动态对比增强MRI在脑胶质瘤分级中计算模型的选择及应用研究
Using dynamic contrast-enhanced MRI to predict the histopathologic grade of cerebral gliomas
目的 探讨动态对比增强MRI(DCE-MRI)不同计算模型在胶质瘤分级诊断中的应用价值.方法 2013年3月至2014月11月共收集41例胶质瘤患者,包括Ⅱ级13例、Ⅲ级14例、Ⅳ级14例.所有患者均进行DCE-MRI检查,通过3种不同的计算模型(Patlak单室模型、Toffs单室模型、Extended Toffs Linear双室模型)测量同一胶质瘤实性部分的容积转运常数(Ktrans),采用Kruskal-Wallis非参数假设检验比较不同等级胶质瘤间Ktrans值的差异,Spearman相关系数分析3种模型计算的Ktrans值之间的相关性,并应用ROC曲线分析不同计算模型的Ktrans值鉴别低级别和高级别胶质瘤的敏感度和特异度.结果 Patlak模型计算Ⅱ、Ⅲ、Ⅳ级胶质瘤的Kttrans值分别为0.008(0.004 ~ 0.043)、0.021 (0.005~ 0.088)、0.035(0.017 ~ 0.061) min-1,Toffs模型计算的Ktrans5值分别为0.085(0.041~ 0.158)、0.140(0.063~0.315)、0.229(0.126~ 0.419) min-1,Extended Toffs Linear模型计算的Ktrans值分别为0.012(0.004~0.092)、0.048(0.010~0.188)、0.094(0.036 ~ 0.215)min-1,3种模型计算所得Ktrans值随着胶质瘤的级别的增高而升高,在不同胶质瘤间差异具有统计学意义(H值分别为18.31、18.09、20.18,P值均<0.01).Extended Tofts Linear双室模型与Patlak模型、Toffs单室模型Ktrans值均有较好的相关性(r值分别为0.933、0.893,P值均<0.05),Patlak模型与Toffs单室模型Ktrans值相关性稍差(r=0.822,P<0.05).3种模型计算的Ktrans值在鉴别低级别胶质瘤(LGG)与高级别胶质瘤(HGG)时具有较高的敏感度与特异度,其中Extended Toffs Linear双室模型的综合诊断效能最佳,敏感度为92.3%,特异度为85.7%.结论 应用DCE-MRI可以为胶质瘤分级提供重要参考,Extended Toffs Linear双室模型更适用于评价胶质瘤分级.
更多Objective To evaluate three different tracer-kinetic models used for dynamic contrast-enhanced MRI (DCE-MRI) data processing in the prediction of the histopathologic grade of cerebral gliomas.Methods Forty-one patients with histopathologically graded gliomas (grade Ⅱ 13,grade Ⅲ 14,grade Ⅳ 14)were imaged with DCE-MRI from March,2013 to November,2014.The values of Ktrans of gliomas were obtained by three tracer-kinetic models,which were Patlak model,Tofts model and Extended Tofts Linear model.All data were analyzed statistically by a Graphpad 6.0 statistical software.Comparison of the differences of Ktrans among different grades of gliomas was conducted using the Kruskal-Wallis test and Dunn's multiple comparisons test for the data not conform to normal distribution.Correlations of Ktrans values among those three models were analyzed using linear regression analysis,The differences of Ktrans between low grades and high grades of gliomas was conducted using the Mann-Whitney U test.Receiver operating characteristic (ROC) curve analyses were performed to determine the cut-off values for Ktrans to distinguish different low grades and high grades of gliomas.Results The Ktrans values obtained by Patlak model was 0.008(0.004-0.043) min-1for grade Ⅱ,0.021(0.005-0.088) min-1 for grade Ⅲ,and 0.035(0.017-0.061) min-1 for grade Ⅳ.The Ktrans values obtained by Tofts model was 0.085 (0.041-0.158)min 1for grade Ⅱ,0.140 (0.063-0.315) min-1for grade Ⅲ,0.229 (0.126-0.419)min 1 for grade Ⅳ.The Ktrans values obtained by Extended Tofts Linear model was 0.012 (0.004-0.092) min 1 for grade Ⅱ,0.048 (0.010-0.188) min-t for grade Ⅲ,0.094 (0.036-0.215)min 1 for grade Ⅳ.All the Ktrans values obtained by three models increased when the histological grades increased,with statistical significance between grade Ⅱ and Ⅲ (H=18.31,18.09,20.18,P<0.05).Ktrans values among the three models had good linear correlations.The Ktrans obtained by Extended Tofts Linear model had good linear correlations with both Patlak model and Tofts model (r=0.933,0.893,P<0.05),and the Ktrans obtained by Patlak model had less linear correlation with Tofts model (r=0.822,P<0.05).The K values were statistically different between LGG and HGG (P<0.01).The cut-off value of K provided good combination of sensitivity and specificity in the differentiation between LGG and HGG,and the K obtained by Extended Tofts Linear model had the best sensitivity and specificity among the three models (sensitivity 92.3%,specificity 85.7%).Conclusions K from DCE-MRI has a high performance in predicting the histopathologic grade of brain glioma,and the Extended Tofts Linear model is more suitable for the evaluation of cerebral glioma.
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