基于 DCE-MRI 的多参数分析可提高腮腺肿瘤鉴别诊断的准确性。
A multiparametric analysis based on DCE-MRI to improve the accuracy of parotid tumor discrimination.
机构信息
Department of Radiology, The First People's Hospital of Foshan, Foshan, Guangdong, China.
Department of MR, Shantou Central Hospital, Shantou, Guangdong, China.
出版信息
Eur J Nucl Med Mol Imaging. 2019 Oct;46(11):2228-2234. doi: 10.1007/s00259-019-04447-9. Epub 2019 Aug 1.
BACKGROUND
Recently, semiquantitative time-intensity curve (TIC) analysis based on DCE-MRI and apparent diffusion coefficient (ADC) value-based diffusion-weighted imaging (DWI) were used to improve the diagnostic efficiency when diagnosing parotid tumors (PTs). However, quantitative DCE-MRI biomarkers have not been emphasized previously.
PURPOSE
To explore the diagnostic efficiency of perfusion parameters alone or in combination based on quantitative DCE-MRI and DWI in the differential diagnosis of PTs.
METHODS
In total, 112 patients with parotid masses were prospectively recruited in our hospital from August 2013 to March 2017. All patients were evaluated with DCE-MRI and DWI before surgery. TIC and quantitative parameters based on DCE MRI and ADCs were analyzed. Receiver operating characteristic analysis and linear discriminant analysis (LDA) was used to determine their diagnostic performance.
RESULTS
In total, 87% (27/31) of pleomorphic adenoma (PA) showed type A TIC, 74% (65/88) of Warthin's tumors showed type B TIC, and 95% (19/20) of malignant tumors showed TIC type C. Pearson X test showed a significant difference between TIC patterns in benign and malignant tumors (X = 38.78, p < 0.001). ROC analysis revealed that ADC achieved the best diagnostic performance for distinguishing PA and Warthin's tumor from others, with area under the curve (AUC) values of 0.945 and 0.925 (p < 0.01), respectively. Furthermore, the TIC type was the only useful biomarker for distinguishing malignant from benign PTs, with an AUC of 0.846 (p < 0.01). Concerning the accuracy of the combined application of multiple parameters of DCE-MRI and ADC values, a combination of TIC pattern and extracellular volume ratio (Ve) provided the best results among five protocols, producing the highest accuracy of 0.75, followed by the combined use of the TIC pattern and ADC (accuracy was 0.70).
CONCLUSION
TIC pattern in combination with the Ve biomarker based on DCE-MRI could achieve optimal diagnostic accuracy in the differential diagnosis of PTs.
背景
最近，基于动态对比增强磁共振成像（DCE-MRI）的半定量时间-强度曲线（TIC）分析和表观扩散系数（ADC）值的扩散加权成像（DWI）已被用于提高诊断腮腺肿瘤（PTs）的效率。然而，以前并未强调定量 DCE-MRI 生物标志物。
目的
探讨基于定量 DCE-MRI 和 DWI 的灌注参数单独或联合在 PTs 鉴别诊断中的诊断效率。
方法
本研究前瞻性纳入 2013 年 8 月至 2017 年 3 月于我院就诊的 112 例腮腺肿块患者，所有患者均在术前接受 DCE-MRI 和 DWI 检查。分析 TIC 及基于 DCE MRI 的定量参数和 ADC 值。采用受试者工作特征分析和线性判别分析（LDA）来确定它们的诊断性能。
结果
多形性腺瘤（PA）中 87%（27/31）呈 A 型 TIC，Warthin 瘤中 74%（65/88）呈 B 型 TIC，恶性肿瘤中 95%（19/20）呈 C 型 TIC。Pearson X 检验显示良性和恶性肿瘤的 TIC 模式之间存在显著差异（X=38.78，p<0.001）。ROC 分析显示 ADC 对鉴别 PA 和 Warthin 瘤与其他肿瘤具有最佳诊断性能，曲线下面积（AUC）值分别为 0.945 和 0.925（p<0.01）。此外，TIC 类型是唯一有用的鉴别良恶性 PTs 的生物标志物，AUC 值为 0.846（p<0.01）。关于 DCE-MRI 和 ADC 值的多个参数联合应用的准确性，在五种方案中，TIC 模式与细胞外容积比（Ve）的结合提供了最佳结果，其准确率最高为 0.75，其次是 TIC 模式与 ADC 的联合应用（准确率为 0.70）。
结论
基于 DCE-MRI 的 TIC 模式联合 Ve 标志物可在 PTs 的鉴别诊断中达到最佳诊断准确性。
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