부산대학교 도서관

In positron emission tomography (PET) imaging, accurate clinical assessment is often affected by the partial volume effect (PVE) leading to overestimation (spill-in) or underestimation (spill-out) of activity in various small regions. The spill-in correction, in particular, can be very challenging when the target region is close to a hot background region. Therefore, this article evaluates and compares the performance of various recently developed spill-in correction techniques, namely, background correction (BC), local projection (LP), and hybrid kernelized [hybrid kernel expectation maximization (HKEM)] methods. We used a simulated digital phantom and [ 18 F]-NaF PET data of three patients with abdominal aortic aneurysms (AAAs) acquired with Siemens Biograph mMR and mCT scanners, respectively. Region of interest (ROI) analysis was performed and the extracted SUV mean , SUV max , and target-to-background ratio (TBR) scores were compared. Results showed substantial spill-in effects from hot regions to targeted regions, which are more prominent in small structures. The phantom experiment demonstrated the feasibility of spill-in correction with all methods. For the patient data, large differences in SUV mean SUV max and TBR max scores were observed between the ROIs drawn over the entire aneurysm and ROIs excluding some regions close to the bone. Overall, BC yielded the best performance in spill-in correction in both phantom and patient studies.