Breast magnetic resonance elastography: a review of clinical work and future perspectives

Analysis of friction in quantitative micro-elastography

Quantitative micro-elastography (QME) is a compression-based optical coherence elastography technique capable of measuring the mechanical properties of tissue on the micro-scale. As QME requires contact between the imaging window and the sample, the presence of friction affects the accuracy of the estimated elasticity. In previous implementations, a lubricant was applied at the contact surfaces, which was assumed to result in negligible friction. However, recently, errors in the estimation of elasticity caused by friction have been reported. This effect has yet to be characterized and is, therefore, not well understood. In this work, we present a systematic analysis of friction in QME using silicone phantoms. We demonstrate that friction, and, therefore, the elasticity accuracy, is influenced by several experimental factors, including the viscosity of the lubricant, the mechanical contrast between the compliant layer and the sample, and the time after the application of a compressive strain. Elasticity errors over an order of magnitude were observed in the absence of appropriate lubrication when compared to uniaxial compression testing. Using an optimized lubrication protocol, we demonstrate accurate elasticity estimation (<10% error) for nonlinear elastic samples with Young's moduli ranging from 3 kPa to 130 kPa. Finally, using a structured phantom, we demonstrate that friction can significantly reduce mechanical contrast in QME. We believe that the framework established in this study will facilitate more robust elasticity estimations in QME, as well as being readily adapted to understand the effects of friction in other contact elastography techniques.

Definition and evaluation of a finite element model of the human heel for diabetic foot ulcer prevention under shearing loads

Diabetic foot ulcers are triggered by mechanical loadings applied to the surface of the plantar skin. Strain is considered to play a crucial role in relation to ulcer etiology and can be assessed by Finite Element (FE) modeling. A difficulty in the generation of these models is the choice of the soft tissue material properties. In the literature, many studies attempt to model the behavior of the heel soft tissues by implementing constitutive laws that can differ significantly in terms of mechanical response. Moreover, current FE models lack of proper evaluation techniques that could estimate their ability to simulate realistic strains. In this article, we propose and evaluate a FE model of the human heel for diabetic foot ulcer prevention. Soft tissue constitutive laws are defined through the fitting of experimental stretch-stress curves published in the literature. The model is then evaluated through Digital Volume Correlation (DVC) based on non-rigid 3D Magnetic Resonance Image Registration. The results from FE analysis and DVC show similar strain locations in the fat pad and strain intensities according to the type of applied loads. For additional comparisons, different sets of constitutive models published in the literature are applied into the proposed FE mesh and simulated with the same boundary conditions. In this case, the results in terms of strains show great diversity in locations and intensities, suggesting that more research should be developed to gain insight into the mechanical properties of these tissues.

Mechanotransduction in tumor dynamics modeling

Mechanotherapy is a groundbreaking approach to impact carcinogenesis. Cells sense and respond to mechanical stimuli, translating them into biochemical signals in a process known as mechanotransduction. The impact of stress on tumor growth has been studied in the last three decades, and many papers highlight the role of mechanics as a critical self-inducer of tumor fate at the in vitro and in vivo biological levels. Meanwhile, mathematical models attempt to determine laws to reproduce tumor dynamics. This review discusses biological mechanotransduction mechanisms and mathematical-biomechanical models together. The aim is to provide a common framework for the different approaches that have emerged in the literature from the perspective of tumor avascularity and to provide insight into emerging mechanotherapies that have attracted interest in recent years.

Vascular elasticity measurement of the great saphenous vein based on optical coherence elastography

Vascular elasticity is important in physiological and clinical problems. The mechanical properties of the great saphenous vein (GSV) deserve attention. This research aims to measure the radial elasticity of ex vivo GSV using the optical coherence elasticity (OCE). The finite element model of the phantom is established, the displacement field is calculated, the radial mechanical characteristics of the simulation body are obtained. Furthermore, we performed OCE on seven isolated GSVs. The strain field is obtained by combining the relationship between strain and displacement to obtain the radial elastic modulus of GSVs. In the phantom experiment, the strain of the experimental region of interest is mainly between 0.1 and 0.4, while the simulation result is between 0.06 and 0.40. The radial elastic modulus of GSVs ranged from 3.83 kPa to 7.74 kPa. This study verifies the feasibility of the OCE method for measuring the radial elastic modulus of blood vessels.

Preclinical Three-Dimensional Vibrational Shear Wave Elastography for Mapping of Tumour Biomechanical Properties In Vivo

Preclinical investigation of the biomechanical properties of tissues and their treatment-induced changes are essential to support drug-discovery, clinical translation of biomarkers of treatment response, and studies of mechanobiology. Here we describe the first use of preclinical 3D elastography to map the shear wave speed (cs), which is related to tissue stiffness, in vivo and demonstrate the ability of our novel 3D vibrational shear wave elastography (3D-VSWE) system to detect tumour response to a therapeutic challenge. We investigate the use of one or two vibrational sources at vibrational frequencies of 700, 1000 and 1200 Hz. The within-subject coefficients of variation of our system were found to be excellent for 700 and 1000 Hz and 5.4 and 6.2%, respectively. The relative change in cs measured with our 3D-VSWE upon treatment with an anti-vascular therapy ZD6126 in two tumour xenografts reflected changes in tumour necrosis. U-87 MG drug vs vehicle: Δcs = −24.7 ± 2.5 % vs 7.5 ± 7.1%, (p = 0.002) and MDA-MB-231 drug vs vehicle: Δcs = −12.3 ± 2.7 % vs 4.5 ± 4.7%, (p = 0.02). Our system enables rapid (<5 min were required for a scan length of 15 mm and three vibrational frequencies) 3D mapping of quantitative tumour viscoelastic properties in vivo, allowing exploration of regional heterogeneity within tumours and speedy recovery of animals from anaesthesia so that longitudinal studies (e.g., during tumour growth or following treatment) may be conducted frequently.

In vivo measurement of breast tissues stiffness using a light aspiration device

BACKGROUND

This paper addresses the question of the in vivo measurement of breast tissue stiffness, which has been poorly adressed until now, except for elastography imaging which has shown promising results but which is still difficult for clinicians to use on a day-to-day basis. Estimating subject-specific tissue stiffness is indeed a critical area of research due to the development of a large number of Finite Element (FE) breast models for various medical applications.

METHODS

This paper proposes to use an original aspiration device, put into contact with breast surface, and to estimate tissue stiffness using an inverse analysis of the aspiration experiment. The method assumes that breast tissue is composed of a bilayered structure made of fatty and fribroglandular tissues (lower layer) superimposed with the skin (upper layer). Young moduli of both layers are therefore estimated based on repeating low intensity suction tests (<40 mbar) of breast tissues using cups of 7 different diameters.

FINDINGS

Seven volunteers were involved in this pilot study with average Young moduli of 56.3 kPa  ± 16.4 and 3.04 kPa  ± 1.17 respectively for the skin and the fatty and fibroglandular tissue. The measurements were carried out in a reasonable time scale (<60 min in total) without any discomfort perceived by the participants. These encouraging results should be confirmed in a clinical study that will include a much larger number of volunteers and patients.

Deep neural networks for magnetic resonance elastography acceleration in thermal ablation monitoring

PURPOSE

To develop a deep neural network for accelerating magnetic resonance elastography (MRE) acquisition, to validate the ability to generate reliable MRE results with the down-sampled k-space data, and to demonstrate the feasibility of the proposed method in monitoring the stiffness changes during thermal ablation in a phantom study.

MATERIALS AND METHODS

MRE scans were performed with 60 Hz excitation on porcine ex-vivo liver gel phantoms in a 0.36T MRI scanner to generate the training dataset. The acquisition protocol was based on a spin-echo MRE pulse sequence with tailored motion-sensitive gradients to reduce echo time (TE). A U-Net based deep neural network was developed and trained to interpolate the missing data from down-sampled k-space. We calculated the errors of 80 sets magnitude/phase images reconstructed from the zero-filled, compressive sensing (CS) and deep learning (DL) method for comparison. The peak signal-to-noise rate (PSNR) and structural similarity (SSIM) of the magnitude/phase images were also calculated for comparison. The stiffness changes were recorded before, during, and after ablation. The mean stiffness values over the region of interest (ROI) were compared between the elastograms reconstructed from the fully-sampled k-space and interpolated k-space after thermal ablation.

RESULTS

The mean absolute error (MAE), PSNR, and SSIM of the proposed deep learning approach were significantly better than the results from the zero-filled method (p<0.0001) and CS (p<0.0001). The stiffness changes before and after thermal ablation assessed by the proposed approach (before: 7.7±1.1 kPa, after: 11.9±4.0 kPa, 4.2-kPa increase) gave close agreement with the values calculated from the fully-sampled data (before: 8.0±1.0 kPa, after: 12.6±4.2 kPa, 4.6-kPa increase). In contrast, the stiffness changes computed from the zero-filled method (before: 4.9±1.4 kPa, after: 5.6±2.8 kPa, 0.7-kPa increase) were substantially underestimated.

CONCLUSION

This study demonstrated the capability of the proposed deep learning method for rapid MRE acquisition and provided a promising solution for monitoring the MRI-guided thermal ablation. This article is protected by copyright. All rights reserved.

An electromagnetic actuator for brain magnetic resonance elastography with high frequency accuracy

Our goal is to design, test and verify an electromagnetic actuator for brain magnetic resonance elastography (MRE). We proposed a grappler-shaped design that can transmit stable vibrations into the brain. To validate its performance, simulations were carried out to ensure the electromagnetic field generated by the actuator did not interfere with the B₀ field. The actuation vibration spectrum was analyzed to verify the actuation accuracy. Phantom and volunteer experiments were carried out to evaluate the performance of the actuator. Simulation of the magnetic field showed that the proposed actuator has a fringe field of less than 3 G in the imaging region. The phantom experiments showed that the proposed actuator did not interfere with the routine imaging sequences. The measured vibration spectra demonstrated that the frequency offset was about one third that of a pneumatic device and the transmission efficiency was three times higher. The shear moduli estimated from brain MRE were consistent with those from the literature. The actuation frequency of the proposed actuator has less frequency offset and off-center frequency components compared with the pneumatic counterpart. The whole actuator weighted only 980 g. The actuator can carry out multifrequency MRE on the brain with high accuracy. It is easy to use, comfortable for the patient and portable.

Impact of axisymmetric deformation on MR elastography of a nonlinear tissue-mimicking material and implications in peri-tumour stiffness quantification

Solid tumour growth is often associated with the accumulation of mechanical stresses acting on the surrounding host tissue. Due to tissue nonlinearity, the shear modulus of the peri-tumoural region inherits a signature from the tumour expansion which depends on multiple factors, including the soft tissue constitutive behaviour and its stress/strain state. Shear waves used in MR-elastography (MRE) sense the apparent change in shear modulus along their propagation direction, thereby probing the anisotropic stiffness field around the tumour. We developed an analytical framework for a heterogeneous shear modulus distribution using a thick-shelled sphere approximation of the tumour and soft tissue ensemble. A hyperelastic material (plastisol) was identified to validate the proposed theory in a phantom setting. A balloon-catheter connected to a pressure sensor was used to replicate the stress generated from tumour pressure and growth while MRE data were acquired. The shear modulus anisotropy retrieved from the reconstructed elastography data confirmed the analytically predicted patterns at various levels of inflation. An alternative measure, combining the generated deformation and the local wave direction and independent of the reconstruction strategy, was also proposed to correlate the analytical findings with the stretch probed by the waves. Overall, this work demonstrates that MRE in combination with non-linear mechanics, is able to identify the apparent shear modulus variation arising from the strain generated by a growth within tissue, such as an idealised model of tumour. Investigation in real tissue represents the next step to further investigate the implications of endogenous forces in tissue characterisation through MRE.

Shear wave cardiovascular MR elastography using intrinsic cardiac motion for transducer-free non-invasive evaluation of myocardial shear wave velocity

Changes in myocardial stiffness may represent a valuable biomarker for early tissue injury or adverse remodeling. In this study, we developed and validated a novel transducer-free magnetic resonance elastography (MRE) approach for quantifying myocardial biomechanics using aortic valve closure-induced shear waves. Using motion-sensitized two-dimensional pencil beams, septal shear waves were imaged at high temporal resolution. Shear wave speed was measured using time-of-flight of waves travelling between two pencil beams and corrected for geometrical biases. After validation in phantoms, results from twelve healthy volunteers and five cardiac patients (two left ventricular hypertrophy, two myocardial infarcts, and one without confirmed pathology) were obtained. Torsional shear wave speed in the phantom was 3.0 ± 0.1 m/s, corresponding with reference speeds of 2.8 ± 0.1 m/s. Geometrically-biased flexural shear wave speed was 1.9 ± 0.1 m/s, corresponding with simulation values of 2.0 m/s. Corrected septal shear wave speeds were significantly higher in patients than healthy volunteers [14.1 (11.0-15.8) m/s versus 3.6 (2.7-4.3) m/s, p = 0.001]. The interobserver 95%-limits-of-agreement in healthy volunteers were ± 1.3 m/s and interstudy 95%-limits-of-agreement - 0.7 to 1.2 m/s. In conclusion, myocardial shear wave speed can be measured using aortic valve closure-induced shear waves, with cardiac patients showing significantly higher shear wave speeds than healthy volunteers. This non-invasive measure may provide valuable insights into the pathophysiology of heart failure.

Poroelasticity as a Model of Soft Tissue Structure: Hydraulic Permeability Reconstruction for Magnetic Resonance Elastography in Silico

Magnetic Resonance Elastography allows noninvasive visualization of tissue mechanical properties by measuring the displacements resulting from applied stresses, and fitting a mechanical model. Poroelasticity naturally lends itself to describing tissue - a biphasic medium, consisting of both solid and fluid components. This article reviews the theory of poroelasticity, and shows that the spatial distribution of hydraulic permeability, the ease with which the solid matrix permits the flow of fluid under a pressure gradient, can be faithfully reconstructed without spatial priors in simulated environments. The paper describes an in-house MRE computational platform - a multi-mesh, finite element poroelastic solver coupled to an artificial epistemic agent capable of running Bayesian inference to reconstruct inhomogenous model mechanical property images from measured displacement fields. Building on prior work, the domain of convergence for inference is explored, showing that hydraulic permeabilities over several orders of magnitude can be reconstructed given very little prior knowledge of the true spatial distribution.

MR Elastography of the Breast: Evolution of Technique, Case Examples, and Future Directions

Recognizing that breast cancers present as firm, stiff lesions, the foundation of breast magnetic resonance elastography (MRE) is to combine tissue stiffness parameters with sensitive breast MR contrast-enhanced imaging. Breast MRE is a non-ionizing, cross-sectional MR imaging technique that provides for quantitative viscoelastic properties, including tissue stiffness, elasticity, and viscosity, of breast tissues. Currently, the technique continues to evolve as research surrounding the use of MRE in breast tissue is still developing. In the setting of a newly diagnosed cancer, associated desmoplasia, stiffening of the surrounding stroma, and necrosis are known to be prognostic factors that can add diagnostic information to patient treatment algorithms. In fact, mechanical properties of the tissue might also influence breast cancer risk. For these reasons, exploration of breast MRE has great clinical value. In this review, we will: (1) address the evolution of the various MRE techniques; (2) provide a brief overview of the current clinical studies in breast MRE with interspersed case examples; and (3) suggest directions for future research.

A review on methods for diagnosis of breast cancer cells and tissues

Breast cancer has seriously been threatening physical and mental health of women in the world, and its morbidity and mortality also show clearly upward trend in China over time. Through inquiry, we find that survival rate of patients with early‐stage breast cancer is significantly higher than those with middle‐ and late‐stage breast cancer, hence, it is essential to conduct research to quickly diagnose breast cancer. Until now, many methods for diagnosing breast cancer have been developed, mainly based on imaging and molecular biotechnology examination. These methods have great contributions in screening and confirmation of breast cancer. In this review article, we introduce and elaborate the advances of these methods, and then conclude some gold standard diagnostic methods for certain breast cancer patients. We lastly discuss how to choose the most suitable diagnostic methods for breast cancer patients. In general, this article not only summarizes application and development of these diagnostic methods, but also provides the guidance for researchers who work on diagnosis of breast cancer.

Current and Emerging Magnetic Resonance-Based Techniques for Breast Cancer

Breast cancer is the most commonly diagnosed cancer among women worldwide, and early detection remains a principal factor for improved patient outcomes and reduced mortality. Clinically, magnetic resonance imaging (MRI) techniques are routinely used in determining benign and malignant tumor phenotypes and for monitoring treatment outcomes. Static MRI techniques enable superior structural contrast between adipose and fibroglandular tissues, while dynamic MRI techniques can elucidate functional characteristics of malignant tumors. The preferred clinical procedure-dynamic contrast-enhanced MRI-illuminates the hypervascularity of breast tumors through a gadolinium-based contrast agent; however, accumulation of the potentially toxic contrast agent remains a major limitation of the technique, propelling MRI research toward finding an alternative, noninvasive method. Three such techniques are magnetic resonance spectroscopy, chemical exchange saturation transfer, and non-contrast diffusion weighted imaging. These methods shed light on underlying chemical composition, provide snapshots of tissue metabolism, and more pronouncedly characterize microstructural heterogeneity. This review article outlines the present state of clinical MRI for breast cancer and examines several research techniques that demonstrate capacity for clinical translation. Ultimately, multi-parametric MRI-incorporating one or more of these emerging methods-presently holds the best potential to afford improved specificity and deliver excellent accuracy to clinics for the prediction, detection, and monitoring of breast cancer.

A review of various modalities in breast imaging: technical aspects and clinical outcomes

Background

Nowadays, breast cancer is the second cause of death after cardiovascular diseases. In general, about one out of eight women (about 12%) suffer from this disease during their life in the USA and European countries. If breast cancer is detected at an early stage, its survival rate will be very high. Several methods have been introduced to diagnose breast cancer with their clinical advantages and disadvantages.

Main text

In this review, various methods of breast imaging have been introduced. Furthermore, the sensitivity and specificity of each of these methods have been investigated. For each of the imaging methods, articles that were relevant to the past 10 years were selected through electronic search engines, and then the most relevant papers were selected. Finally, about 40 articles were studied and their results were categorized and presented in the form of a report as follows. Various breast cancer imaging techniques were extracted as follows: mammography, contrast-enhanced mammography, digital tomosynthesis, sonography, sonoelastography, magnetic resonance imaging, magnetic elastography, diffusion-weighted imaging, magnetic spectroscopy, nuclear medicine, optical imaging, and microwave imaging.

Conclusion

The choice of these methods depends on the patient’s state and stage, the age of the individual and the density of the breast tissue. Hybrid imaging techniques appear to be an acceptable way to improve detection of breast cancer. This review article can be useful in choosing the right method for imaging in people suspected of breast cancer.

Imaging brain function with simultaneous BOLD and viscoelasticity contrast: fMRI/fMRE

Magnetic resonance elastography (MRE) is emerging as a new tool for studying viscoelastic changes in the brain resulting from functional processes. Here, we demonstrate a novel time series method to generate robust functional magnetic resonance elastography (fMRE) activation maps in response to a visual task with a flashing checkerboard stimulus. Using a single-shot spin-echo (SS-SE) pulse sequence, the underlying raw images inherently contain blood-oxygen-level dependent (BOLD) contrast, allowing simultaneous generation of functional magnetic resonance imaging (fMRI) activation maps from the magnitude and functional magnetic resonance elastography (fMRE) maps from the phase. This allows an accurate comparison of the spatially localized stiffness (fMRE) and BOLD (fMRI) changes within a single scan, eliminating confounds inherent in separately acquired scans. Results indicate that tissue stiffness within the visual cortex increases 6-11% with visual stimuli, whereas the BOLD signal change was 1-2%. Furthermore, the fMRE and fMRI activation maps have strong spatial overlap within the visual cortex, providing convincing evidence that fMRE is possible in the brain. However, the fMRE temporal SNR (tSNR_fMRE) maps are heterogeneous across the brain. Using a dictionary matching approach to characterize the time series, the viscoelastic changes are consistent with a viscoelastic response function (VRF) time constant of 12.1 ​s ± 3.0 ​s for a first-order exponential decay, or a shape parameter of 8.1 ​s ± 1.4 ​s for a gamma-variate.

Investigating the Contribution of Collagen to the Tumor Biomechanical Phenotype with Noninvasive Magnetic Resonance Elastography

Increased stiffness in the extracellular matrix (ECM) contributes to tumor progression and metastasis. Therefore, stromal modulating therapies and accompanying biomarkers are being developed to target ECM stiffness. Magnetic resonance (MR) elastography can noninvasively and quantitatively map the viscoelastic properties of tumors in vivo and thus has clear clinical applications. Herein, we used MR elastography, coupled with computational histopathology, to interrogate the contribution of collagen to the tumor biomechanical phenotype and to evaluate its sensitivity to collagenase-induced stromal modulation. Elasticity (G d) and viscosity (G l) were significantly greater for orthotopic BT-474 (G d = 5.9 ± 0.2 kPa, G l = 4.7 ± 0.2 kPa, n = 7) and luc-MDA-MB-231-LM2-4 (G d = 7.9 ± 0.4 kPa, G l = 6.0 ± 0.2 kPa, n = 6) breast cancer xenografts, and luc-PANC1 (G d = 6.9 ± 0.3 kPa, G l = 6.2 ± 0.2 kPa, n = 7) pancreatic cancer xenografts, compared with tumors associated with the nervous system, including GTML/Trp53KI/KI medulloblastoma (G d = 3.5 ± 0.2 kPa, G l = 2.3 ± 0.2 kPa, n = 7), orthotopic luc-D-212-MG (G d = 3.5 ± 0.2 kPa, G l = 2.3 ± 0.2 kPa, n = 7), luc-RG2 (G d = 3.5 ± 0.2 kPa, G l = 2.3 ± 0.2 kPa, n = 5), and luc-U-87-MG (G d = 3.5 ± 0.2 kPa, G l = 2.3 ± 0.2 kPa, n = 8) glioblastoma xenografts, intracranially propagated luc-MDA-MB-231-LM2-4 (G d = 3.7 ± 0.2 kPa, G l = 2.2 ± 0.1 kPa, n = 7) breast cancer xenografts, and Th-MYCN neuroblastomas (G d = 3.5 ± 0.2 kPa, G l = 2.3 ± 0.2 kPa, n = 5). Positive correlations between both elasticity (r = 0.72, P < 0.0001) and viscosity (r = 0.78, P < 0.0001) were determined with collagen fraction, but not with cellular or vascular density. Treatment with collagenase significantly reduced G d (P = 0.002) and G l (P = 0.0006) in orthotopic breast tumors. Texture analysis of extracted images of picrosirius red staining revealed significant negative correlations of entropy with G d (r = -0.69, P < 0.0001) and G l (r = -0.76, P < 0.0001), and positive correlations of fractal dimension with G d (r = 0.75, P < 0.0001) and G l (r = 0.78, P < 0.0001). MR elastography can thus provide sensitive imaging biomarkers of tumor collagen deposition and its therapeutic modulation. SIGNIFICANCE: MR elastography enables noninvasive detection of tumor stiffness and will aid in the development of ECM-targeting therapies.

Application of in vivo MR methods in the study of breast cancer metabolism

In the last two decades, various in vivo MR methodologies have been evaluated for their potential in the study of cancer metabolism. During malignant transformation, metabolic alterations occur, leading to morphological and functional changes. Among various MR methods, in vivo MRS has been extensively used in breast cancer to study the metabolism of cells, tissues or whole organs. It provides biochemical information at the metabolite level. Altered choline, phospholipid and energy metabolism has been documented using proton (¹ H), phosphorus (³¹ P) and carbon (¹³ C) isotopes. Increased levels of choline-containing compounds, phosphomonoesters and phosphodiesters in breast cancer, which are indicative of altered choline and phospholipid metabolism, have been reported using in vivo, in vitro and ex vivo NMR studies. These changes are reversed on successful therapy, which depends on the treatment regimen given. Monitoring the various tumor intermediary metabolic pathways using nuclear spin hyperpolarization of ¹³ C-labeled substrates by dynamic nuclear polarization has also been recently reported. Furthermore, the utility of various methods such as diffusion, dynamic contrast and perfusion MRI have also been evaluated to study breast tumor metabolism. Parameters such as tumor volume, apparent diffusion coefficient, volume transfer coefficient and extracellular volume ratio are estimated. These parameters provide information on the changes in tumor microstructure, microenvironment, abnormal vasculature, permeability and grade of the tumor. Such changes seen during cancer progression are due to alterations in the tumor metabolism, leading to changes in cell architecture. Due to architectural changes, the tissue mechanical properties are altered; this can be studied using magnetic resonance elastography, which measures the elastic properties of tissues. Moreover, these structural MRI methods can be used to investigate the effect of therapy-induced changes in tumor characteristics. This review discusses the potential of various in vivo MR methodologies in the study of breast cancer metabolism.