--- license: cc-by-nc-3.0 task_categories: - image-segmentation tags: - medical - ct - lung - nsclc - lung-cancer - tumor-segmentation - gtv - inter-observer - radiotherapy - dicom - tcia pretty_name: NSCLC-Radiomics-Interobserver1 size_categories: - n<1K dataset_info: features: - name: patient_id dtype: string - name: ct_series_uid dtype: string - name: rt_series_uid dtype: string - name: num_ct_slices dtype: int32 - name: slice_index dtype: int32 - name: n_observers dtype: int32 - name: consensus_voxels dtype: int64 - name: mean_pairwise_dice dtype: float32 - name: obs1_voxels dtype: int64 - name: obs2_voxels dtype: int64 - name: obs3_voxels dtype: int64 - name: obs4_voxels dtype: int64 - name: obs5_voxels dtype: int64 - name: image dtype: image - name: mask dtype: image - name: overlay dtype: image - name: agreement dtype: image splits: - name: preview num_bytes: 5181371 num_examples: 21 download_size: 5201009 dataset_size: 5181371 configs: - config_name: default data_files: - split: preview path: data/preview-* --- # NSCLC-Radiomics-Interobserver1 Multiple-delineation **inter-observer / inter-method variability** study of gross-tumour-volume (GTV) contouring on pre-treatment thoracic CT of non-small-cell lung cancer (NSCLC). For each tumour, **five radiation oncologists** independently delineated the GTV **twice** — once **manually** (`vis`) and once **auto-segmentation-assisted then edited** (`auto`) — giving up to **10 GTV delineations per patient**. The collection exists specifically to quantify contouring variability, so **there is no single gold-standard mask** by design; all delineations are retained. > ⚠️ **This is NOT the main NSCLC-Radiomics ("Lung1", n=422) collection.** > It is the separate *Interobserver1* sub-collection (22 patients) from the same > Maastricht/Dana-Farber radiomics programme. It is also distinct from the > *RIDER-LungCT-Seg* test/retest arm. See "Relationship to other collections". ## Dataset Details | Field | Value | |---|---| | Modality | CT (pre-treatment, radiotherapy-planning thorax; mostly contrast-enhanced) | | Body part | Thorax / lung | | Task | 3D tumour (GTV) segmentation; inter-observer variability study | | Patients | 22 (21 with delineations; **interobs09** is CT-only) | | Series | 64 total — 22 CT, 21 RTSTRUCT, 21 DICOM SEG | | CT slices | 3,844 | | Observers | 5 radiation oncologists (obs **1 & 3 = trainees**; **2, 4, 5 = experienced**) | | Methods | 2 per observer: `vis` (manual) and `auto` (auto-assisted + manual edit) | | Format | DICOM (CT + RTSTRUCT). DICOM SEG omitted from this mirror — see below | | License | **CC BY-NC 3.0 Unported** (Data Citation Required) | | Source | The Cancer Imaging Archive (TCIA), official author upload | This HuggingFace mirror is a **LEAN raw-DICOM** copy: it contains the **CT images (`images/`)** and the **RTSTRUCT contour objects (`segmentations/`)**. The collection's DICOM **SEG** objects — a rasterised duplicate of the same RTSTRUCT contours — are **not** included here; RTSTRUCT carries every delineation losslessly. A v3 (2020-08-31) revision of the original collection fixed an inadvertent label mismatch between the DICOM SEG and RTSTRUCT objects; this mirror was downloaded after that fix (REST API serves the current version). ## Annotation structure (RTSTRUCT ROI names) Each patient's RTSTRUCT encodes the delineations in its ROI names: | ROI name pattern | Meaning | |---|---| | `GTV-1vis-{1..5}` | **Primary/index tumour**, **manual** delineation by observer 1–5 — present for **all 21** annotated patients | | `GTV-1auto-{1..5}` | Primary tumour, **auto-assisted** delineation by observer 1–5 (20/21; `interobs19` has none) | | `GTV-2{vis|auto}-{1..5}` | **Second tumour** (multi-lesion patients only); observer coverage varies | | `suv2,5` / `suv_2.5` | Auxiliary PET SUV-2.5 threshold auto-contour (not an observer delineation) | | `treshold0,34` / `treshhold0,34` / `tresh_34%` | Auxiliary PET 34%-SUVmax threshold auto-contour | | `treshold-pr` / `treshold-ln` | Auxiliary PET threshold contour (primary / lymph node) | The auxiliary PET-threshold ROIs are part of the original radiotherapy-planning structure sets but are **not** the manual observer delineations and should be excluded from inter-observer analyses. ## Recommended ground truth Because the study is about variability, **all observer delineations are kept**. For benchmarking that needs a single reference mask, the recommended default is the **STAPLE consensus of the five manual delineations of the index tumour** (`GTV-1vis-1` … `GTV-1vis-5`) — a principled probabilistic consensus across all five experts, using the pure-manual (not auto-assisted) contours, available for every annotated patient. Individual per-observer (`vis`/`auto`) contours remain available in the RTSTRUCT for variability studies; second-tumour (`GTV-2*`) and PET-threshold ROIs are present but excluded from the default reference. ## Relationship to other collections - **NSCLC-Radiomics ("Lung1", n=422)** — *different cohort*. Interobserver1 PatientIDs use the `interobsNN` namespace (e.g. `interobs01`), disjoint from Lung1's `LUNG1-xxx`, and use a different CT protocol (contrast-enhanced RT-planning vs. Lung1 non-contrast). No ID-level collision. Still, dedup by `PatientID` / `SeriesInstanceUID` before any joint benchmark. - **RIDER-LungCT-Seg** — the test/retest arm of the same parent radiomics programme; potential shared provenance if both are used together. - `series_to_patient.json` preserves `PatientID`, `SeriesInstanceUID`, `StudyInstanceUID`, `Modality`, and per-series metadata for cross-referencing. ## Structure ``` images///*.dcm # 22 CT series segmentations///*.dcm # 21 RTSTRUCT (Modality=RTSTRUCT) series_to_patient.json # per-series metadata + cross-ref IDs ``` `PatientID` ranges over `interobs01` … `interobs33` (non-contiguous). Each RTSTRUCT references its source CT series via `ReferencedFrameOfReferenceSequence → RTReferencedStudySequence → RTReferencedSeriesSequence → SeriesInstanceUID`. ## Splits The collection does not prescribe train/val/test splits. ## Source - TCIA collection: https://www.cancerimagingarchive.net/collection/nsclc-radiomics-interobserver1/ - DOI: `10.7937/tcia.2019.cwvlpd26` - Fully public — no registration required. ## Citation ```bibtex @misc{wee2019nsclcinterobserver1, author = {Wee, Leonard and Aerts, Hugo J. W. L. and Kalendralis, Petros and Dekker, Andre}, title = {Data From NSCLC-Radiomics-Interobserver1 [Data set]}, year = {2019}, publisher = {The Cancer Imaging Archive}, doi = {10.7937/tcia.2019.cwvlpd26} } @article{kalendralis2020fair, author = {Kalendralis, Petros and Shi, Zhenwei and Traverso, Alberto and others}, title = {FAIR-compliant clinical, radiomics and DICOM metadata of RIDER, interobserver, Lung1 and head-Neck1 TCIA collections}, journal = {Medical Physics}, volume = {47}, number = {11}, pages = {5931--5940}, year = {2020}, doi = {10.1002/mp.14322} } @article{aerts2014decoding, author = {Aerts, Hugo J. W. L. and Velazquez, Emmanuel Rios and Leijenaar, Ralph T. H. and others}, title = {Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach}, journal = {Nature Communications}, volume = {5}, pages = {4006}, year = {2014}, doi = {10.1038/ncomms5006} } @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} } ```