimates along both axial (parallel to the acoustic beam) and lateral (perpendicular to the beam) directions is an important task for several clinical applications such as shear strain imaging, modulus reconstruction and temperature imaging, where a full description of the two or three-dimensional (2D/3D) deformation field is required. In this study we propose an improved speckle tracking algorithm where axial and lateral motion estimations are simultaneously performed to enhance motion tracking accuracy. More specifically, using conventional ultrasound echo data, this algorithm first finds an iso-contour in the vicinity of the peak correlation between two segments of the pre- and post-deformation ultrasound radiofrequency echo data. The algorithm then attempts to find the center of the iso-contour of the correlation function that corresponds to the unknown (sub-sample) motion vector between these two segments of echo data. This algorithm has been tested using computer-simulated data, studies with a tissue-mimicking phantom, and in vivo breast lesion data. Computer simulation results show that the method improves the accuracy of both lateral and axial tracking. Such improvements are more significant when the deformation is small or along the lateral direction. Results from the tissue-mimicking phantom study are consistent with findings observed in computer simulations. Using in vivo breast lesion data we found that, compared to the 2D quadratic subsample displacement estimation methods, higher quality axial strain and shear strain images (e.g. 18.6% improvement in contrast-to-noise ratio for shear strain images) can be obtained for large deformations (up to 5% frame-to-frame and 15% local strains) in a multi-compression technique. Our initial results demonstrated that this conceptually and computationally simple method could improve the image quality of ultrasound-based strain elastography with current clinical equipment.

Acoustic Properties of Breast Fat.

OBJECTIVES: The American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) atlas for ultrasound (US) qualitatively describes the echogenicity and attenuation of a mass, where fat lobules serve as a standard for comparison. This study aimed to estimate acoustic properties of breast fat under clinical imaging conditions to determine the degree to which properties vary among patients. METHODS: Twenty-four women with solid breast masses scheduled for biopsy were scanned with a Siemens S2000 scanner and 18L6 linear array transducer (Siemens Medical Solutions, Malvern, PA). Offline analysis estimated the attenuation coefficient and backscatter coefficients (BSCs) from breast fat using the reference phantom method. The average BSC was calculated over 6 to 12 MHz to objectively quantify the BI-RADS US echo pattern descriptor, and effective scatterer diameters were also estimated. RESULTS: A power law fit to the attenuation coefficient versus frequency yielded an attenuation coefficient of 1.28 dB·cm(-1) MHz(-0.73). The mean attenuation coefficient versus frequency slope ± SD at 7 MHz was 0.73 ± 0.23 dB·cm(-1) MHz(-1), in agreement with previously reported values. The BSC versus frequency showed close agreement among all patients, both in magnitude and frequency dependence, with a power law fit of (0.6 ± 0.25) ×10(-4) sr(-1) cm(-1) MHz(-2.49). The average backscatter in the 6-12-MHz range was 0.004 ± 0.002 sr(-1) cm(-1). The mean effective scatterer diameter for fat was 60.2 ± 9.5 µm. CONCLUSIONS: The agreement in parameter estimates for breast fat among these patients supports the use of fat as a standard for comparison with tumors. Results also suggest that objective quantification of these BI-RADS US descriptors may reduce subjectivity when interpreting B-mode image data.

Noninvasive In-Vivo Quantification of Mechanical Heterogeneity of Invasive Breast Carcinomas.

Heterogeneity is a hallmark of cancer whether one considers the genotype of cancerous cells, the composition of their microenvironment, the distribution of blood and lymphatic microvasculature, or the spatial distribution of the desmoplastic reaction. It is logical to expect that this heterogeneity in tumor microenvironment will lead to spatial heterogeneity in its mechanical properties. In this study we seek to quantify the mechanical heterogeneity within malignant and benign tumors using ultrasound based elasticity imaging. By creating in-vivo elastic modulus images for ten human subjects with breast tumors, we show that Young's modulus distribution in cancerous breast tumors is more heterogeneous when compared with tumors that are not malignant, and that this signature may be used to distinguish malignant breast tumors. Our results complement the view of cancer as a heterogeneous disease on multiple length scales by demonstrating that mechanical properties within cancerous tumors are also spatially heterogeneous.