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 journalArticle

1 Citation (Scopus)

Abstract

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 (US)
Article number84
JournalCancers
Volume11
Issue number1
DOIs
StatePublished - Jan 1 2019
Externally publishedYes

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Glioblastoma
Magnetic Resonance Imaging
Survival
ROC Curve
Kaplan-Meier Estimate
Survival Analysis
Brain Neoplasms
Area Under Curve
Blood Vessels
Neoplasms
Multivariate Analysis
Perfusion
Sensitivity and Specificity

Keywords

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

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

Cite this

Puig, J., Biarnés, C., Daunis-i-Estadella, P., Blasco, G., Gimeno, A., Essig, M., ... Pedraza, S. (2019). Macrovascular networks on contrast-enhanced magnetic resonance imaging improves survival prediction in newly diagnosed glioblastoma. Cancers, 11(1), [84]. https://doi.org/10.3390/cancers11010084

Macrovascular networks on contrast-enhanced magnetic resonance imaging improves survival prediction in newly diagnosed glioblastoma. / Puig, Josep; Biarnés, Carles; Daunis-i-Estadella, Pepus; Blasco, Gerard; Gimeno, Alfredo; Essig, Marco; Balaña, Carme; Alberich-Bayarri, Angel; Jimenez-Pastor, Ana; Camacho, Eduardo; Thio-Henestrosa, Santiago; Capellades, Jaume; Sanchez-Gonzalez, Javier; Navas-Martí, Marian; Domenech-Ximenos, Blanca; Barco, Sonia Del; Puigdemont, Montserrat; Leiva-Salinas, Carlos; Wintermark, Max; Nael, Kambiz; Jain, Rajan; Pedraza, Salvador.

In: Cancers, Vol. 11, No. 1, 84, 01.01.2019.

Research output: Contribution to journalArticle

Puig, J, Biarnés, C, Daunis-i-Estadella, P, Blasco, G, Gimeno, A, Essig, M, Balaña, C, Alberich-Bayarri, A, Jimenez-Pastor, A, Camacho, E, Thio-Henestrosa, S, Capellades, J, Sanchez-Gonzalez, J, Navas-Martí, M, Domenech-Ximenos, B, Barco, SD, Puigdemont, M, Leiva-Salinas, C, Wintermark, M, Nael, K, Jain, R & Pedraza, S 2019, 'Macrovascular networks on contrast-enhanced magnetic resonance imaging improves survival prediction in newly diagnosed glioblastoma', Cancers, vol. 11, no. 1, 84. https://doi.org/10.3390/cancers11010084
Puig, Josep ; Biarnés, Carles ; Daunis-i-Estadella, Pepus ; Blasco, Gerard ; Gimeno, Alfredo ; Essig, Marco ; Balaña, Carme ; Alberich-Bayarri, Angel ; Jimenez-Pastor, Ana ; Camacho, Eduardo ; Thio-Henestrosa, Santiago ; Capellades, Jaume ; Sanchez-Gonzalez, Javier ; Navas-Martí, Marian ; Domenech-Ximenos, Blanca ; Barco, Sonia Del ; Puigdemont, Montserrat ; Leiva-Salinas, Carlos ; Wintermark, Max ; Nael, Kambiz ; Jain, Rajan ; Pedraza, Salvador. / Macrovascular networks on contrast-enhanced magnetic resonance imaging improves survival prediction in newly diagnosed glioblastoma. In: Cancers. 2019 ; Vol. 11, No. 1.
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AU - Biarnés, Carles

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AU - Gimeno, Alfredo

AU - Essig, Marco

AU - Balaña, Carme

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AU - Thio-Henestrosa, Santiago

AU - Capellades, Jaume

AU - Sanchez-Gonzalez, Javier

AU - Navas-Martí, Marian

AU - Domenech-Ximenos, Blanca

AU - Barco, Sonia Del

AU - Puigdemont, Montserrat

AU - Leiva-Salinas, Carlos

AU - Wintermark, Max

AU - Nael, Kambiz

AU - Jain, Rajan

AU - Pedraza, Salvador

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