DICOM converted Slide Microscopy images for the TCGA-PCPG collection

<p>This dataset corresponds to a collection of images and/or image-derived data available from National Cancer Institute <a href="https://portal.imaging.datacommons.cancer.gov/">Imaging Data Commons (IDC)</a> [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: <a href="https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection_id=tcga_pcpg">TCGA-PCPG</a>. You can use the manifests included in this Zenodo record to download the content of the collection following the <b>Download instructions</b> below.</p> <h3>Collection description</h3> <p> Paraganglioma is a rare cancer that originates in the nerve cells of the adrenal glands, organs on top of each kidney that produce important hormones. Paraganglioma that develops in the center of the adrenal gland is called pheochromocytoma. Paraganglioma that forms outside of the adrenal gland, often along blood vessels and nerves in the head and neck, is called extra-adrenal paraganglioma, or simply paraganglioma. Each year, between 2 and 8 people per million worldwide are diagnosed with paraganglioma and pheochromocytoma. 10% of all cases occur in children. In both adults and children, pheochromocytoma is more common than paraganglioma. No known environmental, dietary, or lifestyle risk factors have been associated with these cancers.</p> <p> Please see the <a href="https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga/studied-cancers/paraganglioma" target="_blank">TCGA-PCPG</a> information page to learn more about the images and to obtain any supporting metadata for this collection.</p> <p> Citation guidelines can be found on the <a href="https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga/using-tcga/citing-tcga" target="_blank">Citing TCGA in Publications and Presentations</a> information page.</p> <h3>Files included</h3> <p>A manifest file's name indicates the IDC data release in which a version of collection data was first introduced. For example, <code>collection_id-idc_v8-aws.s5cmd</code> corresponds to the contents of the <code>collection_id</code> 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.</p> <ol> <li><code>tcga_pcpg-idc_v10-aws.s5cmd</code>: manifest of files available for download from public IDC Amazon Web Services buckets</li> <li><code>tcga_pcpg-idc_v10-gcs.s5cmd</code>: manifest of files available for download from public IDC Google Cloud Storage buckets</li> <li><code>tcga_pcpg-idc_v10-dcf.dcf</code>: Gen3 manifest (for details see <a href="Gen3 manifest documentation">https://learn.canceridc.dev/data/organization-of-data/guids-and-uuids</a>)</li> </ol> <p>Note that manifest files that end in <code>-aws.s5cmd</code> reference files stored in Amazon Web Services (AWS) buckets, while <code>-gcs.s5cmd</code> reference files in Google Cloud Storage. The actual files are identical and are mirrored between AWS and GCP.</p> <h3>Download instructions</h3> <p>Each of the manifests include instructions in the header on how to download the included files.</p> <p>To download the files using <code>.s5cmd</code> manifests:</p> <ol> <li>install <a href="https://github.com/ImagingDataCommons/idc-index">idc-index</a> package: <code>pip install --upgrade idc-index</code></li> <li>download the files referenced by manifests included in this dataset by passing the <code>.s5cmd</code> manifest file: <code>idc download manifest.s5cmd</code>.</li> </ol> <p>To download the files using <code>.dcf</code> manifest, see manifest header.</p> <h3>Acknowledgments</h3> <p>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.</p> <h3>References</h3> <p>[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., Krishnaswamy, D., Thiriveedhi, V. K., Ciausu, C., Schacherer, D. P., Bontempi, D., Pihl, T., Wagner, U., Farahani, K., Kim, E. &amp; Kikinis, R. <i>National Cancer Institute Imaging Data Commons: Toward Transparency, Reproducibility, and Scalability in Imaging Artificial Intelligence</i>. RadioGraphics (2023). <a href="https://doi.org/10.1148/rg.230180">https://doi.org/10.1148/rg.230180</a></p>