ArticleJournal of applied clinical medical physics2021
Does the beta regularization parameter of bayesian penalized likelihood reconstruction always affect the quantification accuracy and image quality of positron emission tomography computed tomography?
Article in Journal of applied clinical medical physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Impact of local tumor-to-background uptake ratio on PET metabolic response assessment.Radiation protection dosimetry · 2026Article
- Comparative study of the quantitative accuracy of oncological PET imaging based on deep learning methods.Quantitative imaging in medicine and surgery · 2023Article
- Rapid Whole-Body FDG PET/MRI in Oncology Patients: Utility of Combining Bayesian Penalised Likelihood PET Reconstruction and Abbreviated MRI.Diagnostics (Basel, Switzerland) · 2023Article
- Impact of γ factor in the penalty function of Bayesian penalized likelihood reconstruction (Q.Clear) to achieve high-resolution PET images.EJNMMI physics · 2023Article
- The effect of Q.Clear reconstruction on quantification and spatial resolution of 18F-FDG PET in simultaneous PET/MR.EJNMMI physics · 2022Article
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Abstract
purposeThis 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.
methodsA 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-to-noise 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.
resultsWith 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).
conclusionOur 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.
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