README.md

---
license: cc-by-4.0
task_categories:
  - image-segmentation
tags:
  - medical
  - ct
  - pelvis
  - prostate
  - radiotherapy
  - organs-at-risk
  - rtstruct
  - dicom
  - tcia
  - autosegmentation
  - edge-cases
pretty_name: Prostate Anatomical Edge Cases (pelvic OAR CT)
size_categories:
  - n<1K
---

# Prostate-Anatomical-Edge-Cases

**Stress-Testing Pelvic Autosegmentation Algorithms Using Anatomical Edge Cases** —
a TCIA collection of **pelvic radiotherapy planning CT** with manually contoured
organs at risk, curated so that most cases contain anatomy known to break
autosegmentation algorithms (Kanwar et al., *Phys Imaging Radiat Oncol* 2023).

> **Read before using — the name is misleading in two ways:**
> 1. **This is CT, not MRI.** Despite "Prostate" in the name it is *not* a prostate
>    mpMRI/zonal dataset: there is no T2W/DWI/ADC, no peripheral or transition
>    zone, no urethra, and **no lesion labels**. It is RT simulation CT with
>    pelvic organ-at-risk contours, and 4 of the 5 classes are not the prostate.
> 2. **"Edge cases" means difficult *anatomy*, not difficult lesions.** The cohort
>    was selected for hip arthroplasty hardware, prostatic median-lobe hypertrophy,
>    "droopy" seminal vesicles, Foley catheters, SpaceOAR hydrogel, brachytherapy
>    seeds/calcifications, extracapsular surface irregularity, narrow rectum,
>    in-field bowel and morbid obesity — features that degrade atlas-, model- and
>    deep-learning-based contouring.

## Dataset Details

| Field | Value |
|---|---|
| Modality | CT (RT simulation) + DICOM RTSTRUCT contours |
| Body part | Pelvis — prostate and surrounding organs at risk |
| Task | 3D multi-organ segmentation |
| Patients | 131 (112 anatomical edge cases + 19 normal controls) |
| Series | 262 = 131 CT + 131 RTSTRUCT (1:1 paired) |
| CT slices | 23,359 (min 86 / median 167 / max 379 per case) |
| Scanner | Philips Brilliance Big Bore (100%); RTSTRUCT exported from Varian ARIA RTM |
| Format | DICOM (CT) + DICOM RTSTRUCT (contours) |
| Size | ~17 GB |
| License | CC BY 4.0 |
| DOI | `10.7937/QSTF-ST65` |
| Source | Oregon Health & Science University (single institution) |

There is **no train/val/test split** — this is a stress-test cohort, not a
challenge. Splitting is left to the consumer.

## Classes

Five foreground structures, present in the `StructureSetROISequence` of every
case, named per TG-263 and all typed `ORGAN`:

| Label | ROI name |
|---|---|
| 0 | background |
| 1 | `Prostate` |
| 2 | `Rectum` |
| 3 | `Bladder` |
| 4 | `Femur_Head_L` |
| 5 | `Femur_Head_R` |

## Ground Truth — single manual tier

Every ROI in every case carries `ROIGenerationAlgorithm = MANUAL`. The contours
were drawn by a single radiation oncologist, peer-reviewed, and used clinically
for treatment planning — so there is exactly one annotation tier and no rater
ambiguity.

The three autosegmentation outputs benchmarked in the paper (atlas-based/MIM,
model-based/RayStation, deep-learning U-Net/RayStation v9B) were **not** deposited;
all 262 series report `ThirdPartyAnalysis = NO`. The RTSTRUCTs here are the gold
standard, not algorithm output.

## Important Notes for Loaders

These were verified by parsing all 131 RTSTRUCT objects and are easy to get wrong:

- **15 of 131 cases declare an ROI with zero contours.** The ROI appears in
  `StructureSetROISequence` but its `ContourSequence` is empty, so naive code
  silently emits an all-background mask for that class instead of skipping it.
  Only **116/131 have all five structures non-empty**:

  | Empty structure | n | Patient IDs (`Prostate-AEC-…`) |
  |---|---|---|
  | `Rectum` | 7 | 009, 116, 117, 119, 125, 127, 134 |
  | `Femur_Head_L` | 4 | 020, 037, 106, 111 |
  | `Femur_Head_R` | 3 | 010, 012, 027 |
  | `Prostate` | 1 | 072 |
  | `Bladder` | 0 | — (always present) |

- **`Prostate-AEC-101` carries a sixth ROI, `BODY`** (external contour). Build
  masks by matching ROI **name**, never by ROI index or order.
- **Patient IDs are non-contiguous**: `Prostate-AEC-001` … `Prostate-AEC-134`
  with **021, 032 and 043 absent** → 131 patients.
- **`ApprovalStatus = UNAPPROVED` on all 131.** This is a de-identification
  re-export artifact and contradicts the paper's "clinically approved" statement —
  do **not** use it as a quality filter.
- **`Prostate-AEC-072` is doubly suspect**: empty `Prostate` plus a `Rectum` whose
  contours integrate to an anatomically implausible volume. Consider excluding it.
- **Dates are shifted** (`StudyDate` reads 1992–2003 for a 2011–2019 cohort) and
  `PatientIdentityRemoved = YES`.
- **Rasterisation**: each RTSTRUCT references exactly one CT series via
  `ReferencedFrameOfReferenceSequence`, so contour→labelmap conversion with
  `rt_utils` (or manual polygon filling against the CT `ImagePositionPatient` grid)
  is unambiguous.

## Cohort labels (edge case vs control) are NOT in this release

The paper's Data Availability statement says "edge case labels and basic
demographic data have been deposited on TCIA", but **they were not**. TCIA exposes
only the manifest and the NBIA digest; the RTSTRUCT headers carry no edge-case
tag, no `ClinicalTrialSubjectID` and no `PatientComments`.

The 112-vs-19 edge/control assignment and the 8 anatomical-variant classes
(prostate hypertrophy 52, droopy seminal vesicles 37, hip arthroplasty 11, surface
irregularity 9, calcifications/seeds 8, Foley catheter 4, SpaceOAR 4, narrow rectum
2, in-field bowel 1, morbid obesity 1 — overlapping, so multi-label) exist **only
in the paper's Supplementary Table 2**. That table also numbers cases 1–131
contiguously while TCIA uses 001–134 with gaps, so the join is not the identity
map. This mirror deliberately ships **only what TCIA publishes** rather than a
derived mapping.

## Cross-dataset Overlap

**None known.** Every widely-used prostate segmentation set is MRI from a different
institution, whereas this is CT from OHSU: PROMISE12, PI-CAI, QIN-PROSTATE,
Prostate-3T, PROSTATEx, NCI-ISBI 2013, MSD Task05_Prostate, ProstateX-Seg-HiRes,
Prostate-MRI-US-Biopsy and Prostate Fused-MRI-Pathology all share neither modality
nor cohort. TCIA reports "No related Collections found", and there is no
cross-reference ID field — `Prostate-AEC-###` IDs are collection-local.

## Structure

```
images/<PatientID>/<SeriesInstanceUID>/*.dcm          # CT (131 series, 23,359 slices)
segmentations/<PatientID>/<SeriesInstanceUID>/*.dcm    # RTSTRUCT (131 objects, 1 per patient)
series_to_patient.json                                 # series-level metadata (all 262)
LICENSE.txt
```

`series_to_patient.json` keys each `SeriesInstanceUID` to: `PatientID`,
`Collection`, `StudyInstanceUID`, `Modality`, `SeriesDescription`, `SeriesNumber`,
`BodyPartExamined`, `Manufacturer`, `ManufacturerModelName`, `ImageCount`,
`FileSize`, `License`, `DOI`, `ThirdPartyAnalysis`, and the relative `path` — so
CT↔RTSTRUCT pairing needs no TCIA round-trip.

## Source & Citation

- TCIA collection: https://www.cancerimagingarchive.net/collection/prostate-anatomical-edge-cases/
- DOI: `10.7937/QSTF-ST65`
- Official, author-deposited (Thompson, Kanwar, Merz, Cohen, Fisher, Rana, Claunch,
  Hung); fully public, no registration required.

```bibtex
@article{kanwar2023edgecases,
  author  = {Kanwar, Aasheesh and Merz, Brandon and Claunch, Cheryl and
             Rana, Shushan and Hung, Arthur and Thompson, Reid F.},
  title   = {Stress-testing pelvic autosegmentation algorithms using anatomical
             edge cases},
  journal = {Physics and Imaging in Radiation Oncology},
  volume  = {25},
  pages   = {100413},
  year    = {2023},
  doi     = {10.1016/j.phro.2023.100413}
}

@misc{thompson2023paec,
  author    = {Thompson, R. F. and Kanwar, A. and Merz, B. and Cohen, E. and
               Fisher, H. and Rana, S. and Claunch, C. and Hung, A.},
  title     = {Stress-Testing Pelvic Autosegmentation Algorithms Using Anatomical
               Edge Cases [Data set]},
  year      = {2023},
  publisher = {The Cancer Imaging Archive},
  doi       = {10.7937/QSTF-ST65}
}

@article{clark2013tcia,
  author  = {Clark, Kenneth and Vendt, Bruce and Smith, Kirk and others},
  title   = {The Cancer Imaging Archive (TCIA): Maintaining and Operating a
             Public Information Repository},
  journal = {Journal of Digital Imaging},
  volume  = {26},
  number  = {6},
  pages   = {1045--1057},
  year    = {2013},
  doi     = {10.1007/s10278-013-9622-7}
}
```