ArticleEJNMMI physics2024
Reducing pediatric total-body PET/CT imaging scan time with multimodal artificial intelligence technology.
Article in EJNMMI physics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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The trial behind it
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Who cites it
11 citing papers in PubMed, 16 citations in OpenAlex.
- Application of artificial intelligence in paediatric oncology imaging.Pediatric radiology · 2026Review
- An integrated PET/CT simulation framework for virtual imaging trials and quantitative performance evaluation.Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) · 2026Article
- Acquisition time/dose reduction in pediatric PET imaging using patch-based deep learning.EJNMMI physics · 2026Article
- Continuous bed motion versus step-and-shoot acquisition in LAFOV PET/CT: insights from multi-phantom and patient studies.EJNMMI physics · 2026Article
- Scanner-integrated reconstruction versus post-processing deep learning for low-countEJNMMI physics · 2026Article
- CT-Free Attenuation Correction in Paediatric Long Axial Field-of-View Positron Emission Tomography Using Synthetic CT from Emission Data.Diagnostics (Basel, Switzerland) · 2024Article
- Recent Breakthroughs in PET-CT Multimodality Imaging: Innovations and Clinical Impact.Bioengineering (Basel, Switzerland) · 2024Review
- Long-Axial Field-of-View PET Imaging in Patients with Lymphoma: Challenges and Opportunities.PET clinics · 2024Review
- Dose Reduction in Pediatric Oncology Patients with Delayed Total-Body [Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2024Article
- Paediatric Thoracic Imaging in Cystic Fibrosis in the Era of Cystic Fibrosis Transmembrane Conductance Regulator Modulation.Children (Basel, Switzerland) · 2024Review
- Whole-body PET image denoising for reduced acquisition time.Frontiers in medicine · 2024Article
Corrections and comments
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
Abstract
objectivesThis study aims to decrease the scan time and enhance image quality in pediatric total-body PET imaging by utilizing multimodal artificial intelligence techniques.
methodsA total of 270 pediatric patients who underwent total-body PET/CT scans with a uEXPLORER at the Sun Yat-sen University Cancer Center were retrospectively enrolled.
resultsMultimodal artificial intelligence techniques can significantly improve PET image quality. When fused with prior CT information, the anatomical information of the images was enhanced, and 60 s of scan data produced images of quality comparable to that of the full-time data.
conclusionMultimodal artificial intelligence techniques can effectively improve the quality of pediatric total-body PET/CT images acquired using ultrashort scan times. This has the potential to decrease the use of sedation, enhance guardian confidence, and reduce the probability of motion artifacts.
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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.