(Monday, 7/15/2019) 4:30 PM - 6:00 PM
Room: 221CD
Technological advances associated with medical imaging are being applied in nuclear medicine allowing for the opportunity for dose optimization. However, challenges still exist for certain patient populations such as children that are considered to be at higher risk to ionizing radiation. In addition, the ability of hybrid imaging including PET/CT to provide the clinician with functional or metabolic image data closely registered to the patient’s anatomy can lead to an improved diagnostic representation of the patient but with a cost of higher absorbed dose. This session will review the application of dose optimization to children. The dosimetric issues presented by the incorporation of CT into hybrid PET/CT as well as the impact that PET/MR may have on dose optimization will be presented. Lastly, the application of deep learning to the reconstruction of SPECT data and its promise in the context of improved diagnostic image quality and dose optimization will be discussed.
Learning Objectives:
• Describe 3 factors contributing to the difference in estimating dose and radiation risk in children relative to that for adults,
• Define 2 current projects seeking to improve the radiopharmaceutical dosimetry in children
• List 3 ways in which the CT dose associated with PET/CT can be optimized,
• Discuss 3 ways that PET/MR can lead to improved diagnostic image quality at a lower absorbed dose,
• Describe 2 ways in which deep learning can improve the quality and safety associated with SPECT reconstruction.
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