Three-dimensional fractal dimension and lacunarity features may noninvasively predict TERT promoter mutation status in grade 2 meningiomas

Abstract

Purpose The 2021 World Health Organization classification includes telomerase reverse transcriptase promoter (TERTp) mutation status as a factor for differentiating meningioma grades. Therefore, preoperative prediction of TERTp mutation may assist in clinical decision making. However, no previous study has applied fractal analysis for TERTp mutation status prediction in meningiomas. The purpose of this study was to assess the utility of three-dimensional (3D) fractal analysis for predicting the TERTp mutation status in grade 2 meningiomas. Methods Forty-eight patients with surgically confirmed grade 2 meningiomas (41 TERTp-wildtype and 7 TERTp-mutant) were included. 3D fractal dimension (FD) and lacunarity values were extracted from the fractal analysis. A predictive model combining clinical, conventional, and fractal parameters was built using logistic regression analysis. Receiver operating characteristic curve analysis was used to assess the ability of the model to predict TERTp mutation status. Results Patients with TERTp-mutant grade 2 meningiomas were older (P = 0.029) and had higher 3D FD (P = 0.026) and lacunarity (P = 0.004) values than patients with TERTp-wildtype grade 2 meningiomas. On multivariable logistic analysis, higher 3D FD values (odds ratio = 32.50, P = 0.039) and higher 3D lacunarity values (odds ratio = 20.54, P = 0.014) were significant predictors of TERTp mutation status. The area under the curve, accuracy, sensitivity, and specificity of the multivariable model were 0.84 (95% confidence interval 0.71–0.93), 83.3%, 71.4%, and 85.4%, respectively. Conclusion 3D FD and lacunarity may be useful imaging biomarkers for predicting TERTp mutation status in grade 2 meningiomas.

Radiomics-Based Prediction of TERT Promotor Mutations in Intracranial High-Grade Meningiomas

“…In our own series, we further demonstrated a para-sagittal tumor location as a strong predictor for TERT promotor mutations in high-grade meningiomas [19]. Similarly, three-dimensional fractal dimension and lacunarity features were previously shown to strongly correlate with TERT promotor mutation status [29], further underlining the immense potential of imaging characteristics to predict molecular alterations in general, and especially of TERT, in meningiomas. However, investigator-based imaging analyses typically suffer from subjectivity and subsequent inter-observer variability and are mostly restricted to small patient cohorts.…”

Predicting glioma IDH mutation using multi-parametric MRI and fractal analysis

“…We hypothesize that FD can provide valuable information that correlates with the genotype and phenotype of a tumor. Existing studies on fractal analysis have shown promising results, including predicting TERTp mutation status in meningiomas [1], prediction of prostate cancer grade [2], etc. To our knowledge, there has been no study applying fractal analysis to IDH mutation status prediction, although there was a recent study using radiomics to predict IDH mutation with MGMG promoter methylation subtype [3].…”