ONCOhabitats results for Ivy Glioblastoma Atlas Project (Ivy Gap): Segmentation and Hemodynamic Tissue Signature

This dataset contains the ONCOhabitats processing results for the patients with complete pre-surgical MRI (T1, T1-Gd, T2, FLAIR and DSC perfusion) included at the Ivy Glioblastoma Atlas Project (Ivy GAP) 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.

*Users of this data results should include references to the following citations:

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.

The original data was presented in: 

Shah, N., Feng, X., Lankerovich, M., Puchalski, R. B., & Keogh, B. (2016). Data from Ivy Glioblastoma Atlas Project (IvyGAP) [Data set]. The Cancer Imaging Archive. https://doi.org/10.7937/K9/TCIA.2016.XLwaN6nL

Puchalski RB, Shah N, Miller J, Dalley R, Nomura SR, Yoon J-G, Smith KA, Lankerovich M, Bertagnolli D, Bickley K, Boe AF, Brouner K, Butler S, Caldejon S, Chapin M, Datta S, Dee N, Desta T, Dolbeare T, Dotson N, Ebbert A, Feng D, Feng X, Fisher M, Gee G, Goldy J, Gourley L, Gregor BW, Gu G, Hejazinia N, Hohmann J, Hothi P, Howard R, Joines K, Kriedberg A, Kuan L, Lau C, Lee F, Lee H, Lemon T, Long F, Mastan N, Mott E, Murthy C, Ngo K, Olson E, Reding M, Riley Z, Rosen D, Sandman D, Shapovalova N, Slaughterbeck CR, Sodt A, Stockdale G, Szafer A, Wakeman W, Wohnoutka PE, White SJ, Marsh D, Rostomily RC, Ng L, Dang C, Jones A, Keogh B, Gittleman HR, Barnholtz-Sloan JS, Cimino PJ, Uppin MS, Keene CD, Farrokhi FR, Lathia JD, Berens ME, Iavarone A, Bernard A, Lein E, Phillips JW, Rostad SW, Cobbs C, Hawrylycz MJ, Foltz GD. (2018). An anatomic transcriptional atlas of human glioblastoma. Science, 360(6389), 660–663. https://doi.org/10.1126/science.aaf2666

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. Journal of Digital Imaging, 26(6), 1045–1057. https://doi.org/10.1007/s10278-013-9622-7