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@rmadupuri rmadupuri commented Jan 22, 2026

What?

Enhancement to the previous PR #2015

  • Added multi-modal imaging data for TCGA Pan Cancer studies, organized into separate tabs.
  • Enables filtering of imaging resources by modality.

Details on how the data is generated:
https://github.com/cBioPortal/datahub/blob/2615fc6c90fb0e30994d43a09c13d1f2abb81122/docs/tcga_pan_can_atlas/ohif-viewer.md

Available Imaging Modalities:

Code Modality Viewer Resource ID Resource Tab Name
CR Computed Radiography OHIF IDC_OHIF_CR Computed Radiography
CT Computed Tomography OHIF IDC_OHIF_CT CT Scan
DX Digital Radiography OHIF IDC_OHIF_DX Digital Radiography
MG Mammography OHIF IDC_OHIF_MG Mammography
MR Magnetic Resonance OHIF IDC_OHIF_MR Magnetic Resonance
NM Nuclear Medicine OHIF IDC_OHIF_NM Nuclear Medicine
PT Positron Emission Tomography OHIF IDC_OHIF_PT PET Scan
SM Slide Microscopy (H&E) SLIM IDC_SLIM H&E Slide

Testing:

  1. BLCA pancan : https://triage.cbioportal.mskcc.org/study/summary?id=blca_tcga_pan_can_test
  2. LIHC pancan : https://triage.cbioportal.mskcc.org/study/summary?id=lihc_tcga_pan_can_atlas_2018
  3. BRCA pancan : https://triage.cbioportal.mskcc.org/study/summary?id=brca_pancan_test1

H&E Slide using SLIM viewer:
Screenshot 2026-01-23 at 13 57 27

CT Scan using OHIF viewer:
Screenshot 2026-01-23 at 14 36 58

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Looks good to me!

```bash
for f in $(cut -f2 ~/Downloads/idc_ohif.tsv | gsort | uniq | grep tcga_ | grep -v Filters | grep -v coad | grep -v read); do (head -1 coadread_tcga_pan_can_atlas_2018/data_resource_patient.txt; cut -f1,2,4 ~/Downloads/idc_ohif.tsv | tail -n +9 | grep $f | cut -f1,3 | awk -vFS='\t' -vOFS='\t' '{$1=substr($1,0,12); $3="https://viewer.imaging.datacommons.cancer.gov/viewer/"$2; $2="IDC_OHIF_V2"; print $0}' | gsort -k1,1 | uniq | rev | uniq -f2 | rev; ) > ${f/tcga_/}_tcga_pan_can_atlas_2018/*data_resource*patient*; done
```
**Note**: While a single study may contain multiple imaging modalities, data was extracted at the study level and then split by modality for cBioPortal integration. This modality-level organization allows users to selectively access specific imaging types (e.g., CT scans vs. H&E slides) for each patient.
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The URL patterns you provide at the bottom of this document are at the study level, so this paragraph is confusing.

1. Downloading TCGA imaging metadata from IDC using the idc-index package
2. Linking patients to their imaging studies via OHIF and SLIM viewer URLs

**Script**: [generate_imaging_resources.py](https://github.com/cBioPortal/datahub-study-curation-tools/tree/master/generate_imaging_resources)
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The script referenced uses custom code to generate viewer URLs. I recommend you use this function in IDCClient: https://idc-index.readthedocs.io/en/latest/api/idc_index.html#idc_index.index.IDCClient.get_viewer_URL. Note that your URLs point to the legacy OHIF Viewer v2, which will be deprecated. You should instead use OHIF Viewer v3. The function will generate OHIF v3 viewer links for radiology studies.

### Generate Resource Files

Patient-level resource files are generated for each TCGA Pan Cancer study by:
1. Downloading TCGA imaging metadata from IDC using the idc-index package
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You should keep track of the version of IDC data you use for generating those links. You can get it with https://idc-index.readthedocs.io/en/latest/api/idc_index.html#idc_index.index.IDCClient.get_idc_version. It would also be best if you updated your links after each IDC release. Although data removal is rare, it can happen, and would lead to broken viewer links.

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4 participants