Semiautomatic method to identify the best phase for gated RT in lung region by 4D-PET/CT acquisitions.

PURPOSE

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

Estimation of lesion motion by the proposed semiautomatic algorithm can be used to evaluate tumor motion due to breathing.