ArticleAnnals of nuclear medicine2020
Ordered subset expectation maximisation vs Bayesian penalised likelihood reconstruction algorithm in 18F-PSMA-1007 PET/CT.
Article in Annals of nuclear medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed.
- Innovations in clinical PET image reconstruction: advances in Bayesian penalized likelihood algorithm and deep learning.Annals of nuclear medicine · 2025Review
- PSMA PET/CT for prostate cancer diagnosis: current applications and future directions.Journal of cancer research and clinical oncology · 2025Review
- Comparative evaluation of Ordered Subset Expectation Maximization and Bayesian Penalized Likelihood algorithms for PET/CT image reconstruction in various malignancies usingFrontiers in oncology · 2025Article
- β1600 Q.Clear Digital Reconstruction of [Journal of clinical medicine · 2024Article
- Comparison of quantitative whole body PET parameters on [Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- Can Q.Clear reconstruction be used to improve [68 Ga]Ga-DOTANOC PET/CT image quality in overweight NEN patients?European journal of nuclear medicine and molecular imaging · 2022Article
- Assessing the impact of different penalty factors of the Bayesian reconstruction algorithm Q.Clear on in vivo low count kinetic analysis of [EJNMMI research · 2022Article
- Quantitative evaluation of PSMA PET imaging using a realistic anthropomorphic phantom and shell-less radioactive epoxy lesions.EJNMMI physics · 2022Article
- The Impact of Total Variation Regularized Expectation Maximization Reconstruction onFrontiers in medicine · 2022Article
- New PET technologies - embracing progress and pushing the limits.European journal of nuclear medicine and molecular imaging · 2021Article
- Evaluation of Quantitative Ga-68 PSMA PET/CT Repeatability of Recurrent Prostate Cancer Lesions Using Both OSEM and Bayesian Penalized Likelihood Reconstruction Algorithms.Diagnostics (Basel, Switzerland) · 2021Article
- Performance evaluation of the Q.Clear reconstruction framework versus conventional reconstruction algorithms for quantitative brain PET-MR studies.EJNMMI physics · 2021Article
- Impact of total variation regularized expectation maximization reconstruction on the image quality ofThe British journal of radiology · 2021Article
- Optimization of [EJNMMI physics · 2020Article
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5 authors.
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Abstract
backgroundThe aim of the study was to compare widely used ordered subset expectation maximisation (OSEM) algorithm with a new Bayesian penalised likelihood (BPL) Q.Clear algorithm in 18F-PSMA-1007 PET/CT.
methodsWe retrospectively assessed 25 18F-PSMA-1007 PET/CT scans with both OSEM and Q.Clear reconstructions available. Each scan was independently reported by two physicians both in OSEM and Q.Clear. SUVmax, SUVmean and tumour-to-background ratio (TBR) of each lesion were measured. Reports were also compared for their final conclusions and the number and localisation of lesions.
resultsIn both reconstructions the same 87 lesions were reported. Mean SUVmax, SUVmean and TBR were higher for Q.Clear than OSEM (7.01 vs 6.53 [p = 0.052], 4.16 vs 3.84 [p = 0.036] and 20.2 vs 16.8 [p < 0.00001], respectively). Small lesions (< 10 mm) had statistically significant higher SUVmax, SUVmean and TBR in Q.Clear than OSEM (5.37 vs 4.79 [p = 0.032], 3.08 vs 2.70 [p = 0.04] and 15.5 vs 12.5 [p = 0.00214], respectively). For lesions ≥ 10 mm, no significant differences were observed. Findings with higher tracer avidity (SUVmax ≥ 5) tended to have higher SUVmax, SUVmean and TBR values in Q.Clear (11.6 vs 10.3 [p = 0.00278], 7.0 vs 6.7 [p = 0.077] and 33.9 vs 26.7 [p < 0.00001, respectively). Mean background uptake did not differ significantly between Q.Clear and OSEM (0.42 vs 0.39, p = 0.07).
conclusionsIn 18F-PSMA-1007 PET/CT, Q.Clear SUVs and TBR tend to be higher (regardless of lesion localisation), especially for small and highly avid lesions. Increase in SUVs is also higher for lesions with high tracer uptake. Still, Q.Clear does not affect 18F-PSMA-1007 PET/CT specificity and sensitivity.
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