DOI: 10.5281/zenodo.12666872
title: DICOM converted Slide Microscopy images for the HTAN-HMS collection

description: 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: HTAN-HMS. 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 Human Tumor Atlas Network (HTAN) [2], part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. 

We are constructing a multi-dimensional atlas of pre-melanoma focused on understanding genetic and epigenetic events that transform melanocytes into invasive tumors. Melanoma is a cancer of increasing prevalence that is curable with minor surgery if detected early but life-threatening when it metastasizes. Melanomas metastasize when still small, making early detection essential but challenging. Our atlas will delineate the precise sequence of events leading up to pre-melanoma through detailed spatial analysis of cell-autonomous events such as oncogene mutation and non-autonomous events such as escape from immune surveillance. The atlas is based on highly-multiplexed tissue imaging and single cell sequencing and focused on samples in which the full sequence of events from atypia to invasive melanoma can be visualized in a single specimen. The atlas will serve as a publicly accessible resource for research scientists, physicians, and patients and improve our ability to (i) highlight lesions likely to progress to cancer, (ii) identify high-risk patients to inform decisions on surgery, (iii) identify low-risk patients to reduce unnecessary procedures, (iv) design improved procedures for routine screening of all individuals, and (v) inform treatment options when surgery is insufficient. Complementary studies with similar goals (but not supported by HTAN) are studying later stage melanomas.

Please see the  HTAN-HMS    information page to learn more about the images and to obtain any supporting metadata for this collection.

Citation guidelines can be found on the  HTAN Publication Policy    information page.

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.



htan_hms-idc_v10-aws.s5cmd: manifest of files available for download from public IDC Amazon Web Services buckets

htan_hms-idc_v10-gcs.s5cmd: manifest of files available for download from public IDC Google Cloud Storage buckets

htan_hms-idc_v10-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

Collection of the images that were converted by IDC was supported through the Human Tumor Atlas Network, grants 1U2CCA233262-01 "Pre-cancer atlases of cutaneous and hematologic origin (PATCH Center)" and 1U24CA233243-01 "Human Tumor Atlas Network: Data Coordinating Center" from National Cancer Institute.

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., 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 (2023). https://doi.org/10.1148/rg.230180

[2] Rozenblatt-Rosen, O., Regev, A., Oberdoerffer, P., Nawy, T., Hupalowska, A., Rood, J. E., Ashenberg, O., Cerami, E., Coffey, R. J., Demir, E., Ding, L., Esplin, E. D., Ford, J. M., Goecks, J., Ghosh, S., Gray, J. W., Guinney, J., Hanlon, S. E., Hughes, S. K., Hwang, E. S., Iacobuzio-Donahue, C. A., Jané-Valbuena, J., Johnson, B. E., Lau, K. S., Lively, T., Mazzilli, S. A., Pe’er, D., Santagata, S., Shalek, A. K., Schapiro, D., Snyder, M. P., Sorger, P. K., Spira, A. E., Srivastava, S., Tan, K., West, R. B., Williams, E. H. & Human Tumor Atlas Network. The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution. Cell 181, 236–249 (2020). http://dx.doi.org/10.1016/j.cell.2020.03.053