Image-derived arterial input function for quantitative fluorescence imaging of receptor-drug binding in vivo

Area of Science:

• Biomedical Imaging
• Molecular Imaging
• Neurosurgery

Background:

• Receptor concentration imaging (RCI) allows in vivo immunohistochemistry in preclinical models.
• RCI's application in fluorescence-guided resection (FGR) for in situ quantitative molecular imaging is highly impactful.
• Limitations for RCI in human neurosurgery include pharmacokinetic assumptions and lack of a reference region.

Purpose of the Study:

• To present an arterial input graphic analysis (AIGA) method enabled by independent component analysis (ICA).
• To validate the AIGA method for accurate receptor concentration and distribution volume mapping.
• To demonstrate the first reported receptor concentration and distribution volume maps during open craniotomy in a rat glioblastoma model.

Main Methods:

• Developed and applied an arterial input graphic analysis (AIGA) method.
• Utilized independent component analysis (ICA) to derive an image-based arterial input function (AIFICA).
• Validated AIGA against invasive arterial input function measurements in mice and applied it in a rat orthotopic glioblastoma model.

Main Results:

• The AIGA method showed a low percent difference (2.0 ± 2.7%) compared to invasive measurements in mice.
• Distribution volume and receptor concentration estimates using AIGA did not significantly differ from invasive methods (p = 0.12).
• Generated the first receptor concentration and distribution volume maps during open craniotomy in a rat glioblastoma model.

Conclusions:

• The AIGA method, using ICA, provides accurate, non-invasive arterial input function estimation for RCI.
• This technique overcomes limitations of previous RCI methods, enabling quantitative molecular imaging in human neurosurgery.
• The study demonstrates the potential of AIGA for real-time receptor mapping during glioblastoma surgery.