Cells within tissues are continuously exposed to physical forces including hydrostatic pressure, shear stress, and compression and tension forces. Cells dynamically adapt to force by modifying their behaviour and remodelling their microenvironment. They also sense these forces through mechanoreceptors and respond by exerting reciprocal actomyosin- and cytoskeletal-dependent cell-generated force by a process termed 'mechanoreciprocity'. Loss of mechanoreciprocity has been shown to promote the progression of disease, including cancer. Moreover, the mechanical properties of a tissue contribute to disease progression, compromise treatment and might also alter cancer risk. Thus, the changing force that cells experience needs to be considered when trying to understand the complex nature of tumorigenesis.

/pdf/a-tense-situation-forcing-tumour-progression-4myf9i89al.pdf

A Tense Situation: Forcing Tumour Progression

Deformable image registration is a fundamental task in medical image processing. Among its most important applications, one may cite: 1) multi-modality fusion, where information acquired by different imaging devices or protocols is fused to facilitate diagnosis and treatment planning; 2) longitudinal studies, where temporal structural or anatomical changes are investigated; and 3) population modeling and statistical atlases used to study normal anatomical variability. In this paper, we attempt to give an overview of deformable registration methods, putting emphasis on the most recent advances in the domain. Additional emphasis has been given to techniques applied to medical images. In order to study image registration methods in depth, their main components are identified and studied independently. The most recent techniques are presented in a systematic fashion. The contribution of this paper is to provide an extensive account of registration techniques in a systematic manner.

/pdf/deformable-medical-image-registration-a-survey-2uee59wp1z.pdf

Deformable Medical Image Registration: A Survey

Applied Numerical Analysis. By C.F. Gerald. Pp. xii, 340. £3·60. 1970. (Addison-Wesley.)

Magnetic resonance elastography: Non-invasive mapping of tissue elasticity

Tumors are stiff and data suggest that the extracellular matrix stiffening that correlates with experimental mammary malignancy drives tumor invasion and metastasis. Nevertheless, the relationship between tissue and extracellular matrix stiffness and human breast cancer progression and aggression remains unclear. We undertook a biophysical and biochemical assessment of stromal–epithelial interactions in noninvasive, invasive and normal adjacent human breast tissue and in breast cancers of increasingly aggressive subtype. Our analysis revealed that human breast cancer transformation is accompanied by an incremental increase in collagen deposition and a progressive linearization and thickening of interstitial collagen. The linearization of collagen was visualized as an overall increase in tissue birefringence and was most striking at the invasive front of the tumor where the stiffness of the stroma and cellular mechanosignaling were the highest. Amongst breast cancer subtypes we found that the stroma at the invasive region of the more aggressive Basal-like and Her2 tumor subtypes was the most heterogeneous and the stiffest when compared to the less aggressive luminal A and B subtypes. Intriguingly, we quantified the greatest number of infiltrating macrophages and the highest level of TGF beta signaling within the cells at the invasive front. We also established that stroma stiffness and the level of cellular TGF beta signaling positively correlated with each other and with the number of infiltrating tumor-activated macrophages, which was highest in the more aggressive tumor subtypes. These findings indicate that human breast cancer progression and aggression, collagen linearization and stromal stiffening are linked and implicate tissue inflammation and TGF beta.

/pdf/human-breast-cancer-invasion-and-aggression-correlates-with-34trfn6aqu.pdf

Human Breast Cancer Invasion and Aggression Correlates with ECM Stiffening and Immune Cell Infiltration

A quasistatic magnetic resonance elastography (MRE) method for the evaluation of breast cancer is proposed. Using a phase contrast, stimulated echo MRI approach, strain imaging in phantoms and volunteers is presented. First-order assessment of tissue biomechanical properties based on inverse strain mapping is outlined and demonstrated. The accuracy of inverse strain imaging is studied through simulations in a two-dimensional model and in an anthropomorphic, three-dimensional finite-element model of the breast. To improve the accuracy of modulus assessment by elastography, inverse methods are discussed as an extension to strain imaging, and simulations quantify MRE in terms of displacement signal/noise required for robust inversion. A direct inversion strategy providing information on tissue modulus and pressure distribution is described along with a novel iterative method utilizing a priori knowledge of tissue geometry. It is shown that through the judicious choice of information from previous contrast-enhanced MRI breast images, MRE data acquisition requirements can be significantly reduced while maintaining robust modulus reconstruction in the presence of strain noise. An experimental apparatus for clinical breast MRE and preliminary images of a normal volunteer are presented.

https://iopscience.iop.org/article/10.1088/0031-9155/45/6/314/pdf

Visualization and quantification of breast cancer biomechanical properties with magnetic resonance elastography.

Over the past decade, several methods have been proposed to image tissue elasticity based on imaging methods collectively called elastography. While progress in developing these systems has been rapid, the basic understanding of tissue properties to interpret elastography images is generally lacking. To address this limitation, we developed a system to measure the Young's modulus of small soft tissue specimens. This system was designed to accommodate biological soft tissue constraints such as sample size, geometry imperfection and heterogeneity. The measurement technique consists of indenting an unconfined small block of tissue while measuring the resulting force. We show that the measured force-displacement slope of such a geometry can be transformed to the tissue Young's modulus via a conversion factor related to the sample's geometry and boundary conditions using finite element analysis. We also demonstrate another measurement technique for tissue elasticity based on quasi-static magnetic resonance elastography in which a tissue specimen encased in a gelatine-agarose block undergoes cyclical compression with resulting displacements measured using a phase contrast MRI technique. The tissue Young's modulus is then reconstructed from the measured displacements using an inversion technique. Finally, preliminary elasticity measurement results of various breast tissues are presented and discussed.

https://iopscience.iop.org/article/10.1088/0031-9155/48/14/310/pdf

Measuring the elastic modulus of ex vivo small tissue samples

Breast tissue deformation modeling has recently gained considerable interest in various medical applications. A biomechanical model of the breast is presented using a finite element (FE) formulation. Emphasis is given to the modeling of breast tissue deformation which takes place in breast imaging procedures. The first step in implementing the FE modeling (FEM) procedure is mesh generation. For objects with irregular and complex geometries such as the breast, this step is one of the most difficult and tedious tasks. For FE mesh generation, two automated methods are presented which process MRI breast images to create a patient-specific mesh. The main components of the breast are adipose, fibroglandular and skin tissues. For modeling the adipose and fibroglandular tissues, we used eight noded hexahedral elements with hyperelastic properties, while for the skin, we chose four noded hyperelastic membrane elements. For model validation, an MR image of an agarose phantom was acquired and corresponding FE meshes were created. Based on assigned elasticity parameters, a numerical experiment was performed using the FE meshes, and good results were obtained. The model was also applied to a breast image registration problem of a volunteer's breast. Although qualitatively reasonable, further work is required to validate the results quantitatively.

Biomechanical 3-D finite element modeling of the human breast using MRI data

The propagation of shear waves in ex vivo tissue samples, agar/gel phantoms, and human volunteers was investigated. A moving coil apparatus was constructed to generate low acoustic frequency shear perturbations of 50 to 400 Hz. Oscillating gradients phase-locked with the shear stimulus were used to generate a series of phase contrast images of the shear waves at different time-points throughout the wave cycle. Quantitative measurements of wave velocity and attenuation were obtained to evaluate the effects of temperature, frequency, and tissue anisotropy. Results of these experiments demonstrate significant variation in shear wave behavior with tissue type, whereas frequency and anisotropic behavior was mixed. Temperature-dependent behavior related mainly to the presence of fat. Propagation velocities ranged from 1 to 5 m/sec, and attenuation coefficients of from 1 to 3 nepers/unit wavelength, depending on tissue type. These results confirm the potential of elastic imaging attributable to the intrinsic variability of elastic properties observed in normal tissue, although some difficulty may be experienced in clinical implementation because of viscous attenuation in fat.

Magnetic resonance imaging of shear wave propagation in excised tissue.

A reconstruction technique for breast tissue elasticity modulus is described. This technique assumes that the geometry of normal and suspicious tissues is available from a contrast-enhanced magnetic resonance image. Furthermore, it is assumed that the modulus is constant throughout each tissue volume. The technique, which uses quasi-static strain data, is iterative where each iteration involves modulus updating followed by stress calculation. Breast mechanical stimulation is assumed to be done by two compressional rigid plates. As a result, stress is calculated using the finite element method based on the well-controlled boundary conditions of the compression plates. Using the calculated stress and the measured strain, modulus updating is done element-by-element based on Hooke's law. Breast tissue modulus reconstruction using simulated data and phantom modulus reconstruction using experimental data indicate that the technique is robust.

Jonathan Bishop

Papers

Visualization and quantification of breast cancer biomechanical properties with magnetic resonance elastography.

Measuring the elastic modulus of ex vivo small tissue samples

Biomechanical 3-D finite element modeling of the human breast using MRI data

Magnetic resonance imaging of shear wave propagation in excised tissue.

A constrained modulus reconstruction technique for breast cancer assessment