磁共振弥散峰度成像在腮腺肿瘤诊断与鉴别诊断的临床价值

The clinical value of diagnosis and differential diagnosis of magnetic resonance diffusion kurtosis imaging for parotid tumors

目的:探讨磁共振弥散峰度成像在鉴别腮腺肿瘤良性和恶性的应用价值。方法:选取32例腮腺肿瘤患者,术前行常规磁共振成像(MRI)及弥散峰度成像(DKI)扫描,应用弥散峰度评估软件测定平均峰度(MK)值、各向异性(FA)值和平均扩散率(MD)值,应用ROC曲线分析获得MK值、FA值和MD值,鉴别腮腺肿瘤良性和恶性的敏感度、特异度及曲线下面积等诊断效能指标。结果:腮腺良性肿瘤的平均MK值明显低于恶性腮腺肿瘤,差异有统计学意义(Z=2.934,P=0.003);腮腺良性肿瘤FA值低于恶性肿瘤,差异有统计学意义(Z=2.348,P=0.019);腮腺良性肿瘤MD值明显高于恶性肿瘤腮腺,差异有统计学意义(Z=2.077,P=0.047)。腮腺良性和恶性肿瘤MK值、FA值和MD值的诊断临界值分别是1.0528、0.2396和0.6472(×10-3mm2/s);MK值鉴别腮腺肿瘤良恶性的诊断效能优于MD值和FA值。结论:DKI相比传统弥散(DWI)和弥散张量成像(DTI)在腮腺肿瘤良性和恶性鉴别方面有更好的特异度和敏感度。MK值可以显示腮腺肿瘤病理特性并提供定量信息,有助于肿瘤的鉴别诊断。

Objective： This study aimed to explore the application values of diffusion kurtosis imaging（DKI） in differential diagnosis of benign and malignant parotid tumors.Methods： 32 patients with parotid tumor were examined preoperative with conventional magnetic resonance imaging（MRI） and DKI, respectively. The data of DKI were analyzedwith diffusion kurtosis estimator to calculate mean kurtosis（MK）, mean diffusivity（MD） and fractional anisotropy（FA）. And the MK, MD and FA can be got by ROC curve. The diagnostic accuracy of MK, MD and FA values was evaluated with series of diagnosis effectiveness indicators, such as sensitivity, specificity, and area under receiver operating characteristic（ROC） curve. Results： There was a significant difference between benign and malignant parotid tumors in the values of MK, FA and MD（P=0.003, 0.019 and 0.047, respectively）. The mean MK value of benign parotid tumors was significantly lower than malignant parotid tumors; The mean FA value of benign parotid tumors was significantly lower than malignant parotid tumors; and the mean MD value of benign tumors was significantly higher than malignant tumors. The diagnosis of cut-off point between benign and malignant parotid tumors for MK, FA and MD was 1.0528, 0.2396 and 0.6472（×10-3mm2/s）, respectively. The sensitivity, specificity and AUC for MK, FA and MD in differentiating benign and malignant parotid tumor were 0.853, 75.00%, 91.30%; 0.783, 75%, 82.61%; 0.739, 50%, 95.65%; respectively. Conclusion： DKI showed higher specificity and sensitivity than did conventional diffusion-weighted and diffusion-tensor imaging for assessment and differential diagnosis of benign and malignant parotid tumors. MK enables differentiation and characterisation of parotid tumors, and provides quantitative information for the parotid tumors.