title: Automated quantification of radiological patterns predicts survival in idiopathic pulmonary fibrosis.
abstract: Accurate assessment of prognosis in idiopathic pulmonary fibrosis remains elusive due to significant individual radiological and physiological variability. We hypothesised that short-term radiological changes may be predictive of survival. We explored the use of CALIPER (Computer-Aided Lung Informatics for Pathology Evaluation and Rating), a novel software tool developed by the Biomedical Imaging Resource Laboratory at the Mayo Clinic Rochester (Rochester, MN, USA) for the analysis and quantification of parenchymal lung abnormalities on high-resolution computed tomography. We assessed baseline and follow-up (time-points 1 and 2, respectively) high-resolution computed tomography scans in 55 selected idiopathic pulmonary fibrosis patients and correlated CALIPER-quantified measurements with expert radiologists' assessments and clinical outcomes. Findings of interval change (mean 289 days) in volume of reticular densities (hazard ratio 1.91, p=0.006), total volume of interstitial abnormalities (hazard ratio 1.70, p=0.003) and per cent total interstitial abnormalities (hazard ratio 1.52, p=0.017) as quantified by CALIPER were predictive of survival after a median follow-up of 2.4 years. Radiologist interpretation of short-term global interstitial lung disease progression, but not specific radiological features, was also predictive of mortality. These data demonstrate the feasibility of quantifying interval short-term changes on high-resolution computed tomography and their possible use as independent predictors of survival in idiopathic pulmonary fibrosis.
authors.affiliation: Mayo Clinic Rochester, Rochester, MN.
authors.forename: Fabien
authors.initials: F
authors.lastname: Maldonado
authors.forename: Teng
authors.initials: T
authors.lastname: Moua
authors.forename: Srinivasan
authors.initials: S
authors.lastname: Rajagopalan
authors.forename: Ronald A
authors.initials: RA
authors.lastname: Karwoski
authors.forename: Sushravya
authors.initials: S
authors.lastname: Raghunath
authors.forename: Paul A
authors.initials: PA
authors.lastname: Decker
authors.forename: Thomas E
authors.initials: TE
authors.lastname: Hartman
authors.forename: Brian J
authors.initials: BJ
authors.lastname: Bartholmai
authors.forename: Richard A
authors.initials: RA
authors.lastname: Robb
authors.forename: Jay H
authors.initials: JH
authors.lastname: Ryu
mesh_terms: D000368:Aged; D018450:Disease Progression; D005260:Female; D006801:Humans; D054990:Idiopathic Pulmonary Fibrosis / Q000000981:diagnostic imaging* / Q000401:mortality; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008168:Lung / Q000000981:diagnostic imaging*; D008297:Male; D010363:Pattern Recognition, Automated / Q000379:methods*; D011379:Prognosis; D016016:Proportional Hazards Models; D013147:Spirometry; D014057:Tomography, X-Ray Computed