Optimal image-derived input function models for multi-parameter analysis and acceptably reduced acquisition time in...

Area of Science:

• Nuclear Medicine
• Radiochemistry
• Oncology

Background:

• Lung tumors possess a dual blood supply, potentially influencing kinetic parameters in PET imaging.
• [¹⁸F]F-FAPI-42 is a novel tracer for fibroblast activation protein (FAP) imaging.
• Accurate kinetic parameter quantification is crucial for assessing tumor characteristics.

Purpose of the Study:

• To evaluate factors affecting [¹⁸F]F-FAPI-42 kinetic parameter quantification in lung cancer.
• To determine the optimal image-derived input function (IDIF) model.
• To establish an acceptable shortened acquisition time for dynamic PET/CT scans.

Main Methods:

• 19 lung cancer patients underwent 60-minute dynamic [¹⁸F]F-FAPI-42 PET/CT.
• Kinetic parameters (K1-K3, Ki) were calculated using a two-tissue irreversible comparative (2TiC) model.
• Evaluated IDIF models (right ventricle [RV], left ventricle [LV], descending aorta [DA]), tumor size, location, and subtype.

Main Results:

• The RVIF model yielded kinetic parameters comparable to the full 60-minute scan in just 26 minutes.
• Tumor size significantly impacted kinetic parameters in RVIF and LVIF models.
• Tumor location and pathohistological subtype did not significantly affect quantification.
• Image quality metrics (SUVmean, SNR, CNR, TBR) remained high at the shortened acquisition time.

Conclusions:

• The RVIF model is superior to the descending aorta input function (DAIF) model for [¹⁸F]F-FAPI-42 kinetic analysis in lung cancer.
• A shortened acquisition time of 26 minutes is feasible and reliable using the RVIF model.
• This optimized protocol can improve efficiency in lung cancer PET/CT imaging.