Image Driven Multi-Scale Modeling to Predict Treatment Response in Breast Cancer

描述（由申请人提供）：能够在治疗过程的早期识别对特定新辅助方案无反应的患者，将提供转向潜在更有效治疗和改变当前实践的机会。不幸的是，现有的确定早期反应的方法是不够的。该项目的愿景是开发肿瘤预测方法，以预测单个乳腺癌患者在单周期新辅助治疗后的反应。我们建议将时间分辨率的药物反应细胞尺度数据与生理和组织尺度成像数据相结合，以初始化和约束多尺度血管生成-细胞增殖模型，该模型旨在预测治疗完成时乳腺肿瘤的大小和空间特征。为实现这一目标，我们将努力实现以下具体目标：(临床前验证

DESCRIPTION (provided by applicant): The ability to identify-early in the course of therapy-patients that are not responding to a particular neoadjuvant regimen would provide the opportunity to switch to a potentially more efficacious treatment and transform current practice. Unfortunately, existing methods of determining early response are inadequate. The vision for this program is to develop tumor-forecasting methods for predicting response in individual breast cancer patients after a single cycle of neoadjuvant therapy. We propose to combine time-resolved drug- response cell scale data with physiological and tissue scale imaging data in order to initialize and constrain a multi-scale angiogenesis-cell proliferation model designed to predict both size and spatial characteristics of breast tumors at the completion of therapy. To achieve this goal, we will pursue the following specific aims: 1. (Pre-clinical validation) In the BT-474 HER2+ human breast cancer cell line, we will obtain: 1a. (cell scale) in vitro data quantifying rates of entry of proliferating cells into quiescence and apoptosis; 1b. (physiologica scale) in vivo MRI and PET measurements of cellularity, vascularity, and metabolism; 1c. (tissue scale) in vivo MR elastography measurements to quantify the tumor mechanical properties; 1d. (all scales) in situ data from fixed tumor tissue to corroborate cell and imaging-based metrics. These data will be integrated into the multi-scale model to predict tumor response after one cycle of the targeted anti-HER2 agents trastuzumab and lapatinib. 2. (Clinical application) In HER2+ patients receiving neoadjuvant trastuzumab and lapatinib, we will obtain: 2a. (physiological scale) in vivo MRI and PET measurements of cellularity, vascularity, and metabolism; 2b. (tissue scale) in vivo MR elastography measurements to quantify tumor mechanical properties. Guided by the results from Aim 1, these data will be integrated into the multi-scale model and make predictions on breast tumor response outcomes after a single cycle of trastuzumab and/or lapatinib. If successful, our approach would be the foundation for high-impact, large-scale application in clinical settings.