| --- |
| 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} |
| } |
| ``` |
| |
