Rhabdomyosarcoma Images Now Available Through NCI’s Imaging Data Commons
You can now access digital, whole-slide, hematoxylin and eosin (H&E) stained Rhabdomyosarcoma (RMS) images in DICOM format1 via NCI’s Imaging Data Commons (IDC)2.
The images are from diagnostic specimens of 403 RMS patients who participated in Children’s Oncology Group trials between 1998 and 20173. You have access to metadata added by researchers and the benefit of DICOM whole-slide microscopy representation4,5 using custom, open-source scripts and tools6.
In addition, you can get:
- accompanying clinical data via the SQL interface in IDC BigQuery tables7.
- gene panel sequencing data through the database of Genotypes and Phenotypes phs000720.v4.p1.
- an inventory of these data in the Childhood Cancer Data Initiative’s Childhood Cancer Data Catalog.
Researchers used these diagnostic H&E images to train deep learning models for identifying tumor features, predicting the presence of high-risk mutations, assessing relative risk, and predicting molecular subtypes and survival in RMS8. This methodology extends to other pediatric and adult malignancies, with the potential to integrate deep learning algorithms into clinical decision-making and precision medicine. Such advancements hold promise for the future of cancer care.
2 NCI Imaging Data Commons. Cancer Research, 2021.
3 Genomic Classification and Clinical Outcome in Rhabdomyosarcoma: A Report from an International Consortium. Journal of Clinical Oncology, 2021.
5Implementing the DICOM Standard for Digital Pathology. Journal of Pathology Informatics, 2018.