The Quantitative Imaging Network (QIN), supported by the National Cancer Institute, is designed to promote research and development of quantitative imaging methods and candidate biomarkers for the measurement of tumor response in clinical trial settings. An integral aspect of the QIN mission is to facilitate collaborative activities that seek to develop best practices for the analysis of cancer imaging data. The QIN working groups and teams are developing new algorithms for image analysis and novel biomarkers for the assessment of response to therapy. To validate these algorithms and biomarkers and translate theminto clinical practice, algorithms need to be compared and evaluated on large and diverse data sets. Analysis competitions, or “challenges,” are being conducted within the QIN as a means to accomplish this goal. The QIN has demonstrated, through its leveraging of The Cancer Imaging Archive (TCIA), that data sharing of clinical images across multiple sites is feasible and that it can enable and support these challenges. In addition to Digital Imaging and Communications in Medicine (DICOM) imaging data, many TCIA collections provide linked clinical, pathology, and “ground truth” data generated by readers that could be used for further challenges. The TCIA-QIN partnership is a successful model that provides resources for multisite sharing of clinical imaging data and the implementation of challenges to support algorithm and biomarker validation.

由美国国家癌症研究所支持的定量成像网络 (QIN) 旨在促进定量成像方法和候选生物标志物的研究和开发，以在临床试验环境中测量肿瘤反应。QIN 任务的一个组成部分是促进协作活动，旨在开发分析癌症成像数据的最佳实践。QIN 工作组和团队正在开发用于图像分析的新算法和用于评估治疗反应的新生物标志物。为了验证这些算法和生物标志物并将 themin 转化为临床实践，需要在大量不同的数据集上对算法进行比较和评估。作为实现这一目标的手段，秦国内部正在开展分析竞赛或“挑战”。秦国已经证明，通过利用癌症成像档案 (TCIA)，跨多个站点的临床图像数据共享是可行的，并且可以实现和支持这些挑战。除了医学数字成像和通信 (DICOM) 成像数据之外，许多 TCIA 馆藏还提供了由读者生成的相关临床、病理学和“基本事实”数据，可用于进一步的挑战。TCIA-QIN 合作伙伴关系是一个成功的模式，为临床影像数据的多站点共享以及支持算法和生物标志物验证的挑战的实施提供资源。除了医学数字成像和通信 (DICOM) 成像数据之外，许多 TCIA 馆藏还提供了由读者生成的相关临床、病理学和“基本事实”数据，可用于进一步的挑战。TCIA-QIN 合作伙伴关系是一个成功的模式，为临床影像数据的多站点共享以及支持算法和生物标志物验证的挑战的实施提供资源。除了医学数字成像和通信 (DICOM) 成像数据之外，许多 TCIA 馆藏还提供了由读者生成的相关临床、病理学和“基本事实”数据，可用于进一步的挑战。TCIA-QIN 合作伙伴关系是一个成功的模式，为临床影像数据的多站点共享以及支持算法和生物标志物验证的挑战的实施提供资源。