An initial investigation of hyperpolarized gas tagging magnetic resonance imaging in evaluating deformable image registration-based lung ventilation

Abstract

Background: Deformable image registration (DIR)-based lung ventilation mapping is attractive due to its simplicity, and also challenging due to its susceptibility to errors and uncertainties. In this study, we explored the use of 3D Hyperpolarized (HP) gas tagging MRI to evaluate DIR-based lung ventilation.

Method and material: Three healthy volunteers included in this study underwent both 3D HP gas tagging MRI (t-MRI) and 3D proton MRI (p-MRI) using balanced steady-state free precession pulse sequence at end of inhalation and end of exhalation. We first obtained the reference displacement vector fields (DVFs) from the t-MRIs by tracking the motion of each tagging grid between the exhalation and the inhalation phases. Then, we determined DIR-based DVFs from the p-MRIs by registering the images at the two phases with two commercial DIR algorithms. Lung ventilations were calculated from both the reference DVFs and the DIR-based DVFs using the Jacobian method and then compared using cross correlation and mutual information.

Results: The DIR-based lung ventilations calculated using p-MRI varied considerably from the reference lung ventilations based on t-MRI among all three subjects. The lung ventilations generated using Velocity AI were preferable for the better spatial homogeneity and accuracy compared to the ones using MIM, with higher average cross correlation (0.328 vs 0.262) and larger average mutual information (0.528 vs 0.323).

Conclusion: We demonstrated that different DIR algorithms resulted in different lung ventilation maps due to underlining differences in the DVFs. HP gas tagging MRI provides a unique platform for evaluating DIR-based lung ventilation.

Keywords: DIR; MRI; hyperpolarized gas; lung cancer; lung ventilation.

Figure 1

Schematic diagram of the MR image acquisitions. The subjects inhaled 1.5 L hyperpolarized gas, held breath for a few seconds at EOI, then exhaled 0.75 L of gas and held breath for another few seconds at EOE. A HP gas t‐MRI acquisition of 2.2 s duration and a Low‐R (4.5 mm isotropic voxel size) p‐MRI of acquisition of 4.2 s duration were acquired during both EOI and EOE periods. High‐R (2.5 mm isotropic voxel size) p‐MRI acquisitions of 17‐s duration were acquired in a separate breathing cycle with the same 1.5 L inhalation and 0.75 L exhalation volumes. [Color figure can be viewed at wileyonlinelibrary.com]

Figure 2

The overall study design for the evaluation of DIR‐based lung ventilation estimation based on HP gas tagging MRI. [Color figure can be viewed at wileyonlinelibrary.com]

Figure 3

Representative coronal views of the t‐MRI (a, d), the Low‐R p‐MRI (b, e), and the High‐R MRI (c, f) images of Subject 2 inhaling the HP ³He gas at EOI (a, b, c) and EOE (d, e, f), respectively. The images were displayed in the same scale and the same lung heights were measured (indicated by the yellow lines). The FOVs were cropped to only display the lungs. [Color figure can be viewed at wileyonlinelibrary.com]

Figure 4

3D illustrations of the t‐MRI images at EOI (a) and EOE (b). The same intensity threshold was used to display the tagging grids in three dimensions. [Color figure can be viewed at wileyonlinelibrary.com]

Figure 5

Comparison of 3D displacement vector fields generated from the t‐MRI images with manual tracking (red) and the High‐R p‐MRI images with Velocity AI (blue) for subject 2. [Color figure can be viewed at wileyonlinelibrary.com] [Color figure can be viewed at wileyonlinelibrary.com]

Figure 6

Demonstrate of the registration results for subject 2. The deformed moving images with MIM (b) and Velocity AI (c) were compared to the target image (a) using the difference images (d, e). The gray scale in the corresponding difference maps represents the residual errors of each registration at a given voxel. The brighter a voxel is, the larger residual error there is in that voxel.

Figure 7

Comparison of lung ventilations in three orthogonal views for subject 2. [Color figure can be viewed at wileyonlinelibrary.com]

Figure 8

Distributions of three ventilations of each voxel for subject 2. Red solid line represents the distribution of the reference ventilation, t‐VENT, and blue dash line and pink dotted lines represent those of two DIR‐based results, p‐VENT_{V el} and p‐VENT_{MIM ,} respectively. [Color figure can be viewed at wileyonlinelibrary.com]

Figure 9

Joint histograms for t‐VENT vs p‐VENT_{V el} (a) and for t‐VENT vs the p‐VENT_MIM (b) for a representative subject. The horizontal and the vertical axes correspond to the reference ventilation (calculated from t‐DVF) and the DIR‐based ventilations, respectively. The color scale indicates the number of voxels with the given values of p‐VENT and t‐VENT. The white line represents the joint histogram of a perfect correlation between p‐VENT and t‐VENT. [Color figure can be viewed at wileyonlinelibrary.com]