扩散峰度成像对上皮性卵巢癌分型的鉴别诊断

目的 探讨扩散峰度成像（DKI）对Ⅰ型与Ⅱ型上皮性卵巢癌（EOC）的鉴别诊断价值。 方法 回顾性收集经手术病理证实的45例EOC病人的临床、病理及影像资料,平均年龄（50±13）岁。根据术后病理结果对EOC病人进行分组,分为Ⅰ型组（24例）和Ⅱ型组（21例）。所有病人均于术前行盆腔DKI检查,由2名放射科医师在DKI各参数伪彩图上分别测量平均扩散峰度（MK）、平行扩散峰度（Ka）、垂直扩散峰度（Kr）、平均扩散系数（MD）、平行扩散系数（Da）、垂直扩散系数（Dr）、各向异性分数（FA）、峰度各向异性分数（FAk）。采用Fisher确切概率检验、独立样本t检验或Mann-Whitney U检验比较2组间临床、病理及影像资料的差异,对差异有统计学意义的参数绘制受试者操作特征（ROC）曲线,分析其鉴别诊断效能。 结果 病理表现上,Ⅰ型中交界性肿瘤占比最高（50.0%）,Ⅱ型中浆液性癌占比最高（61.9%）;Ⅰ型中高分化癌占50%,Ⅱ型多表现为中低分化癌 （76.2%）,Ⅰ型EOC的分化程度高于Ⅱ型;Ⅰ型多数处于Ⅰ期（79.2%）,Ⅱ型多处于Ⅲ期(57.1%)（均P<0.05）。MRI影像上, Ⅰ型病灶多表现为囊性(41.7%)或囊实性（33.3%）,Ⅱ型多表现为实性（52.3%）;Ⅱ型（66.7%）腹水发生率高于Ⅰ型（29.2%）（均P<0.05）。Ⅰ型的MK、Ka和Kr值低于Ⅱ型,MD、Da和Dr值高于Ⅱ型（均P<0.05）。ROC曲线分析显示,MK阈值为0.504时,鉴别2组诊断的曲线下面积（AUC,0.817）最大,诊断敏感度（95.2%）、阴性预测值（92.9%）、准确度（78.9%）也最高,Da阈值为2.190时鉴别诊断的AUC（0.770）最小,而特异度（76.2%）、阳性预测值（75.9%）最高。 结论 DKI序列的定量参数MK、Ka、Kr、MD、Da及Dr均有助于鉴别Ⅰ型与Ⅱ型EOC,其中MK值鉴别诊断效能更大。

The diagnostic value of diffusion kurtosis imaging for differentiating types of epithelial ovarian cancer

Objective To explore the diagnostic value of diffusion kurtosis imaging (DKI) in differentiating typeⅠand typeⅡof epithelial ovarian cancer (EOC). Methods The clinical and imaging data of 45 patients (50±13 years old) with confirmed by surgery and pathology were retrospectively collected. According to postoperative pathological results, 24 patients were assigned to typeⅠgroup and 21 patients to typeⅡgroup. Preoperative pelvic DKI was performed in all patients. DKI parameters including the mean kurtosis (MK), axial kurtosis (Ka), radial kurtosis (Kr), mean diffusivity (MD), axial diffusivity (Da), radial diffusivity (Dr), fractional anisotropy (FA), and fractional anisotropy of kurtosis (FAk) were measured on pseudo-color maps by two radiologists. Fisher exact test, independent sample t test or Mann-Whitney U test were used to compare the difference in clinical, pathological and imaging data between the 2 groups. The receiver operator characteristic (ROC) curve was drawn for the statistically significant parameters to analyze their differential diagnostic efficacy. Results On the pathological analysis, borderline cancers were common(50.0%) in the typeⅠcancers, and serous cancers accounted for the highest proportion (61.9%) in the typeⅡcancers. In the type Ⅰ cancers, highly differentiated cancers accounted for 50%, while in the typeⅡcancers, moderately and poorly differentiated cancers were more common (76.2%), and the differentiation degrees of typeⅠcancers were higher than that of typeⅡcancers; most of typeⅠcancers were in stageⅠ(79.2%), and most of typeⅡcancers were in stageⅢ(57.1%) (all P<0.05). On MRI, the most common lesion was cystic (41.7%) or solid-cystic (33.3%) in the type Ⅰ cancers, while solid (52.3%) lesions were more common in the typeⅡcancers. The incidence of ascites in the typeⅡcancers (66.7%) was higher than that in the typeⅠcancers (29.2%) (all P<0.05). The MK, Ka and Kr values of the typeⅠcancers were lower than those of the typeⅡcancers, and the MD, Da and Dr Values were higher than those of the typeⅡcancers (all P<0.05). ROC curve analysis indicated when the MK threshold was 0.504, the AUC (0.817) of differential diagnosis was the highest, the diagnostic sensitivity (95.2%), negative predictive value (92.9%) and accuracy (78.9%) were the highest, and the AUC (0.770) of differential diagnosis was the lowest when the Da threshold was 2.190, uhile the specificity (76.2%) and positive predictive value (75.9%) were the highest. Conclusion The quantitative parameters MK, Ka, Kr, MD, Da and Dr of DKI can be used for differentiating typeⅠand typeⅡEOC, and the MK value performs best.