ArticlePloS one2022
Three-dimensional fractal dimension and lacunarity features may noninvasively predict TERT promoter mutation status in grade 2 meningiomas.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 7 citations in OpenAlex.
- Fractal-geometry analysis of pediatric posterior fossa tumors - a preoperative tool for prediction of histopathology.Neurosurgical review · 2026Article
- Fractal analysis of tumor subregions differentiates benign from malignant breast lesions.Polish journal of radiology · 2026Article
- [Predicting Invasive Non-mucinous Lung Adenocarcinoma IASLC Grading: A Nomogram Based on Dual-energy CT Imaging and Conventional Features].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2025Article
- Consistency and grade prediction of intracranial meningiomas based on fractal geometry analysis.Neurosurgical review · 2025Article
- Study of prediction model for high-grade meningioma using fractal geometry combined with radiological features.Journal of neuro-oncology · 2025Article
- Radiomics-Based Prediction of TERT Promotor Mutations in Intracranial High-Grade Meningiomas.Cancers · 2023Article
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9 authors at 1 institution in 1 country.
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Abstract
purposeThe 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.
methodsForty-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.
resultsPatients 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.
conclusion3D FD and lacunarity may be useful imaging biomarkers for predicting TERTp mutation status in grade 2 meningiomas.
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