Background: Multiple radiomics models have been proposed for
grading glioma using different algorithms, features, and sequences of magnetic
resonance imaging. The research seeks to assess the present overall performance
of radiomics for grading glioma. Methods: A systematic literature review
of the databases Ovid MEDLINE PubMed, and Ovid EMBASE for publications published
on radiomics for glioma grading between 2012 and 2023 was performed. The
systematic review was carried out following the criteria of Preferred Reporting
Items for Systematic Reviews and Meta-Analysis. Results: In the
meta-analysis, a total of 7654 patients from 40 articles, were assessed.
R-package mada was used for modeling the joint estimates of specificity (SPE) and
sensitivity (SEN). Pooled event rates across studies were performed with a
random-effects meta-analysis. The heterogeneity of SPE and SEN were based on the
Announcements
Open Access
Systematic Review
The Current Diagnostic Performance of MRI-Based Radiomics for Glioma Grading: A Meta-Analysis
Lucio De Maria1, Francesco Ponzio2, Hwan-ho Cho3, Karoline Skogen4, Ioannis Tsougos5, Mauro Gasparini6, Marco Zeppieri7,*, Tamara Ius8, Lorenzo Ugga9, Pier Paolo Panciani1, Marco Maria Fontanella1, Waleed Brinjikji10, Edoardo Agosti1
Show Less
1
Division of Neurosurgery, Department of Surgical Specialties, Radiological Sciences, and Public Health, University of Brescia, 25123 Brescia, Italy
2
Interuniversity Department of Regional and Urban Studies and Planning, Politecnico di Torino, 10125 Torino, Italy
3
Department of Medical Artificial Intelligence, Konyang University, 35365 Daejeon, Republic of Korea
4
Department of Radiology and Nuclear Medicine, University of Oslo, 0372 Oslo, Norway
5
Department of Medical Physics, University of Thessaly, 413 34 Larissa, Greece
6
Department of Mathematical Sciences “Giuseppe Luigi Lagrange”, Politecnico di Torino, 10123 Torino, Italy
7
Department of Ophthalmology, University Hospital of Udine, 33100 Udine, Italy
8
Neurosurgery Unit, Head-Neck and NeuroScience Department University Hospital of Udine, p.le S. Maria della Misericordia 15, 33100 Udine, Italy
9
Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80126 Naples, Italy
10
Department of Neurosurgery and Interventional Neuroradiology, Mayo Clinic, Rochester, MN 55905, USA
*Correspondence: markzeppieri@hotmail.com (Marco Zeppieri)
J. Integr. Neurosci. 2024, 23(5), 100;
https://doi.org/10.31083/j.jin2305100
Submitted: 13 November 2023 | Revised: 28 December 2023 | Accepted: 4 January 2024 | Published: 14 May 2024
Copyright: © 2024 The Author(s). Published by IMR Press.
This is an open access article under the CC BY 4.0 license.
Abstract
Keywords
glioma grading
radiomics
magnetic resonance imaging (MRI) features
systematic review
meta-analysis
Figures
Fig. 1.