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Collaborative Research: Physics-Based Modeling and Simulation for Post-Mastectomy Breast Reconstructive Surgery

Collaborative Research: Physics-Based Modeling and Simulation for Post-Mastectomy Breast Reconstructive Surgery
合作研究:基于物理的乳房切除术后乳房重建手术建模与仿真
批准号:
0402591
负责人:
Ioannis Kakadiaris
金额:
$27.25万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2004
资助国家:
美国
项目状态:
已结题
起止时间:
2004-09-01 至 2007-08-31

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中文摘要
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英文摘要
0402591KakadiarisBreast cancer is the second most frequent cancer diagnosis among American women today, after skin cancer. Post-mastectomy breast reconstruction is the third most frequently performed reconstructive procedure, superseded only by tumor removal and hand surgery. The psychological distress that accompanies a lump found in the breast, and the subsequent mastectomy is compounded by the limitations of contemporary reconstructive procedures; without a trusted reconstruction procedure, the specter of a disfiguring operation adds to the fear. Conventional procedures for reconstructing breast, or other soft tissue defects requiring adipose tissue, involve "robbing Peter to pay Paul". That is, tissue from a donor site on the patient is used to reconstruct the receiving site. However, it is difficult to predict exactly how the breast will be changed by a specific procedure in any particular patient. What size of donor tissue will yield the desired breast shape? How large a tension will be generated in the skin? Is there enough tissue to recreate a breast that would meet the expectations of the patient? Currently, there are no methods that would predict the outcome of the surgery.The goal of this proposal is to develop a predictive methodology to replace the trial and error method currently practiced. The proposed method is based on the large deformation analysis of mechanics; the skin covering the breast is modeled as a nonlinear elastic membrane or shell whose mechanical properties must be determined. After the shape, the size, and the mass of implant tissue and the skin on the breast are known, a nonlinear analysis will be used to calculate the resulting end shape. Conversely, if the end shape is prescribed, the analysis should yield the amount of implant tissue, and the shape and size of the skin necessary. The specific aims of this project were: 1) to develop an analytical model and numerical simulations to predict the breast shape for known initial conditions using generic data as well as physical and computational phantoms. This is based on the mechanics of finitely deforming bodies, 2) to develop a parametric deformable model that describes the shape of a female breast mathematically and 3) to experimentally verify these methods using phantoms and to demonstrate their utility for breast reconstructive surgery. Successful completion of this research has the potential to improve the quality of life for individuals recovering from post-mastectomy reconstruction operations. The predictive methodology will also lead to reduction in surgical time. The models that will be developed will apply to other organs and tissues as well and thus will increase understanding of soft tissue modeling and surgical simulation.
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NSF Convergence Accelerator Track J: Artificial-Intelligence-Based Decision Support for Equitable Food and Nutrition Security in the Houston Area
  • 批准号:
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  • 财政年份:
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  • 批准年份:
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  • 负责人:
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  • 依托单位:
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