Quality assessment of the MRI-radiomics studies for MGMT promoter methylation prediction in glioma: a systematic review and meta-analysis

Abstract

Objectives: To evaluate the methodological quality and diagnostic accuracy of MRI-based radiomic studies predicting O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status in gliomas.

Methods: PubMed Medline, EMBASE, and Web of Science were searched to identify MRI-based radiomic studies on MGMT methylation in gliomas published until December 31, 2022. Three raters evaluated the study methodological quality with Radiomics Quality Score (RQS, 16 components) and Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis Or Diagnosis (TRIPOD, 22 items) scales. Risk of bias and applicability concerns were assessed with QUADAS-2 tool. A meta-analysis was performed to estimate the pooled area under the curve (AUC) and to assess inter-study heterogeneity.

Results: We included 26 studies, published from 2016. The median RQS total score was 8 out of 36 (22%, range 8-44%). Thirteen studies performed external validation. All studies reported AUC or accuracy, but only 4 (15%) performed calibration and decision curve analysis. No studies performed phantom analysis, cost-effectiveness analysis, and prospective validation. The overall TRIPOD adherence score was between 50% and 70% in 16 studies and below 50% in 10 studies. The pooled AUC was 0.78 (95% CI, 0.73-0.83, I² = 94.1%) with a high inter-study heterogeneity. Studies with external validation and including only WHO-grade IV gliomas had significantly lower AUC values (0.65; 95% CI, 0.57-0.73, p < 0.01).

Conclusions: Study RQS and adherence to TRIPOD guidelines was generally low. Radiomic prediction of MGMT methylation status showed great heterogeneity of results and lower performances in grade IV gliomas, which hinders its current implementation in clinical practice.

Clinical relevance statement: MGMT promoter methylation status appears to be variably correlated with MRI radiomic features; radiomic models are not sufficiently robust to be integrated into clinical practice to accurately predict MGMT promoter methylation status in patients with glioma before surgery.

Key points: • Adherence to the indications of TRIPOD guidelines was generally low, as was RQS total score. • MGMT promoter methylation status prediction with MRI radiomic features provided heterogeneous diagnostic accuracy results across studies. • Studies that included grade IV glioma only and performed external validation had significantly lower diagnostic accuracy than others.

Keywords: Glioma; Magnetic resonance imaging; Meta-analysis; O(6)-Methylguanine-DNA methyltransferase; Systematic review.

Fig. 1

Study selection flowchart

Fig. 2

Summary of radiomics quality scores (RQS) assessment results of the 26 included studies per domain. Each row of the plot shows the distribution of the scores achieved by the studies for a domain. Colors from red to green denote progressive increase from minimum to maximum score obtainable for each item. Abbreviations: RQS, Radiomics Quality Score

Fig. 3

Forest plot of radiomic studies with available data on the AUC and its uncertainty. The estimate of the pooled AUC based on the random effect model is reported on the last line of the plot. Abbreviations: RE, Random Effect; AUC, area under the curve

Fig. 4

Forest plots with the results of the subgroup analysis. Studies were grouped based on the combination of two factors: (1) whether an external validation was performed; (2) whether WHO-grade IV glioma were only included in their analysis. Abbreviations: AUC, area under the curve; SE, standard error; CI, confidence interval