表观扩散系数直方图分析鉴别纤维型脑膜瘤与非纤维型 WHO 分级 1 级脑膜瘤。
Apparent diffusion coefficient histogram analysis for differentiating fibroblastic meningiomas from non-fibroblastic WHO grade 1 meningiomas.
机构信息
Department of Radiology, Lanzhou University Second Hospital, Lanzhou 730030, China; Second Clinical School, Lanzhou University, Lanzhou 730030, China; Key Laboratory of Medical Imaging of Gansu Province, Lanzhou 730030, China; Gansu International Scientific and Technological Cooperation Base of Medical Imaging Artificial Intelligence, Lanzhou 730030, China.
Image Center of affiliated Hospital of Qinghai University, Xining 810001, China.
出版信息
Clin Imaging. 2023 Dec;104:110019. doi: 10.1016/j.clinimag.2023.110019. Epub 2023 Nov 11.
PURPOSE
To investigate the role of apparent diffusion coefficient (ADC) histogram analysis in differentiating fibroblastic meningiomas (FM) from non-fibroblastic WHO grade 1 meningiomas (nFM).
METHODS
This retrospective study analyzed the histopathological and diagnostic imaging data of 220 patients with histopathologically confirmed FM and nFM. The whole tumors were delineated on axial ADC images, and histogram parameters (mean, variance, skewness, kurtosis, as well as the 1st, 10th, 50th, 90th, and 99th percentile ADC [ADCp1, ADCp10, ADCp50, ADCp90, and ADCp99, respectively]) were obtained. Multivariate logistic regression analysis was used to identify the most valuable variables for discriminating FM from nFM WHO grade 1 meningiomas, and their diagnostic efficacy in differentiating FM from nFM before surgery was assessed using receiver operating characteristic (ROC) curves.
RESULTS
The mean, variance, ADCp50, ADCp90, and ADCp99 of the FM group were all lower than those of the nFM group (P < 0.05), there was significant difference in location and sex (P < 0.05). Multivariate logistic regression showed ADCp99 (P < 0.001) and location (P = 0.007) were the most valuable parameters in the discrimination of FM and nFM WHO grade 1 meningiomas. The diagnostic efficacy was achieved an AUC of 0.817(95% CI, 0.759-0.866), the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were 66.4%, 83.6%, 75.0%, 80.2%, and 71.3%, respectively.
CONCLUSION
ADC histogram analysis is helpful in noninvasive differentiation of FM and nFM WHO grade 1 meningiomas, and combined ADCp99 and location have the best diagnostic efficacy.
目的
探讨表观扩散系数（ADC）直方图分析在鉴别纤维型脑膜瘤（FM）和非纤维型 WHO 1 级脑膜瘤（nFM）中的作用。
方法
本回顾性研究分析了 220 例经组织病理学证实的 FM 和 nFM 患者的组织病理学和诊断影像学数据。在轴位 ADC 图像上勾画全肿瘤，获得直方图参数（平均值、方差、偏度、峰度以及 ADC 的第 1、10、50、90 和 99 百分位数[ADCp1、ADCp10、ADCp50、ADCp90 和 ADCp99]）。采用多变量逻辑回归分析确定鉴别 FM 和 nFM 的最有价值变量，并采用受试者工作特征（ROC）曲线评估其术前鉴别 FM 和 nFM 的诊断效能。
结果
FM 组的平均值、方差、ADCp50、ADCp90 和 ADCp99 均低于 nFM 组（P<0.05），位置和性别存在显著差异（P<0.05）。多变量逻辑回归显示，ADCp99（P<0.001）和位置（P=0.007）是鉴别 FM 和 nFM 的最有价值参数。诊断效能达到 AUC 为 0.817（95%CI，0.759-0.866），灵敏度、特异度、准确度、阳性预测值和阴性预测值分别为 66.4%、83.6%、75.0%、80.2%和 71.3%。
结论
ADC 直方图分析有助于无创鉴别 FM 和 nFM 的 WHO 1 级脑膜瘤，且联合 ADCp99 和位置具有最佳的诊断效能。
Zotero 插件