Whole-Body Multiparametric PET in Clinical Oncology: Current Status, Challenges, and Opportunities

Area of Science:

• Nuclear Medicine
• Radiochemistry
• Oncologic Imaging

Background:

• Static PET reconstructions using Standardized Uptake Values (SUVs) have limitations in oncologic imaging.
• SUV-based methods are dependent on uptake times and can reduce lesion conspicuity in high-background organs.

Purpose of the Study:

• To review the current state of multiparametric PET in whole-body oncologic imaging.
• To guide oncologic imagers in deciding whether to implement multiparametric PET.

Main Methods:

• Utilizes dynamic PET imaging and Patlak modeling, which assumes irreversible tracer trapping.
• Generates multiparametric PET images quantifying tracer net trapping rate and apparent volume of distribution.

Main Results:

• Multiparametric PET separates bound and free tracer fractions, improving quantitative stability and lesion conspicuity.
• Potential for greater accuracy in differentiating malignant from benign lesions.

Conclusions:

• Dynamic PET with Patlak modeling offers significant advantages over static SUV-based PET.
• Despite complexity, multiparametric PET presents opportunities for enhanced oncologic imaging accuracy and decision-making.