ArticleEuropean journal of nuclear medicine and molecular imaging2022
Can Q.Clear reconstruction be used to improve [68 Ga]Ga-DOTANOC PET/CT image quality in overweight NEN patients?
Article in European journal of nuclear medicine and molecular imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed.
- Optimizing acquisition time and injected dose inBMC medical informatics and decision making · 2026Article
- Evaluation of regularization factor and attenuation correction method of Q.Clear reconstruction for brain PET/MR in epileptic patients.EJNMMI physics · 2026Article
- Innovations in clinical PET image reconstruction: advances in Bayesian penalized likelihood algorithm and deep learning.Annals of nuclear medicine · 2025Review
- Diagnostic accuracy of dual-phaseScientific reports · 2025Article
- Impact of patient size on image quality of OSEM3D and BSREM reconstructions in [EJNMMI physics · 2025Article
- Comparison ofEJNMMI physics · 2025Article
- Comparative evaluation of Ordered Subset Expectation Maximization and Bayesian Penalized Likelihood algorithms for PET/CT image reconstruction in various malignancies usingFrontiers in oncology · 2025Article
- β1600 Q.Clear Digital Reconstruction of [Journal of clinical medicine · 2024Article
- Reduction of [EJNMMI physics · 2024Article
- Rapid Whole-Body FDG PET/MRI in Oncology Patients: Utility of Combining Bayesian Penalised Likelihood PET Reconstruction and Abbreviated MRI.Diagnostics (Basel, Switzerland) · 2023Article
- 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.Journal of imaging · 2023Article
- Deep progressive learning achieves whole-body low-doseEJNMMI physics · 2022Article
- Positron Range Corrections and Denoising Techniques for Gallium-68 PET Imaging: A Literature Review.Diagnostics (Basel, Switzerland) · 2022Review
- The Impact of Total Variation Regularized Expectation Maximization Reconstruction onFrontiers in medicine · 2022Article
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10 authors.
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Abstract
AIM/
introductionDigital PET/CT allows Q.Clear image reconstruction with different Beta (β) levels. However, no definitive standard β level for [68 Ga]Ga-DOTANOC PET/CT has been established yet. As patient's body mass index (BMI) can affect image quality, the aim of the study was to visually and semi-quantitatively assess different β levels compared to standard OSEM in overweight patients. MATERIALS AND
methodsInclusion criteria: (1) patients with NEN included in a prospective CE-approved electronic archive; (2) [68 Ga]Ga-DOTANOC PET/CT performed on a digital tomograph between September2019/March2021; (3) BMI ≥ 25. Images were acquired following EANM guidelines and reconstructed with OSEM and Q.Clear with three β levels (800, 1000, 1600). Scans were independently reviewed by three expert readers, unaware of clinical data, who independently chose the preferred β level reconstruction for visual overall image quality. Semi-quantitative analysis was performed on each scan: SUVmax of the highest uptake lesion (SUVmax-T), liver background SUVmean (SUVmean-L), SUVmax-T/SUVmean-L, Signal-to-noise ratio for both liver (LSNR) and the highest uptake lesion (SNR-T), Contrast-to-noise ratio (CNR).
resultsOverall, 75 patients (median age: 63 years old [23-87]) were included: pre-obesity sub-group (25 ≤ BMI < 30, n = 50) and obesity sub-group (BMI ≥ 30, n = 25). PET/CT was positive for disease in 45/75 (60.0%) cases (14 obese and 31 pre-obese patients). Agreement among readers' visual rating was high (Fleiss κ = 0.88) and the β1600 was preferred in most cases (in 96% of obese patients and in 53.3% of pre-obese cases). OSEM was considered visually equal to β1600 in 44.7% of pre-obese cases and in 4% of obese patients. In a minority of pre-obese cases, OSEM was preferred (2%). In the whole population, CNR, SNR-T and LSNR were significantly different (p < 0.001) between OSEM and β1600, conversely to SUVmean-L (not significant). These results were also confirmed when calculated separately for the pre-obesity and obesity sub-groups β800 and β1000 were always rated inferior.
conclusionsQ.Clear is a new technology for PET/CT image reconstruction that can be used to increase CNR and SNR-T, to subsequently optimise overall image quality as compared to standard OSEM. Our preliminary data on [68 Ga]Ga-DOTANOC PET/CT demonstrate that in overweight NEN patients, β1600 is preferable over β800 and β1000. Further studies are warranted to validate these results in lesions of different anatomical region and size; moreover, currently employed interpretative PET positivity criteria should be adjusted to the new reconstruction method.
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