UPENN-GBM – Multi-parametric MRI for De Novo Glioblastoma (University of Pennsylvania Health System)
The UPENN-GBM collection provides multi-parametric magnetic resonance imaging (mpMRI) scans and corresponding clinical, histopathologic, and radiomic data from 630 patients with de novo glioblastoma (GBM).
The dataset was curated by the University of Pennsylvania Health System and released through The Cancer Imaging Archive (TCIA) as a comprehensive, open-access imaging resource for studying glioblastoma biology, segmentation reproducibility, and radiogenomic biomarkers.
Each subject includes co-registered and skull-stripped mpMRI scans together with automated and manually corrected tumor segmentation labels that delineate histologically distinct subregions (enhancing core, necrotic core, edema, etc.). These segmentations were refined and approved by expert board-certified neuroradiologists, enabling quantitative analyses without repeated manual annotation.
The dataset also provides a large panel of radiomic features, clinical outcomes, and molecular data, supporting cross-disciplinary research linking imaging, histology, and genomics. For a subset of cases, matched H&E-stained whole-slide histopathology images from resected tumor tissue are available, enabling radiology–pathology correlation.
Overview
- Dataset name: UPENN-GBM (Multi-parametric MRI for De Novo Glioblastoma)
- Institution: University of Pennsylvania Health System
- Repository: The Cancer Imaging Archive (TCIA)
- Species: Human
- Subjects: 630 patients
- Cancer type: Glioblastoma multiforme (GBM)
- Data types: MRI (DICOM/NIfTI), segmentation labels, histopathology, demographics, molecular and radiomic features
- Total size: ~357 GB
- Version: 2 (Updated 2022-10-24)
- DOI: 10.7937/TCIA.709X-DN49
- License: Creative Commons Attribution 4.0 International (CC BY 4.0)
Imaging and Data Modalities
| Data Type | Format | Description | Size | Access |
|---|---|---|---|---|
| MRI Images | DICOM | mpMRI scans including T1, T1-Gd, T2, and FLAIR | 139.4 GB | Download via NBIA Data Retriever |
| MRI + Segmentation | NIfTI | Co-registered mpMRI with tumor and whole-brain segmentation labels | 69 GB | Requires IBM Aspera Connect |
| Histopathology Images | NDPI | Digitized H&E slides from resected tumors | 149 GB | Requires IBM Aspera Connect |
| Clinical Data | CSV | Demographics, molecular tests, and outcomes | 64.9 KB | Direct download |
| Radiomic Features | ZIP/CSV | CaPTk-extracted intensity, texture, and morphologic features | 15.4 MB | Direct download |
| Radiology–Pathology Mapping | CSV | Links imaging and histology IDs | 2.5 KB | Direct download |
| Acquisition Parameters | CSV | MRI scanner and sequence details | 194 KB | Direct download |
| Data Availability per Subject | CSV | File completeness summary | 125 KB | Direct download |
| Radiomic Parameter File | CSV | CaPTk configuration reference | 3.8 KB | Direct download |
Study Description
This dataset integrates clinical, imaging, and molecular data to enable large-scale computational and translational research in glioblastoma.
All MRI volumes were preprocessed (skull stripping and co-registration) prior to segmentation, which was performed via an automated pipeline followed by manual expert correction.
Derived features include:
- Intensity and histogram-based measures
- Volumetric and morphological statistics
- Textural parameters (GLCM, GLRLM, etc.)
- Radiomic descriptors consistent with CaPTk and IBSI standards
The dataset supports:
- Benchmarking of automated tumor segmentation algorithms
- Radiogenomic association studies linking imaging phenotypes to molecular subtypes
- Outcome prediction (e.g., overall survival, progression-free survival)
- Radiology–pathology correlation and cross-modality feature harmonization
Data Access
All data are publicly available through The Cancer Imaging Archive (TCIA).
Use of NBIA Data Retriever or IBM Aspera Connect is required for large downloads.
Version 2 Updates (October 2022):
- Added digitized histopathology (NDPI format)
- Added radiology–pathology mapping CSV
- Harmonized radiomic feature files and metadata
Citation
Bakas, S., Sako, C., Akbari, H., Bilello, M., Sotiras, A., Shukla, G., Rudie, J. D., Flores Santamaria, N., Fathi Kazerooni, A., Pati, S., Rathore, S., Mamourian, E., Ha, S. M., Parker, W., Doshi, J., Baid, U., Bergman, M., Binder, Z. A., Verma, R., … Davatzikos, C. (2021).
Multi-parametric magnetic resonance imaging (mpMRI) scans for de novo Glioblastoma (GBM) patients from the University of Pennsylvania Health System (UPENN-GBM) (Version 2).
The Cancer Imaging Archive.
https://doi.org/10.7937/TCIA.709X-DN49
Users must include this citation in all publications derived from this dataset.
Usage Policy
This collection is released under CC BY 4.0, allowing sharing and adaptation for any purpose (including commercial), provided appropriate attribution is given.
All users must comply with the TCIA Data Usage Policy and Restrictions.
Acknowledgments
This dataset was developed through the collaboration of the University of Pennsylvania Health System, The Cancer Imaging Archive (TCIA), and the National Cancer Institute’s Cancer Imaging Program (CIP).
We thank the contributing radiologists, data scientists, and patients for enabling open-access cancer imaging research.
External Resources
© 2025 The Cancer Imaging Archive (TCIA).
Prepared for redistribution under data-others/disease/upenn-gbm by the Pittsburgh Fiber Data Hub.