ArticleEJNMMI physics2020
Reconstructed spatial resolution and contrast recovery with Bayesian penalized likelihood reconstruction (Q.Clear) for FDG-PET compared to time-of-flight (TOF) with point spread function (PSF).
Article in EJNMMI physics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
33 citing papers in PubMed.
- Reconstruction-dependent differences in brain [18F]FDG PET: a large-scale same-acquisition comparison of Q.Clear and VUE Point FX.Annals of nuclear medicine · 2026Article
- Q.Clear reconstruction shortening the scanning time forEJNMMI physics · 2026Article
- Enhancing reader confidence through dual-time imaging and alternative reconstruction algorithms with [EJNMMI research · 2026Article
- Evaluation of a Sensitive Visual Read Algorithm for Assessing 3R/4R Tau PET Images.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2025Article
- Innovations in clinical PET image reconstruction: advances in Bayesian penalized likelihood algorithm and deep learning.Annals of nuclear medicine · 2025Review
- Effects of a deep learning-based image quality enhancement method on a digital-BGO PET/CT system forEJNMMI physics · 2025Article
- β1600 Q.Clear Digital Reconstruction of [Journal of clinical medicine · 2024Article
- The Additional Role of F18-FDG PET/CT in Characterizing MRI-Diagnosed Tumor Deposits in Locally Advanced Rectal Cancer.Tomography (Ann Arbor, Mich.) · 2024Article
- Development of a bespoke phantom to optimize molecular PET imaging of pituitary tumors.EJNMMI physics · 2023Article
- A machine learning tool to improve prediction of mediastinal lymph node metastases in non-small cell lung cancer using routinely obtainable [European journal of nuclear medicine and molecular imaging · 2023Article
- Synthetic PET via Domain Translation of 3-D MRI.IEEE transactions on radiation and plasma medical sciences · 2023Article
- Hot spot imaging in cardiovascular diseases: an information statement from SNMMI, ASNC, and EANM.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023Article
- Impact of framing scheme optimization and smoking status on binding potential analysis in dynamic PET with [EJNMMI research · 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
- A personal acquisition time regimen ofCancer imaging : the official publication of the International Cancer Imaging Society · 2022Article
- Phantom and clinical evaluation of the effect of a new Bayesian penalized likelihood reconstruction algorithm (HYPER Iterative) onEJNMMI research · 2022Article
- CT radiomics to predict Deauville score 4 positive and negative Hodgkin lymphoma manifestations.Scientific reports · 2022Article
- Small lesion depiction and quantification accuracy of oncologicalEJNMMI physics · 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
- Influences on PET Quantification and Interpretation.Diagnostics (Basel, Switzerland) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBayesian penalized likelihood reconstruction for PET (e.g., GE Q.Clear) aims at improving convergence of lesion activity while ensuring sufficient signal-to-noise ratio (SNR). This study evaluated reconstructed spatial resolution, maximum/peak contrast recovery (CRmax/CRpeak) and SNR of Q.Clear compared to time-of-flight (TOF) OSEM with and without point spread function (PSF) modeling.
methodsThe NEMA IEC Body phantom was scanned five times (3 min scan duration, 30 min between scans, background, 1.5-3.9 kBq/ml F18) with a GE Discovery MI PET/CT (3-ring detector) with spheres filled with 8-, 4-, or 2-fold the background activity concentration (SBR 8:1, 4:1, 2:1). Reconstruction included Q.Clear (beta, 150/300/450), "PSF+TOF
resultsSpatial resolution of Q.Clear
conclusionsQ.Clear consistently improved reconstructed spatial resolution at high and medium SBR compared to PSF+TOF and OSEM+TOF, but only with beta = 150. However, this is at the cost of inferior SNR with Q.Clear
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.