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A Physics-based Biomechanical Model To Help Predict Outcomes After Reconstructive Surgery Of The Female Breast
Mazen Diab, Ph.D.1,2, Gregory P. Reece, M.D.2, Summer E. Hanson, M.D., Ph.D.2, Mary Catherine A. Bordes2, Gary J. Whitman, M.D.3, Mia K. Markey, Ph.D.4,5, Krishnaswamy Ravi-Chandar, Ph.D.1.
1Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin, Austin, TX, USA, 2Department of Plastic Surgery, The University of Texas MD Anderson Cancer Center, Houston, TX, USA, 3Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA, 4Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, USA, 5Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.

PURPOSE: There has been a steady increase in the number of patients who elect to undergo reconstructive surgery to restore breast shape after mastectomy. Many options for reconstruction exist with a major challenge being the ability to accurately predict the outcome of autologous or implant-based breast reconstruction. Our overarching objective is to develop a physics-based computational biomechanical model of the female breast to simulate breast shape following different reconstructive procedures. Simulated outcomes will hopefully help new patients understand likely appearance changes after breast reconstruction and make well-informed decisions about the type of procedure that is best for them.
METHODS: MR and CT images of patients were collected and de-identified of patient health information at the University of Texas MD Anderson Cancer Center. Patients provided informed consent in accordance with an institutional review board-approved protocol. A computational biomechanical model for the female breast was constructed using MR and CT images of the chest wall to provide the basic geometry of the pectoralis muscle, breast mound and skin. Material properties of the skin and the breast tissues were determined from experiments on freshly excised tissues. The biomechanical model was further calibrated using a 3D vision system (3dMDtorso™ system; 3dMD® LLC, Atlanta, GA) mounted on a tilt bed that provided a full 3D surface profile of the full human torso at varying angular positions.
RESULTS: Our results show that the segmented pectoralis major muscle obtained from MR images (patient prone) and CT images (patient supine) for the same patient show a significant deformation of the pectoralis muscle and sliding of the breast which necessitates incorporating the deformation of the underlying structure in developing a robust biomechanical model. Moreover, simulation results show that the underlying anatomical structure of the breast and the boundary and loading conditions of the breast are very crucial in developing the biomechanical model. Finally, we present a simulation framework to show how the biomechanical model can be used to predict outcome following an implant-based breast reconstruction.
CONCLUSION: Biomechanical models for the female breast offer a promising tool to simulate outcome after reconstructive surgery. Incorporating the underlying anatomical structure and its mechanical properties are essential for developing a robust anatomically-based biomechanical model of the breast capable of predicting accurate breast shape changes after reconstructive surgery.


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