Abstract
ObjectivesPulmonary perfusion abnormalities are prevalent in patients with chronic obstructive pulmonary disease (COPD), are potentially reversible, and may be associated with emphysema development. Therefore, we aimed to evaluate the clinical meaningfulness of perfusion defects in percent (QDP) using DCE-MRI.MethodsWe investigated a subset of baseline DCE-MRIs, paired inspiratory/expiratory CTs, and pulmonary function testing (PFT) of 83 subjects (age = 65.7 ± 9.0 years, patients-at-risk, and all GOLD groups) from one center of the “COSYCONET” COPD cohort. QDP was computed from DCE-MRI using an in-house developed quantification pipeline, including four different approaches: Otsu’s method, k-means clustering, texture analysis, and 80th percentile threshold. QDP was compared with visual MRI perfusion scoring, CT parametric response mapping (PRM) indices of emphysema (PRMEmph) and functional small airway disease (PRMfSAD), and FEV1/FVC from PFT.ResultsAll QDP approaches showed high correlations with the MRI perfusion score (r = 0.67 to 0.72, p < 0.001), with the highest association based on Otsu’s method (r = 0.72, p < 0.001). QDP correlated significantly with all PRM indices (p < 0.001), with the strongest correlations with PRMEmph (r = 0.70 to 0.75, p < 0.001). QDP was distinctly higher than PRMEmph (mean difference = 35.85 to 40.40) and PRMfSAD (mean difference = 15.12 to 19.68), but in close agreement when combining both PRM indices (mean difference = 1.47 to 6.03) for all QDP approaches. QDP correlated moderately with FEV1/FVC (r = − 0.54 to − 0.41, p < 0.001).ConclusionQDP is associated with established markers of disease severity and the extent corresponds to the CT-derived combined extent of PRMEmph and PRMfSAD. We propose to use QDP based on Otsu’s method for future clinical studies in COPD.Key Points• QDP quantified from DCE-MRI is associated with visual MRI perfusion score, CT PRM indices, and PFT.• The extent of QDP from DCE-MRI corresponds to the combined extent of PRMEmph and PRMfSAD from CT.• Assessing pulmonary perfusion abnormalities using DCE-MRI with QDP improved the correlations with CT PRM indices and PFT compared to the quantification of pulmonary blood flow and volume.
Highlights
chronic obstructive pulmonary disease (COPD) is characterized by progressive airflow limitation caused by airway obstruction and emphysematous lung destruction
Arterial input functions (AIFs) Arterial input function ANOVA One-way analysis of variance contrast agent (CA) Contrast agent CCA Cross-correlation analysis COPD Chronic obstructive pulmonary disease DCE-MRI Dynamic contrast-enhanced magnetic resonance imaging FD Fourier decomposition FEV1%predicted Forced expiratory volume in 1 s percent predicted FEV1/FVC Ratio between forced expiratory volume in 1 s and forced vital capacity functional small airways disease (fSAD) Functional small airways disease hypoxic pulmonary vasoconstriction (HPV) Hypoxic pulmonary vasoconstriction pulmonary blood flow (PBF) Pulmonary blood flow pulmonary blood volume (PBV) Pulmonary blood volume pulmonary function testing (PFT) Pulmonary function testing parametric response mapping (PRM) Parametric response mapping QDP Perfusion defects in percent Rmax map Residue function map at the time point of maximum contrast enhancement R(t) map Time-resolved residue function map COPD is characterized by progressive airflow limitation caused by airway obstruction and emphysematous lung destruction
We developed new methods to quantify QDP using DCEMRI, which combine the advantages of unsupervised image clustering algorithms and mathematical models of tracer kinetics
Summary
COPD is characterized by progressive airflow limitation caused by airway obstruction and emphysematous lung destruction. The alveolar-capillary bed and pulmonary vessels are obliterated by emphysematous destruction Both processes, HPV and the loss of lung capillaries, become apparent on functional imaging as regional perfusion abnormalities. Perfusion abnormalities using DCE-MRI are assessed either by visual scoring systems or by computational methods for quantitative evaluation [1, 2]. The use of semi-quantitative scoring systems to monitor treatment effects on pulmonary perfusion might be challenging in early clinical studies designed to test treatments that slow emphysema progression. Due to the relatively slow disease progression in COPD and the short follow-up-intervals (up to 3 months) in early clinical studies, only relatively subtle changes in pulmonary perfusion are expected in such settings, which may remain undetected by scoring systems [3]
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