Does the beta regularization parameter of bayesian penalized likelihood reconstruction always affect the quantification accuracy and image quality of positron emission tomography computed tomography?

Abstract

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.

The effect of Q.Clear reconstruction on quantification and spatial resolution of 18F-FDG PET in simultaneous PET/MR

“…Our findings were similar to previous studies on PET/MR using 68 Ga-prostate-specific membrane antigen (400–550) [ 1 ]. Previous studies on PET/CT suggested similar optimal β value of 350–400 ( 18 F-FDG) [ 12 , 15 , 16 ], 300–550 ( 18 F-fluciclovine) [ 17 ] and 300 ( 18 F-NaF) [ 14 ], 350 ( 68 Ga-labeled radiopharmaceuticals) [ 11 ], 400–550 ( 18 F-fluorocholine) [ 18 ]. While a few other studies of PET/CT suggested a higher β value of 500–750 [ 19 – 24 ], a study on the detection of sub-centimeter lesions suggested a β value of 200 [ 25 ].…”

Impact of γ factor in the penalty function of Bayesian penalized likelihood reconstruction (Q.Clear) to achieve high-resolution PET images

“…The recent replacement of photomultiplier tubes (PMT) with SiPM has led to PET detectors with smaller crystals, better timing resolution and higher photon-detection efficiency [ 28 ]. A SiPM-PET/CT system combined with BPL reconstruction can detect of lesions < 1 cm [ 15 , 29 , 30 ]. Thus, the optimal γ factor of BPL in a SiPM-PET/CT scanner should be determined to detect sub-centimeter lesions as described herein.…”

Rapid Whole-Body FDG PET/MRI in Oncology Patients: Utility of Combining Bayesian Penalised Likelihood PET Reconstruction and Abbreviated MRI

“…The β value is the only variable parameter in the BPL method; it determines the degree of noise regularization in the iterative loop of image reconstruction but it also affects image contrast and quantitative values. Therefore, appropriate β values must be chosen when using BPL as an alternative to conventional methods [22,23]. In another study, an optimal β value of 600 was suggested for detectability and reproducibility in 68 Ga-PSMA PET/CT scans, although the study was not intended to shorten scanning duration [24].…”