Evidence map›Paper›PMID 30646519›Full record

ArticleCancers2019

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 and 12 more

Abstract read
In one paragraph

Article in Cancers, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Evaluating angioarchitectural characteristics of glial and metastatic brain tumors with conventional magnetic resonance imaging.Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia · 2020
    Article
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Josep PuigDepartment of Radiology, University of Manitoba, Winnipeg, MB R3T 2N2, Canada. jpuig@hsc.mb.ca.
Carles BiarnésResearch Unit of Diagnostic Imaging Institute (IDI), Department of Radiology (Girona Biomedical Research Institute) IDIBGI, Hospital Universitari Dr Josep Trueta, 17007 Girona, Spain. carlesbiarnes90@gmail.com.
Pepus Daunis-I-EstadellaDepartment of Computer Science, Applied Mathematics and Statistics, University of Girona, 17003 Girona, Spain. pepus@imae.udg.edu.
Gerard BlascoResearch Unit of Diagnostic Imaging Institute (IDI), Department of Radiology (Girona Biomedical Research Institute) IDIBGI, Hospital Universitari Dr Josep Trueta, 17007 Girona, Spain. gbs.blasco@gmail.com.
Alfredo GimenoResearch Unit of Diagnostic Imaging Institute (IDI), Department of Radiology (Girona Biomedical Research Institute) IDIBGI, Hospital Universitari Dr Josep Trueta, 17007 Girona, Spain. fredigimeno1989@gmail.com.
Marco EssigDepartment of Radiology, University of Manitoba, Winnipeg, MB R3T 2N2, Canada. messig@exchange.hsc.mb.ca.
Carme BalañaMedical Oncology, Institut Catala Oncologia (ICO), Applied Research Group in Oncology (B-ARGO), IGTP, Badalona, 08916 Barcelona, Spain. cbalana@iconcologia.net.ORCID 0000-0003-0771-0390
Angel Alberich-BayarriQUIBIM SL, Quantitative Imaging Biomarkers in Medicine, 46026 Valencia, Spain. angel@quibim.com.
Ana Jimenez-PastorQUIBIM SL, Quantitative Imaging Biomarkers in Medicine, 46026 Valencia, Spain. anajimenez@quibim.com.ORCID 0000-0002-0978-9429
Eduardo CamachoQUIBIM SL, Quantitative Imaging Biomarkers in Medicine, 46026 Valencia, Spain. educamacho@quibim.com.
Santiago Thio-HenestrosaDepartment of Computer Science, Applied Mathematics and Statistics, University of Girona, 17003 Girona, Spain. santiago.thio@udg.edu.ORCID 0000-0003-2555-6489
Jaume CapelladesDepartment of Radiology, Hospital del Mar, 08003 Barcelona, Spain. jaumecapellades@gmail.com.
Javier Sanchez-GonzalezPhilips Healthcare Ibérica, 28050 Madrid, Spain. javier.sanchez.gonzalez@philips.com.
Marian Navas-MartíResearch Unit of Diagnostic Imaging Institute (IDI), Department of Radiology (Girona Biomedical Research Institute) IDIBGI, Hospital Universitari Dr Josep Trueta, 17007 Girona, Spain. marianmarti33@gmail.com.
Blanca Domenech-XimenosResearch Unit of Diagnostic Imaging Institute (IDI), Department of Radiology (Girona Biomedical Research Institute) IDIBGI, Hospital Universitari Dr Josep Trueta, 17007 Girona, Spain. bl.domenech@gmail.com.
Sonia Del BarcoMedical Oncology, Institut Catala Oncologia (ICO), 17007 Girona, Spain. Sdelbarco@iconcologia.net.
Montserrat PuigdemontHospital Cancer Registry, ICO, Hospital Universitari Dr Josep Trueta, 17007 Girona, Spain. mpuigdemont@iconcologia.net.
Carlos Leiva-SalinasDepartment of Radiology, University of Missouri, Columbia, MO 65212, USA. carlosleivasalinas@gmail.com.
Max WintermarkDepartment of Radiology, Neuroradiology Division, Stanford University, Stanford, CA 94304, USA. mwinterm@stanford.edu.
Kambiz NaelDepartment of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. kambiznael@gmail.com.
Rajan JainDepartments of Radiology and Neurosurgery, New York University School of Medicine, New York, NY 10016, USA. Rajan.Jain@nyumc.org.
Salvador PedrazaResearch Unit of Diagnostic Imaging Institute (IDI), Department of Radiology (Girona Biomedical Research Institute) IDIBGI, Hospital Universitari Dr Josep Trueta, 17007 Girona, Spain. sapedraza@gmail.com.

Funding

Fundació La Marato TV3 665/C/2013
6 · The paper itself

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 volume

Indexed as

angiogenesisbiomarkerglioblastomamagnetic resonance imagingsurvival

Identifiers

PMID30646519
PMCPMC6356693

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.