3D computer technology addresses body-image issues of breast reconstruction

In the United States, one in eight women can expect to be diagnosed with breast cancer within her lifetime. Treatment of breast cancer often involves mastectomy, the surgical removal of the breast(s). Women at heightened risk may also elect to undergo mastectomy to reduce the chances of developing breast cancer. Many women who undergo a mastectomy have concerns about their body image—i.e., how they view their appearance and the overall functioning of their body. The goal of breast reconstruction is to recreate the appearance of the patient’s breasts in a way that restores her body image. Breast reconstruction typically requires multiple procedures over time to obtain a final result. Many women are candidates for more than one form of breast reconstruction, such as reconstruction using either an implant or some of the patient’s own tissue (autologous reconstruction). There are a large number of factors a woman must consider when making her treatment decisions, including time, cost, and body-image preferences. For a woman to make optimal decisions about breast reconstruction, she needs some very specific information to understand her surgical options and how her preferences, including her appearance after the surgery, can best be met. This article describes our approach to quantifying a patient’s appearance via imaging and 3D modeling techniques.1–11 We note, however, that developing a greater understanding of patient preferences in terms of quality-of-life measures such as body image12 and modeling the decision-making process for breast reconstruction13 are equally important aspects of our research program. To extract relevant information about appearance changes, we analyzed both 2D and 3D surface images to quantify the Figure 1. Surface-curvature analysis produces automated identification of the sternal notch (S), nipples (N), and umbilicus (U). These fiducial points can be used to calculate quantitative measures such as symmetry. Figure prepared by Manas Kawale.

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