Perfusion Imaging: An Advection Diffusion Approach.

Area of Science:

• Medical Imaging
• Biophysics
• Quantitative MRI

Background:

• Perfusion imaging is crucial for diagnosing diseases like stroke and brain tumors.
• Current methods often rely on contrast agents and estimating the arterial input function (AIF), which can be complex and neglect spatial variations.
• Existing contrast-agent-free methods are not yet standard clinical practice.

Purpose of the Study:

• To introduce PIANO, a novel approach for quantitative perfusion imaging.
• To estimate velocity and diffusion fields using an advection-diffusion model without requiring an AIF.
• To provide a method that accounts for spatial dependencies and is independent of contrast agent bolus shape.

Main Methods:

• Developed PIANO, an approach estimating velocity and diffusion fields from perfusion dynamics.
• Employed a convenient parameterization and numerical estimation strategy.
• Validated the method through extensive simulations and application to a public brain MR perfusion dataset of acute stroke patients.

Main Results:

• Simulation experiments demonstrated PIANO's robustness, effectiveness, and ability to differentiate advection from diffusion.
• PIANO successfully resolved ambiguities in velocity and diffusion fields on real patient data.
• The method yielded sensitive measures for stroke assessment, outperforming conventional perfusion metrics.

Conclusions:

• PIANO offers a new AIF-independent method for quantitative perfusion analysis.
• The approach provides valuable insights into perfusion dynamics, accounting for spatial dependencies.
• PIANO shows promise for improved clinical assessment of acute stroke and other perfusion-related diseases.