IEEE Trans Med Imaging. 2024 Jul;43(7):2411-2419. doi: 10.1109/TMI.2024.3357799. Epub 2024 Jul 1.
Positron emission tomography (PET) imaging enables quantitative assessment of tissue physiology. Dynamic pharmacokinetic analysis of PET images requires accurate estimation of the radiotracer plasma input function to derive meaningful parameter estimates, and small discrepancies in parameter estimation can mimic subtle physiologic tissue variation. This study evaluates the impact of input function interpolation method on the accuracy of Patlak kinetic parameter estimation through simulations modeling the pharmacokinetic properties of [68Ga]-PSMA-11. This study evaluated both trained and untrained methods. Although the mean kinetic parameter accuracy was similar across all interpolation models, the trained node weighting interpolation model estimated accurate kinetic parameters with reduced overall variability relative to standard linear interpolation. Trained node weighting interpolation reduced kinetic parameter estimation variance by a magnitude approximating the underlying physiologic differences between normal and diseased prostatic tissue. Overall, this analysis suggests that trained node weighting improves the reliability of Patlak kinetic parameter estimation for [68Ga]-PSMA-11 PET.
正电子发射断层扫描（PET）成像能够定量评估组织生理学。要对 PET 图像进行动态药代动力学分析，需要准确估计示踪剂血浆输入函数，以得出有意义的参数估计值，而参数估计中的微小差异可能模拟微妙的生理组织变化。本研究通过模拟 [68Ga]-PSMA-11 的药代动力学特性，评估输入函数内插方法对 Patlak 动力学参数估计准确性的影响。本研究评估了训练有素的方法和未经训练的方法。虽然所有插值模型的平均动力学参数准确性相似，但与标准线性插值相比，经过训练的节点加权插值模型估计出的准确动力学参数具有较低的总体变异性。训练有素的节点加权插值通过近似正常和患病前列腺组织之间的生理差异的幅度，减少了动力学参数估计的方差。总的来说，这项分析表明，对于 [68Ga]-PSMA-11 PET，经过训练的节点加权可以提高 Patlak 动力学参数估计的可靠性。
