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肝脏的动态对比增强磁共振成像:线性和非线性转换对肝脏灌注定量及可重复性的影响

DCE-MRI of the liver: effect of linear and nonlinear conversions on hepatic perfusion quantification and reproducibility.

作者信息

Aronhime Shimon, Calcagno Claudia, Jajamovich Guido H, Dyvorne Hadrien Arezki, Robson Philip, Dieterich Douglas, Fiel M Isabel, Martel-Laferriere Valérie, Chatterji Manjil, Rusinek Henry, Taouli Bachir

机构信息

Translational and Molecular Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

出版信息

J Magn Reson Imaging. 2014 Jul;40(1):90-8. doi: 10.1002/jmri.24341. Epub 2013 Nov 4.

Abstract

PURPOSE

To evaluate the effect of different methods to convert magnetic resonance (MR) signal intensity (SI) to gadolinium concentration ([Gd]) on estimation and reproducibility of model-free and modeled hepatic perfusion parameters measured with dynamic contrast-enhanced (DCE)-MRI.

MATERIALS AND METHODS

In this Institutional Review Board (IRB)-approved prospective study, 23 DCE-MRI examinations of the liver were performed on 17 patients. SI was converted to [Gd] using linearity vs. nonlinearity assumptions (using spoiled gradient recalled echo [SPGR] signal equations). The [Gd] vs. time curves were analyzed using model-free parameters and a dual-input single compartment model. Perfusion parameters obtained with the two conversion methods were compared using paired Wilcoxon test. Test-retest and interobserver reproducibility of perfusion parameters were assessed in six patients.

RESULTS

There were significant differences between the two conversion methods for the following parameters: AUC60 (area under the curve at 60 s, P < 0.001), peak gadolinium concentration (Cpeak, P < 0.001), upslope (P < 0.001), Fp (portal flow, P = 0.04), total hepatic flow (Ft, P = 0.007), and MTT (mean transit time, P < 0.001). Our preliminary results showed acceptable to good reproducibility for all model-free parameters for both methods (mean coefficient of variation [CV] range, 11.87-23.7%), except for upslope (CV = 37%). Among modeled parameters, DV (distribution volume) had CV <22% with both methods, PV and MTT showed CV <21% and <29% using SPGR equations, respectively. Other modeled parameters had CV >30% with both methods.

CONCLUSION

Linearity assumption is acceptable for quantification of model-free hepatic perfusion parameters while the use of SPGR equations and T1 mapping may be recommended for the quantification of modeled hepatic perfusion parameters.

摘要

目的

评估将磁共振(MR)信号强度(SI)转换为钆浓度([Gd])的不同方法对动态对比增强(DCE)-MRI测量的无模型和建模肝脏灌注参数估计及可重复性的影响。

材料与方法

在这项经机构审查委员会(IRB)批准的前瞻性研究中,对17例患者进行了23次肝脏DCE-MRI检查。使用线性与非线性假设(使用扰相梯度回波[SPGR]信号方程)将SI转换为[Gd]。使用无模型参数和双输入单室模型分析[Gd]随时间的曲线。使用配对Wilcoxon检验比较两种转换方法获得的灌注参数。在6例患者中评估灌注参数的重测和观察者间的可重复性。

结果

两种转换方法在以下参数上存在显著差异:AUC60(60秒时曲线下面积,P < 0.001)、钆峰值浓度(Cpeak,P < 0.001)、上升斜率(P < 0.001)、Fp(门静脉血流,P = 0.04)、肝脏总血流(Ft,P = 0.007)和MTT(平均通过时间,P < 0.001)。我们的初步结果表明,两种方法的所有无模型参数的可重复性均可接受至良好(平均变异系数[CV]范围为11.87 - 23.7%),上升斜率除外(CV = 37%)。在建模参数中,两种方法的DV(分布容积)的CV < 22%,使用SPGR方程时PV和MTT的CV分别< 21%和< 29%。其他建模参数两种方法的CV均> 30%。

结论

线性假设对于无模型肝脏灌注参数的量化是可接受的,而对于建模肝脏灌注参数的量化,可能建议使用SPGR方程和T1映射。

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