Published June 16, 2026 | Version 2.0.0

RCC-AID: Renal Cell Carcinoma AI Dataset for Medical Imaging Research

  • 1. ROR icon Radboud University Medical Center
  • 2. ROR icon Charité - Universitätsmedizin Berlin
  • 3. ROR icon Technical University of Munich
  • 4. ROR icon IRCCS Ospedale San Raffaele
  • 5. German Heart Center Munich

Description

Associated publication: de Boer, Häntze, et al. Accessible and Reproducible Renal Cell Carcinoma Research Through Open-Sourcing Data and Annotations medRxiv (preprint).

Background

This dataset provides voxel-level segmentation annotations for CT imaging from three TCGA renal cell carcinoma (RCC) cohorts: clear cell (TCGA-KIRC), papillary (TCGA-KIRP), and chromophobe (TCGA-KICH). It was created to support accessible and reproducible AI research for RCC and addresses the common problem of TCGA imaging data lacking easily accessible public annotations. A total of 129 annotated CT scans from 91 patients are included (85 clear cell, 26 papillary, 18 chromophobe RCC).

Dataset Contents

File Description
images\ NifTI (.nii.gz) files of CT images, converted from TCIA DICOM source data
annotations\ NifTI (.nii.gz) segmentation masks, one per scan
metadata.csv Case-level metadata including RCC subtype, patient demographics, and TCIA series identifiers. Reproduced from TCIA source collections (CC BY 3.0).
manifest.tcia TCIA Data Retriever manifest. Opening this file with the NBIA Data Retriever will download the original DICOM images directly from TCIA.

 

Segmentation label map:

  • 0 - Background
  • 1 - Kidney
  • 2 - Tumor
  • 3 - Cyst

The specific RCC subtype for each case (clear cell, papillary, or chromophobe) is provided in metadata.csv.

Version log

Version 2.0.0: 129 CT from 91 patients. Some of the DICOM to NIfTI conversions in version 1.0.0 silently failed. The issues have been resolved in version 2.0.0 and the files that were irrevisibily broken have been removed. Additionally, contrast phase annotations have been added.

Version 1.0.0: 142 CT from 101 patients. 

License

Segmentation annotations: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).

NIfTI images and metadata.csv are derived from or reproduced from TCIA source collections (see Attribution below), which are published under CC BY 3.0 (https://creativecommons.org/licenses/by/3.0/).

Citation

If you use this dataset, please cite our paper (preprint until published):

  • de Boer, Häntze, et al. Accessible and Reproducible Renal Cell Carcinoma Research Through Open-Sourcing Data and Annotations. medRxiv. 

If a peer-reviewed version is available, please cite that instead.

Additionally, please cite the following TCIA source collections and include the TCGA disclaimer:

  • Akin, O., et al. (2016). The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma Collection (TCGA-KIRC) (Version 3) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2016.V6PBVTDR
  • Linehan, M., et al. (2016). The Cancer Genome Atlas Kidney Renal Papillary Cell Carcinoma Collection (TCGA-KIRP) (Version 4) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2016.ACWOGBEF
  • Linehan, M. W., et al. (2016). The Cancer Genome Atlas Kidney Chromophobe Collection (TCGA-KICH) (Version 3) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2016.YU3RBCZN

Acknowledgements

This research is funded by the European Union under HORIZON-HLTH-2022: COMFORT (101079894). Views and opinions expressed are those of the author(s) only and do not necessarily reflect those of the European Union or the European Health and Digital Executive Agency (HADEA). Neither the European Union nor the granting authority can be held responsible for them. 

The results published here are in whole or in part based upon data generated by the TCGA Research Network: http://cancergenome.nih.gov/.

Files

images.zip

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Additional details

Funding

European Commission
COMFORT - COMputational Models FOR patienT stratification in urologic cancers – Creating robust and trustworthy multimodal AI for health care 101079894

References