Abstract
Learning Objectives: On successful completion of this activity, participants should be able to (1) describe examples of the application of PET tracer kinetic analysis to oncology; (2) list applications research and possible clinical applications in oncology where kinetic analysis is helpful; and (3) discuss future applications of kinetic modeling to cancer research and possible clinical cancer imaging practice.
Financial Disclosure: This work was supported by KL2 TR001879, R01 CA211337, R01 CA113941, R33 CA225310, Komen SAC130060, R50 CA211270, and K01 DA040023. Dr. Pantel is a consultant or advisor for Progenics and Blue Earth Diagnostics and is a meeting participant or lecturer for Blue Earth Diagnostics. Dr. Mankoff is on the scientific advisory boards of GE Healthcare, Philips Healthcare, Reflexion, and ImaginAb and is the owner of Trevarx; his wife is the chief executive officer of Trevarx. The authors of this article have indicated no other relevant relationships that could be perceived as a real or apparent conflict of interest.
CME Credit: SNMMI is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to sponsor continuing education for physicians. SNMMI designates each JNM continuing education article for a maximum of 2.0 AMA PRA Category 1 Credits. Physicians should claim only credit commensurate with the extent of their participation in the activity. For CE credit, SAM, and other credit types, participants can access this activity through the SNMMI website (http://www.snmmilearningcenter.org) through April 2025.
Kinetic analysis of dynamic PET imaging enables the estimation of biologic processes relevant to disease. Through mathematic analysis of the interactions of a radiotracer with tissue, information can be gleaned from PET imaging beyond static uptake measures. Part I of this 2-part continuing education paper reviewed the underlying principles and methodology of kinetic modeling. In this second part, the benefits of kinetic modeling for oncologic imaging are illustrated through representative case examples that demonstrate the principles and benefits of kinetic analysis in oncology. Examples of the model types discussed in part I are reviewed here: a 1-tissue-compartment model (15O-water), an irreversible 2-tissue-compartment model (18F-FDG), and a reversible 2-tissue-compartment model (3′-deoxy-3′-18F-fluorothymidine). Kinetic approaches are contrasted with static uptake measures typically used in the clinic. Overall, this 2-part review provides the reader with background in kinetic analysis to understand related research and improve the interpretation of clinical nuclear medicine studies with a focus on oncologic imaging.
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