Discrimination between microcystic meningioma and atypical meningioma using whole-lesion apparent diffusion coefficient histogram analysis

医学 峰度 接收机工作特性 脑膜瘤 有效扩散系数 直方图 核医学 病变 偏斜 百分位 放射科 磁共振弥散成像 病理 磁共振成像 数学 内科学 统计 人工智能 图像(数学) 计算机科学
作者
X. Liu,Xiaoyu Huang,Tao Han,S. Li,Caiqiang Xue,Juan Deng,Zhou Qin,Qing Sun,Junlin Zhou
出处
期刊:Clinical Radiology [Elsevier BV]
卷期号:77 (11): 864-869 被引量:5
标识
DOI:10.1016/j.crad.2022.07.004
摘要

To explore the value of whole-lesion apparent diffusion coefficient (ADC) histogram analysis in discriminating microcystic meningioma (MCM) from atypical meningioma (AM).Clinical and preoperative MRI data of 20 patients with MCM and 26 patients with AM were analysed retrospectively. Whole-lesion apparent diffusion coefficient (ADC) histogram analysis was performed on each patient's lesion to obtain histogram parameters, including mean, variance, skewness, kurtosis, the 1st (ADCp1), 10th (ADCp10), 50th (ADCp50), 90th (ADCp90), and 99th (ADCp99) percentiles of ADC. The differences between the ADC histogram parameters of the two tumours were compared, and the receiver operating characteristic (ROC) curve was used to assess the diagnostic performance of statistically significant parameters in distinguishing the two tumours.The mean, ADCp1, ADCp10, ADCp50, and ADCp90 of MCM were greater than those of AM, and significant differences were observed in these parameters between MCM and AM (all p<0.05). ROC analysis showed that the mean had the highest area under the curve value (AUC) in distinguishing the two tumours (AUC = 0.852), when using 120.46 × 10-6 mm2/s as the optimal threshold, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value for discriminating the two groups were 84.6%, 75%, 80.4%, 81.5%, and 78.9%, respectively.Histogram analysis based on whole-lesion ADC maps was useful for discriminating between MCM from AM preoperatively, with the mean being the most promising potential parameter.

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