Artificial Intelligence in Vascular-PET:: Translational and Clinical Applications.

Autor:	Paravastu SS; Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health (NIH), Bethesda, MD 20892, USA; Skeletal Disorders and Mineral Homeostasis Section, National Institute of Dental and Craniofacial Research, National Institutes of Health (NIH), Bethesda, MD 20892, USA; School of Medicine, University of Missouri-Kansas City, 2411 Holmes Street, Kansas City, MO 64108, USA., Theng EH; Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health (NIH), Bethesda, MD 20892, USA; Skeletal Disorders and Mineral Homeostasis Section, National Institute of Dental and Craniofacial Research, National Institutes of Health (NIH), Bethesda, MD 20892, USA; School of Medicine, University of Missouri-Kansas City, 2411 Holmes Street, Kansas City, MO 64108, USA., Morris MA; Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health (NIH), Bethesda, MD 20892, USA; Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County, Baltimore, MD, USA; Institute for Data Science, Department of Diagnostic Radiology and Nuclear Medicine - University of Miami Miller School of Medicine, Miami, FL, USA., Grayson P; National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, 10 Center Dr, Building 10 Room 12S-253, Bethesda, MD 20892, USA., Collins MT; Skeletal Disorders and Mineral Homeostasis Section, National Institute of Dental and Craniofacial Research, National Institutes of Health (NIH), Bethesda, MD 20892, USA., Maass-Moreno R; Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health (NIH), Bethesda, MD 20892, USA., Piri R; Department of Nuclear Medicine, Odense University Hospital, 5000 Odense C, Denmark; Department of Clinical Research, University of Southern Denmark, Odense, Denmark., Gerke O; Department of Nuclear Medicine, Odense University Hospital, 5000 Odense C, Denmark; Department of Clinical Research, University of Southern Denmark, Odense, Denmark., Alavi A; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA., Flemming Høilund-Carlsen P; Department of Nuclear Medicine, Odense University Hospital, 5000 Odense C, Denmark; Department of Clinical Research, University of Southern Denmark, Odense, Denmark., Edenbrandt L; Region Västra Götaland, Sahlgrenska University Hospital, Department of Clinical Physiology, Gothenburg, Sweden; Department of Molecular and Clinical Medicine, Institute of Medicine, SU Sahlgrenska, 413 45 Göteborg, Sweden., Saboury B; Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health (NIH), Bethesda, MD 20892, USA; Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County, Baltimore, MD, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Electronic address: babak.saboury@nih.gov.
Jazyk:	angličtina
Zdroj:	PET clinics [PET Clin] 2022 Jan; Vol. 17 (1), pp. 95-113.
DOI:	10.1016/j.cpet.2021.09.003
Abstrakt:	Positron emission tomography (PET) offers an incredible wealth of diverse research applications in vascular disease, providing a depth of molecular, functional, structural, and spatial information. Despite this, vascular PET imaging has not yet assumed the same clinical use as vascular ultrasound, CT, and MR imaging which provides information about late-onset, structural tissue changes. The current clinical utility of PET relies heavily on visual inspection and suboptimal parameters such as SUVmax; emerging applications have begun to harness the tool of whole-body PET to better understand the disease. Even still, without automation, this is a time-consuming and variable process. This review summarizes PET applications in vascular disorders, highlights emerging AI methods, and discusses the unlocked potential of AI in the clinical space. Competing Interests: Disclosure The authors have nothing to disclose. (Copyright © 2021 Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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