Macrovascular networks on contrast-enhanced magnetic resonance imaging improves survival prediction in newly diagnosed glioblastoma

Josep Puig, Carles Biarnés, Pepus Daunis-i-Estadella, Gerard Blasco, Alfredo Gimeno, Marco Essig, Carme Balaña, Angel Alberich-Bayarri, Ana Jimenez-Pastor, Eduardo Camacho, Santiago Thio-Henestrosa, Jaume Capellades, Javier Sanchez-Gonzalez, Marian Navas-Martí, Blanca Domenech-Ximenos, Sonia Del Barco, Montserrat Puigdemont, Carlos Leiva-Salinas, Max Wintermark, Kambiz NaelRajan Jain, Salvador Pedraza

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


A higher degree of angiogenesis is associated with shortened survival in glioblastoma. Feasible morphometric parameters for analyzing vascular networks in brain tumors in clinical practice are lacking. We investigated whether the macrovascular network classified by the number of vessel-like structures (nVS) visible on three-dimensional T1-weighted contrast-enhanced (3D-T1CE) magnetic resonance imaging (MRI) could improve survival prediction models for newly diagnosed glioblastoma based on clinical and other imaging features. Ninety-seven consecutive patients (62 men; mean age, 58 ± 15 years) with histologically proven glioblastoma underwent 1.5T-MRI, including anatomical, diffusion-weighted, dynamic susceptibility contrast perfusion, and 3D-T1CE sequences after 0.1 mmol/kg gadobutrol. We assessed nVS related to the tumor on 1-mm isovoxel 3D-T1CE images, and relative cerebral blood volume, relative cerebral flow volume (rCBF), delay mean time, and apparent diffusion coefficient in volumes of interest for contrast-enhancing lesion (CEL), non-CEL, and contralateral normal-appearing white matter. We also assessed Visually Accessible Rembrandt Images scoring system features. We used ROC curves to determine the cutoff for nVS and univariate and multivariate cox proportional hazards regression for overall survival. Prognostic factors were evaluated by Kaplan-Meier survival and ROC analyses. Lesions with nVS > 5 were classified as having highly developed macrovascular network; 58 (60.4%) tumors had highly developed macrovascular network. Patients with highly developed macrovascular network were older, had higher volumeCEL, increased rCBFCEL, and poor survival; nVS correlated negatively with survival (r = ??0.286; p = 0.008). On multivariate analysis, standard treatment, age at diagnosis, and macrovascular network best predicted survival at 1 year (AUC 0.901, 83.3% sensitivity, 93.3% specificity, 96.2% PPV, 73.7% NPV). Contrast-enhanced MRI macrovascular network improves survival prediction in newly diagnosed glioblastoma.

Original languageEnglish
Article number84
Issue number1
StatePublished - 1 Jan 2019


  • Angiogenesis
  • Biomarker
  • Glioblastoma
  • Magnetic resonance imaging
  • Survival


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