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  • The Río Hortega University Hospital Glioblastoma dataset: a comprehensive collection of preoperative, early postoperative and recurrence MRI scans (RHUH-GBM)

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titleData Access

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Localtab
titleDetailed Description

Detailed Description

Image Statistics

Radiology Image Statistics

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Number of Patients


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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. 


Localtab
titleCitations & Data Usage Policy

Citations & Data Usage Policy

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titleData Citation

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


Info
titlePublication Citation

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

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titleVersions

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