Magnetic resonance imaging fractal analysis of O(6)-methylguanine-DNA methyltransferase promoter methylation status in isocitrate dehydrogenase wild-type glioblastoma
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: The methylation status of the O(6)-methylguanine-DNA methyltransferase (MGMT) promoter profoundly influences the response of glioblastoma (GBM) patients to temozolomide (TMZ) chemotherapy. This study evaluates the potential of magnetic resonance imaging (MRI) fractal analysis to predict the methylation status of the MGMT promoter in isocitrate dehydrogenase (IDH) wild-type GBM. Methods: In this retrospective study, 303 GBM patients from two centers were included between 2018 and 2023. The training set consisted of 220 patients from the first center, and the independent validation cohort included 83 patients from the second center. Fractal dimension (FD) and lacunarity were extracted from T2-weighted and post-contrast T1-weighted (T1C) MRI sequences. Statistical analyses, including independent t-tests, Chi-squared tests, and multivariate logistic regression, were performed to explore associations between patient characteristics and fractal parameters. Predictive models were developed and assessed using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis (DCA). Results: Significant differences (P<0.05) were identified between the MGMT-methylated and unmethylated groups for L4-T2, L6-T2, L4-T1C, and gender. A predictive model, incorporating L4-T2WI [odds ratio (OR), 0.881; 95% confidence interval (CI): 0.833–0.933; P<0.001] and L6-T2WI (OR, 1.479; 95% CI: 1.230–1.778; P<0.001), was developed using multivariate regression and visualized through a nomogram. In the validation cohort, the model achieved an AUC of 0.750 (95% CI: 0.644–0.856). The DCA and calibration curves demonstrated good predictive performance and clinical utility of the nomogram. Conclusions: The preoperative fractal analysis is a reliable predictive tool for MGMT promoter methylation status in patients with GBM.
Authors: Caiqiang Xue, Kun Wang, Wenjie Dong, Tao Han, Qing Zhou, Peng Zhang, Lijun Liang, Ping Wang, Junlin Zhou, Shibing Guan, Xuejun Liu
Language: English
Subfield: Genetics
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4415655861
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