CMB-LCA: DICOM converted Slide Microscopy images for the Cancer Moonshot Biobank initiative Lung Cancer collection
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This dataset corresponds to a collection of images and/or image-derived data available from National Cancer Institute Imaging Data Commons (IDC) [1]. This dataset was converted into DICOM representation and ingested by the IDC team. You can explore and visualize the corresponding images using IDC Portal here. You can use the manifests included in this Zenodo record to download the content of the collection following the Download instructions below. Collection description The Cancer Moonshot Biobank (CMB) is a National Cancer Institute initiative to support current and future investigations into drug resistance and sensitivity and other NCI-sponsored cancer research initiatives, with an aim of improving researchers' understanding of cancer and how to intervene in cancer initiation and progression. During the course of this study, biospecimens (blood and tissue removed during medical procedures) and associated data will be collected longitudinally from at least 1000 patients across at least 10 cancer types, who represent the demographic diversity of the U.S. and receiving standard of care cancer treatment at multiple NCI Community Oncology Research Program (NCORP) sites. CMB program is organized into multiple cancer-specific collections. Digital pathology images for each of those collections were converted into DICOM representation by the IDC team and are shared via IDC. This entry corresponds to the CMB-LCA collection (Lung Cancer). Digital pathology images, augmented with the metadata describing their content, were converted into DICOM Whole Slide Microscopy (SM) representation [2,3] using custom open source scripts and tools as described in [4]. Files included A manifest file's name indicates the IDC data release in which a version of collection data was first introduced. For example, collection_id-idc_v8-aws.s5cmd corresponds to the contents of the collection_id collection introduced in IDC data release v8. If there is a subsequent version of this Zenodo page, it will indicate when a subsequent version of the corresponding collection was introduced. For each of the collections, the following manifest files are provided: <collection_id>-idc_v22-aws.s5cmd: manifest of files available for download from public IDC Amazon Web Services buckets <collection_id>-idc_v22-gcs.s5cmd: manifest of files available for download from public IDC Google Cloud Storage buckets <collection_id>-idc_v22-dcf.dcf: Gen3 manifest (for details see https://learn.canceridc.dev/data/organization-of-data/guids-and-uuids) Note that manifest files that end in -aws.s5cmd reference files stored in Amazon Web Services (AWS) buckets, while -gcs.s5cmd reference files in Google Cloud Storage. The actual files are identical and are mirrored between AWS and GCP. Download instructions Each of the manifests include instructions in the header on how to download the included files. To download the files using .s5cmd manifests: install idc-index package: pip install --upgrade idc-index download the files referenced by manifests included in this dataset by passing the .s5cmd manifest file: idc download manifest.s5cmd To download the files using .dcf manifest, see manifest header. Acknowledgments Imaging Data Commons team has been funded in whole or in part with Federal funds from the National Cancer Institute, National Institutes of Health, under Task Order No. HHSN26110071 under Contract No. HHSN261201500003l. References [1] Fedorov, A., Longabaugh, W. J. R., Pot, D., Clunie, D. A., Pieper, S. D., Gibbs, D. L., Bridge, C., Herrmann, M. D., Homeyer, A., Lewis, R., Aerts, H. J. W. L., Krishnaswamy, D., Thiriveedhi, V. K., Ciausu, C., Schacherer, D. P., Bontempi, D., Pihl, T., Wagner, U., Farahani, K., Kim, E. & Kikinis, R. National cancer institute imaging data commons: Toward transparency, reproducibility, and scalability in imaging artificial intelligence. Radiographics 43, (2023). [2] National Electrical Manufacturers Association (NEMA). DICOM PS3.3 - Information Object Definitions: A.32.8 VL Whole Slide Microscopy Image IOD. at <https://dicom.nema.org/medical/dicom/current/output/html/part03.html#sect_A.32.8> [3] Herrmann, M. D., Clunie, D. A., Fedorov, A., Doyle, S. W., Pieper, S., Klepeis, V., Le, L. P., Mutter, G. L., Milstone, D. S., Schultz, T. J., Kikinis, R., Kotecha, G. K., Hwang, D. H., Andriole, K. P., John Lafrate, A., Brink, J. A., Boland, G. W., Dreyer, K. J., Michalski, M., Golden, J. A., Louis, D. N. & Lennerz, J. K. Implementing the DICOM standard for digital pathology. J. Pathol. Inform. 9, 37 (2018). [4] Clunie, D., Fedorov, A. & Herrmann, M. D. ImagingDataCommons/idc-wsi-conversion: Initial release. (Zenodo, 2023). doi:10.5281/ZENODO.8240154
本数据集包含从美国国家癌症研究所影像数据公共库（National Cancer Institute Imaging Data Commons，IDC）[1]获取的图像及/或图像衍生数据。该数据集已由IDC团队转换为DICOM（Digital Imaging and Communications in Medicine）格式并入库。您可通过IDC门户浏览并可视化查看对应图像。您可通过本Zenodo记录中提供的清单文件，按照下述下载指南下载该数据集的全部内容。 数据集说明 癌症登月生物样本库（Cancer Moonshot Biobank，CMB）是美国国家癌症研究所发起的一项计划，旨在支持当前及未来针对药物耐药性、敏感性及其他NCI赞助的癌症研究项目，以加深研究人员对癌症的认知，以及对癌症发生与进展的干预手段。本研究期间，将从全美至少10种癌症类型的1000余名患者中纵向收集生物样本（医疗过程中获取的血液与组织样本）及关联数据，这些患者覆盖美国人口统计学多样性特征，并在多个NCI社区肿瘤研究项目（NCI Community Oncology Research Program，NCORP）试点机构接受标准癌症治疗方案。 CMB计划下设多个针对特定癌症类型的数据集。IDC团队已将各数据集的数字病理图像转换为DICOM格式，并通过IDC平台共享。本条目对应CMB-LCA数据集（肺癌）。 结合描述图像内容的元数据后，数字病理图像已通过自定义开源脚本与工具转换为DICOM全玻片显微成像（Whole Slide Microscopy，SM）格式[2,3]，具体实现方式详见文献[4]。 包含的文件 清单文件的文件名可标识该数据集版本首次引入的IDC数据发布版本。例如，`collection_id-idc_v8-aws.s5cmd`对应IDC数据发布版本v8中首次引入的collection_id数据集内容。若本Zenodo记录后续更新版本，将同步说明对应数据集的更新版本发布时间。 针对每个数据集，均提供以下清单文件： - `<collection_id>-idc_v22-aws.s5cmd`：可从IDC公共亚马逊云服务（AWS）存储桶下载的文件清单 - `<collection_id>-idc_v22-gcs.s5cmd`：可从IDC公共谷歌云存储（GCS）存储桶下载的文件清单 - `<collection_id>-idc_v22-dcf.dcf`：Gen3格式清单（详情请参阅：https://learn.canceridc.dev/data/organization-of-data/guids-and-uuids） 请注意，后缀为`-aws.s5cmd`的清单文件指向存储在亚马逊云服务（AWS）存储桶中的文件，而`-gcs.s5cmd`后缀的清单文件指向谷歌云存储（GCS）中的文件。实际文件内容完全一致，且在AWS与GCP平台间实现了镜像同步。 下载指南 每份清单文件的头部均包含该清单所包含文件的下载说明。 使用`.s5cmd`格式清单下载文件的步骤： 1. 安装`idc-index`工具包：`pip install --upgrade idc-index` 2. 通过指定`.s5cmd`格式的清单文件，下载本数据集中清单指向的所有文件：`idc download manifest.s5cmd` 使用`.dcf`格式清单下载文件的说明，请参阅清单文件头部内容。 致谢 影像数据公共库团队的研究工作全部或部分获得了美国国家卫生研究院下属国家癌症研究所的联邦资金支持，资助合同编号为HHSN261201500003l，任务订单编号为HHSN26110071。 参考文献 [1] Fedorov, A., Longabaugh, W. J. R., Pot, D., Clunie, D. A., Pieper, S. D., Gibbs, D. L., Bridge, C., Herrmann, M. D., Homeyer, A., Lewis, R., Aerts, H. J. W. L., Krishnaswamy, D., Thiriveedhi, V. K., Ciausu, C., Schacherer, D. P., Bontempi, D., Pihl, T., Wagner, U., Farahani, K., Kim, E. & Kikinis, R. National cancer institute imaging data commons: Toward transparency, reproducibility, and scalability in imaging artificial intelligence. *Radiographics*, 43, (2023). [2] National Electrical Manufacturers Association (NEMA). DICOM PS3.3 - Information Object Definitions: A.32.8 VL Whole Slide Microscopy Image IOD. 详见 <https://dicom.nema.org/medical/dicom/current/output/html/part03.html#sect_A.32.8> [3] Herrmann, M. D., Clunie, D. A., Fedorov, A., Doyle, S. W., Pieper, S., Klepeis, V., Le, L. P., Mutter, G. L., Milstone, D. S., Schultz, T. J., Kikinis, R., Kotecha, G. K., Hwang, D. H., Andriole, K. P., John Lafrate, A., Brink, J. A., Boland, G. W., Dreyer, K. J., Michalski, M., Golden, J. A., Louis, D. N. & Lennerz, J. K. Implementing the DICOM standard for digital pathology. *J. Pathol. Inform.*, 9, 37 (2018). [4] Clunie, D., Fedorov, A. & Herrmann, M. D. ImagingDataCommons/idc-wsi-conversion: Initial release. (Zenodo, 2023). doi:10.5281/ZENODO.8240154
