Urban Trinity, Ziegler Erik, Lewis Rob, Hafey Chris, Sadow Cheryl, Van den Abbeele Annick D, Harris Gordon J
Open Health Imaging Foundation, Chicago, Illinois.
Massachusetts General Hospital, Imaging Department, Boston, Massachusetts.
Cancer Res. 2017 Nov 1;77(21):e119-e122. doi: 10.1158/0008-5472.CAN-17-0334.
Oncology clinical trials have become increasingly dependent upon image-based surrogate endpoints for determining patient eligibility and treatment efficacy. As therapeutics have evolved and multiplied in number, the tumor metrics criteria used to characterize therapeutic response have become progressively more varied and complex. The growing intricacies of image-based response evaluation, together with rising expectations for rapid and consistent results reporting, make it difficult for site radiologists to adequately address local and multicenter imaging demands. These challenges demonstrate the need for advanced cancer imaging informatics tools that can help ensure protocol-compliant image evaluation while simultaneously promoting reviewer efficiency. LesionTracker is a quantitative imaging package optimized for oncology clinical trial workflows. The goal of the project is to create an open source zero-footprint viewer for image analysis that is designed to be extensible as well as capable of being integrated into third-party systems for advanced imaging tools and clinical trials informatics platforms. .
肿瘤学临床试验越来越依赖基于图像的替代终点来确定患者的入选资格和治疗效果。随着治疗方法的不断发展和数量的增加，用于表征治疗反应的肿瘤指标标准变得越来越多样化和复杂。基于图像的反应评估日益复杂，加上对快速和一致的结果报告的期望不断提高，使得现场放射科医生难以充分满足本地和多中心的成像需求。这些挑战表明需要先进的癌症成像信息学工具，以帮助确保符合方案的图像评估，同时提高审阅者的效率。LesionTracker是一个针对肿瘤学临床试验工作流程进行优化的定量成像软件包。该项目的目标是创建一个用于图像分析的开源零占用空间查看器，该查看器设计为可扩展的，并且能够集成到用于先进成像工具和临床试验信息学平台的第三方系统中。
