Background and purpose: To compare 68 Ga-fibroblast activation protein inhibitor (FAPI) and 18 F-FDG PET/ CT in imaging locally advanced oesophageal cancer, and evaluate the potential usefulness of 68 Ga-FAPI PET/CT on gross target volume (GTV) delineation aimed at radiotherapy planning for oesophageal cancer as compared with contrast-enhanced CT (CE-CT) and 18 F-FDG PET/CT. Materials and methods: Twenty-one patients with newly diagnosed oesophageal cancer who underwent both 18 F-FDG and 68 Ga-FAPI PET/CT scans were selected. GTVs of the primary tumours based on CE-CT (GTV CT ), PET/CT, and CE-CT plus PET/CT were delineated. Gross tumour lengths were measured by GTVs and endoscopy and recorded. Results: The 68 Ga-FAPI PET showed significantly higher radiotracer uptake than 18 F-FDG PET (median SUVmax 16.71 vs. 11.23; P = 0.002) in the primary tumours. SUV thresholds of FAPI Â20%, 30%, 40%, and FDG Â40% showed similar lesion lengths compared with that in endoscopic examination (P > 0.05). GTV CT demonstrated the largest volume (median: 48.80 mm 3 , range: 14.83-162.23 mm 3 ) than PET-based GTVs. For PET/CT-guided complementary contouring of GTV CT , four patients (19%) were increased by FAPI Â20% and 30%, two patients (9.5%) were increased by FAPI Â40%, and only one patient was increased by FDG Â40%. Furthermore, the volume of GTV based on CE-CT plus FAPI Â20%, 30%, and 40% showed no significant difference with GTV CT and planning target volume based CE-CT plus FAPI-PET and meets the organ at risk standard.
Conclusion:The 68 Ga-FAPI PET/CT methodology showed favourable tumour-to-background contrast in oesophageal cancer and might provide additional information for target volume delineation and help avoid tumour geographic misses.
Despite the modernization and automation in marine technology and the implementation of safety-related regulations, marine accidents are still a main concern for global maritime transportation. It is well known that human error is the key contributor, but human error data is hard to be collected and classified and the factors which influence human behavior should be identified. For this reason, the goal of this paper constructed a case-based HFACS (Human Factor Analysis and Classification System) method for marine human factor data collection and classification, and the data collected produced statics for analysis and safety management.
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