Objective: A new Bayesian penalized likelihood reconstruction algorithm for positron emission tomography (PET) (Q.Clear) is now in clinical use for fludeoxyglucose (FDG) PET/CT. However, experience with non-FDG tracers and in special patient populations is limited. This pilot study aims to compare Q.Clear to standard PET reconstructions for 18 F sodium fluoride ( 18 F-NaF) PET in obese patients.
Methods: 30 whole body 18 F-NaF PET/CT scans (10 patients with BMI 30-40 Kg/m 2 and 20 patients with BMI >40 Kg/m 2 ) and a NEMA image quality phantom scans were analyzed using ordered subset expectation maximization (OSEM) and Q.Clear reconstructions methods with B400, 600, 800 and 1000. The images were assessed for overall image quality (IQ), noise level, background soft tissue, and lesion detectability, contrast recovery (CR), background variability (BV) and contrast-to-noise ratio (CNR) for both algorithms.
Results: CNR for clinical cases was higher for Q.Clear than OSEM ( p < 0.05). Mean CNR for OSEM was (21.62 ± 8.9), and for Q.Clear B400 (31.82 ± 14.6), B600 (35.54 ± 14.9), B800 (39.81 ± 16.1), and B1000 (40.9 ± 17.8). As the β value increased the CNR increased in all clinical cases. B600 was the preferred β value for reconstruction in obese patients. The phantom study showed Q.Clear reconstructions gave lower CR and lower BV than OSEM. The CNR for all spheres was significantly higher for Q.Clear (independent of β) than OSEM ( p < 0.05), suggesting superiority of Q.Clear.
Conclusion: This pilot clinical study shows that Q.Clear reconstruction algorithm improves overall IQ of 18 F-NaF PET in obese patients. Our clinical and phantom measurement results demonstrate improved CNR and reduced BV when using Q.Clear. A β value of 600 is preferred for reconstructing 18 F-NaF PET/CT with Q.Clear in obese patients.
Advances in Knowledge: 18 F-NaF PET/CT is less susceptible to artifacts induced by body habitus. Bayesian penalized likelihood reconstruction with 18 F-NaF PET improves overall IQ in obese patients.