Pre-operative MRI Radiomics for the Prediction of Progression and Recurrence in Meningiomas

doi:10.3389/fneur.2021.636235

CNU IR > Pharmacy and Science > Dept. of Health and Nutrition (including master's program) > Periodical Articles > Item 310902800/34422

Please use this identifier to cite or link to this item: https://ir.cnu.edu.tw/handle/310902800/34422

Title:	Pre-operative MRI Radiomics for the Prediction of Progression and Recurrence in Meningiomas
Authors:	Ko, Ching-Chung Zhang, Yang Chen, Jeon-Hor Chang, Kai-Ting Chen, Tai-Yuan Lim, Sher-Wei Wu, Te-Chang Su, Min-Ying
Contributors:	Chi Mei Med Ctr, Dept Med Imaging Chia Nan Univ Pharm & Sci, Dept Hlth & Nutr Univ Calif Irvine, Dept Radiol Sci, Irvine I Shou Univ, E DA Hosp, Dept Radiol Chang Jung Christian Univ, Grad Inst Med Sci Chi Mei Med Ctr, Dept Neurosurg Min Hwei Coll Hlth Care Management, Dept Nursing Natl Yang Ming Univ, Dept Biomed Imaging & Radiol Sci
Keywords:	magnetic resonance imaging radiomics support vector machine meningioma progression recurrence
Date:	2021
Issue Date:	2023-11-11 11:51:40 (UTC+8)
Publisher:	FRONTIERS MEDIA SA
Abstract:	Objectives: A subset of meningiomas may show progression/recurrence (P/R) after surgical resection. This study applied pre-operative MR radiomics based on support vector machine (SVM) to predict P/R in meningiomas. Methods: From January 2007 to January 2018, 128 patients with pathologically confirmed WHO grade I meningiomas were included. Only patients who had undergone pre-operative MRIs and post-operative follow-up MRIs for more than 1 year were studied. Pre-operative T2WI and contrast-enhanced T1WI were analyzed. On each set of images, 32 first-order features and 75 textural features were extracted. The SVM classifier was utilized to evaluate the significance of extracted features, and the most significant four features were selected to calculate SVM score for each patient. Results: Gross total resection (Simpson grades I-III) was performed in 93 (93/128, 72.7%) patients, and 19 (19/128, 14.8%) patients had P/R after surgery. Subtotal tumor resection, bone invasion, low apparent diffusion coefficient (ADC) value, and high SVM score were more frequently encountered in the P/R group (p < 0.05). In multivariate Cox hazards analysis, bone invasion, ADC value, and SVM score were high-risk factors for P/R (p < 0.05) with hazard ratios of 7.31, 4.67, and 8.13, respectively. Using the SVM score, an AUC of 0.80 with optimal cutoff value of 0.224 was obtained for predicting P/R. Patients with higher SVM scores were associated with shorter progression-free survival (p = 0.003). Conclusions: Our preliminary results showed that pre-operative MR radiomic features may have the potential to offer valuable information in treatment planning for meningiomas.
Relation:	FRONT NEUROL, v.12
Appears in Collections:	[Dept. of Health and Nutrition (including master's program)] Periodical Articles

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