ArticleEuropean radiology2016
18F-FDG PET/CT assessment of histopathologically confirmed mediastinal lymph nodes in non-small cell lung cancer using a penalised likelihood reconstruction.
Article in European radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 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
23 citing papers in PubMed, 56 citations in OpenAlex.
- Diagnostic accuracy of dual-phaseScientific reports · 2025Article
- Deep learning-based time-of-flight (ToF) enhancement of non-ToF PET scans for different radiotracers.European journal of nuclear medicine and molecular imaging · 2025Article
- 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
- Deep learning-based time-of-flight (ToF) image enhancement of non-ToF PET scans.European journal of nuclear medicine and molecular imaging · 2022Article
- 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
- Small lesion depiction and quantification accuracy of oncologicalEJNMMI physics · 2022Article
- Image enhancement of whole-body oncology [European journal of nuclear medicine and molecular imaging · 2022Article
- Changes of [BMC medical imaging · 2021Article
- New PET technologies - embracing progress and pushing the limits.European journal of nuclear medicine and molecular imaging · 2021Article
- Phantom and clinical assessment of small pulmonary nodules using Q.Clear reconstruction on a silicon-photomultiplier-based time-of-flight PET/CT system.Scientific reports · 2021Article
- Does the beta regularization parameter of bayesian penalized likelihood reconstruction always affect the quantification accuracy and image quality of positron emission tomography computed tomography?Journal of applied clinical medical physics · 2021Article
- Impact of the Q.Clear reconstruction algorithm on the interpretation of PET/CT images in patients with lymphoma.EJNMMI research · 2020Article
- Evaluation of block-sequential regularized expectation maximization reconstruction ofEJNMMI physics · 2020Article
- Impact of the Bayesian penalized likelihood algorithm (Q.Clear®) in comparison with the OSEM reconstruction on low contrast PET hypoxic images.EJNMMI physics · 2020Article
- How Do the More Recent Reconstruction Algorithms Affect the Interpretation Criteria of PET/CT Images?Nuclear medicine and molecular imaging · 2019Article
- Immunotherapy by targeting of VGKC complex for seizure control and prevention of cognitive impairment in a mouse model of epilepsy.Molecular medicine reports · 2018Article
- Bayesian penalised likelihood reconstruction (Q.Clear) ofThe British journal of radiology · 2018Article
- All that glitters is not gold - new reconstruction methods using Deauville criteria for patient reporting.European journal of nuclear medicine and molecular imaging · 2018Article
- Simvastatin inhibits the apoptosis of hippocampal cells in a mouse model of Alzheimer's disease.Experimental and therapeutic medicine · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
purposeTo investigate whether using a Bayesian penalised likelihood reconstruction (BPL) improves signal-to-background (SBR), signal-to-noise (SNR) and SUV MATERIALS AND
methods18F-FDG PET/CT scans for NSCLC staging in 47 patients (112 nodal stations with histopathological confirmation) were reconstructed using BPL and compared to OSEM. Node and multiple background SUV parameters were analysed semi-quantitatively and visually.
resultsComparing BPL to OSEM, there were significant increases in SUV
conclusionBPL increases SBR, SNR and SUV KEY POINTS: • Penalised likelihood PET reconstruction was applied for assessing mediastinal nodes in NSCLC. • The new reconstruction generated significant increases in signal-to-background, signal-to-noise and SUVmax. • This led to an improvement in visual sensitivity using the new algorithm. • Higher SUV
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.