Izaguirre E W, Price S G, Yang D, Rangaraj D
Washington University School of Medicine, Saint Louis, MO.
Nuclear Science and Engineering Institute, University of MO, Columbia, MO.
Med Phys. 2012 Jun;39(6Part6):3653. doi: 10.1118/1.4734837.
Cone beam CT (CBCT) is a well established technique to localize patients using bone and soft tissue anatomy. Current protocols are limited to one weekly CBCT due to the considerable imaging dose delivered to the patient. The purpose of this project is to develop and validate a low dose CBCT algorithm to reduce dose and imaging time of current 3D imaging localization procedures using a novel iterative tomosynthesis algorithm to allow daily CBCT for patient positioning and target localization.
The algorithm is based on the combination of a tomosynthesis filtered back propagation (TFBP) acquisition geometry algorithm and a maximum likelihood expectation maximization (MLEM) iterative reconstruction. Circular or arc acquisition trajectory, projection number, and angular projection position are optimized according to the anatomical treatment site and region of interest. The TFBP method provides the first 3D image estimate, and the MLEM improves its quality. In this study, we focused on head and neck treatment localization imaging.
We studied the performance of our tomosynthesis algorithm imaging resolution on an anthropomorphic head and neck phantom to determine image quality as a function of dose reduction techniques. Reconstructed anatomy shows that a 1/8 dose reduction provides similar image quality and resolution as current CBCT protocols. Seven iterations show an optimal compromise between image quality and reconstruction time. Tomosynthesis images provide digitally reconstructed radiographs with similar resolution and contrast as full CBCT. We verified that the iterative process eliminates phantom images originated by the acquired sparse angular data projections.
We developed and validated an iterative algorithm for low dose cone beam CT based on circular or arc tomosynthesis geometries and iterative reconstruction techniques. The algorithm combines the strengths of both techniques to provide a novel low dose method to image patient anatomy for patient positioning and target localization.
锥形束CT(CBCT)是一种利用骨骼和软组织解剖结构对患者进行定位的成熟技术。由于给患者带来的可观成像剂量,当前方案仅限于每周进行一次CBCT。本项目的目的是开发并验证一种低剂量CBCT算法,以减少当前3D成像定位程序的剂量和成像时间,该算法采用一种新颖的迭代断层合成算法,允许每日进行CBCT以用于患者定位和靶区定位。
该算法基于断层合成滤波反投影(TFBP)采集几何算法和最大似然期望最大化(MLEM)迭代重建的结合。根据解剖治疗部位和感兴趣区域优化圆形或弧形采集轨迹、投影数量和角度投影位置。TFBP方法提供初始的3D图像估计,MLEM则提高其质量。在本研究中,我们专注于头颈部治疗定位成像。
我们在一个仿人头颈部体模上研究了断层合成算法成像分辨率的性能,以确定图像质量与剂量降低技术的关系。重建的解剖结构显示,剂量降低至1/8时可提供与当前CBCT方案相似的图像质量和分辨率。七次迭代显示在图像质量和重建时间之间达到了最佳平衡。断层合成图像提供的数字重建射线照片具有与全CBCT相似的分辨率和对比度。我们验证了迭代过程消除了由采集的稀疏角度数据投影产生的伪影图像。
我们开发并验证了一种基于圆形或弧形断层合成几何结构和迭代重建技术的低剂量锥形束CT迭代算法。该算法结合了两种技术的优势,为患者定位和靶区定位提供了一种新颖的低剂量成像患者解剖结构的方法。