Schreibmann Eduard, Crocker Ian, Schuster David M, Curran Walter J, Fox Tim
Department of Radiation Oncology, Emory University School of Medicine and Winship Cancer Institute of Emory University, Atlanta, GA, USA.
Technol Cancer Res Treat. 2014 Dec;13(6):571-82. doi: 10.7785/tcrtexpress.2013.600255. Epub 2013 Aug 31.
Observing early metabolic changes in positron emission tomography (PET) is an essential tool to assess treatment efficiency in radiotherapy. However, for thoracic regions, the use of three-dimensional (3D) PET imaging is unfeasible because the radiotracer activity is smeared by the respiratory motion and averaged during the imaging acquisition process. This motion-induced degradation is similar in magnitude with the treatment-induced changes, and the two occurrences become indiscernible. We present a customized temporal-spatial deformable registration method for quantifying respiratory motion in a four-dimensional (4D) PET dataset. Once the motion is quantified, a motion-corrected (MC) dataset is created by tracking voxels to eliminate breathing-induced changes in the 4D imaging scan. The 4D voxel-tracking data is then summed to yield a 3D MC-PET scan containing only treatment-induced changes. This proof of concept is exemplified on both phantom and clinical data, where the proposed algorithm tracked the trajectories of individual points through the 4D datasets reducing motion to less than 4 mm in all phases. This correction approach using deformable registration can discern motion blurring from treatment-induced changes in treatment response assessment using PET imaging.
观察正电子发射断层扫描（PET）中的早期代谢变化是评估放射治疗疗效的重要工具。然而，对于胸部区域，使用三维（3D）PET成像并不可行，因为放射性示踪剂活性会因呼吸运动而模糊，并在成像采集过程中被平均化。这种运动引起的退化在程度上与治疗引起的变化相似，二者变得难以区分。我们提出了一种定制的时空可变形配准方法，用于量化四维（4D）PET数据集中的呼吸运动。一旦运动被量化，通过跟踪体素创建一个运动校正（MC）数据集，以消除4D成像扫描中呼吸引起的变化。然后将4D体素跟踪数据求和，得到一个仅包含治疗引起变化的3D MC-PET扫描。这一概念验证在体模和临床数据上均得到了例证，其中所提出的算法通过4D数据集跟踪各个点的轨迹，并在所有阶段将运动减少到小于4毫米。这种使用可变形配准的校正方法能够在使用PET成像进行治疗反应评估时，区分运动模糊和治疗引起的变化。
