README.md

---
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.