Annotations for The Clinical Proteomic Tumor Analysis Consortium Clear Cell Renal Cell Carcinoma Collection

This dataset contains image annotations derived from "<a href="https://doi.org/10.7937/K9/TCIA.2018.OBLAMN27">The Clinical Proteomic Tumor Analysis Consortium Clear Cell Renal Cell Carcinoma Collection (CPTAC-CCRCC)</a>”.  This dataset was generated as part of a National Cancer Institute project to augment images from The Cancer Imaging Archive with annotations that will improve their value for cancer researchers and artificial intelligence experts.<h3><strong>Annotation Protocol</strong></h3>For each patient, all scans were reviewed to identify and annotate the clinically relevant time points and sequences/series. Scans were initially annotated by an international team of radiologists holding MBBS degrees or higher, which were then reviewed by US-based board-certified radiologists to ensure accuracy. In a typical patient all available time points were annotated. The following annotation rules were followed:<ol><li>RECIST 1.1 was generally followed for MR and CT imaging. A maximum of 5 lesions were annotated per patient scan (timepoint); no more than 2 per organ. The same 5 lesions were annotated at each time point. Lymph nodes were annotated if > 1 cm in short axis. Other lesions were annotated if > 1 cm. If the primary lesion measures < 1 cm, it was still annotated.</li><li>Three-dimensional segmentations of lesions were created in the axial plane. If no axial plane was available, lesions were annotated in the available plane.</li><li>MRIs were annotated using all axial T1-weighted post contrast sequences.</li><li>CTs were annotated using all axial post contrast series.</li><li>Lesions were labeled separately.</li><li>Seed points were automatically generated, but reviewed by a radiologist.</li><li>A “negative” annotation was created for any exam without findings.</li></ol>At each time point:<ol><li>Volume calculations were performed for each segmented structure.  These calculations are provided in the Annotation Metadata CSV.</li><li>A seed point (kernel) was created for each segmented structure. The seed points for each segmentation are provided in a separate DICOM RTSTRUCT file.</li><li>SNOMED-CT “Anatomic Region Sequence” and “Segmented Property Category Code Sequence” and codes were inserted for all segmented structures.</li><li>“Tracking ID” and “Tracking UID” tags were inserted for each segmented structure to enable longitudinal lesion tracking.</li><li>Imaging time point codes were inserted to help identify each annotation in the context of the clinical trial assessment protocol.<ol><li>“Clinical Trial Time Point ID” was used to encode time point type using one of the following strings as applicable: “pre-dose” or “post-chemotherapy”.</li><li>Content Item in “Acquisition Context Sequence” was added containing "Time Point Type" using Concept Code Sequence (0040,A168) selected from:<ol><li>(255235001, SCT, “Pre-dose”)</li><li>(719864002, SCT, "Post-cancer treatment monitoring")</li></ol></li></ol></li></ol><h3>Important supplementary information and sample code</h3><ol><li>A spreadsheet containing key details about the annotations is available in the <strong>Data Access</strong> section below.</li><li>A Jupyter notebook demonstrating how to use the <a href="https://wiki.cancerimagingarchive.net/display/NBIA/NBIA+Data+Retriever+Command-Line+Interface+Guide">NBIA Data Retriever Command-Line Interface</a> application and the <a href="https://wiki.cancerimagingarchive.net/display/Public/NBIA+Search+REST+API+Guide">REST API</a> to access these data can be found in the <strong>Additional Resources</strong> section below.</li></ol>

本数据集收录了源自《临床蛋白质组肿瘤分析联盟透明细胞肾细胞癌集合》（CPTAC-CCRCC）的图像标注数据。该数据集系美国国家癌症研究所项目的一部分，旨在提升《癌症影像档案》中图像的价值，并为癌症研究人员及人工智能专家提供辅助。标注协议如下：<h3>标注协议</h3>针对每位患者，对所有扫描图像进行审查，以识别和标注临床相关的时点及序列/系列。初期的标注工作由持有MBBS学位或以上资质的国际放射学团队完成，随后由美国执业认证的放射学专家进行复核，以确保标注的准确性。在典型患者中，所有可用的时点均进行标注。遵循以下标注规则：<ol><li>对于MR和CT成像，通常遵循RECIST 1.1标准。每位患者的扫描图像（时点）中最多标注5个病灶，每个器官不超过2个。每个时点标注相同的5个病灶。若淋巴结短轴直径大于1厘米，则进行标注。其他病灶若直径大于1厘米，亦进行标注。若原发灶直径小于1厘米，仍需进行标注。</li><li>在轴向平面上创建病灶的三维分割。若无轴向平面可用，则在可用的平面上进行标注。</li><li>使用所有轴向T1加权的对比增强序列对MRI进行标注。</li><li>使用所有轴向对比增强序列对CT进行标注。</li><li>单独标注病灶。</li><li>自动生成种子点，并由放射学专家进行复核。</li><li>对于无发现结果的任何检查，创建“阴性”标注。</li></ol>在每个时点：<ol><li>对每个分割结构进行体积计算，并在标注元数据CSV文件中提供这些计算结果。</li><li>为每个分割结构创建一个种子点（核），每个分割的种子点提供在单独的DICOM RTSTRUCT文件中。</li><li>为所有分割结构插入SNOMED-CT“解剖区域序列”和“分割属性类别代码序列”及代码。</li><li>为每个分割结构插入“跟踪ID”和“跟踪UID”标签，以实现纵向病灶追踪。</li><li>插入成像时间点代码，以帮助在临床试验评估方案背景下识别每个标注。</li><li>使用“临床试验时间点ID”编码时点类型，采用以下字符串之一：'pre-dose'（剂量前）或'post-chemotherapy'（化疗后）。</li><li>在“采集上下文序列”中添加包含“时点类型”的内容项，使用概念代码序列（0040,A168）选择，选项如下：<ol><li>(255235001, SCT, “剂量前”)</li><li>(719864002, SCT, “癌症治疗监测后”）</li></ol></li></ol></li></ol><h3>重要补充信息和示例代码</h3><ol><li>在以下数据访问部分，提供了一个包含标注关键细节的电子表格。</li><li>在以下附加资源部分，提供了一个Jupyter笔记本，演示了如何使用<a href="https://wiki.cancerimagingarchive.net/display/NBIA/NBIA+Data+Retriever+Command-Line+Interface+Guide">NBIA数据检索命令行界面</a>应用程序和<a href="https://wiki.cancerimagingarchive.net/display/Public/NBIA+Search+REST+API+Guide">REST API</a>来访问这些数据。</li></ol>