This dataset contains the ONCOhabitats processing results for the patients with complete pre-surgical MRI (T1, T1-Gd, T2, FLAIR and DSC perfusion) in The Cancer Genome Atlas Glioblastoma Multiforme (TCGA-GBM) dataset. The ONCOhabitats platform includes two main services: 1. The glioblastoma (GBM) segmentation service implements the MRI preprocessing and GBM morphological segmentation modules. • Preprocessing: Several artefacts are corrected in this module such as magnetic bias field inhomogeneities, noise or spike artifacts. Additionally, automated registration, brain extraction and intensity normalization are conducted to generate a consistent multi-parametric high quality MRI of the brain. • Segmentation: This module implements a state of the art 3D Convolutional Neural Network (CNN) classifier based on a U-Net architecture to delineate the tumor tissues. 2. The GBM Hemodynamic Tissue Signature service implements the MRI preprocessing, GBM morphological segmentation, DSC quantification and the Hemodynamic Tissue Signature modules. • Preprocessing: Several artefacts are corrected in this module such as magnetic bias field inhomogeneities, noise or spike artifacts. Additionally, automated registration, brain extraction and intensity normalization are conducted to generate a consistent multi-parametric high quality MRI of the brain. • Segmentation: This module implements a state of the art 3D Convolutional Neural Network (CNN) classifier based on a U-Net architecture to delineate the tumor tissues. • DSC Perfussion Quantification: This module quantifies the hemodynamic indices derived from of the Dynamic Susceptibility Contrast perfusion sequence. Cerebral Blood Volume (CBV), Cerebral Blood Flow (CBF), Mean Transit Time (MTT) are computed. • Hemodynamic Tissue Signature: Hemodynamic MTS provides an automated unsupervised method to describe the heterogeneity of the enhancing tumor and edema tissues, in terms of the angiogenic process located at these regions. We consider 4 sub-compartments for the GBM, closely related to the more angiogenic enhancing tumor part, the less angiogenic enhancing tumor area, the potentially tumour infilatrated edema and the pure vasogenic edema. For each patient, we include a PDF report containing an analysis summary; two folders with the resulting images in MNI and native spaces; and a third folder with the transformation matrices. Publication that used this data Chelebian, E., Fuster-Garcia, E., Álvarez-Torres, M. D. M., Juan-Albarracín, J., & García-Gómez, J. M. (2020). Higher vascularity at infiltrated peripheral edema differentiates proneural glioblastoma subtype. Plos one, 15(10), e0232500. ONCOhabitats workflow and validation 1. Juan-Albarracín, J., Fuster-Garcia, E., Pérez-Girbés, A., Aparici-Robles, F., Alberich-Bayarri, Á., Revert-Ventura, A., ... & García-Gómez, J. M. (2018). Glioblastoma: vascular habitats detected at preoperative dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging predict survival. Radiology, 287(3), 944-954. 2. Álvarez‐Torres, M., Juan‐Albarracín, J., Fuster‐Garcia, E., Bellvís‐Bataller, F., Lorente, D., Reynés, G., ... & García‐Gómez, J. M. (2020). Robust association between vascular habitats and patient prognosis in glioblastoma: An international multicenter study. Journal of Magnetic Resonance Imaging, 51(5), 1478-1486. Users must abide by the TCIA Data Usage Policy and Restrictions. Attribution should include references to the following citations: TCGA Attribution "The results <published or shown> here are in whole or part based upon data generated by the TCGA Research Network: http://cancergenome.nih.gov/." Data Citation Scarpace, L., Mikkelsen, T., Cha, S., Rao, S., Tekchandani, S., Gutman, D., Saltz, J. H., Erickson, B. J., Pedano, N., Flanders, A. E., Barnholtz-Sloan, J., Ostrom, Q., Barboriak, D., & Pierce, L. J. (2016). The Cancer Genome Atlas Glioblastoma Multiforme Collection (TCGA-GBM) (Version 4) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2016.RNYFUYE9 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

{"references": ["Scarpace, L., Mikkelsen, T., Cha, S., Rao, S., Tekchandani, S., Gutman, D., Saltz, J. H., Erickson, B. J., Pedano, N., Flanders, A. E., Barnholtz-Sloan, J., Ostrom, Q., Barboriak, D., & Pierce, L. J. (2016). Radiology Data from The Cancer Genome Atlas Glioblastoma Multiforme [TCGA-GBM] collection [Data set]. The Cancer Imaging Archive", "Juan-Albarrac\u00edn, J., Fuster-Garcia, E., P\u00e9rez-Girb\u00e9s, A., Aparici-Robles, F., Alberich-Bayarri, \u00c1., Revert-Ventura, A., ... & Garc\u00eda-G\u00f3mez, J. M. (2018). Glioblastoma: vascular habitats detected at preoperative dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging predict survival. Radiology, 287(3), 944-954.", "Juan-Albarrac\u00edn, J., Fuster-Garcia, E., Garc\u00eda-Ferrando, G. A., & Garc\u00eda-G\u00f3mez, J. M. (2019). ONCOhabitats: A system for glioblastoma heterogeneity assessment through MRI. International journal of medical informatics, 128, 53-61.", "\u00c1lvarez\u2010Torres, M., Juan\u2010Albarrac\u00edn, J., Fuster\u2010Garcia, E., Bellv\u00eds\u2010Bataller, F., Lorente, D., Reyn\u00e9s, G., ... & Garc\u00eda\u2010G\u00f3mez, J. M. (2020). Robust association between vascular habitats and patient prognosis in glioblastoma: An international multicenter study. Journal of Magnetic Resonance Imaging, 51(5), 1478-1486.", "Juan-Albarrac\u00edn, J., Fuster-Garcia, E., Manjon, J. V., Robles, M., Aparici, F., Mart\u00ed-Bonmat\u00ed, L., & Garcia-Gomez, J. M. (2015). Automated glioblastoma segmentation based on a multiparametric structured unsupervised classification. PloS one, 10(5), e0125143.", "Juan-Albarrac\u00edn, J. (2020). Unsupervised learning for vascular heterogeneity assessment of glioblastoma based on magnetic resonance imaging: The Hemodynamic Tissue Signature. arXiv preprint arXiv:2009.06288.", "Juan-Albarrac\u00edn, J., Fuster-Garcia, E., & Garc\u00eda-G\u00f3mez, J. M. (2016, October). An online platform for the automatic reporting of multi-parametric tissue signatures: A case study in Glioblastoma. In International Workshop on Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries (pp. 43-51). Springer, Cham.", "Fuster\u2010Garcia, E., Juan\u2010Albarrac\u00edn, J., Garc\u00eda\u2010Ferrando, G. A., Mart\u00ed\u2010Bonmat\u00ed, L., Aparici\u2010Robles, F., & Garc\u00eda\u2010G\u00f3mez, J. M. (2018). Improving the estimation of prognosis for glioblastoma patients by MR based hemodynamic tissue signatures. NMR in Biomedicine, 31(12), e4006.", "Chelebian, E., Fuster-Garcia, E., \u00c1lvarez-Torres, M., Juan-Albarrac\u00edn, J., & Garc\u00eda-G\u00f3mez, J. M. (2020). Higher vascularity at infiltrated peripheral edema differentiates proneural glioblastoma subtype. PloS one, 15(10), e0232500", "Fuster-Garcia, E., Estell\u00e9s, D. L., del Mar \u00c1lvarez-Torres, M., Juan-Albarrac\u00edn, J., Chelebian, E., Rovira, A., ... & Garc\u00eda-G\u00f3mez, J. M. (2021). MGMT methylation may benefit overall survival in patients with moderately vascularized glioblastomas. European radiology, 31(3), 1738-1747.", "\u00c1lvarez\u2010Torres, M., Fuster\u2010Garc\u00eda, E., Reyn\u00e9s, G., Juan\u2010Albarrac\u00edn, J., Chelebian, E., Oleaga, L., ... & Garc\u00eda\u2010G\u00f3mez, J. M. (2021). Differential effect of vascularity between long\u2010and short\u2010term survivors with IDH1/2 wild\u2010type glioblastoma. NMR in Biomedicine, 34(4), e4462."]}