title: MDCT assessment of airway wall thickness in COPD patients using a new method: correlations with pulmonary function tests.
abstract: Quantitative assessment of airway-wall dimensions by computed tomography (CT) has proven to be a marker of airway-wall remodelling in chronic obstructive pulmonary disease (COPD) patients. The objective was to correlate the wall thickness of large and small airways with functional parameters of airflow obstruction in COPD patients on multi-detector (MD) CT images using a new quantification procedure from a three-dimensional (3D) approach of the bronchial tree. In 31 patients (smokers/COPD, non-smokers/controls), we quantitatively assessed contiguous MDCT cross-sections reconstructed orthogonally along the airway axis, taking the point-spread function into account to circumvent over-estimation. Wall thickness and wall percentage were measured and the per-patient mean/median correlated with FEV1 and FEV1%. A median of 619 orthogonal airway locations was assessed per patient. Mean wall percentage/mean wall thickness/median wall thickness in non-smokers (29.6%/0.69 mm/0.37 mm) was significantly different from the COPD group (38.9%/0.83 mm/0.54 mm). Correlation coefficients (r) between FEV1 or FEV1% predicted and intra-individual means of the wall percentage were -0.569 and -0.560, respectively, with p < 0.001. Depending on the parameter, they were increased for airways of 4 mm and smaller in total diameter, being -0.621 (FEV1) and -0.537 (FEV1%) with p < 0.002. The wall thickness was significantly higher in smokers than in non-smokers. In COPD patients, the wall thickness measured as a mean for a given patient correlated with the values of FEV1 and FEV1% predicted. Correlation with FEV1 was higher when only small airways were considered.
authors.affiliation: Department of Diagnostic and Interventional Radiology, Johannes Gutenberg University, Langenbeckstrasse 1, 55101, Mainz, Germany. achenbac@uni-mainz.de
authors.forename: Tobias
authors.initials: T
authors.lastname: Achenbach
authors.forename: Oliver
authors.initials: O
authors.lastname: Weinheimer
authors.forename: Alexander
authors.initials: A
authors.lastname: Biedermann
authors.forename: Sabine
authors.initials: S
authors.lastname: Schmitt
authors.forename: Daniela
authors.initials: D
authors.lastname: Freudenstein
authors.forename: Edula
authors.initials: E
authors.lastname: Goutham
authors.forename: Richard Peter
authors.initials: RP
authors.lastname: Kunz
authors.forename: Roland
authors.initials: R
authors.lastname: Buhl
authors.forename: Christoph
authors.initials: C
authors.lastname: Dueber
authors.forename: Claus Peter
authors.initials: CP
authors.lastname: Heussel
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001185:Artificial Intelligence; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods; D008168:Lung / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D029424:Pulmonary Disease, Chronic Obstructive / Q000175:diagnosis*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012129:Respiratory Function Tests; D012680:Sensitivity and Specificity; D013223:Statistics as Topic; D014057:Tomography, X-Ray Computed / Q000379:methods*