Lobar Ventilation Heterogeneity in Asthma and Cystic Fibrosis Assessed with Hyperpolarized Helium-3 MRI and Computed Tomography
Wei Zha1, Jeffery N Kammerman1, David G Mummy2, Alfonso Rodriguez1, Robert V Cadman1, Scott K Nagle1,3,4, Ronald L Sorkness4,5,6, and Sean B Fain1,2,3

1Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, 2Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, United States, 3Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States, 4Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, United States, 5Medicine-Allergy, Pulmonary & Critical Care, University of Wisconsin-Madison, Madison, WI, United States, 6Pharmacy, University of Wisconsin-Madison, Madison, WI, United States

Synopsis

Seven cystic fibrosis (CF) and 69 asthma subjects with different severities of disease underwent hyperpolarized helium-3 MRI and multidetector computed tomography (MDCT). Lobar segmentation was performed on proton MRI by referencing corresponding MDCT. The lobar ventilation defect percent (VDP) was measured by adaptive K-means. Pairwise comparison showed that lobar VDP variation patterns were different in CF vs. asthma, although patterns were similar in severe vs. non-severe asthma. Disease-related lobar VDP variation patterns may provide a sensitive indicator for early detection and patterns of progression in obstructive lung disease.

Purpose

To quantify and compare patterns of ventilation heterogeneity between lung lobes in asthma vs. cystic fibrosis (CF) using hyperpolarized helium-3 (HP 3He) MRI and multidetector computed tomography (MDCT).

Methods

Seven cystic fibrosis (age: 23±12 years) and 69 asthma subjects with different severities (non-severe: n = 49, 21±12 years; severe: n = 20, 38±14 years) were enrolled in HIPAA-compliant studies with IRB approval. Each subject underwent HP 3He MRI at 1.5T (Signa HDx, GE Healthcare, Milwaukee WI) and MDCT (VCT, GE Medical Systems, Milwaukee, WI) less than 72 hours apart. The 3He scan used a fast 2D multislice gradient-echo sequence with the following parameters: TR/TE = 7.8/4.2 ms; flip angle = 7º; acquisition matrix = 128 × 128; slice thickness = 10 mm for CF and 15 mm for asthma. Proton MRI was performed prior to the 3He scan using a 2D single-shot multislice fast spin echo sequence under equivalent breath-hold conditions (functional residual capacity + ~1L) with acquisition matrix, field of view, slice thickness, and position matching the 3He scan. MDCT was acquired at full inspiration and reconstructed for quantitative measurement at nearly isotropic voxel size with slice thickness = 0.6 mm.

The right and left lungs were segmented on proton MRI using a region-growing method written in MATLAB (MathWorks, Natick, MA). The lung lobes (right upper–RUL, middle–RML and lower–RLL; left upper–LUL and lower–LLL) were segmented manually by drawing the fissure lines on the proton image while referring to the anatomically-matched CT slice.1 The proton image was registered to the 3He image using 3D affine registration by Advanced Normalization Tools.2 The adaptive K-means method3 was used to measure ventilation defect percent (VDP) by lung lobe.

A linear mixed-effects model was used to perform pairwise comparison of VDP among lobes within each subject group. A p < 0.05 was considered significant.

Results

The examples of segmented defects in color-coded lobes (Fig.1) show typical results, with larger focal defects in CF compared to asthma. Although the lungs with severe asthma have larger defects than non-severe asthma, all asthma cases yield similar variation patterns in VDP among the lobes (Fig.2) with RML more affected than RLL, LUL, and LLL with all p < 0.04 (Table 1). In CF subjects, the RUL was most affected (all p < 0.02), with upper lobes generally more defected than lower lobes.

Discussion

The sources of airway obstruction in CF and asthma are known to differ. Obstruction in asthma is thought to be due to a combination of central airway remodeling and small-airway inflammation, while CF is thought to be dominated by central airway obstruction due to mucus plugging. Consistent with the variations in VDP, the airway tree segmented on MDCT using VIDA (VIDA Diagnostics v2.0, Coralville, IA) demonstrated noticeably more pruning in the RUL of a CF subject relative to a subject with non-severe asthma (Fig.3). However, further quantitative analysis such as airway counts, wall thickness, and lumen area by lobe is needed to associate lobar VDP with local airway obstruction. Using HP gas MRI to assess lobar ventilation heterogeneity in different disease processes may reveal the patterns of disease progression in asthma, CF, and other obstructive lung diseases.

Conclusion

Lobar VDP assessed via a combination of HP 3He and MDCT demonstrates disease-related patterns of heterogeneity that are not reflected in whole-lung VDP measurements. These may serve as more sensitive imaging biomarkers for disease progression or treatment effect in obstructive lung disease.

Acknowledgements

We acknowledge support from GE Healthcare, NIH UL1TR000427, NIH/NHLBI U10 HL109168 (The Severe Asthma Research Program), NIH/NCI 5 T32 CA009206 Radiological Science Training Grant, NIH UL1TR000427, and NIH KL2TR000428.

References

1. Fain S, Gonzalez-Fernandez G, Peterson E, et al. Evaluation of structure-function relationships in asthma using multidetector CT and hyperpolarized He-3 MRI. Acad. Radiol. 2008; 15(6):753-762

2. https://github.com/stnava/ANTs

3. Zha W, Kruger S, Cadman R, et al. An adaptive K-means approach for assessment of ventilation defects in asthma and cystic fibrosis using hyperpolarized helium-3 MRI. ISMRM 2015

Figures

Fig.1 Examples of segmented ventilation defect boundaries in lobes (RUL-green, RML-yellow, RLL-cyan, LUL-magenta, LLL-red) for non-severe and severe asthma and CF

Fig.2 Bar graph of ventilation defect percent in lobes for non-severe (blue) and severe (green) asthma and CF (red). Non-severe and severe asthma show similar variation trends among lobes; this trend differs from that observed in CF.

Fig.3 The airway structure automatically segmented from CT scans in VIDA for (a) CF and (b) non-severe asthma. The airway tree in the right upper lobe appears more pruned in the CF subject than in the non-severe asthmatic (white arrows).

Table 1 Pairwise comparison of ventilation defect percent (%) among lobes in severe and non-severe asthma and CF



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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