Martin Rachael, Rubinstein Ashley, Ahmad Moiz, Court Laurence, Pan Tinsu
Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030 and The University of Texas Graduate School of Biomedical Sciences, Houston, Texas 77030.
The University of Texas Graduate School of Biomedical Sciences, Houston, Texas 77030 and Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030.
Med Phys. 2015 Jan;42(1):154-64. doi: 10.1118/1.4903264.
4D CT imaging in mice is important in a variety of areas including studies of lung function and tumor motion. A necessary step in 4D imaging is obtaining a respiratory signal, which can be done through an external system or intrinsically through the projection images. A number of methods have been developed that can successfully determine the respiratory signal from cone-beam projection images of humans, however only a few have been utilized in a preclinical setting and most of these rely on step-and-shoot style imaging. The purpose of this work is to assess and make adaptions of several successful methods developed for humans for an image-guided preclinical radiation therapy system.
Respiratory signals were determined from the projection images of free-breathing mice scanned on the X-RAD system using four methods: the so-called Amsterdam shroud method, a method based on the phase of the Fourier transform, a pixel intensity method, and a center of mass method. The Amsterdam shroud method was modified so the sharp inspiration peaks associated with anesthetized mouse breathing could be detected. Respiratory signals were used to sort projections into phase bins and 4D images were reconstructed. Error and standard deviation in the assignment of phase bins for the four methods compared to a manual method considered to be ground truth were calculated for a range of region of interest (ROI) sizes. Qualitative comparisons were additionally made between the 4D images obtained using each of the methods and the manual method.
4D images were successfully created for all mice with each of the respiratory signal extraction methods. Only minimal qualitative differences were noted between each of the methods and the manual method. The average error (and standard deviation) in phase bin assignment was 0.24 ± 0.08 (0.49 ± 0.11) phase bins for the Fourier transform method, 0.09 ± 0.03 (0.31 ± 0.08) phase bins for the modified Amsterdam shroud method, 0.09 ± 0.02 (0.33 ± 0.07) phase bins for the intensity method, and 0.37 ± 0.10 (0.57 ± 0.08) phase bins for the center of mass method. Little dependence on ROI size was noted for the modified Amsterdam shroud and intensity methods while the Fourier transform and center of mass methods showed a noticeable dependence on the ROI size.
The modified Amsterdam shroud, Fourier transform, and intensity respiratory signal methods are sufficiently accurate to be used for 4D imaging on the X-RAD system and show improvement over the existing center of mass method. The intensity and modified Amsterdam shroud methods are recommended due to their high accuracy and low dependence on ROI size.
小鼠的4D CT成像在包括肺功能研究和肿瘤运动研究在内的多个领域都很重要。4D成像的一个必要步骤是获取呼吸信号，这可以通过外部系统或从投影图像中固有地获取。已经开发出多种方法，可以成功地从人体锥形束投影图像中确定呼吸信号，然而，只有少数方法在临床前环境中得到应用，并且其中大多数依赖于步进式成像。这项工作的目的是评估并改编几种为人体开发的成功方法，以用于图像引导的临床前放射治疗系统。
使用四种方法从在X-RAD系统上扫描的自由呼吸小鼠的投影图像中确定呼吸信号：所谓的阿姆斯特丹覆盖法、基于傅里叶变换相位的方法、像素强度法和质心法。对阿姆斯特丹覆盖法进行了改进，以便能够检测与麻醉小鼠呼吸相关的尖锐吸气峰值。呼吸信号用于将投影分类到相位区间，并重建4D图像。针对一系列感兴趣区域（ROI）大小，计算了与被视为基准事实的手动方法相比，这四种方法在相位区间分配中的误差和标准差。此外，还对使用每种方法获得的4D图像与手动方法进行了定性比较。
使用每种呼吸信号提取方法都成功为所有小鼠创建了4D图像。在每种方法与手动方法之间仅注意到最小的定性差异。傅里叶变换法在相位区间分配中的平均误差（和标准差）为0.24±0.08（0.49±0.11）个相位区间，改进后的阿姆斯特丹覆盖法为0.09±0.03（0.31±0.08）个相位区间，强度法为0.09±0.02（0.33±0.07）个相位区间，质心法为0.37±0.10（0.57±0.08）个相位区间。改进后的阿姆斯特丹覆盖法和强度法对ROI大小的依赖性较小，而傅里叶变换法和质心法对ROI大小表现出明显的依赖性。
改进后的阿姆斯特丹覆盖法、傅里叶变换法和强度呼吸信号方法足够准确，可用于X-RAD系统上的4D成像，并且比现有的质心法有所改进。由于其高精度和对ROI大小的低依赖性，推荐使用强度法和改进后的阿姆斯特丹覆盖法。
