Artificial Intelligence in Vascular-PET:: Translational and Clinical Applications
Sriram S Paravastu1, Elizabeth H Theng1, Michael A Morris2
1Department 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.
Positron emission tomography (PET) offers detailed vascular disease insights but lacks clinical use. Emerging AI methods promise to automate and enhance whole-body PET for better disease understanding and clinical application.
Area of Science:
- Vascular medicine and nuclear imaging science.
Background:
- Positron emission tomography (PET) provides molecular, functional, and structural data for vascular disease research.
- Current clinical use of vascular PET lags behind ultrasound, CT, and MRI due to reliance on visual inspection and suboptimal parameters like SUVmax.
- Whole-body PET applications are emerging for disease understanding but require automation to overcome time and variability issues.
Purpose of the Study:
- To review current PET applications in vascular disorders.
- To highlight emerging artificial intelligence (AI) methods in vascular PET imaging.
- To discuss the potential of AI to advance clinical utility of PET.
Main Methods:
- Literature review of PET applications in vascular disease.
- Review of current and emerging AI techniques relevant to PET imaging.
- Analysis of the potential impact of AI on clinical vascular PET.
Main Results:
- PET offers rich data for vascular disease but is underutilized clinically.
- AI presents opportunities to automate and improve the analysis of PET data.
- Whole-body PET, enhanced by AI, could significantly improve disease assessment.
Conclusions:
- AI holds significant potential to unlock the full clinical value of PET imaging in vascular disorders.
- Automation through AI can address limitations of current PET analysis.
- Further development and integration of AI are crucial for advancing vascular PET in clinical practice.
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