Korobova Natalia V, Wassenaar Nienke P M, Troelstra Marian A, Schrauben Eric M, Gurney-Champion Oliver J
Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam, The Netherlands.
Imaging and Biomarkers, Cancer Center Amsterdam, Amsterdam, The Netherlands.
Magn Reson Med. 2025 Aug;94(2):810-824. doi: 10.1002/mrm.30514. Epub 2025 Mar 30.
Dynamic contrast-enhanced sequences (e.g. spiral, radial, PROPELLER MRI) often rely on oversampling the center of k-space. Instead of the discrete snapshots obtained by Cartesian sampling, oversampling the k-space center results in time-averaging of the signal. We hypothesize that these time-averaged signals decrease the accuracy of pharmacokinetic modeling and propose a model that accounts for this effect.
To test our hypothesis, a modified extended Tofts model tailored to accommodate time-averaged signals is proposed. Simulated Monte Carlo experiments were conducted to compare the performance of the modified model with the conventional model. Additionally, to validate the findings in vivo, models were fitted to pseudo-spiral variable-density dynamic contrast-enhanced MRI scans of pancreatic cancer patients reconstructed at 4, 8, 10, and 15 s/frame.
The simulations demonstrated that for time-averaged acquisitions, our modified extended Tofts model provided more accurate and precise results than conventional models. Additionally, by integrating signals, some information on high temporal behavior was recovered. Particularly, at long acquisitions (15 s/frame), variable-density sampling with the modified model outperformed conventional discrete sampling. In vivo experiments confirmed these findings, as the corrected model showed more consistent estimates of parameters and over the tested sampling frequencies, highlighting its potential to improve accuracy in clinical settings.
Our study demonstrates that time-averaged signals lead to decreased accuracy and precision in pharmacokinetic modeling when ignored. We suggest using our corrected pharmacokinetic model when performing dynamic contrast-enhanced with variable-density acquisitions, especially for dynamic scan times that are 8 s and longer.
动态对比增强序列(如螺旋、径向、螺旋桨MRI)通常依赖于对k空间中心进行过采样。与笛卡尔采样获得的离散快照不同,对k空间中心进行过采样会导致信号的时间平均。我们假设这些时间平均信号会降低药代动力学建模的准确性,并提出一个考虑这种效应的模型。
为了验证我们的假设,提出了一种经过修改的扩展Tofts模型,以适应时间平均信号。进行了模拟蒙特卡罗实验,比较修改后的模型与传统模型的性能。此外,为了在体内验证这些发现,将模型拟合到胰腺癌患者以4、8、10和15秒/帧重建的伪螺旋可变密度动态对比增强MRI扫描中。
模拟结果表明,对于时间平均采集,我们修改后的扩展Tofts模型比传统模型提供了更准确和精确的结果。此外,通过整合信号,恢复了一些关于高时间行为的信息。特别是在长时间采集(15秒/帧)时,使用修改后的模型进行可变密度采样优于传统的离散采样。体内实验证实了这些发现,因为校正后的模型在测试的采样频率上对参数和的估计更一致,突出了其在临床环境中提高准确性的潜力。
我们的研究表明,当忽略时间平均信号时,会导致药代动力学建模的准确性和精确性降低。我们建议在进行可变密度采集的动态对比增强时,特别是对于8秒及更长的动态扫描时间,使用我们校正后的药代动力学模型。