---
license: cc-by-4.0
task_categories:
  - image-segmentation
tags:
  - medical
  - mri
  - ct
  - pet
  - cervix
  - cervical-cancer
  - tumor-segmentation
  - longitudinal
  - chemoradiation
  - rtstruct
  - dicom
  - tcia
pretty_name: TCIA Cervical Cancer (CC-Tumor-Heterogeneity)
size_categories:
  - n<1K
---

# TCIA_CervicalCancer (CC-Tumor-Heterogeneity)

Longitudinal multi-parametric MRI + 18F-FDG PET/CT collection of locally
advanced cervical cancer patients undergoing chemoradiation, with
radiation-oncologist tumor contours (RTSTRUCT) defined on T2-weighted MRI as
the gold standard. Each patient was imaged at three time points spanning the
chemoradiation course.

## Dataset Details

| Field | Value |
|---|---|
| Modalities | MR (T1W, T2W, DCE, DWI), 18F-FDG PET, CT |
| Body part | Cervix / pelvis |
| Task | 3D tumor segmentation on T2W MRI (longitudinal) |
| Patients | 23 (CCTH-A01 … CCTH-A12, CCTH-B01 … CCTH-B11) |
| Time points | 3 per patient — Baseline (0 Gy) / Early (~20–25 Gy, 2–2.5 wk) / Mid-treatment (~45–50 Gy, 4–5 wk) |
| Studies | 171 |
| Series | 821 |
| Images | 131,556 DICOM slices |
| MR series | 523 (15.91 GB) |
| CT series | 65 (11.48 GB) |
| PET series | 68 (0.99 GB) |
| RTSTRUCT files | 68 (≈ 23 patients × 3 time points; CCTH-A06 has 2) |
| REG (registration) files | 97 |
| Format | DICOM (images) + DICOM RTSTRUCT (contours) + DICOM REG (registrations) |
| License | CC BY 4.0 |

## Segmentation

Tumor contours are stored as DICOM **RTSTRUCT** files in `segmentations/`.
Each RTSTRUCT references a single MR T2W sagittal series via
`ReferencedFrameOfReferenceSequence → RTReferencedStudySequence →
RTReferencedSeriesSequence.SeriesInstanceUID` — that referenced series is the
image volume the contour is defined on. ROI names follow `Ut-MRT2-Sag-{1|2|3}`
where the trailing index matches the time point (1 = Baseline, 2 = Early,
3 = Mid-treatment), and `StructureSetName` carries `Timepoint{1|2|3}`.

The collection paper describes contours as **tumor volume only — no OARs and
no lymph nodes**, drawn by the study radiation oncologists with T2W MRI
chosen for its highest soft-tissue contrast for cervical tumor delineation.

## Structure

```
images_mr/<PatientID>/<StudyInstanceUID>/<SeriesInstanceUID>/*.dcm     # MR (T1W, T2W, DCE, DWI variants)
images_ct/<PatientID>/<StudyInstanceUID>/<SeriesInstanceUID>/*.dcm     # CT
images_pt/<PatientID>/<StudyInstanceUID>/<SeriesInstanceUID>/*.dcm     # PET
segmentations/<PatientID>/<StudyInstanceUID>/<SeriesInstanceUID>/*.dcm  # RTSTRUCT (one per time point)
registrations/<PatientID>/<StudyInstanceUID>/<SeriesInstanceUID>/*.dcm  # DICOM REG (PET/CT ↔ MR coregistration)
series_to_patient.json                                                  # series-level index
```

`PatientID` ranges over `CCTH-A01..A12` and `CCTH-B01..B11`. `StudyDescription`
in each RTSTRUCT carries `MR1` / `MR2` / `MR3`, identifying the time point.
CCTH-B11 has no CT series; CCTH-A06 has 2 RTSTRUCTs (one time point missing).

## Source

- TCIA collection: https://www.cancerimagingarchive.net/collection/cc-tumor-heterogeneity/
- DOI: `10.7937/ERZ5-QZ59`
- License URL: https://creativecommons.org/licenses/by/4.0/
- Released: 2023-01-20 (now fully public, no registration required)

## Citation

```bibtex
@misc{mayr2023ccth,
  author    = {Mayr, N. and Yuh, W. T. C. and Bowen, S. and Harkenrider, M. and
               Knopp, M. V. and Lee, E. Y.-P. and Leung, E. and Lo, S. S. and
               Small Jr., W. and Wolfson, A. H.},
  title     = {Cervical Cancer -- Tumor Heterogeneity: Serial Functional and
               Molecular Imaging Across the Radiation Therapy Course in
               Advanced Cervical Cancer (Version 1) [Data set]},
  year      = {2023},
  publisher = {The Cancer Imaging Archive},
  doi       = {10.7937/ERZ5-QZ59}
}

@article{bowen2017radiomic,
  author  = {Bowen, S. R. and Yuh, W. T. C. and Hippe, D. S. and Wu, W. and
             Partridge, S. C. and Elias, S. and Jia, G. and Huang, Z. and
             Sandison, G. A. and Nelson, D. and Knopp, M. V. and Lo, S. S. and
             Kinahan, P. E. and Mayr, N. A.},
  title   = {Tumor radiomic heterogeneity: Multiparametric functional imaging
             to characterize variability and predict response following
             cervical cancer radiation therapy},
  journal = {Journal of Magnetic Resonance Imaging},
  volume  = {47},
  number  = {5},
  pages   = {1388--1396},
  year    = {2017},
  doi     = {10.1002/jmri.25874}
}
```