To evaluate the quantification accuracy of different positron emission tomography-computed tomography (PET/CT) reconstruction algorithms, we measured the recovery coefficient (RC) and contrast recovery (CR) in phantom studies. The results played a guiding role in the partial-volume-effect correction (PVC) for following clinical evaluations. The PET images were reconstructed with four different methods: ordered subsets expectation maximization (OSEM), OSEM with time-of-flight (TOF), OSEM with TOF and point spread function (PSF), and Bayesian penalized likelihood (BPL, known as Q.Clear in the PET/CT of GE Healthcare). In clinical studies, SUVmax and SUVmean (the maximum and mean of the standardized uptake values, SUVs) of 75 small pulmonary nodules (sub-centimeter group: < 10 mm and medium-size group: 10–25 mm) were measured from 26 patients. Results show that Q.Clear produced higher RC and CR values, which can improve quantification accuracy compared with other methods (P < 0.05), except for the RC of 37 mm sphere (P > 0.05). The SUVs of sub-centimeter fludeoxyglucose (FDG)-avid pulmonary nodules with Q.Clear illustrated highly significant differences from those reconstructed with other algorithms (P < 0.001). After performing the PVC, highly significant differences (P < 0.001) still existed in the SUVmean measured by Q.Clear comparing with those measured by the other algorithms. Our results suggest that the Q.Clear reconstruction algorithm improved the quantification accuracy towards the true uptake, which potentially promotes the diagnostic confidence and treatment response evaluations with PET/CT imaging, especially for the sub-centimeter pulmonary nodules. For small lesions, PVC is essential.

This study aims to provide a detailed investigation on the noise penalization factor in Bayesian penalized likelihood (BPL)-based algorithm, with the utilization of partial volume effect correction (PVC), so as to offer the suitable beta value and optimum standardized uptake value (SUV) parameters in clinical practice for small pulmonary nodules. Methods: A National Electrical Manufacturers Association (NEMA) image-quality phantom was scanned and images were reconstructed using BPL with beta values ranged from 100 to 1000. The recovery coefficient (RC), contrast recovery (CR), and background variability (BV) were measured to assess the quantification accuracy and image quality. In the clinical assessment, lesions were categorized into sub-centimeter (<10 mm, n = 7) group and medium size (10-30 mm, n = 16) group. Signal-tonoise ratio (SNR) and contrast-to-noise ratio (CNR) were measured to evaluate the image quality and lesion detectability. With PVC was performed, the impact of beta values on SUVs (SUVmax, SUVmean, SUVpeak) of small pulmonary nodules was evaluated. Subjective image analysis was performed by two experienced readers. Results: With the increasing of beta values, RC, CR, and BV decreased gradually in the phantom work. In the clinical study, SNR and CNR of both groups increased with the beta values (P < 0.001), although the sub-centimeter group showed increases after the beta value reached over 700. In addition, highly significant negative correlations were observed between SUVs and beta values for both lesion-size groups before the PVC (P < 0.001 for all). After the PVC, SUVpeak measured from the sub-centimeter group was no significantly different among different beta values (P = 0.830). Conclusion: Our study suggests using SUVpeak as the quantification parameter with PVC performed to mitigate the effects of beta regularization. Beta values between 300 and 400 were preferred for pulmonary nodules smaller than 30 mm.

Background To evaluate the quantification accuracy, we measured the recovery coefficient (RC) and contrast recovery (CR) in a phantom study and used it as a guide in clinical evaluation about digital positron emission tomography -computed tomography (PET/CT). Methods The RC and CR of the PET images reconstructed with 4 different methods [ordered subsets expectation maximazation (OSEM), time of flight(TOF), TOF-point spread function (PSF), bayesian penalized likelihood (BPL)] were measured in the phantom study. And, SUVmax and SUVmean (the maximum and mean of the standardized uptake values, SUVs) of 75 small pulmonary nodules (sub-centimeter group: <10 mm and medium size group: 10 - 25 mm) from 26 patients were measured with those methods. For lesions smaller than 3 times of the spatial resolution, partial-volume-effect correction (PVC) based on RC values was performed. Results BPL enables higher RC and CR values, which can improve quantification accuracy compared with other methods (P < 0.05), except for the RC of 37 mm sphere (P > 0.05). The SUVs of sub-centimeter fludeoxyglucose (FDG)-avid pulmonary nodules with BPL illustrated highly significant difference from those reconstructed with other algorithms (P<0.001). However, reconstruction algorithms had less impact on SUVs measured in medium group (P>0.05). With the PVC, highly significant difference (P<0.001) still existed in the SUVmean measured on BPL compared with those measured on the other 3 algorithms, although PVC had the least effect on BPL. Conclusions BPL on the digital PET/CT demonstrated improved quantification accuracy. For small pulmonary nodules, PVC is important.

Background To evaluate the quantification accuracy, we measured the recovery coefficient (RC) and contrast recovery (CR) in a phantom study and used it as a guide in clinical evaluation about digital positron emission tomography -computed tomography (PET/CT). Methods The RC and CR of the PET images reconstructed with 4 different methods [ordered subsets expectation maximazation (OSEM), time of flight(TOF), TOF-point spread function (PSF), bayesian penalized likelihood (BPL)] were measured in the phantom study. And, SUVmax and SUVmean (the maximum and mean of the standardized uptake values, SUVs) of 75 small pulmonary nodules (sub-centimeter group: <10 mm and medium size group: 10 - 25 mm) from 26 patients were measured with those methods. For lesions smaller than 3 times of the spatial resolution, partial-volume-effect correction (PVC) based on RC values was performed. Results BPL enables higher RC and CR values, which can improve quantification accuracy compared with other methods (P < 0.05), except for the RC of 37 mm sphere (P > 0.05). The SUVs of sub-centimeter fludeoxyglucose (FDG)-avid pulmonary nodules with BPL illustrated highly significant difference from those reconstructed with other algorithms (P<0.001). However, reconstruction algorithms had less impact on SUVs measured in medium group (P>0.05). With the PVC, highly significant difference (P<0.001) still existed in the SUVmean measured on BPL compared with those measured on the other 3 algorithms, although PVC had the least effect on BPL. Conclusions BPL on the digital PET/CT demonstrated improved quantification accuracy. For small pulmonary nodules, PVC is important.