Real-time In Vivo MRI Biomarkers for Breast Cancer Pre-operative Treatment Trials

描述（由申请人提供）：该项目是UCSF和Sentinelle Medical，Inc.研究人员之间的学术工业合作伙伴关系（AIP），在现有的图像检查工作站上实现用于评估对治疗的反应的乳房MR图像分析系统。该项目的目标是通过实时提供成像生物标志物作为乳腺MRI临床工作流程的一部分，更好地将成像生物标志物整合到临床试验中。加州大学旧金山分校的研究人员领导了一项大型多中心研究，研究MRI和分子标记物用于评估乳腺癌对术前化疗的反应。这些努力预计将导致后续试验的适应性设计，包括定量MRI测量，以评估反应和修改治疗。Sentinelle Medical，Inc.，制造具有先进乳腺MR成像和介入功能的成像和活检系统。该系统包括一个工作站和软件平台Aegis，用于图像审查和活检引导。Aegis是符合DICOM标准的软件系统，可与MRI扫描仪和PACS服务器进行通信。我们建议在这个AIP项目中开发两个新的软件模块，将其添加到Aegis平台，以支持实时图像分析和显示来自动态对比增强（DCE）和其他功能MRI数据的生物标志物数据。具体目标1的目标是开发一个治疗反应模块（TRM），该模块将提供导入和分析图像的功能，并生成彩色显示和数字生物标志物信息。TRM的输出将在检查时立即可用，以指导活检靶向和治疗反应的临床评估。Specific Aim 2的目标是开发一个生物标志物优化模块（BOM），旨在作为一种研究工具，用于基于注释有相关临床相关因素和结局的临床试验数据库对成像生物标志物进行回顾性优化、测试和比较。BOM将允许通过调整生物标志物定量参数来优化生物标志物性能，例如预测无病生存期的能力。BOM还允许比较替代指标，例如曲线下面积（AUC）和药代动力学参数ktranss，两者均用于量化造影剂摄取动力学。BOM将支持基于累积临床试验数据的成像指标培训，预计将导致TRM中提供的参数分析的细化和改进。本AIP旨在为参与临床试验的研究中心提供具有TRM和BOM功能的Aegis工作站。 公共卫生相关性 非侵入性成像方法有可能加速对新癌症治疗方法的评估。分子和功能成像技术可以提供治疗效果的敏感措施，并可以作为对治疗反应的体内生物标志物。这种学术-工业合作伙伴关系的目标是推进乳腺MRI技术，以允许在临床试验的背景下测量成像生物标志物，以实时评估反应和确定治疗修改。该项目还将支持基于临床结果的MRI成像生物标志物的优化和比较。

DESCRIPTION (provided by applicant): This project is an academic industrial partnership (AIP) between researchers at UCSF and Sentinelle Medical, Inc., to implement a breast MR image analysis system for assessing response to treatment, on an existing image review workstation. The goal of this project is to better enable the integration of imaging biomarkers into clinical trials by making imaging biomarkers available in real-time as part of the clinical workflow for breast MRI. Investigators at UCSF lead a large multi-center effort investigating MRI and molecular markers for assessing breast cancer response to pre-operative chemotherapy. These efforts are expected to lead to subsequent trials with adaptive designs that incorporate quantitative MRI measurements to assess response and revise treatment. Sentinelle Medical, Inc., manufactures an imaging and biopsy system with advanced capabilities for breast MR imaging and intervention. The system includes a workstation and software platform, Aegis, for image review and biopsy guidance. Aegis is a DICOM-compliant software system that communicates with both the MRI scanner and PACS server. We propose in this AIP project to develop two new software modules that will be added to the Aegis platform to support real-time image analysis and display of biomarker data derived from dynamic contrast-enhanced (DCE) and other functional MRI data. The goal of Specific Aim 1 is to develop a therapeutic response module (TRM) that will provide capabilities for importing and analyzing images, and producing colorized displays and numeric biomarker information. Output from the TRM will be immediately available at the time of the exam to direct biopsy-targeting and for clinical assessment of treatment response. The goal of Specific Aim 2 is to develop a biomarker optimization module (BOM), designed to be a research tool for retrospective optimization, testing and comparison of imaging biomarkers based on clinical trial databases annotated with relevant clinical correlates and outcomes. The BOM will allow biomarker performance, for example, ability to predict disease-free survival, to be optimized by adjusting biomarker quantification parameters. The BOM will also allow alternative metrics to be compared, for example, area under the curve (AUC) and the pharmacokinetic parameter ktrans, both used to quantify contrast uptake kinetics. The BOM will support the training of imaging metrics based on accumulated clinical trials data and is expected to lead to refinements and improvements in the parametric analyses provided in the TRM. It is the intent of this AIP to provide Aegis workstations with TRM and BOM capabilities to the participating clinical trial sites. PUBLIC HEALTH RELEVANCE Non-invasive imaging methods have the potential to accelerate the evaluation of new cancer treatments. Molecular and functional imaging techniques can provide sensitive measures of treatment effects and can serve as in vivo biomarkers of response to treatment. The goal of this academic-industrial partnership is to advance breast MRI technology to allow imaging biomarkers to be measured in the context of clinical trials for real-time assessment of response and determination of treatment modifications. This project will also support the optimization and comparison of MRI-based imaging biomarkers based on clinical outcomes.