表观扩散系数直方图鉴别弥漫性较低级别脑胶质瘤分子亚型的价值

目的 研究基于肿瘤全域的表观扩散系数(ADC)信号灰度直方图鉴别弥漫性较低级别胶质瘤分子亚型的价值。方法 回顾经手术及病理证实为WHO Ⅱ、Ⅲ级胶质瘤,术前接受过头颅磁共振成像平扫、增强及扩散加权成像检查的55例患者的病理及影像学资料。先将其分为异柠檬酸脱氢酶(IDH)突变(IDH ^mut)组和IDH野生(IDH ^wt)组,再将IDH ^mut组分为IDH突变伴1p19q联合缺失(IDH ^mut1p19q ^del)组和IDH突变不伴1p19q联合缺失(IDH ^mut1p19q ^int)组。其中IDH ^wt组14例、IDH ^mut1p19q ^int组19例、IDH ^mut1p19q ^del组22例。记录不同分子亚型组的ADC直方图参数,包括平均值、最小值、 ADC5%、ADC10%、 ADC25%、 ADC50%、 ADC75%、 ADC90%、ADC95%、最大值、众数、峰度、偏度、标准差、不均一性、极差、熵值,并采用独立样本t检验(正态分布)或Mann-Whitney U检验(偏态分布)比较。采用受试者工作特征曲线(ROC)评价ADC直方图参数鉴别诊断WHO Ⅱ、Ⅲ级胶质瘤不同分子亚型的效能。结果 IDH ^mut组的 ADC75%(P=0.021)、 ADC90%(P=0.015)、ADC95%(P=0.014)、最大值(P=0.035)、标准差(P=0.001)、不均一性(P=0.001)和极差(P=0.009)均低于IDH ^wt组,而最小值(P=0.031)和峰度(P=0.020)则高于IDH ^wt组,差异有统计学意义。IDH ^mut1p19q ^del组的平均值(P=0.010)、ADC5%(P=0.016)、ADC10%(P=0.012)、 ADC25%(P=0.007)、 ADC50%(P=0.005)、ADC75%(P=0.015)及众数(P=0.002)均低于IDH ^mut1p19q ^int组。不均一性鉴别IDH ^wt组和IDH ^mut组的效能优于其他参数,ROC曲线下面积为0.811,以0.229为截断值鉴别二者的敏感度和特异度分别为85.7%和73.2%;众数鉴别IDH ^mut1p19q ^del组和IDH ^mut1p19q ^int组的效能高于其他参数,ROC曲线下面积为0.744,以1448.75×10 ^-6mm ²/s为截断值鉴别二者的灵敏度和特异度分别为57.9%和90.9%。结论 基于肿瘤全域感兴趣区的ADC信号强度直方图可以为弥漫性较低级别胶质瘤分子亚型的鉴别提供更多信息。

Apparent Diffusion Coefficient Histogram Analysis:Differentiation of Genetic Subtypes of Diffuse Lower-grade Gliomas

Objective To explore the utility of apparent diffusion coefficient(ADC)histogram analysis for differentiating genetic subtypes of diffuse lower-grade gliomas. Methods A total of 55 patients with WHO grade Ⅱ/Ⅲ diffuse lower-grade gliomas who underwent preoperative routine brain magnetic resonance imaging and diffusion weighted imaging in our center were retrospectively evaluated.Among whom there were 14 patients with isocitrate dehydrogenase(IDH)wild-type gliomas(IDH ^wt group),19 patients with IDH-mutant 1p19q intact gliomas(IDH ^mut1p19q ^int group),and 22 patients with IDH-mutant 1p19q co-deleted gliomas(IDH ^mut1p19q ^del group).The whole-lesion ADC values derived from histogram analysis(including ADC_mean,ADC_minimum,ADC5%,ADC10%,ADC25%,ADC50%,ADC75%,ADC90%,ADC95%,ADC_maximum,mode,range,skewness,kurtosis,standard deviation,inhomogeneity,and entrophy)were measured for each patient.All parameters between the different genetic subtypes were compared by using the Student’s t test or Mann-Whitney U test.Receiver operating curve(ROC)analysis was used to assess the diagnostic performance of ADC histogram in distinguishing the different genetic subtypes. Results Compared with IDH ^wt group,the ADC75%(P=0.021),ADC90%(P=0.015),ADC95%(P=0.014),ADC_maximum (P=0.035),range(P=0.009),standard deviation(P=0.001)and inhomogeneity(P=0.001)were significantly lower in IDH ^mut group;in contrast,the ADC_minimum (P=0.031)and kurtosis(P=0.020)of IDH ^mut group were significantly higher than those in IDH ^wt group.The ADC_mean(P=0.010),ADC5%(P=0.016),ADC10%(P=0.012),ADC25%(P=0.007),ADC50%(P=0.005),ADC75%(P=0.015),and mode(P=0.002)were significantly higher in IDH ^mut1p19q ^int group than in IDH ^mut1p19q ^del group.Inhomogeneity achieved the highest area under ROC(AUC)(0.811)in differentiating IDH ^mut gliomas and IDH ^wt gliomas,with a cutoff value of 0.229;the sensitivity and specificity were 85.7% and 73.2%.The mode achieved the highest AUC(0.744)in differentiating IDH ^mut1p19q ^int gliomas and IDH ^mut1p19q ^del gliomas,with a cutoff value was 1448.75×10 ^-6 mm ²/s;the sensitivity and specificity were 57.9% and 90.9%.Conclusion ADC histograms analysis may be helpful to differentiate genetic subtypes in lower-grade gliomas.