Axial-shear strain imaging for differentiating benign and malignant breast masses

Mechanical properties of human tumour tissues and their implications for cancer development

The mechanical properties of cells and tissues help determine their architecture, composition and function. Alterations to these properties are associated with many diseases, including cancer. Tensional, compressive, adhesive, elastic and viscous properties of individual cells and multicellular tissues are mostly regulated by reorganization of the actomyosin and microtubule cytoskeletons and extracellular glycocalyx, which in turn drive many pathophysiological processes, including cancer progression. This Review provides an in-depth collection of quantitative data on diverse mechanical properties of living human cancer cells and tissues. Additionally, the implications of mechanical property changes for cancer development are discussed. An increased knowledge of the mechanical properties of the tumour microenvironment, as collected using biomechanical approaches capable of multi-timescale and multiparametric analyses, will provide a better understanding of the complex mechanical determinants of cancer organization and progression. This information can lead to a further understanding of resistance mechanisms to chemotherapies and immunotherapies and the metastatic cascade.

Importance of the Ultrasound Probe Angle on the Rotation Fill-in Signature in Ultrasound Axial-Shear Strain Imaging

The rotation fill-in is a signature of tumor benignity in rotation elastograms and has been used for breast tumor classification. It is a consequence of the bonding condition at the tumor-tissue interface. In vivo studies have revealed the presence of fluctuations when inclined uniaxial external compression is applied. However, the physical meaning of these fluctuations is not yet fully understood. In this article we present an experimental and numerical study of the rotation fill-in signature as a function of the probe's tilt angle. This angle introduces asymmetries in the stress field, modifying the bonding condition. We numerically consider this asymmetry by using a model of friction with a simple angular dependence, which allows us to capture the experimental trends. We argue that the formulation of a tumor model with a bonding condition dependence may have potential implications in correct tumor classification.

Simultaneous comparison between strain and shear wave elastography of breast masses for the differentiation of benign and malignant lesions by qualitative and quantitative assessments

PURPOSE

To compare the addition of diagnostic strain elastography (SE) and shear wave elastography (SWE) values to the conventional B-mode ultrasonography in differentiating between benign and malignant breast masses by qualitative and quantitative assessments.

MATERIALS AND METHODS

B-mode ultrasound, SE, and SWE were simultaneously performed using one ultrasound system in 148 breast masses; 88 of them were malignant. The breast imaging reporting and data system category in the B-mode, Tsukuba score (SE_Tsu), Fat-Lesion-Ratio (SE_FLR) in SE, and five-point color assessment (SWE_col) and elasticity values (SWE_ela) in SWE were assessed. The results were compared using the area under the receiver-operating characteristic curve (AUC).

RESULT

The AUC for B-mode and each elastography were similar (B-mode, 0.889; SE_Tsu, 0.885; SE_FLR, 0.875; SWE_col, 0.881; SWE_ela, 0.885; P > 0.05). The combined sets between B-mode and either of the elastography technique showed good diagnostic performance (B-mode + SE_Tsu, 0.903; B-mode + SE_FLR, 0.909; B-mode + SWE_col, 0.919; B-mode + SWE_ela, 0.914). B-mode + SWE_col and B-mode + SWE_ela showed a higher AUC than B-mode alone (P = 0.026 and 0.029), and B-mode + SE_Tsu and B-mode + SE_FLR showed comparable AUC to B-mode alone (P = 0.196 and 0.085). There was no significant difference between qualitative and quantitative assessments for the combined sets of B-mode and elastography (P > 0.05).

CONCLUSION

The addition of both SE and SWE to B-mode ultrasound improved the diagnostic performance with increased AUC, and especially SWE was more useful than SE, and no significant difference was found between qualitative and quantitative assessments.

3-D Single Breath-Hold Shear Strain Estimation for Improved Breast Lesion Detection and Classification in Automated Volumetric Ultrasound Scanners

Automated breast volume scanner (ABVS) is an ultrasound imaging modality used in breast cancer screening. It has high sensitivity but limited specificity as it is hard to discriminate between benign and malignant lesions by echogenic properties. Specificity might be improved by shear strain imaging as malignant lesions, firmly bonded to its host tissue, show different shear patterns compared to benign lesions, often loosely bonded. Therefore, 3-D quasi-static elastography was implemented in an ABVS-like system. Plane wave instead of conventional focused transmissions were used to reduce scan times within a single breath hold. A 3-D strain tensor was obtained and shear strains were reconstructed in phantoms containing firmly and loosely bonded lesions. Experiments were also simulated in finite-element models (FEMs). Experimental results, confirmed by FEM-results, indicated that loosely bonded lesions showed increased maximal shear strains (~2.5%) and different shear patterns compared to firmly bonded lesions (~0.9%). To conclude, we successfully implemented 3-D elastography in an ABVS-like system to assess lesion bonding by shear strain imaging.

Comparison and Combination of Strain and Shear Wave Elastography of Breast Masses for Differentiation of Benign and Malignant Lesions by Quantitative Assessment: Preliminary Study

OBJECTIVES

To compare the diagnostic performance of strain and shear wave elastography of breast masses for quantitative assessment in differentiating benign and malignant lesions and to evaluate the diagnostic accuracy of combined strain and shear wave elastography.

METHODS

Between January and February 2016, 37 women with 45 breast masses underwent both strain and shear wave ultrasound (US) elastographic examinations. The American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) final assessment on B-mode US imaging was assessed. We calculated strain ratios for strain elastography and the mean elasticity value and elasticity ratio of the lesion to fat for shear wave elastography. Diagnostic performances were compared by using the area under the receiver operating characteristic curve (AUC).

RESULTS

The 37 women had a mean age of 47.4 years (range, 20-79 years). Of the 45 lesions, 20 were malignant, and 25 were benign. The AUCs for elasticity values on strain and shear wave elastography showed no significant differences (strain ratio, 0.929; mean elasticity, 0.898; and elasticity ratio, 0.868; P > .05). After selectively downgrading BI-RADS category 4a lesions based on strain and shear wave elastographic cutoffs, the AUCs for the combined sets of B-mode US and elastography were improved (B-mode + strain, 0.940; B-mode + shear wave; 0.964; and B-mode, 0.724; P < .001). Combined strain and shear wave elastography showed significantly higher diagnostic accuracy than each individual elastographic modality (P = .031).

CONCLUSIONS

These preliminary results showed that strain and shear wave elastography had similar diagnostic performance. The addition of strain and shear wave elastography to B-mode US improved diagnostic performance. The combination of strain and shear wave elastography results in a higher diagnostic yield than each individual elastographic modality.

Ultrasound Strain Elastography for Breast Lesions: Computer-Aided Evaluation With Quantifiable Elastographic Features

OBJECTIVES

To develop and evaluate a set of quantifiable elastographic features based on ultrasound real-time strain elastography (SE) in differentiating between benign and malignant breast lesions.

METHODS

The SE and conventional B-mode ultrasound images of 226 breast lesions (81 malignant, 145 benign) were obtained from 226 consecutive women. By using a computer-aided tool, four elastographic features (elasticity score, lesion stiffness degree, lesion-to-fat strain ratio, and elastography-to-B-mode lesion area ratio) were respectively calculated and evaluated. Histopathologic results were used as the reference standard. B-mode Breast Imaging Reporting and Data System categorization was used to compare the performances between B-mode ultrasound and SE. Sensitivity, specificity, positive and negative predictive values, and receiver operating characteristic curve analyses were performed to evaluate the diagnostic performances for three data sets (conventional B-mode ultrasound alone, SE features alone, combined SE features).

RESULTS

Quantifiable SE features for malignant lesions all showed significantly higher values than those for benign lesions (all P < .001). The evaluation with any individual SE feature significantly improved the specificity in breast lesion differentiation compared with B-mode ultrasound (all P <.001). The logistic regression model combing SE features significantly improved the diagnostic performance compared with B-mode US, with significantly increased specificity (95.2% versus 54.5%; P < .001) and area under the receiver operating characteristic curve (0.988 versus 0.921, P < .001).

CONCLUSIONS

Computer-aided tool with SE provided further elasticity information for breast characterization. Evaluation using quantifiable SE features showed better diagnostic performance than conventional B-mode ultrasound in breast lesion differentiation.

Effect of Interstitial Fluid Pressure on Ultrasound Axial Strain and Axial Shear Strain Elastography

Ultrasound elastography is an imaging modality that has been used to diagnose tumors of the breast, thyroid, and prostate. Both axial strain elastography and axial shear strain elastography (ASSE) have shown significant potentials to differentiate between benign and malignant tumors. Elevated interstitial fluid pressure (IFP) is a characteristic of many malignant tumors and a major barrier in targeted drug delivery therapies. This parameter, however, has not received significant attention in ultrasound elastography and, in general, in most diagnostic imaging modalities yet. In this paper, we investigate the effect of an underlying IFP contrast on ultrasound axial strain and axial shear strain imaging using finite element analysis. Our results show that an underlying contrast in IFP creates a new contrast mechanism in both the axial strain and axial shear strain elastographic images. This information might be important for a better interpretation of elastographic images of tumors.

Ultrasound elastography assessment of bone/soft tissue interface

We report on the use of elastographic imaging techniques to assess the bone/soft tissue interface, a region that has not been previously investigated but may provide important information about fracture and bone healing. The performance of axial strain elastograms and axial shear strain elastograms at the bone/soft tissue interface was studied ex vivo on intact and fractured canine and ovine tibias. Selected ex vivo results were corroborated on intact sheep tibias in vivo. The elastography results were statistically analyzed using elastographic image quality tools. The results of this study demonstrate distinct patterns in the distribution of the normalized local axial strains and axial shear strains at the bone/soft tissue interface with respect to the background soft tissue. They also show that the relative strength and distribution of the elastographic parameters change in the presence of a fracture and depend on the degree of misalignment between the fracture fragments. Thus, elastographic imaging modalities might be used in the future to obtain information regarding the integrity of bones and to assess the severity of fractures, alignment of bone fragments as well as to follow bone healing.

An analysis of the segmentation threshold used in axial-shear strain elastography

Axial-shear strain elastography was introduced recently to image the tumor-host tissue boundary bonding characteristics. The image depicting the axial-shear strain distribution in a tissue under axial compression was termed as an axial-shear strain elastogram (ASSE). It has been demonstrated through simulation, tissue-mimicking phantom experiments, and retrospective analysis of in vivo breast lesion data that metrics quantifying the pattern of axial-shear strain distribution on ASSE can be used as features for identifying the lesion boundary condition as loosely-bonded or firmly-bonded. Consequently, features from ASSE have been shown to have potential in non-invasive breast lesion classification into benign versus malignant. Although there appears to be a broad concurrence in the results reported by different groups, important details pertaining to the appropriate segmentation threshold needed for - (1) displaying the ASSE as a color-overlay on top of corresponding Axial Strain Elastogram (ASE) and/or sonogram for feature visualization and (2) ASSE feature extraction are not yet fully addressed. In this study, we utilize ASSE from tissue mimicking phantom (with loosely-bonded and firmly-bonded inclusions) experiments and freehand - acquired in vivo breast lesion data (7 benign and 9 malignant) to analyze the effect of segmentation threshold on ASSE feature value, specifically, the "fill-in" feature that was introduced recently. We varied the segmentation threshold from 20% to 70% (of the maximum ASSE value) for each frame of the acquisition cine-loop of every data and computed the number of ASSE pixels within the lesion that was greater than or equal to this threshold value. If at least 40% of the pixels within the lesion area crossed this segmentation threshold, the ASSE frame was considered to demonstrate a "fill-in" that would indicate a loosely-bonded lesion boundary condition (suggestive of a benign lesion). Otherwise, the ASSE frame was considered not to demonstrate a "fill-in" indicating a firmly-bonded lesion boundary condition (suggestive of a malignant lesion). The results demonstrate that in the case of in vivo breast lesion data the appropriate range for the segmentation threshold value seems to be 40-60%. It was noted that for a segmentation threshold within this range (for example, at 50%) all of the analyzed breast lesion cases can be correctly classified into benign and malignant, based on the percentage number of frames within the acquisition cine-loop that demonstrate a "fill-in".

3-D visualization and non-linear tissue classification of breast tumors using ultrasound elastography in vivo

The goal of the study described here was to introduce new methods for the classification and visualization of human breast tumors using 3-D ultrasound elastography. A tumor's type, shape and size are key features that can help the physician to decide the sort and extent of necessary treatment. In this work, tumor type, being either benign or malignant, was classified non-invasively for nine volunteer patients. The classification was based on estimating four parameters that reflect the tumor's non-linear biomechanical behavior, under multi-compression levels. Tumor prognosis using non-linear elastography was confirmed with biopsy as a gold standard. Three tissue classification parameters were found to be statistically significant with a p-value < 0.05, whereas the fourth non-linear parameter was highly significant, having a p-value < 0.001. Furthermore, each breast tumor's shape and size were estimated in vivo using 3-D elastography, and were enhanced using interactive segmentation. Segmentation with level sets was used to isolate the stiff tumor from the surrounding soft tissue. Segmentation also provided a reliable means to estimate tumors volumes. Four volumetric strains were investigated: the traditional normal axial strain, the first principal strain, von Mises strain and maximum shear strain. It was noted that these strains can provide varying degrees of boundary enhancement to the stiff tumor in the constructed elastograms. The enhanced boundary improved the performance of the segmentation process. In summary, the proposed methods can be employed as a 3-D non-invasive tool for characterization of breast tumors, and may provide early prognosis with minimal pain, as well as diminish the risk of late-stage breast cancer.

In Vivo response to compression of 35 breast lesions observed with a two-dimensional locally regularized strain estimation method

The objective of this study was to assess the in vivo performance of our 2-D locally regularized strain estimation method with 35 breast lesions, mainly cysts, fibroadenomas and carcinomas. The specific 2-D deformation model used, as well as the method's adaptability, led to an algorithm that is able to track tissue motion from radiofrequency ultrasound images acquired in clinical conditions. Particular attention was paid to strain estimation reliability, implying analysis of the mean normalized correlation coefficient maps. For all lesions examined, the results indicated that strain image interpretation, as well as its comparison with B-mode data, should take into account the information provided by the mean normalized correlation coefficient map. Different trends were observed in the tissue response to compression. In particular, carcinomas appeared larger in strain images than in B-mode images, resulting in a mean strain/B-mode lesion area ratio of 2.59 ± 1.36. In comparison, the same ratio was assessed as 1.04 ± 0.26 for fibroadenomas. These results are in agreement with those of previous studies, and confirm the interest of a more thorough consideration of size difference as one parameter discriminating between malignant and benign lesions.

Tissue mimicking materials for the detection of prostate cancer using shear wave elastography: a validation study

PURPOSE

Quantification of stiffness changes may provide important diagnostic information and aid in the early detection of cancers. Shear wave elastography is an imaging technique that assesses tissue stiffness using acoustic radiation force as an alternate to manual palpation reported previously with quasistatic elastography. In this study, the elastic properties of tissue mimicking materials, including agar, polyacrylamide (PAA), and silicone, are evaluated with an objective to determine material characteristics which resemble normal and cancerous prostate tissue.

METHODS

Acoustic properties and stiffness of tissue mimicking phantoms were measured using compressional mechanical testing and shear wave elastography using supersonic shear imaging. The latter is based on the principles of shear waves generated using acoustic radiation force. The evaluation included tissue mimicking materials (TMMs) within the prostate at different positions and sizes that could mimic cancerous and normal prostate tissue. Patient data on normal and prostate cancer tissues quantified using biopsy histopathology were used to validate the findings. Pathologist reports on histopathology were blinded to mechanical testing and elastographic findings.

RESULTS

Young's modulus values of 86.2 ± 4.5 and 271.5 ± 25.7 kPa were obtained for PAA mixed with 2% Al(2)O(3) particles and silicone, respectively. Young's modulus of TMMs from mechanical compression testing showed a clear trend of increasing stiffness with an increasing percentage of agar. The silicone material had higher stiffness values when compared with PAA with Al(2)O(3). The mean Young's modulus value in cancerous tissue was 90.5 ± 4.5 kPa as compared to 93.8 ± 4.4 and 86.2 ± 4.5 kPa obtained with PAA with 2% Al(2)O(3) phantom at a depth of 52.4 and 36.6 mm, respectively.

CONCLUSIONS

PAA mixed with Al(2)O(3) provides the most suitable tissue mimicking material for prostate cancer tumor material, while agar could form the surrounding background to simulate normal prostate tissue.

Nonlinear characterization of breast cancer using multi-compression 3D ultrasound elastography in vivo

The main objective of this article is to introduce a new nonlinear elastography based classification method for human breast masses. Multi-compression elastography imaging is elucidated in this study to differentiate malignant from benign lesions, based on their nonlinear mechanical behavior under compression. Three classification parameters were used and compared in this work: a new nonlinear parameter based on a power-law behavior of the strain difference between breast masses and healthy tissues, mass-soft tissue strain ratio and the mass relative volume between B-mode and elastography imaging. Using 3D elastography, these parameters were tested in vivo. A pilot study on 10 patients was performed, and results were compared with biopsy diagnosis as a gold standard. Initial elastography results showed a good agreement with biopsy outcomes. The new estimated nonlinear parameter had an average value of 0.163±0.063 and 1.642±0.261 for benign and malignant masses, respectively. Strain ratio values for the benign and malignant masses had an average value of 2.135±0.707 and 4.21±2.108, respectively. Relative mass volume was 0.848±0.237 and 2.18±0.522 for benign and malignant masses. In addition to the traditional normal axial strain, new strain types were used for elastography and constructed in 3D, including the first principal, maximum shear and Von Mises strains. The new strains provided an enhanced distinction of the stiff lesion from the soft tissue. In summary, the proposed elastographic techniques can be used as a noninvasive quantitative characterization tool for breast cancer, with the capability of visualizing and separating the masses in a three dimensional space. This may reduce the number of unnecessary painful breast biopsies.

Breast elastography: the technical process and its applications

Breast elastography is being increasingly used to better characterize breast lesions. Published studies have shown that it improved specificity of B mode ultrasound. Two elastography modes are available: free-hand elastography and shear wave elastography. Free-hand elastography is obtained by a mechanic wave induced by the ultrasound probe, deforming the target, either by small movements induced by breathe. An elastogram is obtained and displayed either as a colour map or a size ratio or elasticity ratio measurement. The second mode is shear wave elastography; two methods are available: Shear Wave Elastography (SWE) and ARFI mode (Acoustic Radiation Force Impulse). Shear wave elastography is less operator-dependent than free-hand elastography mode and provides a quantitative approach. A value of over 80kPa (SWE) or velocity results of over 2m/s (ARFI) are considered as suspicious. False negatives may occur in soft breast cancers (mucinous carcinoma, carcinoma with an inflammatory stroma, etc.) and false positives may be seen with poorly deformable benign lesions such as old fibrous adenomas. In practical use, elastography is a useful complementary tool for undetermined breast lesions categorized as BI-RADS 4a or BI-RADS 3, or for cystic lesions but cannot avoid fine needle aspiration or core biopsy if ultrasound features are clearly suspicious.

Comparison of cardiac displacement and strain imaging using ultrasound radiofrequency and envelope signals

Echocardiographic strain imaging is a promising new method for quantifying and displaying the health of cardiac muscle. Accurate regional myocardial function analysis requires high spatial and temporal resolution in addition to fidelity to the underlying deformation. However, all current clinical approaches use speckle-tracking algorithms applied to B-mode images derived from envelope signals. Such approaches are inherently of lower spatial resolution, since they require larger data blocks for deformation tracking due to the absence of phase information. In this paper, we compare the strain estimation performance using B-mode, envelope and radiofrequency signals, utilizing data acquired from a uniformly elastic tissue mimicking phantom, cardiac simulation, and clinical in vivo data. Signal-to-noise ratio improvements using radiofrequency signals for linear and phased array geometries were 5.80 dB and 9.48 dB over that obtained with envelope signals (at peak strain) in phantom studies, respectively. Cardiac simulation studies demonstrate that when averaged over the two cardiac cycles, the mean standard deviation of estimated strain using envelope signals from two of the six segments for a short-axes view (anterior and anterolateral) were 48% and 44% higher than that obtained using radiofrequency signals. These segments were chosen since one was along while the other was situated lateral to the beam propagation direction. In a similar manner, in vivo analysis on a volunteer also indicate that the standard deviation of the estimated strain using B-mode and envelope signals were 16% and 42% higher than that obtained using radiofrequency signals in the anteroseptal segment, and 45% and 27% in the anterior segment. These results demonstrate the significant reduction in the variability of strain estimated along with improvements in the spatial resolution and signal-to-noise ratios obtained using radiofrequency signals.

Normal and shear strain imaging using 2D deformation tracking on beam steered linear array datasets

PURPOSE

Previous publications have reported on the use of one-dimensional cross-correlation analysis with beam-steered echo signals. However, this approach fails to accurately track displacements at larger depths (>4.5 cm) due to lower signal-to-noise. In this paper, the authors present the use of adaptive parallelogram shaped two-dimensional processing blocks for deformation tracking.

METHODS

Beam-steered datasets were acquired using a VFX 9L4 linear array transducer operated at a 6 MHz center frequency for steered angles from -15 to 15° in increments of 1°, on both uniformly elastic and single-inclusion tissue-mimicking phantoms. Echo signals were acquired to a depth of 65 mm with the focus set at 40 mm corresponding to the center of phantom. Estimated angular displacements along and perpendicular to the beam direction are used to compute axial and lateral displacement vectors using a least-squares approach. Normal and shear strain tensor component are then estimated based on these displacement vectors.

RESULTS

Their results demonstrate that parallelogram shaped two-dimensional deformation tracking significantly improves spatial resolution (factor of 7.79 along the beam direction), signal-to-noise (5 dB improvement), and contrast-to-noise (8-14 dB improvement) associated with strain imaging using beam steering on linear array transducers.

CONCLUSIONS

Parallelogram shaped two-dimensional deformation tracking is demonstrated in beam-steered radiofrequency data, enabling its use in the estimation of normal and shear strain components.

On the advantages of imaging the axial-shear strain component of the total shear strain in breast tumors

Axial-shear strain elastography was described recently as a method to visualize the state of bonding at an inclusion boundary. Although total shear strain elastography was initially proposed for this purpose, it did not evolve beyond the initial reported finite element model (FEM) and simulation studies. One of the major reasons for this was the practical limitation in estimating the tissue motion perpendicular (lateral) to the ultrasound (US) beam as accurately as the motion along the US beam (axial). Nevertheless, there has been a sustained effort in developing methods to improve the lateral motion tracking accuracy and thereby obtain better quality total shear strain elastogram (TSSE). We hypothesize that in some cases, even if good quality TSSE becomes possible, it may still be advantageous to utilize only the axial-shear strain (one of the components of the total shear strain) elastogram (ASSE). Specifically, we show through FEM and corroborating tissue-mimicking gelatin phantom experiments that the unique "fill-in" discriminant feature that was introduced recently for asymmetric breast lesion classification is depicted only in the ASSE and not in the TSSE. Note that the presence or conspicuous absence of this feature in ASSE was shown to characterize asymmetric inclusions' boundaries as either loosely-bonded or firmly-bonded to the surrounding, respectively. This might be an important observation because the literature suggests that benign breast lesions tend to be loosely-bonded, while malignant tumors are usually firmly-bonded. The results from the current study demonstrate that the use of shear strain lesion "fill-in" as a discriminant feature in the differentiation between asymmetric malignant and benign breast lesions is only possible when using the ASSEs and not the TSSEs.

The nanomechanical signature of breast cancer

Cancer initiation and progression follow complex molecular and structural changes in the extracellular matrix and cellular architecture of living tissue. However, it remains poorly understood how the transformation from health to malignancy alters the mechanical properties of cells within the tumour microenvironment. Here, we show using an indentation-type atomic force microscope (IT-AFM) that unadulterated human breast biopsies display distinct stiffness profiles. Correlative stiffness maps obtained on normal and benign tissues show uniform stiffness profiles that are characterized by a single distinct peak. In contrast, malignant tissues have a broad distribution resulting from tissue heterogeneity, with a prominent low-stiffness peak representative of cancer cells. Similar findings are seen in specific stages of breast cancer in MMTV-PyMT transgenic mice. Further evidence obtained from the lungs of mice with late-stage tumours shows that migration and metastatic spreading is correlated to the low stiffness of hypoxia-associated cancer cells. Overall, nanomechanical profiling by IT-AFM provides quantitative indicators in the clinical diagnostics of breast cancer with translational significance.

In vivo classification of breast masses using features derived from axial-strain and axial-shear images

Breast cancer is currently the second leading cause of cancer deaths in women. Early detection and accurate classification of suspicious masses as benign or malignant is important for arriving at an appropriate treatment plan. In this article, we present classification results for features extracted from ultrasound-based, axial-strain and axial-shear images of breast masses. The breast-mass stiffness contrast, size ratio, and a normalized axial-shear strain area feature are evaluated for the classification of in vivo breast masses using a leave-one-out classifier. Radiofrequency echo data from 123 patients were acquired using Siemens Antares or Elegra clinical ultrasound systems during freehand palpation. Data from four different institutions were analyzed. Axial displacements and strains were estimated using a multilevel, pyramid-based two-dimensional cross-correlation algorithm, with final processing block dimensions of 0.385 mm × 0.507 mm (three A-lines). Since mass boundaries on B-mode images for 21 patients could not be delineated (isoechoic), the combined feature analysis was only performed for 102 patients. Results from receiver operating characteristic (ROC) demonstrate that the area under the curve was 0.90, 0.84, and 0.52 for the normalized axial-shear strain, size ratio, and stiffness contrast, respectively. When these three features were combined using a leave-one-out classifier and support vector machine approach, the overall area under the curve improved to 0.93.

Analysis of shear strain imaging for classifying breast masses: finite element and phantom results

PURPOSE

Features extracted from axial-shear strain images of breast masses have been previously utilized to differentiate and classify benign from malignant breast masses. In this paper, we compare shear strain patterns exhibited by both the full-shear (axial and lateral component) versus only the axial-shear strain component for differentiating between bound masses (malignant) when compared to unbound masses (benign).

METHODS

We examine different breast mass characteristics such as mass shape, asymmetric location of masses, stiffness variations, and mass bonding characteristics to background tissue to assess their impact on shear strain patterns generated due to a uniaxial applied deformation. Two-dimensional finite element simulations of both circular and elliptical inclusions embedded within a uniform background were utilized. Different degrees of bonding were characterized using friction coefficient values ranging from 0.01 to 100 denoting loosely bound to firmly bound masses. Single-inclusion tissue-mimicking phantoms mimicking firmly bound and loosely bound ellipsoidal masses oriented at four different angles to the applied deformation were studied to corroborate the mass differentiation performance.

RESULTS

Our results indicate that the normalized axial-shear strain and full-shear strain area features are larger for bound when compared to unbound masses. A higher stiffness ratio or contrast between the inclusion and background also improves differentiation. Larger applied deformations reduce the discrimination performance for masses with friction coefficients lower than 0.4, due to increased mass slippage with applied deformations. Potential errors with the use of these features would occur for unbound inclusions at larger applied deformations and for asymmetric mass positions within the background normal tissue.

CONCLUSIONS

Finite element and tissue-mimicking phantom results demonstrate the feasibility of utilizing both the normalized axial-shear and full-shear strain area features to classify breast masses. Differentiation between bound or unbound masses was not affected by the mass size or shape for masses where the applied deformation is normal to the mass surface. Shear strain patterns vary significantly especially within unbound masses, when the mass surface is not normal to the applied deformation. Discrimination performance for unbound masses was improved by utilizing only the normalized shear strain area patterns located outside the mass as illustrated in this paper.

Bayesian regularization applied to ultrasound strain imaging

Noise artifacts due to signal decorrelation and reverberation are a considerable problem in ultrasound strain imaging. For block-matching methods, information from neighboring matching blocks has been utilized to regularize the estimated displacements. We apply a recursive Bayesian regularization algorithm developed by Hayton et al. [Artif. Intell., vol. 114, pp. 125-156, 1999] to phase-sensitive ultrasound RF signals to improve displacement estimation. The parameter of regularization is reformulated, and its meaning examined in the context of strain imaging. Tissue-mimicking experimental phantoms and RF data incorporating finite-element models for the tissue deformation and frequency-domain ultrasound simulations are used to compute the optimal parameter with respect to nominal strain and algorithmic iterations. The optimal strain regularization parameter was found to be twice the nominal strain and did not vary significantly with algorithmic iterations. The technique demonstrates superior performance over median filtering in noise reduction at strains 5% and higher for all quantitative experiments performed. For example, the strain SNR was 11 dB higher than that obtained using a median filter at 7% strain. It has to be noted that for applied deformations lower than 1%, since signal decorrelation errors are minimal, using this approach may degrade the displacement image.