--- license: cc-by-3.0 task_categories: - image-segmentation tags: - medical - mri - brain - glioblastoma - tumor-segmentation - neuro-oncology - radiomics - BraTS configs: - config_name: default data_files: - split: test path: data/test-* dataset_info: features: - name: patient_id dtype: string - name: study_date dtype: string - name: num_slices dtype: int32 - name: tumor_slice_idx dtype: int32 - name: tumor_voxels_upenn dtype: int64 - name: has_cwru_mask dtype: bool - name: T1 dtype: image - name: T1c dtype: image - name: T2 dtype: image - name: FLAIR dtype: image - name: seg_UPenn dtype: image - name: overlay_UPenn dtype: image - name: seg_CWRU dtype: image - name: overlay_CWRU dtype: image - name: age dtype: string - name: gender dtype: string - name: histopathology dtype: string - name: location dtype: string - name: extent_of_resection dtype: string - name: survival_days dtype: string - name: molecular_subtype dtype: string - name: idh1 dtype: string - name: mgmt dtype: string - name: egfr dtype: string - name: included_upenn dtype: string - name: included_cwru dtype: string splits: - name: test num_bytes: 4779075 num_examples: 34 download_size: 4795822 dataset_size: 4779075 --- # IvyGAP-Radiomics (SRI-atlas subset) Multi-parametric brain-MRI **glioblastoma (GBM)** segmentation dataset: 4 co-registered, skull-stripped MRI sequences per subject with **expert tumor sub-compartment masks** from **two independent institutions**, plus precomputed radiomic features. From the TCIA *Analysis Result* collection **IvyGAP-Radiomics** (Pati et al., 2020). ## ⚠️ Scope — this is a preprocessed subset of the full Ivy GAP project "IvyGAP-Radiomics" is **not** the complete Ivy Glioblastoma Atlas Project (Ivy GAP). It is a derived analysis result containing only the **pre-operative** scans, **skull-stripped** and **co-registered to the SRI24 atlas**, converted to NIfTI, with expert tumor masks and radiomic features added. It does **not** include the original DICOM imaging (~140 GB), histology (ISH), or gene-expression / genomic data of the parent Ivy GAP collection. Only the **SRI-atlas** package is mirrored here (the alternate **MNI-atlas / CWRU-only** package is not included). ## 🔴 Cross-dataset overlap with BraTS (evaluation-integrity hazard) Pre-operative IvyGAP data is **included in the BraTS challenge training set** (together with TCGA-GBM, TCGA-LGG, CPTAC-GBM), and these masks were produced with the **BraTS preprocessing pipeline** (SRI24 atlas, skull-strip) and follow the **BraTS labeling convention**. **Do not** benchmark these subjects against any BraTS-trained model, or alongside `Angelou0516/brats2023-*`, without treating the results as non-held-out — there is likely train/test leakage. Subjects are identified by Ivy GAP IDs (`W1`…`W55`); there is **no published BraTS-ID cross-reference column**, so any mapping to BraTS subjects must be done externally via the Ivy GAP → BraTS name tables. ## Two expert raters — no single gold standard (by design) The dataset's purpose is **inter-rater reproducibility**. Each tumor was segmented independently by board-certified neuroradiologists at **two institutions**: - **UPenn** (Hospital of the University of Pennsylvania) — **34 subjects** - **CWRU** (Case Western Reserve University) — **31 subjects** **31 subjects are paired** (annotated by both). The paper anoints **neither** rater as "the" ground truth — both are equally-valid expert annotations. Both mask sets are provided here. For a single-GT workflow, the recommended default is **UPenn** (broader coverage: 34 vs 31). Subjects without a CWRU mask: **W6, W30, W54**. ## Labels (BraTS convention) | value | sub-compartment | |------:|-----------------| | 0 | background | | 1 | NCR/NET — necrotic & non-enhancing tumor core | | 2 | ED — peritumoral edema / invaded tissue | | 4 | ET — enhancing tumor | Composite regions: **TC** (tumor core) = {1,4}; **WT** (whole tumor) = {1,2,4}; **ET** = {4}. Mask dtypes as released: UPenn `uint16`, CWRU `float32` — both encode the integer labels above (content is preserved byte-for-byte; cast to integer when loading). ## Geometry All volumes are **240 × 240 × 155 @ 1.0 mm isotropic** in **SRI24** space, skull-stripped, LPS orientation. One pre-operative study per subject. ## Structure ``` W{n}/ # one folder per subject, at the repo root W{n}_t1.nii.gz # native T1 W{n}_t1c.nii.gz # post-contrast T1 (T1-Gd; original token "t1gd") W{n}_t2.nii.gz # T2 W{n}_flair.nii.gz # T2-FLAIR W{n}_seg-UPenn.nii.gz # UPenn expert mask (all 34 subjects) W{n}_seg-CWRU.nii.gz # CWRU expert mask (31 subjects) atlas/spgr_unstrip_lps.nii.gz # SRI24 reference template data/test-*.parquet # Dataset Viewer preview only (rendered slices + metadata) radiomic_features/ # CaPTk/IBSI features per rater, feature parameters, reproducibility correlations ivygap_metadata.csv # per-subject clinical & molecular metadata (see below) subject_study_dates.csv # subject -> original study date + which rater masks exist ``` ## `ivygap_metadata.csv` Per-subject metadata keyed by `Patient` (W-ID). Columns include `Included_Upenn`, `Included_CWRU`, `4_Modalities` (inclusion flags), `Age`, `gender`, `Histopathology`, `location`, `EoR` (extent of resection), `Surgery`, `survival_days`, `Molecular_subtype`, `IDH1`, `1p19q_deletion`, `MGMT`/`MGMT PCR`, `EGFR`/`EGFR vIII`, `PTEN`, `KPS(initial)`, time-to-progression / last-follow-up, and cause of death. (The CSV also lists a few subjects that lack 4-modality imaging and are therefore **not** present under `data/`.) ## Provenance, license & citation - **Provenance:** Official TCIA Analysis Result (author-provided), DOI **10.7937/9j41-7d44**. SRI-atlas package downloaded via TCIA IBM-Aspera faspex5. - **License:** **CC BY 3.0** (TCIA Analysis Results) + the TCIA Data Usage Policy. - **Data citation:** Pati, S., Verma, R., Akbari, H., Bilello, M., Hill, V.B., Sako, C., Correa, R., Beig, N., Venet, L., Thakur, S., Serai, P., Ha, S.M., Blake, G.D., Shinohara, R.T., Tiwari, P., Bakas, S. (2020). *Data from the Multi-Institutional Paired Expert Segmentations and Radiomic Features of the Ivy GAP Dataset.* The Cancer Imaging Archive. DOI 10.7937/9j41-7d44. - **Publication:** Pati S, et al. *Reproducibility analysis of multi-institutional paired expert annotations and radiomic features of the Ivy GAP dataset.* Medical Physics 2020;47(12):6039–6052. DOI 10.1002/mp.14556.