12 research outputs found

    BREAST BIOMECANICAL MODELING FOR COMPRESSION OPTIMIZATION IN DIGITAL BREAST TOMOSYNTHESIS

    No full text
    International audienceMammography is a specific type of breast imaging that uses low-dose X-rays to detect cancer in early stage. During the exam, the women breast is compressed between two plates until a nearly uniform breast thickness is obtained. This technique improves image quality and reduces dose but can also be the source of discomfort and sometimes pain for the patient. Therefore, alternative techniques allowing reduced breast compression is of potential interest. The aim of this work is to develop a 3D biomechanical Finite Element (FE) breast model in order to analyze various breast compression strategies and their impact on image quality and radiation dose. Large breast deformations are simulated using this FE model with ANSYS software. A particular attention is granted to the computation of the residual stress in the model due to gravity and boundary conditions (thorax anatomy, position of the patient inside the MRI machine). Previously developed biomechanical breast models use a simplified breast anatomy by modeling adipose and fibroglandular tissues only (Rajagopal et al. in Wiley Interdiscip Rev: Syst Biol Med 2:293–304, 2010). However, breast reconstruction surgery has proven the importance of suspensory ligaments and breast fasciae on breast mechanics (Lockwood in Plast Reconstr Surg 103:1411–1420, 1999). We are therefore consider using a more realistic breast anatomy by including skin, muscles, and suspensory ligaments. The breast tissues are modeled as neo-Hookean materials. A physical correct modeling of the breast requires the knowledge of the stress-free breast configuration. Here, this undeformed shape (i.e., without any residual stress) is computed using the prediction–correction iterative scheme proposed by Eiben et al. (Ann of Biomed Eng 44:154–173, 2016). The unloading procedure uses the breast configuration in prone and supine position in order to find a unique displacement vector field induced by gravitational forces. The 3D breast geometry is reconstructed from MRI images that are segmented (Yushkevich et al. in Neuroimage 31:1116–1128, 2006) to differentiate the four main tissue types. The breast volume is discretized with a hexa-dominant FE meshing tool as a unique volume. Finally, the model is evaluated by comparing the estimated breast deformations under gravity load with the experimental ones measured in three body positions: prone, supine, and oblique supine

    BREAST BIOMECANICAL MODELING FOR COMPRESSION OPTIMIZATION IN DIGITAL BREAST TOMOSYNTHESIS

    No full text
    International audienceThe aim of this work is to develop a biomechanical Finite Element (FE) breast model in order to analyze different breast compression strategies and their impact on image quality. Large breast deformations will be simulated using this FE model. A particular attention will be granted to the computation of the initial stress in the model due to gravity and to boundary conditions imposed by the thorax anatomy. Finally, the model will be validated by comparing the estimated breast deformations under gravity load with the experimental ones measured in three body positions: prone, supine and oblique supine

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

    No full text
    International audienceBackground: Mammography is a specific type of breast imaging that uses low-dose X-rays to detect cancer in early stage. During the exam, the women breast is compressed between two plates in order to even out the breast thickness and to spread out the soft tissues. This technique improves exam quality but can be uncomfortable for the patient. The perceived discomfort can be assessed by the means of a breast biomechanical model. Alternative breast compression techniques may be computationally investigated trough finite elements simulations.Methods: The aim of this work is to develop and evaluate a new biomechanical Finite Element (FE) breast model. The complex breast anatomy is considered including adipose and glandular tissues, muscle, skin, suspensory ligaments and pectoral fascias. Material hyper-elasticity is modeled using the Neo-Hookean material models. The stress-free breast geometry and subject-specific constitutive models are derived using tissues deformations measurements from MR images.Findings: The breast geometry in three breast configurations were computed using the breast stress-free geometry together with the estimated set of equivalent Young's modulus (Ebreast_r=0.3 kPa, Ebreast_l=0.2 kPa, Eskin=4 kPa, Efascia=120 kPa). The Hausdorff distance between estimated and measured breast geometries for prone, supine and supine tilted configurations is equal to 2.17 mm, 1.72mm and 5.90mm respectively.Interpretation: A subject-specific breast model allows a better characterization of breast mechanics. However, the model presents some limitations when estimating the supine tilted breast configuration. The results show clearly the difficulties to characterize soft tissues mechanics at large strain ranges with Neo-Hookean material models

    3D Kinematics and Quasi-Statics of a Growing Robot Eversion

    No full text
    International audienceGrowing robots and their eversion principle have wide applications ranging from surgery to industrial inspection and archaeology. The eversion process involves deploying an inflatable device with a material located at the tip of the robot, which, when under pressure, elongates the robot's body. However, the simulation of this complex kinematic phenomenon is a significant challenge. Our approach proposes to use a combination of kinematics and quasi-static modeling to parameterize the starting conditions of the eversion process. This facilitates the understanding of the behavior of this complex kinematic phenomenon and help identify factors that have a significant impact on the eversion process and its response to external factors. The kinematic model uses the Cosserat rod models for local coordinates, while the quasi-static model is based on finite element analysis. The two models are combined to capture the behavior of the robot tip during eversion. This approach has been implemented and tested using the SOFA framework and has been evaluated on the deployment of a vine robot on a narrow passage. The results of our approach are encouraging to better understand the behaviour of soft growing robot during eversion

    Simulation of breast compression using a new biomechanical model

    No full text
    International audienceMammography is currently the primary imaging modality for breast cancer screening and plays an important role in cancer diagnostics. A standard mammographic image acquisition always includes the compression of the breast prior x-ray exposure. The breast is compressed between two plates (the image receptor and the compression paddle) until a nearly uniform breast thickness is obtained. The breast flattening improves diagnostic image quality 1 and reduces the absorbed dose 2. However, this technique can also be a source of discomfort and might deter some women from attending breast screening by mammography 3,4. Therefore, the characterization of the pain perceived during breast compression is of potential interest to compare different compression approaches. The aim of this work is to develop simulation tools enabling the characterization of existing breast compression techniques in terms of patient comfort, dose delivered to the patient and resulting image quality. A 3D biomechanical model of the breast was developed providing physics-based predictions of tissue motion and internal stress and strain intensity. The internal stress and strain intensity are assumed to be directly correlated with the patient discomfort. The resulting compressed breast model is integrated in an image simulation framework to assess both image quality and average glandular dose. We present the results of compression simulations on two breast geometries, under different compression paddles (flex or rigid)
    corecore