# IDC data release v24 May 2026: New GDC projects, preclinical models, updates from TCIA **URL:** \ **Category:** Announcements\ **Tags:** release\ **Created:** [May 14, 2026, 3:50pm UTC](https://discourse.canceridc.dev/t/idc-data-release-v24-may-2026-new-gdc-projects-preclinical-models-updates-from-tcia/786 "2026-05-14T15:50:42Z")\ **Posts on this page:** 1\ **Page:** 1

**Author:** ![fedorov](https://sea1.discourse-cdn.com/flex015/user_avatar/discourse.canceridc.dev/fedorov/32/3_2.png) [@fedorov](https://discourse.canceridc.dev/u/fedorov)\ **Post date:** [May 14, 2026, 3:50pm UTC](https://discourse.canceridc.dev/t/idc-data-release-v24-may-2026-new-gdc-projects-preclinical-models-updates-from-tcia/786/1 "2026-05-14T15:50:42Z")

NCI Imaging Data Commons (IDC) v24 is live! This is the largest data release by file count since 2022, adding **15 new collections** and approximately **5.7 terabytes (TB) of new data**. With this release we cross the milestone of **1 million publicly available DICOM series** , bringing IDC’s total to nearly **100 TB** (99.3 TB) across 176 collections. Here is a summary of what’s new. ![infographic](https://us1.discourse-cdn.com/flex015/uploads/canceridc/original/1X/5c7e88dde2a6214f907a60cc4d85c4082ba566b7.jpeg) ## 🔬 Digital Pathology v24 brings a major expansion of slide microscopy (SM) content — the dominant addition by data volume (~4 TB of new pathology slides). All of the slide microscopy data available in IDC is harmonized into DICOM from vendor-specific formats. New collections sourced from Genomics Data Commons (GDC), with the matching genomic data available from GDC: - **[CGCI-BLGSP](https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection_id=cgci_blgsp)** — Burkitt Lymphoma Genome Sequencing Project: 388 patients, 1,933 series, 1.6 TB ([DOI](https://doi.org/10.5281/zenodo.17381396)) - **[CGCI-HTMCP-DLBCL](https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection_id=cgci_htmcp_dlbcl)** — Human immunodeficiency virus (HIV)+ Tumor Molecular Characterization, Diffuse Large B-Cell Lymphoma: 43 patients, 496 series, ~545 GB ([DOI](https://doi.org/10.5281/zenodo.17381412)) - **[HCMI-CMDC](https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection_id=hcmi_cmdc)** — Human Cancer Models Initiative: 382 patients, 810 series, ~372 GB ([DOI](https://doi.org/10.5281/zenodo.17381441)) - **[CGCI-HTMCP-CC](https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection_id=cgci_htmcp_cc)** — HIV+ Tumor, Cervical Squamous Cell Carcinoma: 211 patients, 525 series, ~148 GB ([DOI](https://doi.org/10.5281/zenodo.17381404)) - **[CGCI-HTMCP-LC](https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection_id=cgci_htmcp_lc)** — HIV+ Tumor, Lung Cancer: 27 patients, 84 series ([DOI](https://doi.org/10.5281/zenodo.17381428)) - **[CDDP-EAGLE-1](https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection_id=cddp_eagle_1)** — Lung adenocarcinoma: 49 patients, ~23 GB ([DOI](https://doi.org/10.5281/zenodo.17372206)) Digital pathology collections from other contributors: - **[CATCH](https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection_id=catch)** — Canine skin cancers (melanoma, squamous cell carcinoma (SCC), malignant peripheral nerve sheath tumor (MPNST)): 282 cases, 350 series, ~571 GB (converted from the data sourced from TCIA) ([DOI](https://doi.org/10.5281/zenodo.18526942)) - **[PDXNet](https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection_id=pdxnet)** — Patient-Derived Xenograft Network (human + mouse models): 919 subjects, 919 series, ~126 GB (submitted by the PDXNet consortium) ([DOI](https://doi.org/10.5281/zenodo.16967600)) - **[HTAN-TNP-SARDANA](https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection_id=htan_tnp_sardana)** — Human Tumor Atlas Network, multiplexed fluorescence SM: colon mucinous adenocarcinoma (sourced from HTAN) ([DOI](https://doi.org/10.5281/zenodo.18488943)) ## 🩻 Radiology New collections curated by The Cancer Imaging Archive (TCIA) - those are ingested “as is”, and are now available via the resources and tools maintained by IDC: - **[EAY131 (NCI-MATCH trial)](https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection_id=eay131)** — The largest new radiology addition in v24. This collection brings imaging from the National Cancer Institute (NCI) Molecular Analysis for Therapy Choice (MATCH) precision oncology trial: 2,813 patients, 30,293 series (~797 gigabytes (GB)), spanning CT, MR, and PET across abdomen, chest, pelvis, and more ([DOI](https://doi.org/10.7937/c5ke-yx42)). It is accompanied by a new analysis results collection, **[EAY131-Tumor-Annotations](https://portal.imaging.datacommons.cancer.gov/explore/filters/?analysis_results_id=EAY131-Tumor-Annotations)**, with tumor annotations for 15,799 series ([DOI](https://doi.org/10.7937/q9rn-m510)). - **[LDCT-and-Projection-data](https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection_id=ldct_and_projection_data)** — 200 patients, 698 series, ~863 GB of low-dose CT data including raw projection data. Valuable for algorithm development at the sinogram level ([DOI](https://doi.org/10.7937/9npb-2637)). - **[PSMA-PET-CT-Lesions](https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection_id=psma_pet_ct_lesions)** — 378 patients with paired prostate-specific membrane antigen (PSMA) PET/CT imaging and lesion segmentations (CT + PT + SEG, ~117 GB) ([DOI](https://doi.org/10.7937/r7ep-3x37)). - **[Spinal-Multiple-Myeloma-SEG](https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection_id=spinal_multiple_myeloma_seg)** — 67 patients with CT + expert segmentations of spinal multiple myeloma (~304 GB). Paired CT and SEG series for all patients ([DOI](https://doi.org/10.7937/k4qv-hh78)). - **[CPTAC-STAD](https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection_id=cptac_stad)** — Stomach adenocarcinoma imaging from the Clinical Proteomic Tumor Analysis Consortium (CPTAC): 20 patients, CT + ultrasound ([DOI](https://doi.org/10.7937/jw9a-8k71)). A new mouse imaging collection was contributed by the University of Washington team led by Paul Kinahan and McGarry Houghton, as part of the [NCI Co-Clinical Imaging Research Resources Program (CIRP)](https://dctd.cancer.gov/research/networks/cirp) consortium activities: - **[UW-CIRP-Mouse-PET-CT-NSCLC](https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection_id=uw_cirp_mouse_pet_ct_nsclc)** — A preclinical mouse model collection with PET/CT and radiotherapy (RT) structure sets for non-small cell lung cancer (NSCLC) research (14 subjects). IDC’s growing support for non-human imaging continues ([DOI](https://doi.org/10.5281/zenodo.17257735)). ## 🔄 Updated Collections - **[BoneMarrowWSI-PediatricLeukemia](https://portal.imaging.datacommons.cancer.gov/explore/filters/?collection_id=bonemarrowwsi_pediatricleukemia)** — 1,027 updated cell-level expert annotations (DICOM ANN series) to fix issues identified in the previous release of this collection ([DOI](https://doi.org/10.5281/zenodo.14933087)). ## 🚀 Get started - Official LLM IDC skill: [GitHub - ImagingDataCommons/idc-claude-skill: Natural language interface to NCI Imaging Data Commons · GitHub](https://github.com/ImagingDataCommons/idc-claude-skill) - the easiest interface for interacting with IDC - Explore in the portal: [https://portal.imaging.datacommons.cancer.gov](https://portal.imaging.datacommons.cancer.gov) - Programmatic access: `pip install --upgrade idc-index` - Getting started notebooks: [GitHub - ImagingDataCommons/IDC-Tutorials: Self-guided notebook tutorials to help get started with IDC · GitHub](https://github.com/ImagingDataCommons/IDC-Tutorials) Full data release notes: [Data release notes | IDC User Guide](https://learn.canceridc.dev/data/data-release-notes#v24)