Quantitative amyloid imaging using image-derived arterial input function.

Area of Science:

• Neuroimaging
• Nuclear Medicine
• Radiochemistry

Background:

• Amyloid PET imaging is crucial for Alzheimer's disease (AD) diagnosis and monitoring.
• Current quantification methods rely on reference regions, which may introduce bias due to unmet assumptions.
• An alternative quantification technique is needed to improve accuracy and reliability.

Purpose of the Study:

• To evaluate an amyloid imaging quantification technique using an arterial region of interest (ROI) as a reference.
• To avoid potential bias caused by specific binding in the reference region.
• To assess the viability of an image-based arterial input function for quantifying amyloid PET data.

Main Methods:

• 21 participants (age ≥58) underwent Pittsburgh Compound B (PiB) PET and MR imaging (including TOF-MRA).
• Arterial input function was estimated from TOF-MRA using a modeling-based technique.
• Regional distribution volume (VT) and distribution volume ratio (DVR) were calculated using Logan analysis and kinetic modeling, compared against a reference region method (cerebellar cortex).

Main Results:

• Excellent agreement was observed between the arterial ROI-based DVR (DVRkinetic) and reference region-based DVR (DVRREF) (r>0.89, ICC>0.80).
• Estimated cerebellum VT aligned with literature values, showing comparable variability to arterial sampling data.
• The image-based arterial input function approach demonstrated viability for quantifying amyloid PET data.

Conclusions:

• Image-based arterial input function is a viable alternative for quantifying amyloid PET data.
• This method eliminates the need for arterial sampling or a reference region, reducing potential bias.
• This technique offers a valuable tool for amyloid imaging, especially in populations where reference normalization may be inaccurate.