Arterial input function derived from pairwise correlations between PET-image voxels.

Area of Science:

• Nuclear medicine
• Radiochemistry
• Medical imaging analysis

Background:

• Accurate quantification of positron emission tomography (PET) data using compartmental analysis requires a metabolite-corrected arterial input function.
• This is particularly crucial for radioligands lacking suitable reference regions in the brain.
• Current arterial input function measurement is invasive, involving arterial cannulation, which poses risks and patient discomfort.

Purpose of the Study:

• To develop and validate a novel, non-invasive method for obtaining image-derived input functions (IDIFs) for PET data analysis.
• To assess the performance of this new method against existing techniques and traditional arterial measurements.

Main Methods:

• A novel IDIF method was developed using the Pearson correlation coefficient to identify blood-like voxels based on time-activity curve similarity.
• The method was evaluated in human studies using [(11)C]flumazenil and [(11)C]AZ10419369 radioligands.
• Performance was compared with three established methods, and distribution volume (VT) results were compared against traditional arterial measurements.

Main Results:

• The pairwise correlation approach for IDIFs demonstrated good agreement (approximately 3% difference) with traditional arterial measurements for distribution volumes (VT).
• The novel IDIF method performed comparably or superiorly to previously published methods.
• The method shows promise for applied clinical studies.

Conclusions:

• The developed non-invasive, image-derived input function method using pairwise voxel correlation is a viable alternative to invasive arterial measurements.
• This approach facilitates accurate PET data quantification, especially in scenarios without reference regions.
• Further validation with diverse radioligands is recommended for broader clinical adoption.