Mortality prediction in idiopathic pulmonary fibrosis: evaluation of computer-based CT analysis with conventional severity measures.
Computer-based computed tomography (CT) analysis can provide objective quantitation of disease in idiopathic pulmonary fibrosis (IPF). A computer algorithm, CALIPER, was compared with conventional CT and pulmonary function measures of disease severity for mortality prediction.CT and pulmonary function variables (forced expiratory volume in 1 s, forced vital capacity, diffusion capacity of the lung for carbon monoxide, transfer coefficient of the lung for carbon monoxide and composite physiologic index (CPI)) of 283 consecutive patients with a multidisciplinary diagnosis of IPF were evaluated against mortality. Visual and CALIPER CT features included total extent of interstitial lung disease, honeycombing, reticular pattern, ground glass opacities and emphysema. In addition, CALIPER scored pulmonary vessel volume (PVV) while traction bronchiectasis and consolidation were only scored visually. A combination of mortality predictors was compared with the Gender, Age, Physiology model.On univariate analyses, all visual and CALIPER-derived interstitial features and functional indices were predictive of mortality to a 0.01 level of significance. On multivariate analysis, visual CT parameters were discarded. Independent predictors of mortality were CPI (hazard ratio (95% CI) 1.05 (1.02-1.07), p<0.001) and two CALIPER parameters: PVV (1.23 (1.08-1.40), p=0.001) and honeycombing (1.18 (1.06-1.32), p=0.002). A three-group staging system derived from this model was powerfully predictive of mortality (2.23 (1.85-2.69), p<0.0001).CALIPER-derived parameters, in particular PVV, are more accurate prognostically than traditional visual CT scores. Quantitative tools such as CALIPER have the potential to improve staging systems in IPF.
Dept of Radiology, Royal Brompton Hospital, Royal Brompton and Harefield NHS Foundation Trust, London, UK akelajacob@gmail.com.
Joseph
J
Jacob
Division of Radiology, Mayo Clinic Rochester, Rochester, MN, USA.
Brian J
BJ
Bartholmai
Dept of Physiology and Biomedical Engineering, Mayo Clinic Rochester, Rochester, MN, USA.
Srinivasan
S
Rajagopalan
Interstitial Lung Disease Unit, Royal Brompton Hospital, Royal Brompton and Harefield NHS Foundation Trust, London, UK.
Maria
M
Kokosi
Dept of Radiology, Royal Brompton Hospital, Royal Brompton and Harefield NHS Foundation Trust, London, UK.
Arjun
A
Nair
Dept of Physiology and Biomedical Engineering, Mayo Clinic Rochester, Rochester, MN, USA.
Ronald
R
Karwoski
Dept of Radiology, Royal Brompton Hospital, Royal Brompton and Harefield NHS Foundation Trust, London, UK.
Simon L F
SL
Walsh
Interstitial Lung Disease Unit, Royal Brompton Hospital, Royal Brompton and Harefield NHS Foundation Trust, London, UK.
Athol U
AU
Wells
Dept of Radiology, Royal Brompton Hospital, Royal Brompton and Harefield NHS Foundation Trust, London, UK.
David M
DM
Hansell
D000368:Aged; D000465:Algorithms; D005260:Female; D005541:Forced Expiratory Volume; D006801:Humans; D054990:Idiopathic Pulmonary Fibrosis / Q000000981:diagnostic imaging* / Q000401:mortality* / Q000503:physiopathology*; D053208:Kaplan-Meier Estimate; D008168:Lung / Q000000981:diagnostic imaging* / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D011379:Prognosis; D016016:Proportional Hazards Models; D012189:Retrospective Studies; D012720:Severity of Illness Index; D014057:Tomography, X-Ray Computed; D006113:United Kingdom; D014797:Vital Capacity