Response Prediction and Evaluation Using PET in Patients with Solid Tumors Treated with Immunotherapy

Area of Science:

• Oncology
• Radiology
• Immunotherapy

Background:

• Checkpoint inhibitor therapy is a first-line treatment for many cancers, but patient response varies.
• Biomarker research is crucial for identifying patients who will benefit from immunotherapy.
• Molecular imaging, particularly Positron Emission Tomography (PET), is under investigation as a predictive biomarker.

Purpose of the Study:

• To review the utility of Positron Emission Tomography (PET) in predicting and evaluating treatment response to immunotherapy.
• To explore the role of novel PET tracers and artificial intelligence in response prediction.
• To highlight PET's potential in early response assessment and patient stratification.

Main Methods:

• Review of current literature on Positron Emission Tomography (PET) applications in immunotherapy.
• Evaluation of conventional PET tracers (e.g., ¹⁸F-FDG) and novel PD-(L)1 directed tracers.
• Assessment of artificial intelligence (AI) in conjunction with PET for response prediction.

Main Results:

• PET imaging shows promise in predicting patient response to checkpoint inhibitor therapy.
• PET can aid in early evaluation of treatment efficacy, distinguishing response patterns from traditional chemotherapy.
• PET facilitates stratification of patients into complete response or residual disease categories.

Conclusions:

• Positron Emission Tomography (PET) is a valuable tool for predicting and evaluating immunotherapy response.
• PET imaging can guide clinical decisions regarding treatment escalation or discontinuation.
• Further research into PET tracers and AI integration will enhance its role in personalized cancer therapy.