| Literature DB >> 29092955 |
Trinity Urban1,2,3,4, Erik Ziegler1, Rob Lewis1, Chris Hafey1, Cheryl Sadow3,4,5, Annick D Van den Abbeele3,4,6,7, Gordon J Harris8,2,3,4.
Abstract
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. Cancer Res; 77(21); e119-22. ©2017 AACR. ©2017 American Association for Cancer Research.Entities:
Mesh:
Year: 2017 PMID: 29092955 PMCID: PMC5679226 DOI: 10.1158/0008-5472.CAN-17-0334
Source DB: PubMed Journal: Cancer Res ISSN: 0008-5472 Impact factor: 12.701