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

A wavelet neural operator based elastography for localization and quantification of tumors

BACKGROUND AND OBJECTIVES

The application of intelligent imaging techniques and deep learning in the field of computer-aided diagnosis and medical imaging have improved and accelerated the early diagnosis of many diseases. Elastography is an imaging modality where an inverse problem is solved to extract the elastic properties of tissues and subsequently mapped to anatomical images for diagnostic purposes. In the present work, we propose a wavelet neural operator-based approach for correctly learning the non-linear mapping of elastic properties directly from measured displacement field data.

METHODS

The proposed framework learns the underlying operator behind the elastic mapping and thus can map any displacement data from a family to the elastic properties. The displacement fields are first uplifted to a high-dimensional space using a fully connected neural network. On the lifted data, certain iterations are performed using wavelet neural blocks. In each wavelet neural block, the lifted data are decomposed into low, and high-frequency components using wavelet decomposition. To learn the most relevant patterns and structural information from the input, the neural network kernels are directly convoluted with the outputs of the wavelet decomposition. Thereafter the elasticity field is reconstructed from the outputs from convolution. The mapping between the displacement and the elasticity using wavelets is unique and remains stable during training.

RESULTS

The proposed framework is tested on several artificially fabricated numerical examples, including a benign-cum-malignant tumor prediction problem. The trained model was also tested on real Ultrasound-based elastography data to demonstrate the applicability of the proposed scheme in clinical usage. The proposed framework reproduces the highly accurate elasticity field directly from the displacement inputs.

CONCLUSIONS

The proposed framework circumvents different data pre-processing and intermediate steps utilized in traditional methods, hence providing an accurate elasticity map. The computationally efficient framework requires fewer epochs for training, which bodes well for its clinical usability for real-time predictions. The weights and biases from pre-trained models can also be employed for transfer learning, which reduces the effective training time with random initialization.

Clinical Significance of Ultrasound Elastography and Fibrotic Focus and Their Association in Breast Cancer

(1) Background: Ultrasound (US) elastography is an imaging technology that reveals tissue stiffness. This study aimed to investigate whether fibrotic focus (FF) affects elastographic findings in breast cancer, and to evaluate the clinical significance of US elastography and FF in breast cancer. (2) Methods: In this study, 151 patients with breast cancer who underwent surgery were included. Strain elastography was performed and an elasticity scoring system was used to assess the findings. The elasticity scores were classified as negative, equivocal, or positive. FF was evaluated in the surgical specimens. Medical records were reviewed for all patients. (3) Results: Elastographic findings were equivocal in 30 patients (19.9%) and positive in 121 patients (80.1%). FF was present in 68 patients (46.9%). There was no correlation between elastographic findings and FF. Older age, larger tumor size, lymph node metastasis, and higher tumor stage were associated with positive elastographic results. FF showed a positive correlation with age, postmenopausal status, tumor size, lymphovascular invasion, lymph node metastasis, tumor stage, and intratumoral and peritumoral inflammation. (4) Conclusions: Our study showed that positive elastographic results and FF were associated with poor prognostic factors for breast cancer. FF did not affect the elastographic findings of this study.

Biophysics Role and Biomimetic Culture Systems of ECM Stiffness in Cancer EMT

Oncological diseases have become the second leading cause of death from noncommunicable diseases worldwide and a major threat to human health. With the continuous progress in cancer research, the mechanical cues from the tumor microenvironment environment (TME) have been found to play an irreplaceable role in the progression of many cancers. As the main extracellular mechanical signal carrier, extracellular matrix (ECM) stiffness may influence cancer progression through biomechanical transduction to modify downstream gene expression, promote epithelial-mesenchymal transition (EMT), and regulate the stemness of cancer cells. EMT is an important mechanism that induces cancer cell metastasis and is closely influenced by ECM stiffness, either independently or in conjunction with other molecules. In this review, the unique role of ECM stiffness in EMT in different kinds of cancers is first summarized. By continually examining the significance of ECM stiffness in cancer progression, a biomimetic culture system based on 3D manufacturing and novel material technologies is developed to mimic ECM stiffness. The authors then look back on the novel development of the ECM stiffness biomimetic culture systems and finally provide new insights into ECM stiffness in cancer progression which can broaden the fields' horizons with a view toward developing new cancer diagnosis methods and therapies.

Studying Activated Fibroblast Phenotypes and Fibrosis-Linked Mechanosensing Using 3D Biomimetic Models

Fibrosis and solid tumor progression are closely related, with both involving pathways associated with chronic wound dysregulation. Fibroblasts contribute to extracellular matrix (ECM) remodeling in these processes, a crucial step in scarring, organ failure, and tumor growth, but little is known about the biophysical evolution of remodeling regulation during the development and progression of matrix-related diseases including fibrosis and cancer. A 3D collagen-based scaffold model is employed here to mimic mechanical changes in normal (2 kPa, soft) versus advanced pathological (12 kPa, stiff) tissues. Activated fibroblasts grown on stiff scaffolds show lower migration and increased cell circularity compared to those on soft scaffolds. This is reflected in gene expression profiles, with cells cultured on stiff scaffolds showing upregulated DNA replication, DNA repair, and chromosome organization gene clusters, and a concomitant loss of ability to remodel and deposit ECM. Soft scaffolds can reproduce biophysically meaningful microenvironments to investigate early stage processes in wound healing and tumor niche formation, while stiff scaffolds can mimic advanced fibrotic and cancer stages. These results establish the need for tunable, affordable 3D scaffolds as platforms for aberrant stroma research and reveal the contribution of physiological and pathological microenvironment biomechanics to gene expression changes in the stromal compartment.

Correlation of breast cancer microcirculation construction with tumor stem cells (CSCs) and epithelial-mesenchymal transition (EMT) based on contrast-enhanced ultrasound (CEUS)

Objective

This study is to explore the correlation between the contrast-enhanced ultrasound (CEUS) characteristics of breast cancer and the epithelial-mesenchyme transformation (EMT).

Methods

Totally 119 patients of breast cancer underwent CEUS. Tissues in the active area were collected and subjected to the immunohistochemical detection, PT-PCR and Western blot. Correlation analysis was conducted between the clinical pathological parameters and the CEUS indicators.

Results

The expression levels of CD44, N-cadherin, and β-catenin in breast cancer tissues were higher than those in adjacent tissues (P<0.05). However, the expression levels of CD24 and E-cadherin in breast cancer tissues were lower than those in adjacent tissues (P<0.05). There was no significant difference in E-cadherin mRNA and Vimentin levels between cancer and adjacent tissues (P>0.05). The expressions were up-regulated in the CSCs, with higher histological grade, lymph node metastasis, and negative estrogen receptor (ER) expression. Smaller breast tumors, with no lymph node metastasis, lower clinical stage, and positive ER expression, tended to exhibit the up-regulated epithelial phenotype. Breast tumors, with high histological grade, lymph node metastasis, high clinical staging grade, and negative ER expression, tended to exhibit the up-regulated interstitial phenotype. The peak intensity of the time-intensity curve (TIC) for the CEUS was positively correlated with the CSC marker CD44 and the interstitial phenotype marker N-cadherin. The starting time of enhancement was negatively correlated with the N-cadherin. Area under the curve was positively correlated with the expression of CD44 and N-cadherin, while negatively correlated with the epithelial phenotype marker β-catenin. The time to peak was negatively correlated with the interstitial phenotypes Vimentin and N-cadherin, with no correlation with the E-cadherin or β-catenin.

Conclusion

Breast cancers show the enlarged lesions after enlargement and perfusion defect for the CEUS. The fast-in pattern, high enhancement, and high perfusion in the TIC are correlated with the CSCs and EMT expressions, suggesting poor disease prognosis.

Quantitative analysis of shear wave elastic heterogeneity for prediction of lymphovascular invasion in breast cancer

OBJECTIVE

To evaluate the correlation between elastic heterogeneity (EH) and lymphovascular invasion (LVI) in breast cancers and assess the clinical value of using EH to predict LVI pre-operatively.

METHODS

This retrospective study consisted of 376 patients with breast cancers that had undergone shear wave elastography (SWE) with virtual touch tissue imaging quantification between June 2017 and June 2018. The EH was determined as the difference between the averaged three highest and three lowest shear wave value. Clinicalpathological parameters including histological type and grades, LVI, axillary lymph node status and molecular markers (estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2 and Ki-67) were reviewed and recorded. Relationship EH and clinicalpathological parameters was investigated respectively. The diagnostic performance of EH in distinguishing LVI or not was analyzed.

RESULTS

At multivariate regression analysis, only EH (p = 0.017) was positively correlated with LVI in all tumors. EH (p = 0.003) and Ki-67 (p = 0.025) were positively correlated with LVI in tumors ≤ 2 cm. None of clinicalpathological parameters were correlated with LVI in tumors > 2 cm (p > 0.05 for all). Using EH to predict LVI in tumors ≤ 2 cm, the sensitivity and negative predictive value were 93 and 89% respectively.

CONCLUSION

EH has the potential to be served as an imaging biomarker to predict LVI in breast cancer especially for tumors ≤ 2 cm.

ADVANCES IN KNOWLEDGE

There was no association between LVI and other most commonly used elastic features such as SWV_mean and SWV_max. Elastic heterogeneity is an independent predictor of LVI, so it can provide additional prognostic information for routine preoperative breast cancer assessment.For tumors ≤ 2cm, using EH value higher than 1.36 m/s to predict LVI involvement, the sensitivity and negative predictive value can reach to 93% and 89%, respectively, suggesting that breast cancer with negative EH value was more likely to be absent of LVI.

Applications of Mechanical Arm in the Virtual Touch Tissue Imaging Quantification and the Differential Diagnosis of Breast Tumors

ABSTRACT

To assess the diagnostic performance of quantitative parameters for virtual touch tissue imaging quantification by the mechanical arm probe, 128 women with 152 breast lesions (90 benign and 62 malignant) were included and maximum elasticity (Vmax), median elasticity (Vmean), maximum elasticity minus minimum (Vmax-min), and minimum elasticity (Vmin) were measured. Intercorrelation coefficients and Bland-Altman plots were used to compare the repeatability and consistency of handheld probe and mechanical arm measurements. Receiver operating characteristic curve was used to evaluate the diagnostic efficiency. The results showed that intercorrelation coefficients were 0.694 to 0.951 by the mechanical arm and 95% limits of agreement were wider than handheld probe. Using 4.36 m/s as cutoff value for Vmax by the mechanical arm, we achieved sensitivity (88.7%) and specificity (90.0%). We concluded that the mechanical arm can reduce the influence of different scanning pressures on the elastic modulus of breast tissue.

Extracellular matrix and its therapeutic potential for cancer treatment

The extracellular matrix (ECM) is one of the major components of tumors that plays multiple crucial roles, including mechanical support, modulation of the microenvironment, and a source of signaling molecules. The quantity and cross-linking status of ECM components are major factors determining tissue stiffness. During tumorigenesis, the interplay between cancer cells and the tumor microenvironment (TME) often results in the stiffness of the ECM, leading to aberrant mechanotransduction and further malignant transformation. Therefore, a comprehensive understanding of ECM dysregulation in the TME would contribute to the discovery of promising therapeutic targets for cancer treatment. Herein, we summarized the knowledge concerning the following: (1) major ECM constituents and their functions in both normal and malignant conditions; (2) the interplay between cancer cells and the ECM in the TME; (3) key receptors for mechanotransduction and their alteration during carcinogenesis; and (4) the current therapeutic strategies targeting aberrant ECM for cancer treatment.

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.

Finite deformation elastography of articular cartilage and biomaterials based on imaging and topology optimization

Tissues and engineered biomaterials exhibit exquisite local variation in stiffness that defines their function. Conventional elastography quantifies stiffness in soft (e.g. brain, liver) tissue, but robust quantification in stiff (e.g. musculoskeletal) tissues is challenging due to dissipation of high frequency shear waves. We describe new development of finite deformation elastography that utilizes magnetic resonance imaging of low frequency, physiological-level (large magnitude) displacements, coupled to an iterative topology optimization routine to investigate stiffness heterogeneity, including spatial gradients and inclusions. We reconstruct 2D and 3D stiffness distributions in bilayer agarose hydrogels and silicon materials that exhibit heterogeneous displacement/strain responses. We map stiffness in porcine and sheep articular cartilage deep within the bony articular joint space in situ for the first time. Elevated cartilage stiffness localized to the superficial zone is further related to collagen fiber compaction and loss of water content during cyclic loading, as assessed by independent T2 measurements. We additionally describe technical challenges needed to achieve in vivo elastography measurements. Our results introduce new functional imaging biomarkers, which can be assessed nondestructively, with clinical potential to diagnose and track progression of disease in early stages, including osteoarthritis or tissue degeneration.

Non-invasive imaging of Young's modulus and Poisson's ratio in cancers in vivo

Alterations of Young's modulus (YM) and Poisson's ratio (PR) in biological tissues are often early indicators of the onset of pathological conditions. Knowledge of these parameters has been proven to be of great clinical significance for the diagnosis, prognosis and treatment of cancers. Currently, however, there are no non-invasive modalities that can be used to image and quantify these parameters in vivo without assuming incompressibility of the tissue, an assumption that is rarely justified in human tissues. In this paper, we developed a new method to simultaneously reconstruct YM and PR of a tumor and of its surrounding tissues based on the assumptions of axisymmetry and ellipsoidal-shape inclusion. This new, non-invasive method allows the generation of high spatial resolution YM and PR maps from axial and lateral strain data obtained via ultrasound elastography. The method was validated using finite element (FE) simulations and controlled experiments performed on phantoms with known mechanical properties. The clinical feasibility of the developed method was demonstrated in an orthotopic mouse model of breast cancer. Our results demonstrate that the proposed technique can estimate the YM and PR of spherical inclusions with accuracy higher than 99% and with accuracy higher than 90% in inclusions of different geometries and under various clinically relevant boundary conditions.

Fibrosis and cancer: A strained relationship

Tumors are characterized by extracellular matrix (ECM) deposition, remodeling, and cross-linking that drive fibrosis to stiffen the stroma and promote malignancy. The stiffened stroma enhances tumor cell growth, survival and migration and drives a mesenchymal transition. A stiff ECM also induces angiogenesis, hypoxia and compromises anti-tumor immunity. Not surprisingly, tumor aggression and poor patient prognosis correlate with degree of tissue fibrosis and level of stromal stiffness. In this review, we discuss the reciprocal interplay between tumor cells, cancer associated fibroblasts (CAF), immune cells and ECM stiffness in malignant transformation and cancer aggression. We discuss CAF heterogeneity and describe its impact on tumor development and aggression focusing on the role of CAFs in engineering the fibrotic tumor stroma and tuning tumor cell tension and modulating the immune response. To illustrate the role of mechanoreciprocity in tumor evolution we summarize data from breast cancer and pancreatic ductal carcinoma (PDAC) studies, and finish by discussing emerging anti-fibrotic strategies aimed at treating cancer.

Modeling Uncertainty of Strain Ratio Measurements in Ultrasound Breast Strain Elastography: A Factorial Experiment

Strain elastography (SE) is a technique in which images of localized tissue strains are used to detect the relative stiffness of tissues. The application of SE in differentiating malignant breast lesions from benign ones has been broadly investigated. The strain ratio (SR) between the background and the breast tumor has been used and its results have been mixed. Due to the complex nature of tissue elasticity and how it relates to the strain fields measured in SE, the exact reason is not known. In this study, we apply a novel design-of-experiments-based metamodeling approach to mechanical simulation of SE in the human breast. To our knowledge, such a study has not been reported in the ultrasound SE literature. More specifically, we first conduct a screening study to identify the biomechanical factors/simulation inputs that most strongly determine SR. We then apply a response surface experimental design to these factors to produce a metamodel of SR as a function of said factors. Results from the screening study suggest that the SR measurements are primarily influenced by three factors: the initial shear modulus of the lesion, the elastic nonlinearity of the lesion, and the precompression applied during acquisition. In order to investigate the implications of these results, stochastic inputs for these three factors associated with the malignant and benign cases were applied to the resulting response surface. The resulting optimal cutoffs, sensitivity, and specificity were generally in line with a majority (>60%) of 19 clinical trials in the literature.

Triangular correlation (TrC) between cancer aggressiveness, cell uptake capability, and cell deformability

The malignancy potential is correlated with the mechanical deformability of the cancer cells. However, mechanical tests for clinical applications are limited. We present here a Triangular Correlation (TrC) between cell deformability, phagocytic capacity, and cancer aggressiveness, suggesting that phagocytic measurements can be a mechanical surrogate marker of malignancy. The TrC was proved in human prostate cancer cells with different malignancy potential, and in human bladder cancer and melanoma cells that were sorted into subpopulations based solely on their phagocytic capacity. The more phagocytic subpopulations showed elevated aggressiveness ex vivo and in vivo. The uptake potential was preserved, and differences in gene expression and in epigenetic signature were detected. In all cases, enhanced phagocytic and aggressiveness phenotypes were correlated with greater cell deformability and predicted by a computational model. Our multidisciplinary study provides the proof of concept that phagocytic measurements can be applied for cancer diagnostics and precision medicine.

Establishment of primary human breast cancer cell lines using "pulsed hypoxia" method and development of metastatic tumor model in immunodeficient mice

Background

Among breast cancer (BC) patients the outcomes of anticancer therapy vary dramatically due to the highly heterogeneous molecular characteristics of BC. Therefore, an extended panel of BC cell lines are required for in vitro and in vivo studies to find out new characteristic of carcinogenesis and metastasis. The purpose of this study was to develop patient-derived BC cell cultures and metastatic tumor models representing a tool for personal therapy and translational research.

Methods

Breast cancer cells were prepared by optimizing technique from tumor samples. We used real-time RT-PCR, flow cytometry, western blotting, cytotoxicity assay, karyotyping and fluorescent and electron microscopy analyses to characterize the established cell lines. BC xenografts in scid mice were used for in vivo tumorigenicity studies.

Results

The technique of preparing primary cells was optimized and this resulted in a high output of viable and active proliferated cells of nine patient-derived breast cancer cell lines and one breast non-malignant cell line. High E-cadherine and EpCAM expression correlated positively with epithelial phenotype while high expression of N-cadherine and Vimentin were shown in cells with mesenchymal phenotype. All mesenchymal-like cell lines were high HER3-positive—up to 90%. More interesting than that, is that two cell lines under specific culturing conditions (pulsed hypoxia and conditioned media) progressively transformed from mesenchymal to epithelial phenotypes displaying the expression of respective molecular markers proving that the mesenchymal-to-epithelial transition occurred. Becoming epithelial, these cells have lost HER3 and decreased HER2 membrane receptors. Three of the established epithelial cancer cell lines were tumorigenic in SCID mice and the generated tumors exhibited lobules-like structures. Ultrastructure analysis revealed low-differentiate phenotype of tumorigenic cell lines. These cells were in near-triploid range with multiple chromosome rearrangements. Tumorigenic BrCCh4e cells, originated from the patient of four-course chemotherapy, initiated metastasis when they were grafted subcutaneous with colonization of mediastinum lymph nodes.

Conclusions

The developed BC cells metastasizing to mediastinum lymph nodes are a relevant model for downstream applications. Moreover, our findings demonstrate that pulsed hypoxia induces transformation of primary fibroblastoid breast cancer cells to epithelial-like cells and both of these cultures—induced and original—don’t show tumor initiating capacity.

Electronic supplementary material

The online version of this article (10.1186/s12935-019-0766-5) contains supplementary material, which is available to authorized users.

Volumetric quantitative optical coherence elastography with an iterative inversion method

It is widely accepted that accurate mechanical properties of three-dimensional soft tissues and cellular samples are not available on the microscale. Current methods based on optical coherence elastography can measure displacements at the necessary resolution, and over the volumes required for this task. However, in converting this data to maps of elastic properties, they often impose assumptions regarding homogeneity in stress or elastic properties that are violated in most realistic scenarios. Here, we introduce novel, rigorous, and computationally efficient inverse problem techniques that do not make these assumptions, to realize quantitative volumetric elasticity imaging on the microscale. Specifically, we iteratively solve the three-dimensional elasticity inverse problem using displacement maps obtained from compression optical coherence elastography. This is made computationally feasible with adaptive mesh refinement and domain decomposition methods. By employing a transparent, compliant surface layer with known shear modulus as a reference for the measurement, absolute shear modulus values are produced within a millimeter-scale sample volume. We demonstrate the method on phantoms, on a breast cancer sample ex vivo, and on human skin in vivo. Quantitative elastography on this length scale will find wide application in cell biology, tissue engineering and medicine.

Tumour cell invasiveness and response to chemotherapeutics in adipocyte invested 3D engineered anisotropic collagen scaffolds

Breast cancers are highly heterogeneous and their metastatic potential and response to therapeutic drugs is difficult to predict. A tool that could accurately gauge tumour invasiveness and drug response would provide a valuable addition to the oncologist’s arsenal. We have developed a 3-dimensional (3D) culture model that recapitulates the stromal environment of breast cancers by generating anisotropic (directional) collagen scaffolds seeded with adipocytes and culturing tumour fragments therein. Analysis of tumour cell invasion in the presence of various therapeutic drugs, by immunofluorescence microscopy coupled with an optical clearing technique, demonstrated the utility of this approach in determining both the rate and capacity of tumour cells to migrate through the stroma while shedding light also on the mode of migration. Furthermore, the response of different murine mammary tumour types to chemotherapeutic drugs could be readily quantified.

A Normalized Shear Deformation Indicator for Ultrasound Strain Elastography in Breast Tissues: An In Vivo Feasibility Study

The shear deformation under loads contains useful information for distinguishing benign breast lesions from malignant ones. In this study, we proposed a normalized shear deformation indicator (NSDI) that was derived from the concept of principal strains. Since the NSDI requires both high-quality axial and lateral (parallel and perpendicular to the beam, resp.) displacement estimates, a strategy combining high-quality speckle tracking with signal “denoising” was employed. Both techniques were previously published by our group. Finite element (FE) models were used to identify possible causes for elevated NSDI values in and around breast lesions, followed by an analysis of ultrasound data acquired from 26 biopsy-confirmed in vivo breast lesions. We found that, theoretically, the elevated NSDI values could be attributed to two factors: significantly hardened tissue stiffness and increasing heterogeneity. The analysis of in vivo data showed that the proposed NSDI values were higher (p < 0.05) among malignant cancers as compared to those measured from benign ones. In conclusion, our preliminary results demonstrated that the calculation of NSDI value is feasible and NSDI could add value to breast lesion differentiation with current clinical equipment as a postprocessing tool.

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.

Simplifying the assessment of human breast cancer by mapping a micro-scale heterogeneity index in optical coherence elastography

Surgical treatment of breast cancer aims to identify and remove all malignant tissue. Intraoperative assessment of tumor margins is, however, not exact; thus, re-excision is frequently needed, or excess normal tissue is removed. Imaging methods applicable intraoperatively could help to reduce re-excision rates whilst minimizing removal of excess healthy tissue. Optical coherence elastography (OCE) has been proposed for use in breast-conserving surgery; however, intraoperative interpretation of complex OCE images may prove challenging. Observations of breast cancer on multiple length scales, by OCE, ultrasound elastography, and atomic force microscopy, have shown an increase in the mechanical heterogeneity of malignant breast tumors compared to normal breast tissue. In this study, a micro-scale mechanical heterogeneity index is introduced and used to form heterogeneity maps from OCE scans of 10 ex vivo human breast tissue samples. Through comparison of OCE, optical coherence tomography images, and corresponding histology, malignant tissue is shown to possess a higher heterogeneity index than benign tissue. The heterogeneity map simplifies the contrast between tumor and normal stroma in breast tissue, facilitating the rapid identification of possible areas of malignancy, which is an important step towards intraoperative margin assessment using OCE.

Direct Error in Constitutive Equation Formulation for Plane stress Inverse Elasticity Problem

We present a new computational formulation for inverse problems in elasticity with full field data. The formulation is a variant of an error in the constitutive equation formulation, but allows direct solution for the modulus field and accommodates discontinuous strain fields. The development of the formulation is motivated by the relatively poor performance of current direct formulations, reported so far in literature, in dealing with discontinuities in the strain and material property distribution. The formulation relies on minimizing the error in the constitutive equation, and a momentum equation constraint. Numerical results on model problems show that the formulation is capable handling discontinuous, and noisy strain fields, and also converging with mesh refinement for continuous and discontinuous material property distributions. The application to reconstruct the elastic modulus distribution in solid breast tumors is shown.