To assess the capability of oxygen-enhanced 3D radial ultrashort echo time (UTE) MRI (OE-MRI) in detecting disease severity of cystic fibrosis (CF) using ventilation defect percent (VDP) from hyperpolarized helium-3 MRI (HP-MRI) as a reference standard.

Eleven (11) CF subjects with various severities were enrolled in HIPPA-compliant studies with IRB approval. Each underwent OE-MRI and HP-MRI scans at 1.5 T (Signa HDx, GE Healthcare, Waukesha, WI).

OE-MRI: The air-breathing (V₀₂₁) and 100% oxygen-breathing (V₁₀₀) UTE images were acquired sequentially with the following scan parameters: 3.2 mm isotropic resolution, FOV = 32x32 cm, TR/TE=2.9/0.08 ms, flip angle = 8°, with an 8-channel cardiac surface coil (GE Healthcare, Waukesha, WI). The total scan time is 9 min consisting of the following intervals: 3.5 min. air-breathing at V₀₂₁, 2 min. wash-in to avoid transient effects, followed by 3.5 min. of 100% O₂-breathing. Real-time gating to end-expiration with a 50% acceptance window was used to minimize respiratory motion and obtain consistent lung inflation. V₀₂₁ and V₁₀₀ images were reconstructed offline at high (0.7 mm³) resolution for anatomy and at 1cm³ using a Fermi filter to improve signal-to-noise ratio for OE MRI.¹

HP-MRI: The 3He scan used a fast 2D multislice gradient-echo sequence with the following parameters: TR/TE = 6.5/2.9 ms; flip angle = 7°; FOV = 40 x 40 cm, slice thickness = 10 mm. Proton MRI was performed prior to the 3He scan using a 2D single-shot multislice fast spin echo sequence under equivalent breath-hold conditions with acquisition matrix, field of view, slice thickness, and position matching the 3He scan.

Analysis: V₀₂₁ and V₁₀₀ images were intensity corrected using the open source N4ITK² and co-registered using ANTs B-spline deformable registration³. Density changes in normoxic vs. hyperoxic breathing were corrected using the adapted slope model.⁴ The corrected V₀₂₁ was given by $$$V_{021C} =T(V_{021})/det(J_{T})^{S}$$$ where $$$S =\frac{log({T(V_{021})})-log(V_{100})}{log(det(J_{T}))}$$$, T is the deformable transformation and det(J_T) represents the Jacobian determinant of the deformation field. The density corrected percent signal enhancement (PSE) was calculated as $$$PSE =(V_{100}-V_{021C})/V_{021C}$$$. A radiologist with seven years of experience blindly and independently ranked the subjects for disease severity from 1 to 11 with 1 being least severe. Proton images were registered to 3He using 3D affine registration by ANTs.⁵ The whole lung VDP was measured by the adaptive K-means method.⁶

Relative severity rankings from OE-MRI and VDP from HP-MRI were compared using Spearman rank correlation in SAS v9.4 (SAS Institute Inc., Cary NC).

Lung volumes measured at V₀₂₁ were consistently larger than at V₁₀₀ (Table 1). An example of unregistered vs. registered and density corrected PSE map demonstrates improved alignment (orange arrow in Figure 1), while the density correction accounted for local parenchymal density changes that influence in perceived O₂ concentration. Regional patterns of ventilation defects were not consistently well matched between HP-MRI and OE-MRI (Figure 2). However, disease severity, determined from OE-MRI alone (Table 2), were positively related to the whole lung VDP values (ρ = 0.62. p = 0.046, 95% confidence interval = [0.015, 0.89]).The consistent bias in lung volumes observed in V₀₂₁ relative to V₁₀₀ reflects the lower density in V₀₂₁. The applied deformable registration and density correction improved the spatial consistency of PSE maps with anatomy in the presence of systematic physiological volume differences. OE-MRI may ultimately have advantages over other functional MRI techniques in its potential for dissemination. Future work will investigate the waveforms from the bellow signal to assess the effect of uneven breathing, and develop a histogram based approach for quantifying regional disease in PSE maps rather than depending strictly on ordinal ranking.OE-MRI shows promise in characterizing disease severity of CF using HP-MRI as a reference standard. Further advancements in data acquisition, post-processing, and analysis will improve the capability of OE-MRI in regional defect assessment in obstructive lung disease.