Neurosurgery · 2017
Fractal Analysis May Improve the Preoperative Identification of Atypical Meningiomas.
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Czyz Marcin, Radwan Hesham, Li Jian Y, Filippi Christopher G, Tykocki Tomasz, Schulder Michael
Аннотация
BACKGROUND: There is no objective and readily accessible method for the preoperative determination of atypical characteristics of a meningioma grade.
OBJECTIVE: To evaluate the feasibility of using fractal analysis as an adjunctive tool to conventional radiological techniques in visualizing histopathological features of meningiomas.
METHODS: A group of 27 patients diagnosed with atypical (WHO grade II) meningioma and a second group of 27 patients with benign (WHO grade I) meningioma were enrolled in the study. Preoperative brain magnetic resonance (MR) studies (T1-wieghted, post-gadolinium) were processed and analyzed to determine the average fractal dimension (FDa) and maximum fractal dimension (FDm) of the contrast-enhancing region of the tumor using box-count method. FDa and FDm as well as particular radiological features were included in the logistic regression model as possible predictors of malignancy.
RESULTS: The cohort consisted of 34 women and 20 men, mean age of 62 ± 15 yr. Fractal analysis showed good interobserver reproducibility (Kappa >0.70). Both FDa and FDm were significantly higher in the atypical compared to the benign meningioma group (P < .0001). Multivariate logistic regression model reached statistical significance with P = .0001 and AUC = 0.87. The FDm, which was greater than 1.31 (odds ratio [OR], 12.30; P = .039), and nonskull base localization (OR, .052; P = .015) were confirmed to be statistically significant predictors of the atypical phenotype.
CONCLUSION: Fractal analysis of preoperative MR images appears to be a feasible adjunctive diagnostic tool in identifying meningiomas with potentially aggressive clinical behavior.
OBJECTIVE: To evaluate the feasibility of using fractal analysis as an adjunctive tool to conventional radiological techniques in visualizing histopathological features of meningiomas.
METHODS: A group of 27 patients diagnosed with atypical (WHO grade II) meningioma and a second group of 27 patients with benign (WHO grade I) meningioma were enrolled in the study. Preoperative brain magnetic resonance (MR) studies (T1-wieghted, post-gadolinium) were processed and analyzed to determine the average fractal dimension (FDa) and maximum fractal dimension (FDm) of the contrast-enhancing region of the tumor using box-count method. FDa and FDm as well as particular radiological features were included in the logistic regression model as possible predictors of malignancy.
RESULTS: The cohort consisted of 34 women and 20 men, mean age of 62 ± 15 yr. Fractal analysis showed good interobserver reproducibility (Kappa >0.70). Both FDa and FDm were significantly higher in the atypical compared to the benign meningioma group (P < .0001). Multivariate logistic regression model reached statistical significance with P = .0001 and AUC = 0.87. The FDm, which was greater than 1.31 (odds ratio [OR], 12.30; P = .039), and nonskull base localization (OR, .052; P = .015) were confirmed to be statistically significant predictors of the atypical phenotype.
CONCLUSION: Fractal analysis of preoperative MR images appears to be a feasible adjunctive diagnostic tool in identifying meningiomas with potentially aggressive clinical behavior.