{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T12:51:46Z","timestamp":1784119906077,"version":"3.55.0"},"reference-count":36,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,8,29]],"date-time":"2025-08-29T00:00:00Z","timestamp":1756425600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Oncol."],"abstract":"<jats:sec><jats:title>Purpose<\/jats:title><jats:p>This study compares the Ordered Subset Expectation Maximization (OSEM) and Bayesian Penalized Likelihood (BPL) algorithms for Positron Emission Tomography\/Computed Tomography (PET\/CT) image reconstruction using <jats:sup>18<\/jats:sup>F- fluorodeoxyglucose (FDG) and <jats:sup>68<\/jats:sup>Ga-labeled Prostate-Specific Membrane Antigen(<jats:sup>68<\/jats:sup>Ga-PSMA-11) tracers.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A retrospective analysis was conducted on 33 patients with various malignancies, including 25 undergoing <jats:sup>18<\/jats:sup>F-FDG PET\/CT scans and 8 undergoing <jats:sup>68<\/jats:sup>Ga-PSMA-11 PET\/CT scans. Scans were reconstructed using both OSEM and BPL (Q.Clear) algorithms, evaluating key metrics such as Standardized Uptake Value (SUV)max, SUVpeak, background SUV, and tumor-to-background ratio (TBR).<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Thirty-three patients (mean age: 67.53 \u00b1 11.78 years) with 100 lesions (80 FDG, 20 PSMA) were analyzed. In the FDG group, significant differences were observed in lesion SUVpeak, liver SUVpeak, SD of liver SUVmean, bladder SUVmean, SD of bladder SUVmean, and TBR, with BPL generally producing higher values except for liver SUVpeak, SD of liver SUVmean, and SD of bladder SUVmean. In the PSMA group, BPL enhanced most metrics except for the SD of liver SUVmean and the SD of bladder SUVmean. While strong linear correlations between BPL and OSEM metrics were observed (Pearson r&amp;gt;0.85 for most parameters), Bland-Altman analysis revealed wide limits of agreement, particularly for TBR in the PSMA group (-13.00 to 23.89), indicating substantial variability in absolute values between methods. Assessment of the relationship between lesion volume and SUVmax differences (BPL\u2013OSEM) revealed a weak, non-significant negative correlation in the total cohort(r = \u2013 0.14, p = 0.16) and in the FDG subgroup(r= \u2013 0.14, p = 0.24).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Both reconstruction methods demonstrate clinical utility, with BPL producing statistically higher values for several quantitative metrics, such as SUVmax and TBR, without markedly improving lesion detectability. While strong correlations were observed between BPL and OSEM values, the wide limits of agreement, particularly for TBR in PSMA imaging, suggest these methods may not be directly interchangeable in longitudinal studies. Harmonization strategies may help reduce inter-method variability and improve scan comparability in longitudinal or multicenter settings. Prospective approaches, such as reconstruction-specific reference ranges or scaling factors, could further support harmonization efforts in clinical trials. For longitudinal monitoring, consistent use of the same reconstruction method is recommended to ensure reliable quantification.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fonc.2025.1597919","type":"journal-article","created":{"date-parts":[[2025,8,29]],"date-time":"2025-08-29T16:53:55Z","timestamp":1756486435000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Comparative evaluation of Ordered Subset Expectation Maximization and Bayesian Penalized Likelihood algorithms for PET\/CT image reconstruction in various malignancies using 18F-FDG and 68Ga-PSMA-11 tracers"],"prefix":"10.3389","volume":"15","author":[{"given":"Arvin","family":"Naeimi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sara","family":"Harsini","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ramin Akbarian","family":"Aghdam","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ran","family":"Klein","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Farzad","family":"Abbaspour","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,8,29]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"88","DOI":"10.2967\/jnumed.108.054205","article-title":"18F-FDG PET and PET\/CT in the evaluation of cancer treatment response","volume":"50","author":"Ben-Haim","year":"2009","journal-title":"J Nucl Med"},{"key":"B2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13550-019-0526-5","article-title":"Head-to-head comparison of image quality between brain 18 F-FDG images recorded with a fully digital versus a last-generation analog PET camera","volume":"9","author":"Salvadori","year":"2019","journal-title":"EJNMMI Res"},{"key":"B3","first-page":"110","article-title":"Standard OSEM vs. regularized PET image reconstruction: qualitative and quantitative comparison using phantom data and various clinical radiopharmaceuticals","volume":"8","author":"Lantos","year":"2018","journal-title":"Am J Nucl Med Mol imaging"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-010-1711-y","article-title":"Focus on time-of-flight PET: the benefits of improved time resolution","volume":"38","author":"Conti","year":"2011","journal-title":"Eur J Nucl Med Mol imaging"},{"key":"B5","article-title":"Influence of reconstruction iterations on 18F-FDG PET\/CT standardized uptake values","volume":"46","author":"Jaskowiak","year":"2005","journal-title":"J Nucl Med"},{"key":"B6","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1109\/TNS.23","article-title":"A concave prior penalizing relative differences for maximum-a-posteriori reconstruction in emission tomography","volume":"49","author":"Nuyts","year":"2002","journal-title":"IEEE Trans Nucl science"},{"key":"B7","doi-asserted-by":"publisher","first-page":"1100","DOI":"10.3390\/diagnostics11061100","article-title":"Evaluation of quantitative Ga-68 PSMA PET\/CT Repeatability of recurrent prostate cancer lesions using both OSEM and Bayesian penalized likelihood reconstruction Algorithms","volume":"11","author":"Roef","year":"2021","journal-title":"Diagnostics"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.115.159301","article-title":"Phantom and clinical evaluation of the Bayesian penalized likelihood reconstruction algorithm Q. Clear on an LYSO PET\/CT system","volume":"56","author":"Teoh","year":"2015","journal-title":"J Nucl Med"},{"key":"B9","doi-asserted-by":"publisher","first-page":"847","DOI":"10.3390\/diagnostics11050847","article-title":"Impact of the noise penalty factor on quantification in bayesian penalized likelihood (Q. Clear) reconstructions of 68Ga-PSMA PET\/CT scans","volume":"11","author":"Rijnsdorp","year":"2021","journal-title":"Diagnostics"},{"key":"B10","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1186\/s40658-019-0262-y","article-title":"Evaluation of a Bayesian penalized likelihood reconstruction algorithm for low-count clinical 18F-FDG PET\/CT","volume":"6","author":"te Riet","year":"2019","journal-title":"EJNMMI Physics"},{"key":"B11","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.17.18060","article-title":"Effect of a Bayesian penalized likelihood PET reconstruction compared with ordered subset expectation maximization on clinical image quality over a wide range of patient weights","volume":"210","author":"Chilcott","year":"2018","journal-title":"Am J Roentgenology"},{"key":"B12","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1186\/s40658-021-00386-3","article-title":"Performance evaluation of the Q. Clear reconstruction framework versus conventional reconstruction algorithms for quantitative brain PET-MR studies","volume":"8","author":"Ribeiro","year":"2021","journal-title":"EJNMMI physics"},{"key":"B13","doi-asserted-by":"publisher","first-page":"20170727","DOI":"10.1259\/bjr.20170727","article-title":"Bayesian penalised likelihood reconstruction (Q. Clear) of 18F-fluciclovine PET for imaging of recurrent prostate cancer: semi-quantitative and clinical evaluation","volume":"91","author":"Teoh","year":"2018","journal-title":"Br J Radiol"},{"key":"B14","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1186\/s40644-024-00702-x","article-title":"Comparison of quantitative whole body PET parameters on [68Ga] Ga-PSMA-11 PET\/CT using ordered Subset Expectation Maximization (OSEM) vs. bayesian penalized likelihood (BPL) reconstruction algorithms in men with metastatic castration-resistant prostate cancer","volume":"24","author":"Ayati","year":"2024","journal-title":"Cancer Imaging"},{"key":"B15","doi-asserted-by":"publisher","first-page":"65","DOI":"10.3390\/jimaging9030065","article-title":"Comparison of image quality and quantification parameters between Q. Clear and OSEM reconstruction methods on FDG-PET\/CT images in patients with metastatic breast cancer","volume":"9","author":"Naghavi-Behzad","year":"2023","journal-title":"J imaging"},{"key":"B16","doi-asserted-by":"publisher","DOI":"10.1007\/s12149-019-01433-x","article-title":"Ordered subset expectation maximisation vs Bayesian penalised likelihood reconstruction algorithm in 18F-PSMA-1007 PET\/CT","volume":"34","author":"Witkowska-Patena","year":"2020","journal-title":"Ann Nucl Med"},{"key":"B17","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1007\/s00259-017-3740-2","article-title":"EANM\/EARL harmonization strategies in PET quantification: from daily practice to multicentre oncological studies","volume":"44","author":"Aide","year":"2017","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"B18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40658-020-00300-3","article-title":"Impact of the Bayesian penalized likelihood algorithm (Q. Clear\u00ae) in comparison with the OSEM reconstruction on low contrast PET hypoxic images","volume":"7","author":"Texte","year":"2020","journal-title":"EJNMMI physics"},{"key":"B19","doi-asserted-by":"publisher","first-page":"5733","DOI":"10.1088\/0031-9155\/60\/15\/5733","article-title":"Quantitative comparison of OSEM and penalized likelihood image reconstruction using relative difference penalties for clinical PET","volume":"60","author":"Ahn","year":"2015","journal-title":"Phys Med Biol"},{"key":"B20","doi-asserted-by":"publisher","first-page":"10328","DOI":"10.1038\/s41598-021-89725-z","article-title":"Phantom and clinical assessment of small pulmonary nodules using Q. Clear reconstruction on a silicon-photomultiplier-based time-of-flight PET\/CT system","volume":"11","author":"Wu","year":"2021","journal-title":"Sci Rep"},{"key":"B21","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2015.03.010","article-title":"Validation of a semi-automated liver segmentation method using CT for accurate volumetry","volume":"22","author":"Gotra","year":"2015","journal-title":"Acad radiology"},{"key":"B22","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-018-4023-2","article-title":"The impact of a Bayesian penalized-likelihood reconstruction algorithm on delayed-time-point Ga-68-PSMA PET for improved recurrent prostate cancer detection","volume":"45","author":"Sampaio Vieira","year":"2018","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"B23","doi-asserted-by":"publisher","first-page":"111349","DOI":"10.1016\/j.ejrad.2024.111349","article-title":"Impact of different reconstruction algorithms and setting parameters on radiomics features of PSMA PET images: A preliminary study","volume":"172","author":"Fooladi","year":"2024","journal-title":"Eur J Radiol"},{"key":"B24","doi-asserted-by":"publisher","first-page":"1607","DOI":"10.1007\/s00259-021-05592-w","article-title":"Can Q. Clear reconstruction be used to improve [68 Ga] Ga-DOTANOC PET\/CT image quality in overweight NEN patients","volume":"49","author":"Zanoni","year":"2022","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"B25","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.18.20478","article-title":"Evaluation and optimization of a new PET reconstruction algorithm, Bayesian penalized likelihood reconstruction, for lung cancer assessment according to lesion size","volume":"213","author":"Otani","year":"2019","journal-title":"Am J Roentgenology"},{"key":"B26","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-014-2961-x","article-title":"FDG PET\/CT: EANM procedure guidelines for tumour imaging: version 2.0","volume":"42","author":"Boellaard","year":"2015","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"B27","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-017-3853-7","article-title":"EANM\/EARL FDG-PET\/CT accreditation-summary results from the first 200 accredited imaging systems","volume":"45","author":"Kaalep","year":"2018","journal-title":"Eur J Nucl Med Mol imaging"},{"key":"B28","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2019191882","article-title":"The QIBA profile for FDG PET\/CT as an imaging biomarker measuring response to cancer therapy","volume":"294","author":"Kinahan","year":"2020","journal-title":"Radiology"},{"key":"B29","doi-asserted-by":"publisher","DOI":"10.1007\/s12149-021-01709-1","article-title":"New standards for phantom image quality and SUV harmonization range for multicenter oncology PET studies","volume":"36","author":"Akamatsu","year":"2022","journal-title":"Ann Nucl Med"},{"key":"B30","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.108.057307","article-title":"From RECIST to PERCIST: evolving considerations for PET response criteria in solid tumors","volume":"50","author":"Wahl","year":"2009","journal-title":"J Nucl Med"},{"key":"B31","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2021.707023","article-title":"Effects of new Bayesian penalized likelihood reconstruction algorithm on visualization and quantification of upper abdominal Malignant tumors in clinical FDG PET\/CT examinations","volume":"11","author":"Tatsumi","year":"2021","journal-title":"Front Oncol"},{"key":"B32","doi-asserted-by":"publisher","DOI":"10.1016\/j.remnie.2023.07.006","article-title":"The variation of quantitative parameters and Deauville scores with different reconstruction algorithms in FDG PET\/CT imaging of lymphoma patients","volume":"42","author":"Genc","year":"2023","journal-title":"Rev Espa\u00f1ola Medicina Nucl e Imagen Mol (English Edition)"},{"key":"B33","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.106.035774","article-title":"Partial-volume effect in PET tumor imaging. Journal of nuclear medicine","volume":"48","author":"Soret","year":"2007","journal-title":"J Nucl Med"},{"key":"B34","doi-asserted-by":"publisher","DOI":"10.1097\/MNM.0000000000001598","article-title":"Harmonization based on quantitative analysis of standardized uptake value variations across PET\/CT scanners: a multicenter phantom study","volume":"43","author":"Monsef","year":"2022","journal-title":"Nucl Med Commun"},{"key":"B35","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.115.171983","article-title":"Does PET SUV harmonization affect PERCIST response classification","volume":"57","author":"Quak","year":"2016","journal-title":"J Nucl Med"},{"key":"B36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s13550-019-0504-y","article-title":"Comparison between silicon photomultiplier-based and conventional PET\/CT in patients with suspected lung cancer\u2014a pilot study","volume":"9","author":"Economou Lundeberg","year":"2019","journal-title":"EJNMMI Res"}],"container-title":["Frontiers in Oncology"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fonc.2025.1597919\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,29]],"date-time":"2025-08-29T16:53:56Z","timestamp":1756486436000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fonc.2025.1597919\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,29]]},"references-count":36,"alternative-id":["10.3389\/fonc.2025.1597919"],"URL":"https:\/\/doi.org\/10.3389\/fonc.2025.1597919","relation":{},"ISSN":["2234-943X"],"issn-type":[{"value":"2234-943X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,29]]},"article-number":"1597919"}}