Quantifying pulmonary perfusion from noncontrast computed tomography.

Area of Science:

• Medical Imaging
• Radiology
• Pulmonary Medicine

Background:

• Computed tomography (CT) ventilation methods use volume changes as a proxy for ventilation.
• Currently, no noncontrast CT methods exist to derive pulmonary perfusion information.
• Dynamic CT imaging offers potential for novel physiological measurements.

Purpose of the Study:

• Introduce a novel CT-Perfusion (CT-P) method to quantify pulmonary perfusion.
• Utilize magnitude mass changes on dynamic noncontrast CT as a surrogate for perfusion.
• Validate CT-P by comparing its results with single photon emission CT perfusion (SPECT-P).

Main Methods:

• CT-Perfusion is based on a mass conservation model using inhale/exhale CT densities.
• Requires deformable image registration, lung segmentation, and Jacobian estimation.
• Assessed spatial Spearman correlation between CT-P and SPECT-P in pulmonary embolism and lung cancer patient cohorts.

Main Results:

• Median correlations between CT-P and SPECT-P ranged from 0.49 to 0.57 across parameter sweeps.
• Optimal tolerance (τ=0.0385) yielded correlations between 0.02 and 0.82.
• Statistically significant correlations were observed in both pulmonary embolism (median 0.57) and lung cancer (median 0.57) cohorts.

Conclusions:

• CT-Perfusion is the first mechanistic model for quantifying pulmonary perfusion using dynamic noncontrast CT.
• The method demonstrates promising correlations with SPECT-P.
• Further research is needed to optimize CT acquisition protocols and numerical implementations for CT-P imaging.