Journal Article

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

Park, Yae Won, Chang, Jong Hee, Ahn, Sung Soo, Lee, Jun Ho, Kim, Jinna, Lee, Seung-Koo, Won, So Yeon, Lee, Narae, Kim, Se Hoon

2022

Overview

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. 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. 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. 3D FD and lacunarity may be useful imaging biomarkers for predicting TERTp mutation status in grade 2 meningiomas.

• Publisher: Public Library of Science,Public Library of Science (PLoS)
• Subject: Aging / Algorithms / Analysis / Biological markers / Biology and Life Sciences / Biomarkers / Brain cancer / Care and treatment / Cells / Classification / Confidence intervals / Cyclin-dependent kinases / Decision analysis / Decision making / Diagnosis / Fractal analysis / Fractal geometry / Fractal models / Fractals / Gene mutations / Genetic aspects / Health aspects / Humans / Kidney cancer / Magnetic resonance imaging / Medical prognosis / Medicine and Health Sciences / Meningeal Neoplasms - diagnostic imaging / Meningeal Neoplasms - genetics / Meningioma / Meningioma - diagnostic imaging / Meningioma - genetics / Mutants / Mutation / Patients / Physical Sciences / Prediction models / Regression analysis / Research and Analysis Methods / RNA-directed DNA polymerase / Statistical analysis / Telomerase / Telomerase - genetics / Telomerase reverse transcriptase / Three dimensional analysis / Thyroid cancer / Variables