A novel fast helical 4D-CT acquisition technique to generate low-noise sorting artifact-free images at user-selected breathing phases.
A novel fast helical 4D-CT acquisition technique to generate low-noise sorting artifact-free images at user-selected breathing phases.
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DOI：
10.1016/j.ijrobp.2014.01.016
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发表时间：
2014-05-01
影响因子：
7
通讯作者：
Low, Daniel
中科院分区：
文献类型：
--
作者：
Thomas, David;Lamb, James;White, Benjamin;Jani, Shyam;Gaudio, Sergio;Lee, Percy;Ruan, Dan;McNitt-Gray, Michael;Low, Daniel
旨在开发一种新型四维计算机断层扫描（4D-CT）技术，该技术利用标准快速螺旋采集、同步呼吸替代测量、可变形图像配准和呼吸运动模型来消除分选伪影。10名患者在自由呼吸条件下，采用低剂量快速螺旋协议，在交替方向上连续25次使用64层CT扫描仪进行成像。使用腹部风箱作为呼吸替代物。使用可变形配准将第一幅图像（定义为参考图像）配准到随后的24幅分割图像。使用呼吸运动模型确定体素特异性运动模型参数。将25幅图像中的运动模型预测的组织位置与可变形配准的组织位置进行比较，以评估模型预测误差。通过对变形为第一图像几何形状的25个图像进行平均来创建低噪声图像，将统计图像噪声降低5倍。运动模型用于将低噪声参考图像变形为任何用户选择的呼吸相位。应用体素特异性校正来校正作为肺空气填充的函数的肺实质密度的Hounsfield单位。在用户选择的呼吸阶段使用该模型产生的图像没有受到传统4D-CT协议常见的分类伪影的影响。所有患者的呼吸运动模型预测和测量的肺组织位置之间的平均预测误差被确定为1.19 ± 0.37 mm。所提出的技术可以用作临床4D-CT技术。它在存在不规则呼吸的情况下是稳健的，并且允许整个成像剂量有助于产生图像质量，从而在类似于或小于当前4D-CT技术的患者剂量下提供无伪影图像。
To develop a novel 4-dimensional computed tomography (4D-CT) technique that exploits standard fast helical acquisition, a simultaneous breathing surrogate measurement, deformable image registration, and a breathing motion model to remove sorting artifacts. Ten patients were imaged under free-breathing conditions 25 successive times in alternating directions with a 64-slice CT scanner using a low-dose fast helical protocol. An abdominal bellows was used as a breathing surrogate. Deformable registration was used to register the first image (defined as the reference image) to the subsequent 24 segmented images. Voxel-specific motion model parameters were determined using a breathing motion model. The tissue locations predicted by the motion model in the 25 images were compared against the deformably registered tissue locations, allowing a model prediction error to be evaluated. A low-noise image was created by averaging the 25 images deformed to the first image geometry, reducing statistical image noise by a factor of 5. The motion model was used to deform the low-noise reference image to any user-selected breathing phase. A voxel-specific correction was applied to correct the Hounsfield units for lung parenchyma density as a function of lung air filling. Images produced using the model at user-selected breathing phases did not suffer from sorting artifacts common to conventional 4D-CT protocols. The mean prediction error across all patients between the breathing motion model predictions and the measured lung tissue positions was determined to be 1.19 ± 0.37 mm. The proposed technique can be used as a clinical 4D-CT technique. It is robust in the presence of irregular breathing and allows the entire imaging dose to contribute to the resulting image quality, providing sorting artifact–free images at a patient dose similar to or less than current 4D-CT techniques.
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影响因子：
3.5
作者：
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