Department of Radiotherapy, IRCCS Istituto Clinico Humanitas, Rozzano, 20089 Milano, Italy.
Med Phys. 2011 Jan;38(1):354-62. doi: 10.1118/1.3528225.
Delineating tumor motion by four-dimensional positron emission tomography/computed tomography (4D-PET/CT) is a crucial step for gated radiotherapy (RT). This article quantitatively evaluates semiautomatic algorithms for tumor shift estimation in the lung region due to patient respiration by 4D-PET/CT, in order to support the selection of the best phases for gated RT, by considering the most stable phases of the breathing cycle.
Three mobile spheres and ten selected lesions were included in this study. 4D-PET/CT data were reconstructed and classified into six/ten phases. The semiautomatic algorithms required the generation of single sets of images representative of the full target motion, used as masks for segmenting the phases. For 4D-CT, a pre-established HU range was used, whereas three thresholds (100%, 80%, and 40%) were evaluated for 4D-PET. By using these segmentations, the authors estimated the lesion motion from the shifting centroids, and the phases with the least motion were also deduced including the phases with a curve slope less than 2 mm/ delta phase. The proposed algorithms were validated by comparing the results to those generated entirely by manual contouring.
In the phantom study, the mean difference between the manual contour and the semiautomatic technique was 0.1 +/- 0.1 mm for 4D-CT and 0.2 +/- 0.1 mm for the 4D-PET based on 40% threshold. In the patients' series, the mean difference was 0.9 +/- 0.6 mm for 4D-CT and 0.8 +/- 0.2 mm for the 4D-PET based on 40% threshold.
Estimation of lesion motion by the proposed semiautomatic algorithm can be used to evaluate tumor motion due to breathing.
通过四维正电子发射断层扫描/计算机断层扫描（4D-PET/CT）描绘肿瘤运动是门控放疗（RT）的关键步骤。本文通过 4D-PET/CT 定量评估了用于肺部肿瘤移位估计的半自动算法，以支持选择用于门控 RT 的最佳相位，同时考虑呼吸周期中最稳定的相位。
本研究纳入了三个移动球体和十个选定的病变。对 4D-PET/CT 数据进行了重建和分类为六个/十个相位。半自动算法需要生成一组代表整个目标运动的图像，作为分割相位的掩模。对于 4D-CT，使用了预先设定的 HU 范围，而对于 4D-PET，评估了三个阈值（100%、80%和 40%）。通过使用这些分割，作者从移位的质心估计了病变的运动，并推导出了运动最小的相位，包括曲线斜率小于 2 毫米/相的相位。通过将结果与完全手动轮廓生成的结果进行比较，验证了所提出的算法。
在体模研究中，手动轮廓和半自动技术之间的平均差异为 0.1±0.1mm 对于 4D-CT 和 0.2±0.1mm 对于基于 40%阈值的 4D-PET。在患者系列中，4D-CT 的平均差异为 0.9±0.6mm，基于 40%阈值的 4D-PET 为 0.8±0.2mm。
通过所提出的半自动算法估计病变运动可用于评估呼吸引起的肿瘤运动。
