Department of Neurosurgery, Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK.
Geoffrey Jefferson Brain Research Centre, University of Manchester, Stott Lane, Salford, M6 8HD, Greater Manchester, UK.
Sci Rep. 2022 May 24;12(1):8737. doi: 10.1038/s41598-022-12582-x.
Accurate vascular input function (VIF) derivation is essential in brain dynamic contrast-enhanced (DCE) MRI. The optimum site for VIF estimation is, however, debated. This study sought to compare VIFs extracted from the internal carotid artery (ICA) and its branches with an arrival-corrected vascular output function (VOF) derived from the superior sagittal sinus (VOF). DCE-MRI datasets from sixty-six patients with different brain tumours were retrospectively analysed and plasma gadolinium-based contrast agent (GBCA) concentration-time curves used to extract VOF/VIFs from the SSS, the ICA, and the middle cerebral artery. Semi-quantitative parameters across each first-pass VOF/VIF were compared and the relationship between these parameters and GBCA dose was evaluated. Through a test-retest study in 12 patients, the repeatability of each semiquantitative VOF/VIF parameter was evaluated; and through comparison with histopathological data the accuracy of kinetic parameter estimates derived using each VOF/VIF and the extended Tofts model was also assessed. VOF provided a superior surrogate global input function compared to arteries, with greater contrast-to-noise (p < 0.001), higher peak (p < 0.001, repeated-measures ANOVA), and a greater sensitivity to interindividual plasma GBCA concentration. The repeatability of VOF derived semi-quantitative parameters was good to excellent (ICC = 0.717-0.888) outperforming arterial based approaches. In contrast to arterial VIFs, kinetic parameters obtained using a SSS derived VOF permitted detection of intertumoural differences in both microvessel surface area and cell density within resected tissue specimens. These results support the usage of an arrival-corrected VOF as a surrogate vascular input function for kinetic parameter mapping in brain DCE-MRI.
准确的血管输入函数 (VIF) 推导对于脑动态对比增强 (DCE) MRI 至关重要。然而,最佳的 VIF 估计部位仍存在争议。本研究旨在比较从颈内动脉 (ICA) 及其分支提取的 VIF 与从矢状窦 (SSS) 校正到达时间的血管输出函数 (VOF) 。回顾性分析了 66 例不同脑肿瘤患者的 DCE-MRI 数据集,并使用血浆钆基造影剂 (GBCA) 浓度-时间曲线从 SSS、ICA 和大脑中动脉提取 VOF/VIF。比较了每个初次通过 VOF/VIF 的半定量参数,并评估了这些参数与 GBCA 剂量之间的关系。通过 12 例患者的测试-重测研究,评估了每个半定量 VOF/VIF 参数的可重复性;并通过与组织病理学数据的比较,评估了使用每个 VOF/VIF 和扩展 Tofts 模型得出的动力学参数估计的准确性。与动脉相比,VOF 提供了更好的替代全局输入函数,具有更高的对比度噪声比(p<0.001)、更高的峰值(p<0.001,重复测量方差分析),并且对个体间血浆 GBCA 浓度更敏感。从 VOF 提取的半定量参数的重复性良好到优秀(ICC=0.717-0.888),优于基于动脉的方法。与动脉 VIF 相反,使用 SSS 衍生的 VOF 获得的动力学参数允许检测到切除组织标本中肿瘤间微血管表面积和细胞密度的差异。这些结果支持使用校正到达时间的 VOF 作为脑 DCE-MRI 中动力学参数映射的替代血管输入函数。