A biomechanical breast model evaluated with respect to MRI data collected in three different positions

Kirchhoff's law-based velocity-controlled motion models to predict real-time cutting forces in minimally invasive surgeries

A theoretical framework, united by a "system effect" is formulated to model the cutting/haptic force evolution at the cutting edge of a surgical cutting instrument during its penetration into soft biological tissue in minimally invasive surgery. Other cutting process responses, including tissue fracture force, friction force, and damping, are predicted by the model as well. The model is based on a velocity-controlled formulation of the corresponding equations of motion, derived for a surgical cutting instrument and tissue based on Kirchhoff's fundamental energy conservation law. It provides nearly zero residues (absolute errors) in the equations of motion balances. In addition, concurrent closing relationships for the fracture force, friction coefficient, friction force, process damping, strain rate function (a constitutive tissue model), and their implementation within the proposed theoretical framework are established. The advantage of the method is its ability to make precise real-time predictions of the aperiodic fluctuating evolutions of the cutting forces and the other process responses. It allows for the robust modeling of the interactions between a medical instrument and a nonlinear viscoelastic tissue under any physically feasible working conditions. The cutting process model was partially qualitatively verified through numerical simulations and by comparing the computed cutting forces with experimentally measured values during robotic uniaxial biopsy needle constant velocity insertion into artificial gel tissue, obtained from previous experimental research. The comparison has shown a qualitatively similar adequate trend in the evolution of the experimentally measured and numerically predicted cutting forces during insertion of the needle.

Construction of multi-component finite element model to predict biomechanical behaviour of breasts during running and quantification of the stiffness impact of internal structure

This study aims to investigate the biomechanical behaviour and the stiffness impact of the breast internal components during running. To achieve this, a novel nonlinear multi-component dynamic finite element method (FEM) has been established, which uses experimental data obtained via 4D scanning technology and a motion capture system. The data are used to construct a geometric model that comprises the rigid body, layers of soft tissues, skin, pectoralis major muscle, fat, ligaments and glandular tissues. The traditional point-to-point method has a relative mean absolute error of less than 7.92% while the latest surface-to-surface method has an average Euclidean distance (d) of 7.05 mm, validating the simulated results. After simulating the motion of the different components of the breasts, the displacement analysis confirms that when the motion reaches the moment of largest displacement, the displacement of the breast components is proportional to their distance from the chest wall. A biomechanical analysis indicates that the stress sustained by the breast components in ascending order is the glandular tissues, pectoralis major muscle, adipose tissues, and ligaments. The ligaments provide the primary support during motion, followed by the pectoralis major muscle. In addition, specific stress points of the breast components are identified. The stiffness impact experiment indicates that compared with ligaments, the change of glandular tissue stiffness had a slightly more obvious effect on the breast surface. The findings serve as a valuable reference for the medical field and sports bra industry to enhance breast protection during motion.

Evaluation of breast skin and tissue stiffness using a non-invasive aspiration device and impact of clinical predictors

A personalized 3D breast model could present a real benefit for preoperative discussion with patients, surgical planning, and guidance. Breast tissue biomechanical properties have been poorly studied in vivo, although they are important for breast deformation simulation. The main objective of our study was to determine breast skin thickness and breast skin and adipose/fibroglandular tissue stiffness. The secondary objective was to assess clinical predictors of elasticity and thickness: age, smoking status, body mass index, contraception, pregnancies, breastfeeding, menopausal status, history of radiotherapy or breast surgery. Participants were included at the Montpellier University Breast Surgery Department from March to May 2022. Breast skin thickness was measured by ultrasonography, breast skin and adipose/fibroglandular tissue stiffnesses were determined with a VLASTIC non-invasive aspiration device at three different sites (breast segments I-III). Multivariable linear models were used to assess clinical predictors of elasticity and thickness. In this cohort of 196 women, the mean breast skin and adipose/fibroglandular tissue stiffness values were 39 and 3 kPa, respectively. The mean breast skin thickness was 1.83 mm. Only menopausal status was significantly correlated with breast skin thickness and adipose/fibroglandular tissue stiffness. The next step will be to implement these stiffness and thickness values in a biomechanical breast model and to evaluate its capacity to predict breast tissue deformations.

Testing Mechanical Properties of Silicone Gel-Filled Breast Implants and Their Degradation

Breast augmentation procedures using silicone implants have become increasingly popular over the past six decades. This article addresses the concerns of patients regarding implant strength by providing clinicians with valuable information in addition to video and pictorial evidence to share, fostering reassurance. The article focuses on the structural integrity and stability of breast implants, which play a critical role in their long-term performance and patient satisfaction. Specifically, it examines the industry standards outlined by the International Organization for Standardization (ISO), with a particular emphasis on ISO14607-2018, which encompasses a range of mechanical and physio-mechanical tests, including the assessment of silicone gel-fill firmness, evaluation of shell integrity, and examination of the impact of environmental conditions on implant performance. Breast implants are not static devices and are subject to aging and fatigue-based degradation. This emphasizes the need for ongoing monitoring and evaluation to ensure the long-term safety and satisfaction of patients. By providing a comprehensive examination of breast implant structure and industry standards, this article equips clinicians with the necessary knowledge to address patient concerns and foster confidence in the safety and longevity of breast augmentation procedures using silicone implants.Level of Evidence III This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Quantifying changes in shoulder orientation between the prone and supine positions from magnetic resonance imaging

BACKGROUND

Predicting breast tissue motion using biomechanical models can provide navigational guidance during breast cancer treatment procedures. These models typically do not account for changes in posture between procedures. Difference in shoulder position can alter the shape of the pectoral muscles and breast. A greater understanding of the differences in the shoulder orientation between prone and supine could improve the accuracy of breast biomechanical models.

METHODS

19 landmarks were placed on the sternum, clavicle, scapula, and humerus of the shoulder girdle in prone and supine breast MRIs (N = 10). These landmarks were used in an optimization framework to fit subject-specific skeletal models and compare joint angles of the shoulder girdle between these positions.

FINDINGS

The mean Euclidean distance between joint locations from the fitted skeletal model and the manually identified joint locations was 15.7 mm ± 2.7 mm. Significant differences were observed between prone and supine. Compared to supine position, the shoulder girdle in the prone position had the lateral end of the clavicle in more anterior translation (i.e., scapula more protracted) (P < 0.05), the scapula in more protraction (P < 0.01), the scapula in more upward rotation (associated with humerus elevation) (P < 0.05); and the humerus more elevated (P < 0.05) for both the left and right sides.

INTERPRETATION

Shoulder girdle orientation was found to be different between prone and supine. These differences would affect the shape of multiple pectoral muscles, which would affect breast shape and the accuracy of biomechanical models.

Breast simulation pipeline: From medical imaging to patient-specific simulations

BACKGROUND

Breast-conserving surgery is the most acceptable operation for breast cancer removal from an invasive and psychological point of view. Before the surgical procedure, a preoperative MRI is performed in the prone configuration, while the surgery is achieved in the supine position. This leads to a considerable movement of the breast, including the tumor, between the two poses, complicating the surgeon's task.

METHODS

In this work, a simulation pipeline allowing the computation of patient-specific geometry and the prediction of personalized breast material properties was put forward. Through image segmentation, a finite element model including the subject-specific geometry is established. By first computing an undeformed state of the breast, the geometrico-material model is calibrated by surface acquisition in the intra-operative stance.

FINDINGS

Using an elastic corotational formulation, the patient-specific mechanical properties of the breast and skin were identified to obtain the best estimates of the supine configuration. The final results are a shape-fitting closest point residual of 4.00 mm for the mechanical parameters Ebreast=0.32 kPa and Eskin=22.72 kPa, congruent with the current state-of-the-art. The Covariance Matrix Adaptation Evolution Strategy optimizer converges on average between 5 to 30 min depending on the initial parameters, reaching a simulation speed of 20 s. To our knowledge, our model offers one of the best compromises between accuracy and speed.

INTERPRETATION

Satisfactory results were obtained for the estimation of breast deformation from preoperative to intra-operative configuration. Furthermore, we have demonstrated the clinical feasibility of such applications using a simulation framework that aims at the smallest disturbance of the actual surgical pipeline.

Incorporating heterogeneity and anisotropy for surgical applications in breast deformation modeling

BACKGROUND

Simulating soft-tissue breast deformations is of interest for many applications including image fusion, longitudinal registration, and image-guided surgery. For the surgical use case, positional changes cause breast deformations that compromise the use of preoperative imaging to inform tumor excision. Even when acquiring imaging in the supine position, which better reflects surgical presentation, deformations still occur due to arm motion and orientation changes. A biomechanical modeling approach to simulate supine breast deformations for surgical applications must be both accurate and compatible with the clinical workflow.

METHODS

A supine MR breast imaging dataset from n = 11 healthy volunteers was used to simulate surgical deformations by acquiring images in arm-down and arm-up positions. Three linear-elastic modeling approaches with varying levels of complexity were used to predict deformations caused by this arm motion: a homogeneous isotropic model, a heterogeneous isotropic model, and a heterogeneous anisotropic model using a transverse-isotropic constitutive model.

FINDINGS

The average target registration errors for subsurface anatomical features were 5.4 ± 1.5 mm for the homogeneous isotropic model, 5.3 ± 1.5 mm for the heterogeneous isotropic model, and 4.7 ± 1.4 mm for the heterogeneous anisotropic model. A statistically significant improvement in target registration error was observed between the heterogeneous anisotropic model and both the homogeneous and the heterogeneous isotropic models (P < 0.01).

INTERPRETATION

While a model that fully incorporates all constitutive complexities of anatomical structure likely achieves the best accuracy, a computationally tractable heterogeneous anisotropic model provided significant improvement and may be applicable for image-guided breast surgeries.

Digital Volume Correlation for large deformations of soft tissues: Pipeline and proof of concept for the application to breast ex vivo deformations

Being able to reposition tumors from prone imaging to supine surgery stances is key for bypassing current invasive marking used for conservative breast surgery. This study aims to demonstrate the feasibility of using Digital Volume Correlation (DVC) to measure the deformation of a female quarter thorax between two different body positioning when subjected to gravity. A segmented multipart mesh (bones, cartilage and tissue) was constructed and a three-step FE-based DVC procedure with heterogeneous elastic regularization was implemented. With the proposed framework, the large displacement field of a hard/soft breast sample was recovered with low registration residuals and small error between the measured and manually determined deformations of phase interfaces. The present study showed the capacity of FE-based DVC to faithfully capture large deformations of hard/soft tissues.

Soft-tissue simulation of the breast for intraoperative navigation and fusion of preoperative planning

Computational preoperative planning offers the opportunity to reduce surgery time and patient risk. However, on soft tissues such as the breast, deviations between the preoperative and intraoperative settings largely limit the applicability of preoperative planning. In this work, we propose a high-performance accurate simulation model of the breast, to fuse preoperative information with the intraoperative deformation setting. Our simulation method encompasses three major elements: high-quality finite-element modeling (FEM), efficient handling of anatomical couplings for high-performance computation, and personalized parameter estimation from surface scans. We show the applicability of our method on two problems: 1) transforming high-quality preoperative scans to the intraoperative setting for fusion of preoperative planning data, and 2) real-time tracking of breast tumors for navigation during intraoperative radiotherapy. We have validated our methodology on a test cohort of nine patients who underwent tumor resection surgery and intraoperative radiotherapy, and we have quantitatively compared simulation results to intraoperative scans. The accuracy of our simulation results suggest clinical viability of the proposed methodology.

Experimental characterisation and modelling of breast Cooper's ligaments

The aim of this study was to characterise the mechanical behaviour of Cooper's ligaments. Such ligaments are collagenous breast tissue that create a three-dimensional structure over the entire breast volume. Ten ligaments were extracted from a human cadaver, from which 28 samples were cut and used to perform uniaxial tensile tests. Histological analysis showed that the main direction of the fibres visible to the naked eye corresponds to the orientation of the fibres on a microscopic scale. The specimens were cut according to this orientation, which allowed the sample to be stretched in the main fibre direction. From these experimental stretch/stress curves, an original anisotropic hyperelastic constitutive law is proposed to model the behaviour of Cooper's ligaments and the material parameter validity is discussed.

Breast Biomechanics: What Do We Really Know?

Although half the world's population will develop breasts, there is limited research documenting breast structure or motion. Understanding breast structure and motion, however, is imperative for numerous applications, such as breast reconstruction, breast modeling to better diagnose and treat breast pathologies, and designing effective sports bras. To be impactful, future breast biomechanics research needs to fill gaps in our knowledge, particularly related to breast composition and density, and to improve methods to accurately measure the complexities of three-dimensional breast motion. These methods should then be used to investigate breast biomechanics while individuals, who represent the full spectrum of women in the population, participate in a broad range of activities of daily living and recreation.

Biomechanics of Breast Support for Active Women

More systematic breast biomechanics research and better translation of the research outcomes are necessary to provide information upon which to design better sports bras and to develop effective evidence-based strategies to alleviate exercise-induced breast pain for women who want to participate in physical activity in comfort.

Distinct phenotypes of cancer cells on tissue matrix gel

BACKGROUND

Breast cancer cells invading the connective tissues outside the mammary lobule or duct immerse in a reservoir of extracellular matrix (ECM) that is structurally and biochemically distinct from that of their site of origin. The ECM is a spatial network of matrix proteins, which not only provide physical support but also serve as bioactive ligands to the cells. It becomes evident that the dimensional, mechanical, structural, and biochemical properties of ECM are all essential mediators of many cellular functions. To better understand breast cancer development and cancer cell biology in native tissue environment, various tissue-mimicking culture models such as hydrogel have been developed. Collagen I (Col I) and Matrigel are the most common hydrogels used in cancer research and have opened opportunities for addressing biological questions beyond the two-dimensional (2D) cell cultures. Yet, it remains unclear whether these broadly used hydrogels can recapitulate the environmental properties of tissue ECM, and whether breast cancer cells grown on CoI I or Matrigel display similar phenotypes as they would on their native ECM.

METHODS

We investigated mammary epithelial cell phenotypes and metabolic profiles on animal breast ECM-derived tissue matrix gel (TMG), Col I, and Matrigel. Atomic force microscopy (AFM), fluorescence microscopy, acini formation assay, differentiation experiments, spatial migration/invasion assays, proliferation assay, and nuclear magnetic resonance (NMR) spectroscopy were used to examine biological phenotypes and metabolic changes. Student's t test was applied for statistical analyses.

RESULTS

Our data showed that under a similar physiological stiffness, the three types of hydrogels exhibited distinct microstructures. Breast cancer cells grown on TMG displayed quite different morphologies, surface receptor expression, differentiation status, migration and invasion, and metabolic profiles compared to those cultured on Col I and Matrigel. Depleting lactate produced by glycolytic metabolism of cancer cells abolished the cell proliferation promoted by the non-tissue-specific hydrogel.

CONCLUSION

The full ECM protein-based hydrogel system may serve as a biologically relevant model system to study tissue- and disease-specific pathological questions. This work provides insights into tissue matrix regulation of cancer cell biomarker expression and identification of novel therapeutic targets for the treatment of human cancers based on tissue-specific disease modeling.

The Paper Mache Bra: A Postsurgical Breast Taping Technique

Little has been published about dressing the breast after surgery and the potential benefits of added support to the routine use of a nonwired bra postoperatively. We report a postsurgical breast taping method and suggest its use might help reduce minor postsurgical complications and subsequent impaired scarring.

An automated computational biomechanics workflow for improving breast cancer diagnosis and treatment

Clinicians face many challenges when diagnosing and treating breast cancer. These challenges include interpreting and co-locating information between different medical imaging modalities that are used to identify tumours and predicting where these tumours move to during different treatment procedures. We have developed a novel automated breast image analysis workflow that integrates state-of-the-art image processing and machine learning techniques, personalized three-dimensional biomechanical modelling and population-based statistical analysis to assist clinicians during breast cancer detection and treatment procedures. This paper summarizes our recent research to address the various technical and implementation challenges associated with creating a fully automated system. The workflow is applied to predict the repositioning of tumours from the prone position, where diagnostic magnetic resonance imaging is performed, to the supine position where treatment procedures are performed. We discuss our recent advances towards addressing challenges in identifying the mechanical properties of the breast and evaluating the accuracy of the biomechanical models. We also describe our progress in implementing a prototype of this workflow in clinical practice. Clinical adoption of these state-of-the-art modelling techniques has significant potential for reducing the number of misdiagnosed breast cancers, while also helping to improve the treatment of patients.