Poster — Thur Eve — 05: Objective phantom-based and porcine model comparison of filtered back projection, adaptive statistical iterative reconstruction and model based iterative reconstruction algorithms

We performed objective image quality evaluation of three commercial reconstruction algorithms available on a GE DiscoveryCT750HD multi‐detector CT (MDCT) scanner at different dose levels. Using a Catphan500 phantom and a freshly euthanized pig carcass (∼ 36kg), we evaluated the noise and contrast‐to‐noise ratio (CNR) for the three reconstruction algorithms: filtered back‐projection (FBP), adaptive statistical iterative reconstruction (ASIR™) and model based iterative reconstruction (code named VEO™). At a dose of ∼ 1.5 mGy, ASIR™ offers noise reduction up to 54% with the phantom, while VEO™ reduces noise by up to 70% with the porcine model. At low doses, VEO™ offers better noise reduction capabilities over FBP and ASIR™, depending on helical pitch. The level of noise reduction increases as pitch increases. Similar trend was observed with CNR increases as VEO™ offered significantly better CNR over FBP and ASIR™. Compared to FBP, iterative algorithms reduce image noise and increase CNR. The model‐based iterative algorithm (VEO™) produced better noise and contrast resolution in both phantom and porcine images compared to FBP and ASIR™.