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  • Burdenko's Glioblastoma Progression Dataset (Burdenko-GBM-Progression)

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Summary

The Burdenko's Glioblastoma Progression Dataset (B-GBM-PD) is a systematic data collection of pre-radiotherapy MRI images of 180 patients with primary glioblastoma treated at the Burdenko National Medical Research Center of Neurosurgery between 2014 and 2020. We provide four MRI sequences for all patients - T1, T1c, T2, FLAIR; topometric CT scan; and annotations of the GTV area made for radiotherapy planning. Additionally, the data collection contains follow-up studies (from 1 to 7-time points per patient). Each time-point includes 2-4 MRI sequences (with a minimal set of T1c, FLAIR per patient) with contours of the irradiated volumes. The RTDOSE, RTPLAN files; additional genetic information (IDH1/2, MGMT mutations); and treatment response status (tumor progression, tumor pseudoprogression, treatment response) are available for a subset of subjects. MRI studies were performed on various scanners from different vendors. CT studies were conducted in Burdenko National Medical Research Center of Neurosurgery on a single scanner.


Dataset was collected in the radiation therapy department. The benchmark on the current dataset might be closer to clinical practice owing to data minimal preprocessing, heterogeneity in scanning modalities, sufficient size of the dataset, and longitudinal patient imaging data. It is a novel dataset compared to other TCIA collections. It contains four MRI imaging sequences for each patient (and a CT scan) and manual annotations of the glioblastoma gross tumor volumes (GTV) for radiation treatment planning, thus, complementing BraTS and TCIA-GBM datasets for brain tumor segmentation. The task of delineating GTV currently lacks large publicly available data. Availability of follow-up images allows for assessment of treatment response and development of disease progression models. We provide biological and clinical information along with imaging data: sex, age, idh1/2, mgmt mutations, and treatment response.

Acknowledgements

We would like to acknowledge the individuals and institutions that have provided data for this collection:

  • Hospital/Institution Name city, state, country - Special thanks to First Last Names, degree PhD, MD, etc from the Department of xxxxxx, Additional Names from same location.

  • Continue with any names from additional submitting sites if collection consists of more that one.

Data Access

Some data in this collection contains images that could potentially be used to reconstruct a human face. To safeguard the privacy of participants, users must sign and submit a TCIA Restricted License Agreement to help@cancerimagingarchive.net before accessing the data.


Data TypeDownload all or Query/FilterLicense

Images, Segmentations, and Radiation Therapy Structures/Doses/Plans (DICOM, XX.X GB)

<< latter two items only if DICOM SEG/RTSTRUCT/RTDOSE/PLAN exist >>

   

(Download requires NBIA Data Retriever)

Tissue Slide Images (SVS, XX.X GB)

   

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Clinical data (CSV)

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Third Party Analyses of this Dataset

TCIA encourages the community to publish your analyses of our datasets. Below is a list of such third party analyses published using this Collection:

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Detailed Description

Image Statistics

Radiology Image StatisticsPathology Image Statistics

Modalities

CTs, MRIs, RTSTRUCTS, .CSVs

MR, CT, RT

Number of Patients

180


Number of Studies

2000


Number of Series



Number of Images



Images Size (GB)

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Citations & Data Usage Policy

Users must abide by the TCIA Data Usage Policy and Restrictions. Attribution should include references to the following citations:

Data Citation

DOI goes here. Create using Datacite with information from Collection Approval form

Publication Citation

We ask on the proposal form if they have ONE traditional publication they'd like users to cite.

Acknowledgement

Required acknowledgements only (ex:The CPTAC program requests that publications using data from this program...). If they just want to thank someone, that goes in the Acknowledgement section underneath the Summary.

TCIA Citation

Clark, K., Vendt, B., Smith, K., Freymann, J., Kirby, J., Koppel, P., Moore, S., Phillips, S., Maffitt, D., Pringle, M., Tarbox, L., & Prior, F. (2013). The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository. In Journal of Digital Imaging (Vol. 26, Issue 6, pp. 1045–1057). Springer Science and Business Media LLC. https://doi.org/10.1007/s10278-013-9622-7

Other Publications Using This Data

TCIA maintains a list of publications which leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk.

Version X (Current): Updated yyyy/mm/dd

Data TypeDownload all or Query/FilterLicense

Images, Segmentations, and Radiation Therapy Structures/Doses/Plans (DICOM, XX.X GB)

<< latter two items only if DICOM SEG/RTSTRUCT/RTDOSE/PLAN exist >>

    (Download requires the NBIA Data Retriever)

Tissue Slide Images (SVS, XX.X GB)
Clinical data (CSV)

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