Noninvasive Determination of IDH and 1p19q Status of Lower-grade Gliomas Using MRI Radiomics: A Systematic Review

Abstract

BACKGROUND: Determination of isocitrate dehydrogenase (IDH) status and, if IDH-mutant, assessing 1p19q codeletion are an important component of diagnosis of World Health Organization grades II/III or lower-grade gliomas. This has led to research into noninvasively correlating imaging features ("radiomics") with genetic status. PURPOSE: Our aim was to perform a diagnostic test accuracy systematic review for classifying IDH and 1p19q status using MR imaging radiomics, to provide future directions for integration into clinical radiology. DATA SOURCES: Ovid (MEDLINE), Scopus, and the Web of Science were searched in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Diagnostic Test Accuracy guidelines. STUDY SELECTION: Fourteen journal articles were selected that included 1655 lower-grade gliomas classified by their IDH and/or 1p19q status from MR imaging radiomic features. DATA ANALYSIS: For each article, the classification of IDH and/or 1p19q status using MR imaging radiomics was evaluated using the area under curve or descriptive statistics. Quality assessment was performed with the Quality Assessment of Diagnostic Accuracy Studies 2 tool and the radiomics quality score. DATA SYNTHESIS: The best classifier of IDH status was with conventional radiomics in combination with convolutional neural network-derived features (area under the curve ¼ 0.95, 94.4% sensitivity, 86.7% specificity). Optimal classification of 1p19q status occurred with texture-based radiomics (area under the curve ¼ 0.96, 90% sensitivity, 89% specificity). LIMITATIONS: A meta-analysis showed high heterogeneity due to the uniqueness of radiomic pipelines. CONCLUSIONS: Radiogenomics is a potential alternative to standard invasive biopsy techniques for determination of IDH and 1p19q status in lower-grade gliomas but requires translational research for clinical uptake. ABBREVIATIONS: AI ¼ artificial intelligence; AUC ¼ area under the curve; CNN ¼ convolutional neural network; IDH ¼ isocitrate dehydrogenase; IDH-mut ¼ IDH-mutant; LGG ¼ lower-grade gliomas; ML ¼ machine learning; PRISMA-DTA ¼ Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Diagnostic Test Accuracy; QUADAS-2 ¼ Quality Assessment of Diagnostic Accuracy Studies 2; RQS ¼ radiomics quality score; SVM ¼ support vector machine; VASARI ¼ Visually Accessible Rembrandt Images; WHO ¼ World Health Organization

Development and external validation of a non-invasive molecular status predictor of chromosome 1p/19q co-deletion based on MRI radiomics analysis of Low Grade Glioma patients

“…Other studies try to predict 1p/19q status, some of which aim to solve the same problem using MRI [15][16][17][18][19][20][21][22]. They all are using multimodal conventional MRI data, most often combining T2-weighted and contrast enhanced T1-weighted data together.…”

“…In the last few years different studies have demonstrated that 1p19q status can be predicted using MRI [15][16][17][18][19][20][21][22]. Furthermore, Branzoli et al [23] recently identified elevated levels of cystathionine in 1p/19q codeleted gliomas compared to non-codeleted gliomas, using in vivo magnetic resonance spectroscopy.…”

Accuracy of Machine Learning Algorithms for the Classification of Molecular Features of Gliomas on MRI: A Systematic Literature Review and Meta-Analysis

“…Furthermore, as recently suggested by Bhandari et al, a greater effort is needed to start translating these findings into an interpretable format for clinical radiology [ 89 ]. In addition, as several studies focused on singular molecular biomarkers in gliomas, it must be underlined several molecular alterations in astrocytic, oligodendroglial gliomas can occur in different combinations [ 79 ].…”

Quantitative Relaxometry using Synthetic MRI Could be Better than Qualitative T2-FLAIR Mismatch Sign: A Pilot Study

“…Previous studies have reported that the T2-FLAIR mismatch sign has been shown to predict astrocytoma, IDH-mutant with 95-100% speci city [14,15]; however, sensitivity has been low at 46-51% [8, 14, 16]. Inter-rater agreement has been shown to have a wide range of κ = 0.38-0.88 [5,8,14,15].…”