Johansson Adam, Balter James, Feng Mary, Cao Yue
Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan.
Tomography. 2016 Sep;2(3):188-196. doi: 10.18383/j.tom.2016.00145.
Quantitative hepatic perfusion parameters derived by fitting dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) of liver to a pharmacokinetic model are prone to errors if the dynamic images are not corrected for respiratory motion by image registration. The contrast-induced intensity variations in pre- and postcontrast phases pose challenges for the accuracy of image registration. We propose an overdetermined system of transformation equations between the image volumes in the DCE-MRI series to achieve robust alignment. In this method, we register each volume to every other volume. From the transforms produced by all pairwise registrations, we constructed an overdetermined system of transform equations that was solved robustly by minimizing the -norm of the residuals. This method was evaluated on a set of 100 liver DCE-MRI examinations from 35 patients by examining the area under spikes appearing in the voxel time-intensity curves. The robust alignment procedure significantly reduced the area under intensity spikes compared with unregistered volumes (<.001) and volumes registered to a single reference phase (<.001). Our registration procedure provides a larger number of reliable time-intensity curve samples. The additional reliable samples in the precontrast baseline are important for calculating the postcontrast signal enhancement and thereby for converting intensity to contrast concentration. On the intensity ramp, retained samples help to better describe the uptake dynamics, providing a better foundation for parameter estimation. The presented method also simplifies the analysis of data sets with many patients by eliminating the need for manual intervention during registration.
如果未通过图像配准对肝脏动态对比增强(DCE)磁共振成像(MRI)的动态图像进行呼吸运动校正,那么将其拟合到药代动力学模型所得到的定量肝脏灌注参数容易出现误差。对比剂引起的对比前和对比后阶段的强度变化对图像配准的准确性构成了挑战。我们提出了一个超定的变换方程组,用于DCE-MRI序列中图像体积之间的配准,以实现稳健的对齐。在该方法中,我们将每个体积与其他每个体积进行配准。从所有成对配准产生的变换中,我们构建了一个超定的变换方程组,并通过最小化残差的 -范数来稳健地求解。通过检查体素时间-强度曲线中出现的尖峰下面积,在35例患者的100次肝脏DCE-MRI检查数据集上对该方法进行了评估。与未配准的体积(<.001)和配准到单个参考相位的体积(<.001)相比,稳健的对齐程序显著减少了强度尖峰下的面积。我们的配准程序提供了更多可靠的时间-强度曲线样本。对比前基线中的额外可靠样本对于计算对比后信号增强从而将强度转换为对比剂浓度非常重要。在强度斜坡上,保留的样本有助于更好地描述摄取动态,为参数估计提供更好的基础。所提出的方法还通过消除配准过程中对人工干预的需求,简化了对许多患者数据集的分析。