ArticleEJNMMI physics2018
Impact of a Bayesian penalized likelihood reconstruction algorithm on image quality in novel digital PET/CT: clinical implications for the assessment of lung tumors.
Article in EJNMMI physics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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41 citing papers in PubMed.
- Evaluation of deep learning-based reconstruction models on non-TOF BGO PET/CT: impact of acquisition times and BSREM penalization factors on lesion detectability and SNR.EJNMMI physics · 2026Article
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- EnhancingCancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Y-90 PET/MR imaging optimization with a Bayesian penalized likelihood reconstruction algorithm.Physical and engineering sciences in medicine · 2024Article
- Fully automated computational measurement of noise in positron emission tomography.European radiology · 2024Article
- Investigation of PET image quality with acquisition time/bed and enhancement of lesion quantification accuracy through deep progressive learning.EJNMMI physics · 2024Article
- Impact of respiratory motion onJournal of applied clinical medical physics · 2023Article
- A retrospective evaluation of Bayesian-penalized likelihood reconstruction for [Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023Article
- Automated F18-FDG PET/CT image quality assessment using deep neural networks on a latest 6-ring digital detector system.Scientific reports · 2023Article
- Comparative study of the quantitative accuracy of oncological PET imaging based on deep learning methods.Quantitative imaging in medicine and surgery · 2023Article
- Prognostic value of genetic alterations andAmerican journal of cancer research · 2023Article
- Opportunistic deep learning powered calcium scoring in oncologic patients with very high coronary artery calcium (≥ 1000) undergoing 18F-FDG PET/CT.Scientific reports · 2022Article
- Can Dynamic Whole-Body FDG PET Imaging Differentiate between Malignant and Inflammatory Lesions?Life (Basel, Switzerland) · 2022Article
- BSREM for Brain Metastasis Detection with 18F-FDG-PET/CT in Lung Cancer Patients.Journal of digital imaging · 2022Article
- Impact of Bayesian penalized likelihood reconstruction on quantitative and qualitative aspects for pulmonary nodule detection in digital 2-[Scientific reports · 2022Article
- Exploration of the total-body PET/CT reconstruction protocol with ultra-lowEJNMMI physics · 2022Article
- Influences on PET Quantification and Interpretation.Diagnostics (Basel, Switzerland) · 2022Review
- [European radiology · 2022Article
- Clinical evaluation of data-driven respiratory gating for PET/CT in an oncological cohort of 149 patients: impact on image quality and patient management.The British journal of radiology · 2021Article
- Improved detection of in-transit metastases of malignant melanoma with BSREM reconstruction in digital [European radiology · 2021Article
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Abstract
backgroundThe aim of this study was to evaluate and compare PET image reconstruction algorithms on novel digital silicon photomultiplier PET/CT in patients with newly diagnosed and histopathologically confirmed lung cancer. A total of 45 patients undergoing 18F-FDG PET/CT for initial lung cancer staging were included. PET images were reconstructed using ordered subset expectation maximization (OSEM) with time-of-flight and point spread function modelling as well as Bayesian penalized likelihood reconstruction algorithm (BSREM) with different β-values yielding a total of 7 datasets per patient. Subjective and objective image assessment with all image datasets was carried out, including subgroup analyses for patients with high dose (> 2.0 MBq/kg) and low dose (≤ 2.0 MBq/kg) of 18F-FDG injection regimen.
resultsSubjective image quality ratings were significantly different among all different reconstruction algorithms as well as among BSREM using different β-values only (both p < 0.001). BSREM with a β-value of 600 was assigned the highest score for general image quality, image sharpness, and lesion conspicuity. BSREM reconstructions resulted in higher SUV
conclusionsBSREM reconstruction algorithm used in digital detector PET leads to significant increases of lung tumor SUV
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