Characterizing pulmonary blood flow distribution measured using arterial spin labeling

Area of Science:

• Medical Imaging
• Physiology
• Biophysics

Background:

• Arterial spin labeling (ASL) quantifies local perfusion, ideally with signal intensity proportional to blood flow.
• Pulmonary perfusion studies often use relative dispersion (RD) to assess flow heterogeneity.
• RD may be skewed by signals from larger vessels, reflecting blood volume rather than flow.

Purpose of the Study:

• To evaluate if ASL signals for pulmonary blood flow follow a lognormal distribution.
• To determine the influence of larger vessels on this distribution.
• To extract physiologically relevant heterogeneity measures from ASL signals.

Main Methods:

• Quantified ASL signal in six subjects before and after a head-down tilt intervention.
• Compared normal and lognormal distribution fits to ASL signal data.
• Analyzed relative dispersion (RD) and geometric standard deviation (GSD) of ASL signals.

Main Results:

• ASL signal distribution was better characterized by a lognormal model (72% MSE reduction, p < 0.005).
• Head-down tilt reduced the lognormal scale parameter (p = 0.01) but not GSD.
• RD increased significantly post-tilt (17%, p < 0.05), while GSD did not change significantly.

Conclusions:

• Pulmonary blood flow ASL signals are better described by a lognormal distribution.
• Geometric standard deviation (GSD) is a robust measure of pulmonary perfusion heterogeneity.
• GSD is less susceptible to artifacts from larger vessels compared to RD.