Abstract
From 1982, cancer has been the main cause of people death in Taiwan, and lung cancer has been the leading cause of cancer death in recent years. PET provides the glucose metabolic function of tumor cells, helps to cancer diagnosis and staging. By using the semi-quantitative parameter “standard uptake value” in PET images as the index of tumor malignancy could reduce the necessity of invasive exam. Unfortunately, forming a PET image needs to take several minutes to accumulate enough signals. During the acquisition time, tumor motion could be caused by breathing; therefore, the image may become blurred with tumor trajectory. This respiratory effect could enlarge the tumor volume, change the tumor shape and the tumor activity distribution, and finally underestimate the SUV value. The aim of this study is to reduce the respiratory effect on PET images. This study uses the dynamic scan to acquire PET images, and the respiratory detector to acquire the respiratory amplitudes. In the study of point source, there are tree methods to divide the sinograms into subgroups: the respiratory amplitudes, the point source trajectory in sinograms, and the correlations between sinograms. In clinical trial, only uses the respiratory amplitudes to divide sinograms. The results show that, in point source trial, the tumor volume reduction factor (VRF) is up to 57.87%, and the maximum activity concentration recovery factor (MACRF) is up to 110.3%. For the clinical trials, the VRF is up to 18.66%, and the MACRF is up to 6.6%. This study uses tree different methods to reduce the respiratory artifacts on PET images. Images with respiratory correction will improve the accuracy on image quantitative analysis and accurately diagnose the disease. Furthermore, it provides an accurate target volume for radiotherapy and helps to modulate the tumor dose.