Cardiovascular Research Institute Maastricht, 6200 MD Maastricht, The Netherlands.
Med Phys. 2010 Nov;37(11):5746-55. doi: 10.1118/1.3484057.
The goal of this study was to optimize dynamic contrast-enhanced (DCE)-MRI analysis for differently sized contrast agents and to evaluate the sensitivity for microvascular differences in skeletal muscle.
In rabbits, pathophysiological perfusion differences between hind limbs were induced by unilateral femoral artery ligation. On days 14 and 21, DCE-MRI was performed using a medium-sized contrast agent (MCA) (Gadomer) or a small contrast agent (SCA) (Gd-DTPA). Acquisition protocols were adapted to the pharmacokinetic properties of the contrast agent. Model-based data analysis was optimized by selecting the optimal model, considering fit error, estimation uncertainty, and parameter interdependency from three two-compartment pharmacokinetic models (normal and extended generalized kinetic models and Patlak model). Model-based parameters were compared to the model-free parameter area-under-curve (AUC). Finally, the sensitivity of transfer constant Krans and AUC for physiological and pathophysiological microvascular differences was evaluated.
For the MCA, the optimal model included Ktrans and plasma fraction nu(p). For the SCA, Ktrans and interstitial fraction nu(e) should be incorporated. For the MCA, Ktrans were (4.8 +/- 0.2) x 10(-3) min(-1) (mean standard error) and (3.6 +/- 0.1) x 10(-3) min(-1) for the red soleus and white tibialis muscle, respectively, p < 0.01. With the SCA, Ktrans were (81 +/- 5) x 10(-3) min(-1) (soleus) and (66 +/- 5) x 10(-3) min(-1) (tibialis) p < 0.01. In the ischemic limb, Ktrans was significantly decreased relative to the control limb (soleus: 15%-20%; tibialis: 5%-10%). Similar differences in AUC were found for both contrast agents.
For optimal estimation of microvascular parameters, both model-based and model-free analysis should be adapted to the pharmacokinetic properties of the contrast agent. The detection of microvascular differences based on both Ktrans and AUC was most sensitive when the analysis strategy was tailored to the contrast agent used. The MCA was equally sensitive for microvascular differences as the SCA, with the advantage of improved spatial resolution.
本研究旨在优化不同大小对比剂的动态对比增强(DCE)-MRI 分析,并评估其对骨骼肌微血管差异的敏感性。
在兔子中,通过单侧股动脉结扎诱导后肢之间的病理生理学灌注差异。在第 14 天和第 21 天,使用中号对比剂(MCA)(钆美胺)或小号对比剂(SCA)(Gd-DTPA)进行 DCE-MRI。采集方案根据对比剂的药代动力学特性进行了调整。通过从三种双室药代动力学模型(正常和扩展广义动力学模型和 Patlak 模型)中选择最佳模型,考虑拟合误差、估计不确定性和参数相关性,对基于模型的数据进行了优化。将基于模型的参数与无模型参数曲线下面积(AUC)进行了比较。最后,评估了转移常数 Krans 和 AUC 对生理和病理生理微血管差异的敏感性。
对于 MCA,最佳模型包括 Ktrans 和血浆分数 nu(p)。对于 SCA,应纳入 Ktrans 和间质分数 nu(e)。对于 MCA,红色比目鱼肌和白色胫骨前肌的 Ktrans 分别为(4.8±0.2)×10(-3) min(-1)(平均值标准误差)和(3.6±0.1)×10(-3) min(-1),p<0.01。使用 SCA,比目鱼肌和胫骨前肌的 Ktrans 分别为(81±5)×10(-3) min(-1)和(66±5)×10(-3) min(-1),p<0.01。与对照肢体相比,缺血肢体的 Ktrans 显著降低(比目鱼肌:15%-20%;胫骨前肌:5%-10%)。两种对比剂的 AUC 也存在相似的差异。
为了最佳估计微血管参数,基于模型和无模型分析都应适应对比剂的药代动力学特性。当分析策略针对所用对比剂进行调整时,基于 Ktrans 和 AUC 的微血管差异检测最为敏感。MCA 对微血管差异的敏感性与 SCA 相当,具有提高空间分辨率的优势。