ArticleEuropean journal of nuclear medicine and molecular imaging2024
Intelligent ultrafast total-body PET for sedation-free pediatric [
Article in European journal of nuclear medicine and molecular imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 15 citations in OpenAlex.
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- Diffused Multi-scale Generative Adversarial Network for low-dose PET images reconstruction.Biomedical engineering online · 2025Article
- Expert consensus on workflow of PET/CT with long axial field-of-view.European journal of nuclear medicine and molecular imaging · 2025Review
- Performance Characteristics of a New Generation 148-cm Axial Field-of-View uMI Panorama GS PET/CT System with Extended NEMA NU 2-2018 and EARL Standards.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2024Article
- Establishment of a normal control model of children's brain 18-fluorodeoxyglucose positron emission tomography and analysis of the changing pattern in patients aged 0-14 years.Quantitative imaging in medicine and surgery · 2024Article
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Authors and funding
9 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThis study aims to develop deep learning techniques on total-body PET to bolster the feasibility of sedation-free pediatric PET imaging.
methodsA deformable 3D U-Net was developed based on 245 adult subjects with standard total-body PET imaging for the quality enhancement of simulated rapid imaging. The developed method was first tested on 16 children receiving total-body [
resultsThe approach significantly improved the subjective image quality and lesion conspicuity in abdominal and pelvic regions of the generated 6-s data. In the first test set, the proposed method enhanced the objective image quality metrics of 6-s data, such as PSNR (from 29.13 to 37.09, p < 0.01) and SSIM (from 0.906 to 0.921, p < 0.01). Furthermore, the errors of mean standardized uptake values (SUVmean) for lesions between 300-s data and 6-s data were reduced from 12.9 to 4.1% (p < 0.01), and the errors of max SUV (SUVmax) were reduced from 17.4 to 6.2% (p < 0.01). In the prospective test, radiologists reached a high degree of consistency on the clinical feasibility of the enhanced PET images.
conclusionThe proposed method can effectively enhance the image quality of total-body PET scanning with ultrafast acquisition time, leading to meeting clinical diagnostic requirements of lesion detectability and quantification in abdominal and pelvic regions. It has much potential to solve the dilemma of the use of sedation and long acquisition time that influence the health of pediatric patients.
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