Add IvyGAP-Radiomics (SRI-atlas): 34 GBM subjects, 4 MRI seq, UPenn+CWRU masks, radiomics

.gitattributes

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README.md

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+---
+license: cc-by-3.0
+task_categories:
+- image-segmentation
+tags:
+- medical
+- mri
+- brain
+- glioblastoma
+- tumor-segmentation
+- neuro-oncology
+- radiomics
+- BraTS
+---
+
+# 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
+```
+data/
+  W{n}/
+    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
+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.

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