Clinical validation of fully 3-d versus 2.5-d ramla reconstruction on the philips-adac cpet pet scanner

Introduction: Fully three-dimensional (3-D) reconstruction algorithms have the potential to better utilize PET data acquired in true 3-D acquisition modes, as compared to 2-D approaches involving data reduction through rebinning procedures followed by a 2-D or 2.5-D reconstruction. Our previous studies, involving simulated and real phantom data from PET scanners working purely in 3-D acquisition mode, showed that the fully 3-D reconstruction approaches bring appreciable improvement on physical measures and visual image quality as well. Reconstruction procedures utilized in those studies were based upon the row action maximum likelihood algorithm (RAMLA) implemented on our clinical scanners. The purpose of this study was to investigate if the fully 3-D RAMLA reconstruction software brings an appreciable improvement in clinical image quality and reader confidence. Materials and methods: Ninety patient scans acquired on the Philips CPET scanner at our institution were reconstructed using 2.5-D RAMLA and 3-D RAMLA with differing reconstruction parameters. These scans were blindly presented to four experienced PET scan readers who graded various aspects of image quality. Results: Our study concluded that 3-D RAMLA on the CPET scanner reduces artifacts and image noise and improves clinical confidence in interpreting PET images. Conclusion: This study led to the routine use of 3-D RAMLA reconstruction on the CPET scanner at our institution.