importance of defect detectability in positron emission tomography imaging of abdominal lesions

Objective(s): this study was designed to assess defect detectability in positron emission tomography (pet) imaging of abdominal lesions. methods: a national electrical manufactures association international electrotechnical commission phantom was used. the simulated abdominal lesion was scanned for 10 min using dynamic list-mode acquisition method. images, acquired with scan duration of 1-10 min, were reconstructed using vue point hd and a 4.7 mm full-width at half-maximum (fwhm) gaussian filter. iteration-subset combinations of 2-16 and 2-32 were used. visual and physical analyses were performed using the acquired images. to sequentially evaluate defect detectability in clinical settings, we examined two middleaged male subjects. one had a liver cyst (approximately 10 mm in diameter) and the other suffered from pancreatic cancer with an inner defect region (approximately 9 mm in diameter). results: in the phantom study, at least 6 and 3 min acquisition durations were required to visualize 10 and 13 mm defect spheres, respectively. on the other hand, spheres with diameters ≥17 mm could be detected even if the acquisition duration was only 1 min. the visual scores were significantly correlated with background (bg) variability. in clinical settings, the liver cyst could be slightly visualized with an acquisition duration of 6 min, although image quality was suboptimal. for pancreatic cancer, the acquisition duration of 3 min was insufficient to clearly describe the defect region. conclusion: the improvement of bg variability is the most important factor for enhancing lesion detection. our clinical scan duration (3 min/bed) may not be suitable for the detection of small lesions or accurate tumor delineation since an acquisition duration of at least 6 min is required to visualize 10 mm lesions, regardless of reconstruction parameters. improvements in defect detectability are important for radiation treatment planning and accurate pet-based diagnosis.