Clinical Personal Connectomics Using Hybrid PET/MRI

Area of Science:

• Neuroscience
• Medical Imaging
• Network Science

Background:

• Traditional brain connectivity analysis often relies on arbitrary thresholding, creating binary graphs that limit comparative studies between different groups.
• Resting-state functional MRI (fMRI) provides individual interregional brain connectivity based on perfusion signals.
• Fluorodeoxyglucose Positron Emission Tomography (FDG PET) visualizes glucose metabolism topography.

Purpose of the Study:

• To explore the potential relationship between brain metabolism topography (FDG PET) and brain connectivity (resting-state fMRI) for creating personalized connectomics.
• To review the plausibility of using hybrid PET/MRI techniques for interpreting personal connectomics.
• To discuss the future clinical applications of brain connectivity analysis.

Main Methods:

• Utilizing topological analysis with persistent homology to study brain connectivity, overcoming the limitations of thresholding.
• Integrating data from resting-state fMRI and FDG PET, assuming a coupling between metabolism and perfusion.
• Reviewing the statistical frameworks for group comparisons of connectivity derived from FDG PET and resting-state MRI.

Main Results:

• Persistent homology provides a robust method for analyzing brain connectivity without arbitrary thresholding.
• The integration of FDG PET and resting-state fMRI holds promise for developing personalized connectomics.
• Statistical methods for group comparisons of connectivity are established, paving the way for further analysis.

Conclusions:

• Hybrid PET/MRI approaches could enable the interpretation of personal connectomics.
• The development of personal connectomics has the potential for significant clinical applications in the near future.
• Further research is warranted to establish the association between FDG PET and resting-state fMRI for connectomics.