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active | true |
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title | Data Access |
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| Data AccessData Type | Download all or Query/Filter | License |
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Images (DICOM, XX.X GB) |
(Download requires NBIA Data Retriever) | | Brain-extracted Images (NIfTI, 2.9 GB) |
(Download requires Aspera plugin) | | Clinical data (CSV) | | |
Click the Versions tab for more info about data releases. Additional Resources for this DatasetNote to curators! Below are examples for what to do with other external resources/links that don't fit into the above categories. The following external resources have been made available by the data submitters. These are not hosted or supported by TCIA, but may be useful to researchers utilizing this collection.
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Localtab |
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title | Detailed Description |
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| Detailed DescriptionImage Statistics | Radiology Image Statistics |
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Modalities | MR | Number of Patients | 40 | Number of Studies | 121 | Number of Series | 554 | Number of Images | 37,425 (DICOM) + 720 (NIfTI) | Images Size (GB) | XX GB + 2.9 GB (NIfTI) |
Note: in the Clinical data file, “Right Censored” value = “yes” indicate that the person died during the data-gathering period. “No” indicates they were “still alive” when the data-gathering period concluded. The inclusion criteria were: Primary newly diagnosed WHO grade 4 astrocytoma adult patients (age over 18 years) who underwent surgery. Gross total resections (GTR) and Near Total Resection (NTR) were defined as no residual tumor enhancement and an extent of resection of more than 95% of the initial enhancing volume, respectively. Patients were treated according to the Stupp protocol. Tumor progression was defined according to the modified Response assessment in neuro-oncology criteria (RANO). The exclusion criteria were: Other histopathological diagnoses, tumor recurrence cases (second surgery), patients in which it was impossible to establish the diagnosis of progression vs. pseudo-progression, missing MRI sequences, and poor-quality MRI scans due to the presence of artifacts. The dataset includes T1-weighted (T1w), T2-weighted (T2w), FLAIR (Fluid attenuated inversion recovery), T1w contrast-enhanced (T1ce) sequences, and diffusion-weighted imaging-derived apparent diffusion coefficient (ADC) maps. The acquisition protocols were: Scanner manufacturer and field strength: General Electric, Signa HDxT, 1.5 T. T1ce: TR/TE, 7.98 ms/2.57 ms; FOV, 220 x 220mm; matrix, 512 x 512; slice thickness, 1mm. T1w: TR/TE, 5.98ms/1.83ms; FOV, 220 x 220mm; matrix, 512 x 512; slice thickness, 1.6mm. T2w: TR/TE, 5220 ms/96.12 ms; FOV, 220 x 220mm; matrix, 512 x 512; slice thickness, 5mm. FLAIR: TR/TE, 11000ms/142.43ms; FOV, 220 x 220mm; matrix, 512 x 512; slice thickness, 4mm. DWI: TR/TE, 8000ms/111.7ms; FOV, 256 x 256mm; matrix, 128 x 160; slice thickness, 5mm; b-values, 0 and 1000 s/mm2. The dataset includes clinical and pathological information: Age, Sex, preoperative and postoperative Karnofsky performance score, Overall survival, Progression-free survival, percentage of the extent of resection of enhancing tumor, systemic therapy received, details of RT received (dose, technique, number of fractions, isodose), IDH status, ATRX mutation, and Ki-67 index, size of enhancing tumor recurrence. The images have been preprocessed using the CaPTk software (https://cbica.github.io/CaPTk/), according to the BraTS Challenge pipeline (http://braintumorsegmentation.org). The dataset includes the segmentations of the enhancing tumor, necrosis, and peritumoral region from the pre-postoperative and follow-up studies that experts have manually corrected. The dataset represents a sample of unique characteristics by including patients with an extent of resection of > 95 % of the enhancing tumor. |
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title | Citations & Data Usage Policy |
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| Citations & Data Usage Policy Tcia limited license policy |
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Info |
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| Cepeda, S., García-García, S., Arrese, I., Herrero, F., Escudero, T., Zamora, T., & Sarabia, R. (2023) The Río Hortega University Hospital Glioblastoma dataset: a comprehensive collection of preoperative, early postoperative and recurrence MRI scans (RHUH-GBM) [Dataset]. The Cancer Imaging Archive. https://doi.org/10.7937/4545-c905
DRAFT MODE PER APR 21 2023 |
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title | Publication Citation |
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| Cepeda, S., Garcia-Garcia, S., Arrese, I., Herrero, F., Escudero, T., Zamora, T., & Sarabia, R. (2023). The Rio Hortega University Hospital Glioblastoma dataset: a comprehensive collection of preoperative, early postoperative and recurrence MRI scans (RHUH-GBM) (Version 2). arXiv. https://doi.org/10.48550/arXiv.2305.00005 |
Info |
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| 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 DataTCIA maintains a list of publications which leverage TCIA data. If you have a manuscript you'd like to add please contact the TCIA Helpdesk. |
Localtab |
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| Version X (Current): Updated yyyy/mm/ddData Type | Download all or Query/Filter | License |
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Images (DICOM, XX.X GB) |
(Download requires NBIA Data Retriever) | | Brain-extracted Images (NIfTI, XX.X MB) |
(Download requires Aspera plugin) | | Clinical data (CSV) | | |
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