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Objectives: To test HRCT with either visual or quantitative analysis in both short-term and long-term follow-up of stable IPF against long-term (transplant-free) survival, beyond 2 years of disease stability., Methods: Fifty-eight IPF patients had FVC measurements and HRCTs at baseline (HRCT0), 10-14 months (HRCT1) and 22-26 months (HRCT2). Visual scoring, CALIPER quantitative analysis of HRCT measures, and their deltas were evaluated against combined all-cause mortality and lung transplantation by adjusted Cox proportional hazard models at each time interval., Results: At HRCT1, a ≥ 20% relative increase in CALIPER-total lung fibrosis yielded the highest radiological association with outcome (C-statistic 0.62). Moreover, the model combining FVC% drop ≥ 10% and ≥ 20% relative increase of CALIPER-total lung fibrosis improved the stratification of outcome (C-statistic 0.69, high-risk category HR 12.1; landmark analysis at HRCT1 C-statistic 0.66, HR 14.9 and at HRCT2 C-statistic 0.61, HR 21.8). Likewise, at HRCT2, the model combining FVC% decrease trend and ≥ 20% relative increase of CALIPER-pulmonary vessel-related volume (VRS) improved the stratification of outcome (C-statistic 0.65, HR 11.0; landmark analysis at HRCT1 C-statistic 0.62, HR 13.8 and at HRCT2 C-statistic 0.58, HR 12.6). A less robust stratification of outcome distinction was also demonstrated with the categorical visual scoring of disease change., Conclusions: Annual combined CALIPER -FVC changes showed the greatest stratification of long-term outcome in stable IPF patients, beyond 2 years., Key Points: • Longitudinal high-resolution computed tomography (HRCT) data is more helpful than baseline HRCT alone for stratification of long-term outcome in IPF. • HRCT changes by visual or quantitative analysis can be added with benefit to the current spirometric reference standard to improve stratification of long-term outcome in IPF. • HRCT follow-up at 12-14 months is more helpful than HRCT follow-up at 23-26 months in clinically stable subjects with IPF.

Objectives: To determine whether computer-based CT quantitation of change can improve on visual change quantification of parenchymal features in IPF., Methods: Sixty-six IPF patients with serial CT imaging (6-24 months apart) had CT features scored visually and with a computer software tool: ground glass opacity, reticulation and honeycombing (all three variables summed as interstitial lung disease extent [ILD]) and emphysema. Pulmonary vessel volume (PVV) was estimated by computer only. Relationships between changes in CT features and forced vital capacity (FVC) were examined using univariate and multivariate linear regression analyses., Results: On univariate analysis, changes in computer variables demonstrated stronger linkages to FVC change than changes in visual scores (CALIPER ILD:R 2 =0.53, p<0.0001; Visual ILD:R 2 =0.16, p=0.001). PVV increase correlated most strongly with relative FVC change (R 2 =0.57). When PVV constituents (vessel size and location) were examined, an increase in middle zone vessels linked most strongly to FVC decline (R 2 =0.57) and was independent of baseline disease severity (characterised by CT fibrosis extent, FVC, or DLco)., Conclusions: An increase in PVV, specifically an increase in middle zone lung vessels, was the strongest CT determinant of FVC decline in IPF and was independent of baseline disease severity., Key Points: • Computer analysis improves on visual CT scoring in evaluating deterioration on CT • Increasing pulmonary vessel volume is the strongest CT predictor of functional deterioration • Increasing pulmonary vessel volume predicts functional decline independent of baseline disease severity.

Background: Hypersensitivity pneumonitis (HP) has a variable clinical course. Modelling of quantitative CALIPER-derived CT data can identify distinct disease phenotypes. Mortality prediction using CALIPER analysis was compared to the interstitial lung disease gender, age, physiology (ILD-GAP) outcome model., Methods: CALIPER CT analysis of parenchymal patterns in 98 consecutive HP patients was compared to visual CT scoring by two radiologists. Functional indices including forced vital capacity (FVC) and diffusion capacity for carbon monoxide (DLco) in univariate and multivariate Cox mortality models. Automated stratification of CALIPER scores was evaluated against outcome models., Results: Univariate predictors of mortality included visual and CALIPER CT fibrotic patterns, and all functional indices. Multivariate analyses identified only two independent predictors of mortality: CALIPER reticular pattern (p = 0.001) and DLco (p < 0.0001). Automated stratification distinguished three distinct HP groups (log-rank test p < 0.0001). Substitution of automated stratified groups for FVC and DLco in the ILD-GAP model demonstrated no loss of model strength (C-Index = 0.73 for both models). Model strength improved when automated stratified groups were combined with the ILD-GAP model (C-Index = 0.77)., Conclusions: CALIPER-derived variables are the strongest CT predictors of mortality in HP. Automated CT stratification is equivalent to functional indices in the ILD-GAP model for predicting outcome in HP., Key Points: • Computer CT analysis better predicts mortality than visual CT analysis in HP. • Quantitative CT analysis is equivalent to functional indices for prognostication in HP. • Prognostication using the ILD-GAP model improves when combined with quantitative CT analysis.