Kim J-H, Nuyts J, Kyme A, Kuncic Z, Fulton R
Discipline of Medical Imaging and Sciences, University of Sydney, NSW 2006, Australia.
Phys Med Biol. 2015 Mar 7;60(5):2047-73. doi: 10.1088/0031-9155/60/5/2047. Epub 2015 Feb 12.
We propose a method to compensate for six degree-of-freedom rigid motion in helical CT of the head. The method is demonstrated in simulations and in helical scans performed on a 16-slice CT scanner. Scans of a Hoffman brain phantom were acquired while an optical motion tracking system recorded the motion of the bed and the phantom. Motion correction was performed by restoring projection consistency using data from the motion tracking system, and reconstructing with an iterative fully 3D algorithm. Motion correction accuracy was evaluated by comparing reconstructed images with a stationary reference scan. We also investigated the effects on accuracy of tracker sampling rate, measurement jitter, interpolation of tracker measurements, and the synchronization of motion data and CT projections. After optimization of these aspects, motion corrected images corresponded remarkably closely to images of the stationary phantom with correlation and similarity coefficients both above 0.9. We performed a simulation study using volunteer head motion and found similarly that our method is capable of compensating effectively for realistic human head movements. To the best of our knowledge, this is the first practical demonstration of generalized rigid motion correction in helical CT. Its clinical value, which we have yet to explore, may be significant. For example it could reduce the necessity for repeat scans and resource-intensive anesthetic and sedation procedures in patient groups prone to motion, such as young children. It is not only applicable to dedicated CT imaging, but also to hybrid PET/CT and SPECT/CT, where it could also ensure an accurate CT image for lesion localization and attenuation correction of the functional image data.
我们提出了一种在头部螺旋CT中补偿六自由度刚体运动的方法。该方法在模拟以及在16层CT扫描仪上进行的螺旋扫描中得到了验证。在获取霍夫曼脑模型扫描数据的同时,一个光学运动跟踪系统记录了检查床和模型的运动。通过使用运动跟踪系统的数据恢复投影一致性,并采用迭代全三维算法进行重建,从而实现运动校正。通过将重建图像与静止参考扫描图像进行比较来评估运动校正的准确性。我们还研究了跟踪器采样率、测量抖动、跟踪器测量值的插值以及运动数据与CT投影同步对准确性的影响。在对这些方面进行优化之后,运动校正后的图像与静止模型的图像非常接近,相关系数和相似系数均高于0.9。我们使用志愿者头部运动进行了模拟研究,同样发现我们的方法能够有效补偿实际的人体头部运动。据我们所知,这是螺旋CT中广义刚体运动校正的首次实际验证。其临床价值我们尚未探索,但可能意义重大。例如,它可以减少在易发生运动的患者群体(如幼儿)中重复扫描以及资源密集型麻醉和镇静程序的必要性。它不仅适用于专用CT成像,也适用于PET/CT和SPECT/CT混合成像,在这些成像中,它还可以确保获得准确的CT图像用于病变定位和功能图像数据的衰减校正。