New method for 3D parametric visualization of contrast-enhanced pulmonary perfusion MRI data

Area of Science:

• Medical Imaging
• Radiology
• Pulmonary Medicine

Background:

• Three-dimensional dynamic contrast-enhanced magnetic resonance imaging (3D DCE-MRI) is a promising technique for assessing regional lung perfusion.
• Accurate visualization of perfusion parameters is crucial for diagnosing and managing lung diseases.

Purpose of the Study:

• To implement and evaluate a 3D parametric visualization algorithm for lung perfusion using 3D DCE-MRI data.
• To assess the feasibility of using different cutting planes and volume rendering for visualizing lung perfusion.
• To compare interpolation methods for improving spatial resolution in perfusion parameter maps.

Main Methods:

• The study utilized 3D DCE-MRI data from five patients and five healthy volunteers.
• Indicator dilution theory was applied to calculate regional perfusion parameters: tissue blood flow, blood volume, and mean transit time.
• Linear interpolation and a combined linear/nearest-neighbor interpolation were evaluated for volumetric data, followed by ray tracing for 3D visualization.

Main Results:

• The combined interpolation method effectively addressed spatial resolution limitations in the z-direction, unlike linear interpolation which caused errors at lung borders.
• The algorithm enabled visualization of lung perfusion parameters in arbitrary cutting planes and through 3D volume rendering.
• This 3D visualization facilitated better localization of perfusion deficits compared to standard coronal views.

Conclusions:

• A 3D visualization algorithm using a combined interpolation method is feasible for displaying lung perfusion parameters derived from 3D DCE-MRI.
• The developed technique enhances the localization of perfusion deficits.
• Further research is needed to determine the clinical utility and added benefits of 3D lung perfusion visualization.