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MRI Brain

UCSF-PDGM

The University of California San Francisco Preoperative Diffuse Glioma MRI

Brain MRI before surgery of patients with diffuse gliomas on one standardized protocol, with tumor segmentations, molecular markers and survival, for segmentation, molecular prediction and survival modelling. 495 patients from UCSF, with susceptibility, perfusion and diffusion beyond the usual four contrasts.

Overview

UCSF-PDGM is a single-center collection of preoperative brain MRI from patients with diffuse gliomas, released by the Center for Intelligent Imaging at UCSF and hosted by The Cancer Imaging Archive. Unlike most public glioma sets, which stop at four structural contrasts acquired on mixed scanners, every exam here follows one standardized 3 T protocol and adds susceptibility, perfusion and multi-direction diffusion imaging. It is used for tumor segmentation, prediction of molecular markers from imaging and survival modeling.

Composition

The release holds 501 exams of 495 patients. Six exam IDs turned out to be repeat scans of other patients taken 1 to 175 days later; version 3 renamed them with a _FU suffix. Patients had histologically confirmed WHO grade 2 to 4 diffuse gliomas, imaged before their first resection between 2015 and 2021, with no prior tumor treatment other than biopsy. By the WHO 2021 diagnosis in the clinical table, 368 patients have IDH-wildtype glioblastoma. The table also lists sex, age at MRI, grade, IDH, MGMT and 1p/19q status, extent of resection, survival status and overall survival in days, plus the matching BraTS 2021 ID where a case was part of that challenge.

Acquisition

All scans come from one GE Discovery 750 3 T scanner with an 8-channel head coil. The protocol covers 3D T2, FLAIR, pre- and post-contrast T1, SWI, DWI, 3D ASL perfusion and 2D HARDI with 55 directions. HARDI data were eddy-current corrected and fitted with FSL to give mean, axial and radial diffusivity and fractional anisotropy maps. Every contrast was non-linearly registered to the 1 mm isotropic FLAIR space, skull-stripped with a deep-learning tool and shared as NIfTI. No DICOM data are released.

Annotations

Tumor segmentations were made within BraTS 2021: an ensemble of earlier challenge models produced a draft, which trained radiologists corrected and two expert reviewers approved. Labels separate enhancing tumor, non-enhancing or necrotic core and the surrounding FLAIR abnormality.

Known limitations

  • One center and one scanner, so models trained on it may not transfer to other sites.
  • Only preprocessed, co-registered images are provided; the raw acquisitions are not available.
  • MGMT status is missing for most lower-grade tumors, and 1p/19q status is often unknown.
  • Race and ethnicity were not available to the creators.
  • The 2021 preprint counts 500 patients and the release first listed 501; the follow-up duplicates were found later.

Cohort

Aggregate numbers from the sources below. Bars are relative to the 495 subjects.

Age

mean 56.9, median 59

0
50
100
139
10-1920-2930-3940-4950-5960-6970-7980+

column Age at MRI in UCSF-PDGM-metadata_v5.csv clinical data (CC BY 4.0, direct download), counted per patient after dropping the six follow-up exams whose IDs end in _FU

Scanner vendor

  • GE HealthCare 495 100%

Image Acquisition in TCIA UCSF-PDGM collection page (version 5, updated 2025/05/30)

Country

  • United States 495 100%

Patient Population in TCIA UCSF-PDGM collection page (version 5, updated 2025/05/30)

Age by sex

Reported cross table. Missing cells were not published (fewer than 10 or not reported).

Female Male
  • 33
    70-79
    53
  • 61
    60-69
    78
  • 46
    50-59
    58
  • 18
    40-49
    50
  • 23
    30-39
    32
  • n/a
    20-29
    14

columns Sex and Age at MRI in UCSF-PDGM-metadata_v5.csv clinical data (CC BY 4.0, direct download), counted per patient after dropping the six follow-up exams whose IDs end in _FU

License and access

Our reading of the license, not legal advice. Before you use the data, read the original license and confirm that your use is allowed. We take no responsibility for how you use a dataset. Full disclaimer

Access
Open download

Download without an account

Images (NIfTI, skull-stripped and co-registered) download with the IBM Aspera Connect plugin; the clinical CSV is a direct download. Original DICOM data are not provided.

Access page

Creative Commons Attribution 4.0 International

Use, share and adapt the data for any purpose, including commercial use, as long as you credit the creators.

The TCIA page lists CC BY 4.0 for the images, the clinical data and the b-value and b-vector files. Users must also follow the TCIA Data Usage Policy, which asks users to acknowledge the dataset and not to use it "to identify or contact individual participants" (https://www.cancerimagingarchive.net/data-usage-policies-and-restrictions/).

Original license text Version read: 4.0 Checked 2026-10-07

What you can do

  • Yes
  • Yes
  • Yes
  • Yes
  • Yes

What you can share

  • Yes
  • Yes
  • Yes

What you must do

  • Yes
  • Share alike No
  • No
  • No
  • Manuscript review No
  • Release code No
  • Return results No
  • Delete after use No

Limits

  • No
  • Location limits No

Citation

Calabrese E, Villanueva-Meyer JE, Rudie JD, Rauschecker AM, Baid U, Bakas S, Cha S, Mongan JT, Hess CP. The University of California San Francisco Preoperative Diffuse Glioma MRI Dataset. Radiology: Artificial Intelligence 4(6), e220058 (2022). https://doi.org/10.1148/ryai.220058. Data: Calabrese E, et al. (2022). The University of California San Francisco Preoperative Diffuse Glioma MRI (UCSF-PDGM) (Version 5) [dataset]. The Cancer Imaging Archive. https://doi.org/10.7937/tcia.bdgf-8v37

Sources

Every number on this page comes from one of these documents. Each chart names the table or page it is taken from. The raw numbers are in stats.csv.