PURPOSE Microcystic meningioma (MCM) appears similar to atypical meningioma(AM) as per conventional diagnostic imaging. However, considering their different recurrence rate and prognosis, accurate differential diagnosis is essential for determine the appropriate treatment strategy. The aim of the study was to differentiate MCM from AM by diffusion-weighted imaging (DWI), in order to provide the basis for accurate preoperative diagnosis. METHODS The preoperative clinical data, conventional MRI and DWI data of 15 MCM and 30 AM cases were retrospectively analyzed. The average apparent diffusion coefficient (ADCmean), minimum ADC (ADCmin) and normalized ADC (nADC) between MCM and AM were compared using two sample t-tests. The value of ADCmean, ADCmin and nADC in the differential diagnosis of MCM and AM were calculated by the receiver operating curve (ROC) analysis. RESULTS The ADCmean (1.06 ± 0.10 vs 0.80 ± 0.11 × 10-3 mm2/s; P < 0.001), ADCmin (0.99 ± 0.10 vs 0.74 ± 0.12 × 10-3 mm2/s; P < 0.001) and nADC (1.45 ± 0.17 vs 1.07 ± 0.17; P < .0001) were significantly higher in MCM compared to AM. ADCmean of 0.91 × 10-3 mm2/s showed an optimum area under the ROC curve of 0.967 ± 0.022, and distinguished between MCM and AM with 86.67% sensitivity, 100% specificity and 88.89% accuracy. In addition, its positive and negative predictive values were 96.29% and 77.78% respectively. CONCLUSIONS DWI can differentially diagnose MCM and AM, and ADCmean is a potential quantitative tool that can improve preoperative diagnosis of both tumors.

中文翻译：

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使用弥散加权成像将微囊性脑膜瘤与非典型性脑膜瘤区分开。

目的根据常规诊断成像，微囊性脑膜瘤（MCM）看起来与非典型脑膜瘤（AM）相似。但是，考虑到它们的不同复发率和预后，准确的鉴别诊断对于确定适当的治疗策略至关重要。这项研究的目的是通过弥散加权成像（DWI）来区分MCM和AM，以便为准确的术前诊断提供基础。方法回顾性分析15例MCM和30例AM患者的术前临床资料，常规MRI和DWI资料。使用两个样本t检验比较了MCM和AM之间的平均视在扩散系数（ADCmean），最小ADC（ADCmin）和归一化ADC（nADC）。ADCmean的值，通过接收器工作曲线（ROC）分析计算出Mmin和AM鉴别诊断中的ADCmin和nADC。结果ADC平均值（1.06±0.10 vs 0.80±0.11×10-3 mm2 / s; P <0.001），ADCmin（0.99±0.10 vs 0.74±0.12×10-3 mm2 / s; P <0.001）和nADC（1.45±与AM相比，MCM中的0.17比1.07±0.17； P <.0001）显着更高。ADCmean为0.91×10-3 mm2 / s，ROC曲线下的最佳面积为0.967±0.022，在MCM和AM之间可区分，灵敏度为86.67％，特异性为100％，准确度为88.89％。此外，其阳性和阴性预测值分别为96.29％和77.78％。结论DWI可以鉴别MCM和AM，ADCmean是一种潜在的定量工具，可以改善两种肿瘤的术前诊断。10对0.80±0.11×10-3 mm2 / s; P <0.001），ADCmin（0.99±0.10 vs.0.74±0.12×10-3 mm2 / s; P <0.001）和nADC（1.45±0.17 vs 1.07±0.17; P <.0001）与AM相比明显更高。ADCmean为0.91×10-3 mm2 / s，ROC曲线下的最佳面积为0.967±0.022，在MCM和AM之间可区分，灵敏度为86.67％，特异性为100％，准确度为88.89％。此外，其阳性和阴性预测值分别为96.29％和77.78％。结论DWI可以鉴别MCM和AM，ADCmean是一种潜在的定量工具，可以改善两种肿瘤的术前诊断。10对0.80±0.11×10-3 mm2 / s; P <0.001），ADCmin（0.99±0.10 vs.0.74±0.12×10-3 mm2 / s; P <0.001）和nADC（1.45±0.17 vs 1.07±0.17; P <.0001）与AM相比明显更高。ADCmean为0.91×10-3 mm2 / s，ROC曲线下的最佳面积为0.967±0.022，在MCM和AM之间可区分，灵敏度为86.67％，特异性为100％，准确度为88.89％。此外，其阳性和阴性预测值分别为96.29％和77.78％。结论DWI可以鉴别MCM和AM，ADCmean是一种潜在的定量工具，可以改善两种肿瘤的术前诊断。ADCmean为0.91×10-3 mm2 / s，ROC曲线下的最佳面积为0.967±0.022，在MCM和AM之间可区分，灵敏度为86.67％，特异性为100％，准确度为88.89％。此外，其阳性和阴性预测值分别为96.29％和77.78％。结论DWI可以鉴别MCM和AM，ADCmean是一种潜在的定量工具，可以改善两种肿瘤的术前诊断。ADCmean为0.91×10-3 mm2 / s，ROC曲线下的最佳面积为0.967±0.022，在MCM和AM之间可区分，灵敏度为86.67％，特异性为100％，准确度为88.89％。此外，其阳性和阴性预测值分别为96.29％和77.78％。结论DWI可以鉴别MCM和AM，ADCmean是一种潜在的定量工具，可以改善两种肿瘤的术前诊断。