Robert P Thomen1, Laura L Walkup1, David J Roach1, Zackary I Cleveland1, John Paul Clancy2, and Jason C Woods1
1Center for Pulmonary Imaging Research, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States, 2Pulmonology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
Synopsis
We have quantified the extent of ventilation impairment in lungs due to
specific pathologies associated with cystic fibrosis (CF) lung disease using ultrashort
echo-time (UTE) MRI to identify structural abnormalities and hyperpolarized
(HP) 129Xe MRI to identify ventilation deficits. We found that bronchiectasis
demonstrates the best correlation with lung function decline, as measured by
the percent predicted forced expiratory volume in 1 second (FEV1%
predicted) and demonstrated the greatest deficit in HP 129Xe signal
within corresponding defective regions. However, the greatest volume-percentage
of defects identified were due to mucus plugging.
Introduction
Recent advances in ultra-short echo (UTE) techniques have made MRI rival
the resolution and diagnostic quality of x-ray CT1, with regional identification of specific cystic
fibrosis (CF) pathologies, like mucus plugging and bronchiectasis2. Likewise, hyperpolarized (HP) gas MRI of lung
has demonstrated the ability to quantify regional ventilation in lungs with sensitivity
higher than clinically-accepted spirometric techniques3,4. However, a gap
exists in relating regional structural abnormalities to functional deficits. The
purpose of our study was to bridge this gap by identifying specific CF
pathologies via UTE MRI and to relate those structural abnormalities to regional
function, via HP 129Xe MRI. These pulmonary structure-function
relationships may aid in development of regionally-targeted and/or
pathology-specific treatments of CF lung disease, and would be useful in
longitudinal studies to understand disease progression.Methods
Eleven
pediatric CF patients (ages 11.5 ± 2.5, range 7-16) were recruited for this
study. Each subject underwent a free-breathing UTE MRI scan (gated acquisition
at end expiration using an image navigator; FA=5°, TR/TE=5.8ms/0.2ms, voxel size=1.39×1.39×4mm3) and a single-breath HP 129Xe
MRI scan within the same imaging session (inspiration=1/6 total lung capacity,
from functional residual capacity; FA=9-14°; TR/TE=8ms/4ms; matrix=52-96×96-144;
voxel=3×3×15 mm3; duration <16s). The HP 129Xe images
were analyzed for regions of defective ventilation (defined as voxel signal
<60% of the whole-lung signal mean) and quantified as a ventilation defect
percentage (VDP). Using this threshold to define defects, the mean HP 129Xe
signal contained within each defect was also quantified. HP 129Xe
images were then regionally matched to UTE images in order to identify the
following structural pathologies potentially responsible for obstructed
ventilation: bronchiectasis, mucus plugging, bronchial wall thickening, ground
glass opacities, air trapping, and/or consolidation (Figure 1). Defects with no
apparent corresponding pathology were also quantified. The number and volume
percentage of specific defects attributable to each pathology is reported as
well as the average HP 129Xe signal contained within pathology-specific
regions. Whole-lung VDP and patient FEV1% predicted (forced
expiratory volume in 1 second) were also compared.Results
The mean VDP for all subjects was 19.0%±7.3% and mean FEV1%
predicted was 88.0%±15.8% (Pearson correlation r=-0.32, p=0.33). Of all
identified defect regions, 49.7% were attributable to pathology seen in UTE MR
images. Of all attributed pathologies, bronchiectasis was found to correspond
to the lowest average HP 129Xe signal (26.2%±7.8%, expressed as
percentage of lung signal mean), and mucus plugging was responsible for the
greatest number of identified defects (patient mean 5.3±3.8, out of 7.9±5.0
total defects). Individual statistics for each pathology are given in Figure 2. Around
half of the defects identified were not associated with a specific pathology. Defect
percentage due to bronchiectasis was found to correlate best with patient FEV1%
predicted decline (r=-0.34, p=0.31) and was comparable to the correlation
between FEV1% predicted and whole-lung VDP (r=-0.32, p=0.33). Regions
of the lung which did not exhibit ventilation defects averaged 118%±9% of the
whole-lung mean HP 129Xe signal.Discussion
This
method provides an avenue for identification of individual structural
abnormalities that are responsible for regional ventilation deficits. UTE MRI was able to visualize all of the
typical CF-specific structural abnormalities, yet only half of the identified
defects were attributable to identified pathology, potentially due to finite
image resolution. In early CF lung disease, bronchiectasis correlated best with
clinical lung function decline as indicated by VPD and FEV1%
predicted, and defects associated with bronchiectasis demonstrated the lowest 129Xe
signal. While mucus plugging was responsible for the greatest number and volume
of defects, individual defects caused by bronchiectasis were much larger in
size and correlated better with lung function decline. Notably, bronchiectasis
is generally considered permanent lung remodeling, while mucus plugging is
potentially reversible through treatment.Conclusions
Quantifying the extent of lung function decline due to specific
structural pathologies in CF lung disease is feasible using UTE MRI and HP 129Xe
MRI. In these 11 subjects, bronchiectasis correlated best with spirometrically
measured obstruction, and mucus plugging was responsible for the largest number
and volume of attributed defects.Acknowledgements
No acknowledgement found.References
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