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.

Multi-parameter Sub-Hertz Analysis of Viscoelasticity With a Quality Metric for Differentiation of Breast Masses.

We applied sub-Hertz analysis of viscoelasticity (SAVE) to differentiate breast masses in pre-biopsy patients. Tissue response during external ramp-and-hold stress was ultrasonically detected. Displacements were used to acquire tissue viscoelastic parameters. The fast instantaneous response and slow creep-like deformations were modeled as the response of a linear standard solid from which viscoelastic parameters were estimated. These parameters were used in a multi-variable classification framework to differentiate malignant from benign masses identified by pathology. When employing all viscoelasticity parameters, SAVE resulted in 71.43% accuracy in differentiating lesions. When combined with ultrasound features and lesion size, accuracy was 82.24%. Adding a quality metric based on uniaxial motion increased the accuracy to 81.25%. When all three were combined with SAVE, accuracy was 91.3%. These results confirm the utility of SAVE as a robust ultrasound-based diagnostic tool for non-invasive differentiation of breast masses when used as stand-alone biomarkers or in conjunction with ultrasonic features.

Quantification of Morphological Features in Non-Contrast-Enhanced Ultrasound Microvasculature Imaging.

There are significant differences in microvascular morphological features in diseased tissues, such as cancerous lesions, compared to noncancerous tissue. Quantification of microvessel morphological features could play an important role in disease diagnosis and tumor classification. However, analyzing microvessel morphology in ultrasound Doppler is a challenging task due to limitations associated with this technique. Our main objective is to provide methods for quantifying morphological features of microvasculature obtained by ultrasound Doppler imaging. To achieve this goal, we propose multiple image enhancement techniques and appropriate morphological feature extraction methods that enable quantitative analysis of microvasculature structures. Vessel segments obtained by the skeletonization of the regularized microvasculature images are further analyzed to satisfy other constraints, such as vessel segment diameter and length. Measurements of some morphological metrics, such as tortuosity, depend on preserving large vessel trunks. To address this issue, additional filtering methods are proposed. These methods are tested on in vivo images of breast lesion and thyroid nodule microvasculature, and the outcomes are discussed. Initial results show that using vessel morphological features allows for differentiation between malignant and benign breast lesions (p-value < 0.005) and thyroid nodules (p-value < 0.01). This paper provides a tool for the quantification of microvasculature images obtained by non-contrast ultrasound imaging, which may serve as potential biomarkers for the diagnosis of some diseases.

Predictive value of comb-push ultrasound shear elastography for the differentiation of reactive and metastatic axillary lymph nodes: A preliminary investigation.

OBJECTIVES: To evaluate the predictive performance of comb-push ultrasound shear elastography for the differentiation of reactive and metastatic axillary lymph nodes. METHODS: From June 2014 through September 2018, 114 female volunteers (mean age 58.1±13.3 years; range 28-88 years) with enlarged axillary lymph nodes identified by palpation or clinical imaging were prospectively enrolled in the study. Mean, standard deviation and maximum shear wave elastography parameters from 117 lymph nodes were obtained and compared to fine needle aspiration biopsy results. Mann-Whitney U test and ROC curve analysis were performed. RESULTS: The axillary lymph nodes were classified as reactive or metastatic based on the fine needle aspiration outcomes. A statistically significant difference between reactive and metastatic axillary lymph nodes was observed based on comb-push ultrasound shear elastography (CUSE) results (p<0.0001) from mean and maximum elasticity values. Mean elasticity showed the best separation with a ROC analysis resulting in 90.5% sensitivity, 94.4% specificity, 0.97 area under the curve, 95% positive predictive value, and 89.5% negative predictive value with a 30.2-kPa threshold. CONCLUSIONS: CUSE provided a quantifiable parameter that can be used for the assessment of enlarged axillary lymph nodes to differentiate between reactive and metastatic processes.

Viscoelastic biomarker for differentiation of benign and malignant breast lesion in ultra- low frequency range.

Benign and malignant tumors differ in the viscoelastic properties of their cellular microenvironments and in their spatiotemporal response to very low frequency stimuli. These differences can introduce a unique viscoelastic biomarker in differentiation of benign and malignant tumors. This biomarker may reduce the number of unnecessary biopsies in breast patients. Although different methods have been developed so far for this purpose, none of them have focused on in vivo and in situ assessment of local viscoelastic properties in the ultra-low (sub-Hertz) frequency range. Here we introduce a new, noninvasive model-free method called Loss Angle Mapping (LAM). We assessed the performance results on 156 breast patients. The method was further improved by detection of out-of-plane motion using motion compensation cross correlation method (MCCC). 45 patients met this MCCC criterion and were considered for data analysis. Among this population, we found 77.8% sensitivity and 96.3% specificity (p < 0.0001) in discriminating between benign and malignant tumors using logistic regression method regarding the pre known information about the BIRADS number and size. The accuracy and area under the ROC curve, AUC, was 88.9% and 0.94, respectively. This method opens new avenues to investigate the mechanobiology behavior of different tissues in a frequency range that has not yet been explored in any in vivo patient studies.

Ultrasound Radiation Force for the Assessment of Bone Fracture Healing in Children: An In Vivo Pilot Study.

Vibrational characteristics of bone are directly dependent on its physical properties. In this study, a vibrational method for bone evaluation is introduced. We propose a new type of quantitative vibro-acoustic method based on the acoustic radiation force of ultrasound for bone characterization in persons with fracture. Using this method, we excited the clavicle or ulna by an ultrasound radiation force pulse which induces vibrations in the bone, resulting in an acoustic wave that is measured by a hydrophone placed on the skin. The acoustic signals were used for wave velocity estimation based on a cross-correlation technique. To further separate different vibration characteristics, we adopted a variational mode decomposition technique to decompose the received signal into an ensemble of band-limited intrinsic mode functions, allowing analysis of the acoustic signals by their constitutive components. This prospective study included 15 patients: 12 with clavicle fractures and three with ulna fractures. Contralateral intact bones were used as controls. Statistical analysis demonstrated that fractured bones can be differentiated from intact ones with a detection probability of 80%. Additionally, we introduce a "healing factor" to quantify the bone healing progress which successfully tracked the progress of healing in 80% of the clavicle fractures in the study.

Background Removal and Vessel Filtering of Noncontrast Ultrasound Images of Microvasculature.

OBJECTIVE: Recent advances in ultrasound Doppler imaging have made it possible to visualize small vessels with diameters near the imaging resolution limits using spatiotemporal singular value thresholding of long ensembles of ultrasound data. However, vessel images derived based on this method present severe intensity variations and additional background noise that limits visibility and subsequent processing such as centerline extraction and morphological analysis. The goal of this paper is to devise a method to enhance vessel-background separation directly on the power Doppler images by exploiting blood echo-noise independence. METHOD: We present a two-step algorithm to mitigate these adverse effects when using singular value thresholding for obtaining gross vasculature images. Our method comprises a morphological-based filtering for removing global and local background signals and a multiscale Hessian-based vessel enhancement filtering to further improve the vascular structures. We applied our method for in vivo imaging of the microvasculature of kidney in one healthy subject, liver in five healthy subjects, thyroid nodules in five patients, and breast tumors in five patients. RESULTS: Singular value thresholding, top-hat filtering, and Hessian-based vessel enhancement filtering each provided an average peak-to-side level gain of 1.11, 18.55, and 2.26 dB, respectively, resulting in an overall gain of 21.92 dB when compared to the conventional power Doppler imaging using infinite impulse response filtering. CONCLUSION: Singular value thresholding combined with morphological and Hessian-based vessel enhancement filtering provides a powerful tool for visualization of the deep-seated small vessels using long ultrasound echo ensembles without requiring any type of contrast enhancing agents. SIGNIFICANCE: This method provides a fast and cost-effective modality for in vivo assessment of the microvasculature suitable for both clinical and preclinical applications.

Viscoelastic parameters as discriminators of breast masses: Initial human study results.

Shear wave elastography is emerging as a clinically valuable diagnostic tool to differentiate between benign and malignant breast masses. Elastography techniques assume that soft tissue can be modelled as a purely elastic medium. However, this assumption is often violated as soft tissue exhibits viscoelastic properties. In order to explore the role of viscoelastic parameters in suspicious breast masses, a study was conducted on a group of patients using shear wave dispersion ultrasound vibrometry in the frequency range of 50-400 Hz. A total of 43 female patients with suspicious breast masses were recruited before their scheduled biopsy. Of those, 15 patients did not meet the data selection criteria. Voigt model based shear elasticity showed a significantly (p = 7.88x10(-6)) higher median value for the 13 malignant masses (16.76±13.10 kPa) compared to 15 benign masses (1.40±1.12 kPa). Voigt model based shear viscosity was significantly different (p = 4.13x10(-5)) between malignant (8.22±3.36 Pa-s) and benign masses (2.83±1.47 Pa-s). Moreover, the estimated time constant from the Voigt model, which is dependent on both shear elasticity and viscosity, differed significantly (p = 6.13x10(-5)) between malignant (0.68±0.33 ms) and benign masses (3.05±1.95 ms). Results suggest that besides elasticity, viscosity based parameters like shear viscosity and time constant can also be used to differentiate between malignant and benign breast masses.

Automated In Vivo Sub-Hertz Analysis of Viscoelasticity (SAVE) for Evaluation of Breast Lesions.

We present an automated method for acquiring images and contrast parameters based on mechanical properties of breast lesions and surrounding tissue at load frequencies less than 1 Hz. The method called sub-Hertz analysis of viscoelasticity (SAVE) uses a compression device integrated with ultrasound imaging to perform in vivo ramp-and-hold uniaxial creep-like test on human breast in vivo. It models the internal deformations of tissues under constant surface stress as a linear viscoelastic response. We first discuss different aspects of our unique measurement approach and the expected variability of the viscoelastic parameters estimated based on a simplified one-dimensional reconstruction model. Finite-element numerical analysis is used to justify the advantages of using imaging contrast over viscoelasticity values. We then present the results of SAVE applied to a group of patients with breast masses undergoing biopsy.

Automated and real-time segmentation of suspicious breast masses using convolutional neural network.

In this work, a computer-aided tool for detection was developed to segment breast masses from clinical ultrasound (US) scans. The underlying Multi U-net algorithm is based on convolutional neural networks. Under the Mayo Clinic Institutional Review Board protocol, a prospective study of the automatic segmentation of suspicious breast masses was performed. The cohort consisted of 258 female patients who were clinically identified with suspicious breast masses and underwent clinical US scan and breast biopsy. The computer-aided detection tool effectively segmented the breast masses, achieving a mean Dice coefficient of 0.82, a true positive fraction (TPF) of 0.84, and a false positive fraction (FPF) of 0.01. By avoiding positioning of an initial seed, the algorithm is able to segment images in real time (13-55 ms per image), and can have potential clinical applications. The algorithm is at par with a conventional seeded algorithm, which had a mean Dice coefficient of 0.84 and performs significantly better (P< 0.0001) than the original U-net algorithm.

Differentiation of Benign and Malignant Thyroid Nodules by Using Comb-push Ultrasound Shear Elastography: A Preliminary Two-plane View Study.

RATIONALE AND OBJECTIVES: Low specificity of traditional ultrasound in differentiating benign from malignant thyroid nodules leads to a great number of unnecessary (ie, benign) fine-needle aspiration biopsies that causes a significant financial and physical burden to the patients. Ultrasound shear wave elastography is a technology capable of providing additional information related to the stiffness of tissues. In this study, quantitative stiffness values acquired by ultrasound shear wave elastography in two different imaging planes were evaluated for the prediction of malignancy in thyroid nodules. In addition, the association of elasticity measurements with sonographic characteristics of thyroid gland and nodules is presented. MATERIALS AND METHODS: A total number of 155 patients (106 female and 49 male) (average age 57.48 ± 14.44 years) with 173 thyroid nodules (average size 24.89 ± 15.41 mm, range 5-68 mm) scheduled for fine-needle aspiration biopsy were recruited from March 2015 to May 2017. Comb-push shear elastography imaging was performed at longitudinal and transverse anatomic planes. Mean (Emean) and maximum (Emax) elasticity values were obtained. RESULTS: Measurements at longitudinal view were statistically significantly higher than measurements at transverse view. Nodules with calcifications were associated with increased elasticity, and nodules with a vascular component or within an enlarged thyroid gland (goiter) were associated with a lower elasticity value. Receiver operating characteristic curve analysis was performed for Emean and Emax at each imaging plane and for the average of both planes. Sensitivity of 95.45%, specificity of 86.61%, 0.58 positive predictive value, and 0.99 negative predictive value were achieved by the average of the two planes for each Emean and Emax parameters, with area under the curve of 92% and 93%, and a cutoff value of 49.09 kPa and 105.61 kPa, respectively. CONCLUSIONS: The elastic properties of thyroid nodules showed promise to be a good discriminator between malignant and benign nodules (P < .0001). However, probe orientation and internal features such as calcifications, vascular component, and goiter may influence the final elastography measurements. A larger number of malignant nodules need to be studied to further validate our results.

Diagnostic features of quantitative comb-push shear elastography for breast lesion differentiation.

BACKGROUND: Lesion stiffness measured by shear wave elastography has shown to effectively separate benign from malignant breast masses. The aim of this study was to evaluate different aspects of Comb-push Ultrasound Shear Elastography (CUSE) performance in differentiating breast masses. METHODS: With written signed informed consent, this HIPAA- compliant, IRB approved prospective study included patients from April 2014 through August 2016 with breast masses identified on conventional imaging. Data from 223 patients (19-85 years, mean 59.93±14.96 years) with 227 suspicious breast masses identifiable by ultrasound (mean size 1.83±2.45cm) were analyzed. CUSE was performed on all patients. Three regions of interest (ROI), 3 mm in diameter each, were selected inside the lesion on the B-mode ultrasound which also appeared in the corresponding shear wave map. Lesion elasticity values were measured in terms of the Young's modulus. In correlation to pathology results, statistical analyses were performed. RESULTS: Pathology revealed 108 lesions as malignant and 115 lesions as benign. Additionally, 4 lesions (BI-RADS 2 and 3) were considered benign and were not biopsied. Average lesion stiffness measured by CUSE resulted in 84.26% sensitivity (91 of 108), 89.92% specificity (107 of 119), 85.6% positive predictive value, 89% negative predictive value and 0.91 area under the curve (P<0.0001). Stiffness maps showed spatial continuity such that maximum and average elasticity did not have significantly different results (P > 0.21). CONCLUSION: CUSE was able to distinguish between benign and malignant breast masses with high sensitivity and specificity. Continuity of stiffness maps allowed for choosing multiple quantification ROIs which covered large areas of lesions and resulted in similar diagnostic performance based on average and maximum elasticity. The overall results of this study, highlights the clinical value of CUSE in differentiation of breast masses based on their stiffness.

Correlating Tumor Stiffness with Immunohistochemical Subtypes of Breast Cancers: Prognostic Value of Comb-Push Ultrasound Shear Elastography for Differentiating Luminal Subtypes.

PURPOSE: The purpose of our study is to correlate quantitatively measured tumor stiffness with immunohistochemical (IHC) subtypes of breast cancer. Additionally, the influence of prognostic histologic features (cancer grade, size, lymph node status, and histological type and grade) to the tumor elasticity and IHC profile relationship will be investigated. METHODS: Under an institutional review board (IRB) approved protocol, B-mode ultrasound (US) and comb-push ultrasound shear elastography (CUSE) were performed on 157 female patients with suspicious breast lesions. Out of 157 patients 83 breast cancer patients confirmed by pathology were included in this study. The association between CUSE mean stiffness values and the aforementioned prognostic features of the breast cancer tumors were investigated. RESULTS: Our results demonstrate that the most statistically significant difference (p = 0.0074) with mean elasticity is tumor size. When considering large tumors (size ≥ 8mm), thus minimizing the statistical significance of tumor size, a significant difference (p< 0.05) with mean elasticity is obtained between luminal A of histological grade I and luminal B (Ki-67 > 20%) subtypes. CONCLUSION: Tumor size is an independent factor influencing mean elasticity. The Ki-67 proliferation index and histological grade were dependent factors influencing mean elasticity for the differentiation between luminal subtypes. Future studies on a larger group of patients may broaden the clinical significance of these findings.

Update on Breast Cancer Detection Using Comb-Push Ultrasound Shear Elastography.

In this work, tissue stiffness estimates are used to differentiate between benign and malignant breast masses in a group of pre-biopsy patients. The rationale is that breast masses are often stiffer than healthy tissue; furthermore, malignant masses are stiffer than benign masses. The comb-push ultrasound shear elastography (CUSE) method is used to noninvasively assess a tissue's mechanical properties. CUSE utilizes a sequence of simultaneous multiple laterally spaced acoustic radiation force (ARF) excitations and detection to reconstruct the region of interest (ROI) shear wave speed map, from which a tissue stiffness property can be quantified. In this study, the tissue stiffnesses of 73 breast masses were interrogated. The mean shear wave speeds for benign masses (3.42 ± 1.32 m/s) were lower than malignant breast masses (6.04 ± 1.25 m/s). These speed values correspond to higher stiffness in malignant breast masses (114.9 ± 40.6 kPa) than benign masses (39.4 ± 28.1 kPa and p <; 0.001), when tissue elasticity is quantified by Young's modulus. A Young's modulus >83 kPa is established as a cut-off value for differentiating between malignant and benign suspicious breast masses, with a receiver operating characteristic curve (ROC) of 89.19% sensitivity, 88.69% specificity, and 0.911 for the area under the curve (AUC).

Effect of Calcifications on Breast Ultrasound Shear Wave Elastography: An Investigational Study.

PURPOSE: To investigate the effects of macrocalcifications and clustered microcalcifications associated with benign breast masses on shear wave elastography (SWE). METHODS: SuperSonic Imagine (SSI) and comb-push ultrasound shear elastography (CUSE) were performed on three sets of phantoms to investigate how calcifications of different sizes and distributions influence measured elasticity. To demonstrate the effect in vivo, three female patients with benign breast masses associated with mammographically-identified calcifications were evaluated by CUSE. RESULTS: Apparent maximum elasticity (Emax) estimates resulting from individual macrocalcifications (with diameters of 2mm, 3mm, 5mm, 6mm, 9mm, 11mm, and 15mm) showed values over 50 kPa for all cases, which represents more than 100% increase over background (~21kPa). We considered a 2cm-diameter circular region of interest for all phantom experiments. Mean elasticity (Emean) values varied from 26 kPa to 73 kPa, depending on the macrocalcification size. Highly dense clusters of microcalcifications showed higher Emax values than clusters of microcalcification with low concentrations, but the difference in Emean values was not significant. CONCLUSIONS: Our results demonstrate that the presence of large isolated macrocalcifications and highly concentrated clusters of microcalcifications can introduce areas with apparent high elasticity in SWE. Considering that benign breast masses normally have significantly lower elasticity values than malignant tumors, such areas with high elasticity appearing due to presence of calcification in benign breast masses may lead to misdiagnosis.

An experimental phantom study on the effect of calcifications on ultrasound shear wave elastography.

In this study, we investigated the effects of single macrocalcifications and groups of microcalcifications on shear wave elastography. Supersonic shear imaging (SSI) and comb-push ultrasound shear elastography (CUSE) were performed on three sets of phantoms to investigate how calcifications of different sizes and distributions influence measured elasticity. Our results demonstrate that the presence of large isolated macrocalcifications and highly concentrated clusters of microcalcifications can introduce areas with apparent high elasticity when they are evaluated by shear wave elastography.

Imaging errors in localization of COMS-type plaques in choroidal melanoma brachytherapy.

PURPOSE: To investigate mathematically and experimentally the sources of errors in localization of COMS-type plaques in melanoma brachytherapy when using ultrasound and transillumination and to give recommendations to avoid such errors. METHODS: A computer-aided simulation tool was developed to model the errors seen in the patient images when using ultrasound imaging and transillumination during localization of the COMS-type plaque in melanoma brachytherapy. Several laboratory experiments were performed on sheep eyes to confirm the validity of the error sources and the simulator outputs. Results were compared to the intraoperative ultrasonographic patient images for validation. RESULTS: Based on mathematical modeling and computer simulation results, transillumination provides acceptable accuracy for small to medium tumors with less than 7-mm height but shows poor accuracy as the tumor height increases. In ultrasound imaging, two sources of error are predicted in longitudinal scan using our computer simulation modeling, and the results are supported by the experiments on sheep eyes and patient images taken during the operation. Both errors are related to the lens. The first error is due to attenuation and refraction of the lens causing opaque areas and a change of curvature in the image of the plaque edge that is nearest to the lens. The second type of error is related to the total internal reflection from the lens. CONCLUSIONS: The simulation method presented in this article allows quantitative assessment of the sources, mechanisms, and measures of errors in localization of the CMOS-type plaques by ultrasound and transillumination techniques. Errors predicted by the simulation method are validated by experiments. Error assessment by this method provides guidelines for avoiding such errors.