Objective Assessment of Breast Reconstruction Aesthetics

描述（由申请人提供）： 我们的长期目标是开发有助于改善乳腺癌治疗的决策辅助工具。乳腺癌治疗的美学结果是乳腺癌幸存者生活质量的重要因素。美学是指物理特征，如对称和比例。目前，医生、患者或其他观察者以主观、定性的方式评价乳房美学。然而，这种评估通常基于定义模糊的评级量表，观察者内部和观察者之间的一致性很低。它们的定性性质也限制了可以进行的分析。需要具有高可靠性的定量客观测量，以将患者和手术变量与美学结果有意义地联系起来，并比较不同类型乳腺癌治疗的结果（例如，重建程序）。我们量化乳房美学的方法是在临床照片上的解剖标志（基准点）之间进行测量。在拟议的研究中，我们将设计和评估自动图像处理算法，用于计算乳房美学的客观，定量，可重复的措施。我们预计，新系统将导致未来在三个重要的临床领域的研究：（1）治疗方案的结果分析（例如，乳房保留治疗与乳房切除术后重建的比较），（2）开发新的方法，对患者进行治疗选择的教育，以及（3）研究术中成像，以指导外科医生进行乳房重建。 这项研究的具体目标是： 1)设计算法来计算乳房美学的客观，定量，可重复的措施。 2)评估用于计算乳房美学特性的客观测量的算法。 3)通过设计和评估用于自动识别基准点的图像处理算法来扩展我们的方法的效用。

DESCRIPTION (provided by applicant): Our long-term goal is to develop decision aids that will improve breast cancer treatment. The aesthetic outcome of breast cancer treatment is an important factor in breast cancer survivors' quality of life. Aesthetics refers to physical characteristics such as symmetry and proportion. Currently, physicians, patients, or other observers evaluate breast aesthetics in a subjective, qualitative manner. However, such assessments are typically based on vaguely defined rating scales that have low intra- and inter- observer agreement. Their qualitative nature also restricts the analyses that can be performed. Quantitative, objective measures with high reliability are needed to meaningfully relate patient and surgical variables to aesthetic outcomes and to compare the outcomes of different kinds of breast cancer treatments (e.g., reconstruction procedures). Our approach to quantifying breast aesthetics is to make measurements between anatomical landmarks (fiducial points) on clinical photographs. In the proposed study, we will design and evaluate automatic image processing algorithms for computing objective, quantitative, reproducible measures of breast aesthetics. We anticipate that the new system will lead to future studies in three significant clinical areas: (1) outcome analyses of treatment options (e.g., comparison of breast conservation therapy to mastectomy followed by reconstruction), (2) development of new approaches to patient education about treatment options, and (3) investigations of intra-operative imaging to guide surgeons in breast reconstruction. The specific aims of this study are to: 1) Design algorithms to compute objective, quantitative, reproducible measures of breast aesthetics. 2) Evaluate the algorithms for computing objective measures of breast aesthetic properties. 3) Expand the utility of our methods by designing and evaluating image processing algorithms for automatic identification of fiducial points.