Amy M. Sommer

Linear and nonlinear elasticity imaging of soft tissue in vivo: demonstration of feasibility.

We establish the feasibility of imaging the linear and nonlinear elastic properties of soft tissue using ultrasound. We report results for breast tissue where it is conjectured that these properties may be used to discern malignant tumors from benign tumors. We consider and compare three different quantities that describe nonlinear behavior, including the variation of strain distribution with overall strain, the variation of the secant modulus with overall applied strain and finally the distribution of the nonlinear parameter in a fully nonlinear hyperelastic model of the breast tissue.

A novel performance descriptor for ultrasonic strain imaging: a preliminary study

Ultrasonic strain imaging that uses signals from conventional diagnostic ultrasound systems is capable of showing the contrast of tissue elasticity, which provides new diagnostically valuable information. To assess and improve the diagnostic performance of ultrasonic strain imaging, it is essential to have a quantitative measure of image quality. Moreover, it is useful if the image quality measure is simple to interpret and can be used for visual feedback while scanning and as a training tool for operator performance evaluation. This report describes the development of a novel quantitative method for systematic performance assessment that is based on the combination of measures of the accuracy of motion tracking and consistency among consecutive strain fields. The accuracy of motion tracking assesses the reliability of strain images. The consistency among consecutive strain images assesses the signal quality in strain images. The clinical implications of the proposed method to differentiate good or poor strain images are discussed. Results of experiments with tissue-mimicking phantoms and in vivo breast-tissue data demonstrate that the performance measure is a useful method for automatically rating elasticity image quality.

Axial-Shear Strain Imaging for Differentiating Benign and Malignant Breast Masses

Axial strain imaging has been utilized for the characterization of breast masses for over a decade; however, another important feature namely the shear strain distribution around breast masses has only recently been used. In this article, we examine the feasibility of utilizing in vivo axial-shear strain imaging for differentiating benign from malignant breast masses. Radio-frequency data was acquired using a VFX 13-5 linear array transducer on 41 patients using a Siemens SONOLINE Antares real-time clinical scanner at the University of Wisconsin Breast Cancer Center. Free-hand palpation using deformations of up to 10% was utilized to generate axial strain and axial-shear strain images using a two-dimensional cross-correlation algorithm from the radio-frequency data loops. Axial-shear strain areas normalized to the lesion size, applied strain and lesion strain contrast was utilized as a feature for differentiating benign from malignant masses. The normalized axial-shear strain area feature estimated on eight patients with malignant tumors and 33 patients with fibroadenomas was utilized to demonstrate its potential for lesion differentiation. Biopsy results were considered the diagnostic standard for comparison. Our results indicate that the normalized axial-shear strain area is significantly larger for malignant tumors compared with benign masses such as fibroadenomas. Axial-shear strain pixel values greater than a specified threshold, including only those with correlation coefficient values greater than 0.75, were overlaid on the corresponding B-mode image to aid in diagnosis. A scatter plot of the normalized area feature demonstrates the feasibility of developing a linear classifier to differentiate benign from malignant masses. The area under the receiver operator characteristic curve utilizing the normalized axial-shear strain area feature was 0.996, demonstrating the potential of this feature to noninvasively differentiate between benign and malignant breast masses.

In Vitro Uterine Strain Imaging Preliminary Results

Uterine abnormalities, such as leiomyomas, endometrial polyps, and adenomyosis, are often clinically associated with irregular uterine bleeding. These abnormalities can have similar B‐mode characteristics but require different treatment. The objective of this study was to develop diagnostic techniques based on ultrasound strain imaging that would allow in vivo visualization and characterization of endometrial and myometrial uterine abnormalities, enabling physicians to improve diagnosis and treatment.

Elastic nonlinearity imaging

Previous work has demonstrated improved diagnostic performance of highly trained breast radiologists when provided with B-mode plus elastography images over B-mode images alone. In those studies we have observed that elasticity imaging can be difficult to perform if there is substantial motion of tissue out of the image plane. So we are extending our methods to 3D/4D elasticity imaging with 2D arrays. Further, we have also documented the fact that some breast tumors change contrast with increasing deformation and those observations are consistent with in vitro tissue measurements. Hence, we are investigating imaging tissue stress-strain nonlinearity. These studies will require relatively large tissue deformations (e.g., > 20%) which will induce out of plane motion further justifying 3D/4D motion tracking. To further enhance our efforts, we have begun testing the ability to perform modulus reconstructions (absolute elastic parameter) imaging of in vivo breast tissues. The reconstructions are based on high quality 2D displacement estimates from strain imaging. Piecewise linear (secant) modulus reconstructions demonstrate the changes in elasticity image contrast seen in strain images but, unlike the strain images, the contrast in the modulus images approximates the absolute modulus contrast. Nonlinear reconstructions assume a reasonable approximation to the underlying constitutive relations for the tissue and provide images of the (near) zero-strain shear modulus and a nonlinearity parameter that describes the rate of tissue stiffening with increased deformation. Limited data from clinical trials are consistent with in vitro measurements of elastic properties of tissue samples and suggest that the nonlinearity of invasive ductal carcinoma exceeds that of fibroadenoma and might be useful for improving diagnostic specificity. This work is being extended to 3D.

P3D-3 Strain Image Contrast for Differentiating In Vivo Breast Lesions

We are objectively investigating lesion contrast with ultrasound strain imaging of in vivo solid breast lesions. Tissue deformation is performed during real-time strain imaging. A modified block matching algorithm is used to estimate the displacement between frames of radiofrequency (RF) echo data and the gradient of the displacements are computed to form strain images. Displacement estimates from strain image formation are used to compensate for motion, lesion segmentation is performed on each stationary strain image, and strain image contrast is calculated as a function of accumulated strain. Strain image contrast of fibroadenomas are compared to strain image contrast of invasive ductal carcinomas to determine if strain image contrast can aide in distinguishing between most common benign and malignant solid breast lesions

P1C-7 A Novel Strain Formation Algorithm for Ultrasonic Strain Imaging

Ultrasonic strain imaging systems are gaining rapid attention for breast tumor differentiation, despite the fact that consistently obtaining high quality in vivo strain images is a persistent challenge. To enhance the clinical usability of such systems, much effort has been devoted to developing more sophisticated motion tracking algorithms. This study takes an alternate route to investigate a new strain formation scheme for improving in vivo strain image quality. This method is a retrospective processing technique that is not restricted to a particular motion tracking algorithm. A block-matching algorithm was used in this study for our convenience. Radiofrequency (RF) echo data acquired from a Siemens Elegra with freehand scanning of in vivo breast tissue were used to validate this method. Through processing of in vivo breast tissue data (7 data sets with different types of lesions and roughly 700 RF echo frames in total), our findings demonstrate that higher quality strain images can be obtained through the proposed retrospective pairing technique

P3D-2 ROC Analysis of Ultrasound Elasticity Imaging of Breast Abnormalities

Elasticity (mechanical strain) imaging is under rapid development as a tool to improve the specificity of breast ultrasound imaging. Elasticity imaging exploits the fact that benign and malignant breast disease cause inherently different tissue stiffness. We performed a retrospective observer study to determine if elasticity imaging can improve radiologists risk assessment for breast masses over risk assessed with conventional B-mode imaging alone. The best examples of 50 malignant and 48 benign cases were chosen that also represent the distribution of disease from the full data set of 403 breast masses. Other studies precede ours, but our experimental design is unique and this is the first multi-institutional study with multiple expert readers blinded to the tissue pathology. Elasticity imaging was found to increase the ability to assess risk for all observers

Axial shear strain imaging for breast mass differentiation

Breast cancer remains the second-leading cause of cancer deaths in women, and over 200,000 new cases of invasive breast cancer are expected in the USA this year. Very promising data demonstrate that axial strain imaging has an important role in breast tissue classification However, another important parameter; the shear strain has only recently been recognized as having great potential. We examine the feasibility of utilizing in-vivo axial shear strain imaging for differentiating benign from malignant breast masses. A VFX13-5 linear array transducer was utilized to acquire in-vivo radiofrequency echo data on 41 patients using a Siemens SONOLINE Antares real-time clinical scanner at the University of Wisconsin Breast Center. Free-hand palpation imaging with deformation up to 10% was utilized to acquire radiofrequency data loops to generate strain images. In this study, we report on 8 malignant tumors and 33 fibroadenomas to demonstrate the potential of shear strain imaging, compared to biopsy results that were considered the diagnostic standard. Axial strain and axial component of shear strain are estimated using an algorithm based on 2D cross-correlation. Areas of the axial-shear strain, normalized to the lesion size, applied strain and strain contrast was utilized for differentiating benign from malignant masses. Our results on 40 patients indicate that the normalized axial-shear strain area is significantly larger for malignant tumors when compared to benign fibroadenomas. Axial-shear strain pixel values greater than a specified threshold, including only those with correlation coefficient values greater than 0.75, were overlaid on the corresponding B-mode image to aid in diagnosis. Scatter plot of the normalized area feature demonstrate the feasibility of developing a linear classifier to differentiate benign from malignant masses. The area under the Receiver Operating Characteristic curve using the normalized shear strain area parameter was 0.996.