Evaluation and Optimization of a New PET Reconstruction Algorithm, Bayesian Penalized Likelihood Reconstruction, for Lung Cancer Assessment According to Lesion Size
Abstract
OBJECTIVE. The purpose of this study was to characterize the Bayesian penalized likelihood (BPL) reconstruction algorithm in comparison with an ordered subset expectation maximization (OSEM) reconstruction algorithm and to determine its optimal penalization factor (expressed as a beta value) for clinical use. MATERIALS AND METHODS. FDG PET/CT scans of 46 patients with lung cancer were reconstructed using OSEM and BPL with beta values of 200, 300, 400, 500, and 1000. The liver signal-to-noise ratio, mean standardized uptake value (SUV mean ) of the liver, and maximum standardized uptake value (SUV max ) and SUV mean of the cancers were measured. Tumors were categorized into three size groups, and the percentage difference in the tumor SUV max between OSEM and BPL with a beta value of 200 as well as the percentage difference in the SUV max between BPL with a beta value of 200 and BPL with a beta value of 1000 were calculated. Image quality was assessed by visual scoring. RESULTS. BPL showed a significantly higher liver signal-to-noise ratio than OSEM, except for BPL with a beta value of 200. The liver SUV mean showed no statistical difference among all algorithms. The SUV max and SUV mean of tumors decreased as the beta value increased. BPL with a beta value of 200 produced a significantly higher tumor SUV max than did OSEM ( p max than did OSEM ( p max between OSEM and BPL with a beta value of 200 and the percentage difference in the SUV max between BPL with a beta value of 20…
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Inter-method SUV differences may no longer be significant at beta values of 300 to 600, which have been rated as optimal for visual reading of [18F]FDG-PET images by human readers.
“However, this difference is directly dependent on the user-defined penalization factor beta during PL reconstruction, and at beta values of 300 to 600, which have been rated as optimal for visual reading of [18F]FDG-PET images by human readers [107,112,113], inter-method SUV differences may no longer be significant [41,108,111].”
From Influences on PET Quantification and Interpretation (2022) · cites this paper as [113]
PL reconstruction has the potential to systematically improve SNR compared to OSEM-based algorithms.
“Based on the potential of PL reconstruction to systematically improve SNR compared to OSEM-based algorithms [108,113,168]”
From Influences on PET Quantification and Interpretation (2022) · cites this paper as [113]
Several authors have reported improved SNR and image quality with PL reconstruction for different radiopharmaceuticals, including [18F]FDG, [18F]F-PSMA-1007, [68Ga]Ga-PSMA-11, [68Ga]Ga-DOTATATE, and 89Zr-labelled tracers.
“several authors have reported improved SNR and image quality with different radiopharmaceuticals, such as [18F]FDG [107,112,113], [18F]F-PSMA-1007 [143], [68Ga]Ga-PSMA-11 [169,170], [68Ga]Ga-DOTATATE [171] or 89Zr-labelled tracers [172].”
From Influences on PET Quantification and Interpretation (2022) · cites this paper as [113]
PL reconstruction has repeatedly been shown to increase conspicuity and detection rates of pulmonary lesions, even compared to OSEM with PSF and/or TOF.
“PL reconstruction has repeatedly been shown to increase conspicuity and detection rates of pulmonary lesions, even compared to OSEM with PSF and/or TOF [112,113,164,173,174].”
From Influences on PET Quantification and Interpretation (2022) · cites this paper as [113]
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- Authors
- Otani, T., Hosono, M., Kanagaki, M., Onishi, Y., Matsubara, N., Kawabata, K., & Kimura, H.
- Affiliations
- Kyoto University (JP)
- Kindai University (JP)
- Hyogo Prefectural Amagasaki General Medical Center (JP)
- ORCID
- Venue
- American Journal of Roentgenology
- Publisher
- American Roentgen Ray Society
- Published
- 2019-08
- Volume
- 213
- Issue
- 2
- Pages
- W50-W56
- ISSN
- 0002-9580 (ISSN-L)
- 0361-803X
- 1546-3141
- OpenAlex
- W2936311652
- Cited by
- 33
- References
- 16
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 3 · 2023: 8 · 2022: 6 · 2021: 7 · 2020: 4
- FWCI
- 2.81
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Journal of Roentgenology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Japan Society for the Promotion of Science (18K07651)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Diagnosis and Treatment
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiation Dose and Imaging
- Keywords
- Bayesian penalized likelihood reconstruction, PET image reconstruction, lung cancer, tumor size, image quality, quantitative image analysis, small lesions
- MeSH terms
- Positron Emission Tomography Computed Tomography, Aged, Aged, 80 and over, Algorithms, Bayes Theorem, Female, Humans, Lung Neoplasms, Male, Middle Aged, Neoplasm Staging, Radiographic Image Interpretation, Computer-Assisted, Retrospective Studies, Phantoms, Imaging, Radiopharmaceuticals, Fluorodeoxyglucose F18, Signal-To-Noise Ratio
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