T2 mapping成像评估宫颈癌病理学特征

Quantitative analysis of T2 mapping in evaluating pathological features of cervical cancer

探讨T2 mapping成像鉴别宫颈癌类型、分化程度及预测淋巴血管间隙浸润(LVSI)的价值。方法对57例经病理证实的宫颈癌患者于治疗前行常规MR、DWI和T2 mapping检查,测量肿瘤和正常子宫肌层的T2值和ADC值。对比测量参数在肿瘤与正常子宫肌层、鳞癌与腺癌、中高分化与低分化、LVSI阳性与LVSI阴性之间的差别,绘制ROC曲线,评价诊断效能。结果宫颈癌肿瘤与正常子宫肌层之间T2值、ADC值差异均有统计学意义(P均<0.001),鳞癌与腺癌之间T2值、ADC值差异均无统计学意义(P均>0.05),低分化组T2值和ADC值均低于中高分化组(P均<0.05),LVSI阳性组T2值明显低于LVSI阴性组(P=0.002)。LVSI阳性组和LVSI阴性组ADC值差异无统计学意义(P=0.675)。T2值、ADC值鉴别高中分化与低分化宫颈癌的ROC曲线AUC分别为0.709、0.747,T2值预测宫颈癌LVSI的AUC为0.856。结论T2 mapping成像可用于诊断宫颈癌和病理分级,预测宫颈癌LVSI状态优于ADC值。

Objective To investigate the quantitative analysis value of T2 mapping in the evaluation of pathological type,tumor grade and lymphovascular space invasion (LVSI) of cervical cancer.Methods Totally 57 patients with pathologically proven cervical cancer underwent conventional MRI,DWI and T2 mapping before therapy.T2 and ADC values were obtained and compared between tumor and normal tissue (myometrium),squamous cell carcinomas and adenocarcinomas,well/moderately differentiated tumor and poorly differentiated tumor,LVSI-positive and LVSI-negative cervical cancer,respectively.ROC curve was constructed to evaluate diagnostic performances.Results T2 and ADC values showed significant differences between cervical cancer and normal tissue (both P <0.001).No significant difference was observed in T2 and ADC values between squamous cell carcinomas and adenocarcinomas (both P >0.05).Compared to well/moderately differentiated tumors,poorly differentiated tumors showed decreased T2 and ADC values (both P <0.05).T2 values were significantly lower in LVSI-positive than in LVSI-negative cervical cancer ( P =0.002),while ADC values were not significantly different ( P =0.675).The AUC of T2 and ADC values for distinguishing tumor grade were 0.709 and 0.747,respectively.The AUC of T2 value in discriminating the presence of LVSI was 0.856.Conclusion Quantitative T2 mapping can putatively differentiate the grade of cervical cancer.Moreover,quantitative T2 value exhibits better than ADC for discriminating the presence of LVSI.