Purpose: High-resolution chest computed tomography (HRCT) is essential in the characterization of interstitial lung disease. The HRCT features of some diseases can be diagnostic. Longitudinal monitoring with HRCT can assess progression of interstitial lung disease; however, subtle changes in the volume and character of abnormalities can be difficult to assess. Accuracy of diagnosis can be dependent on expertise and experience of the radiologist, pathologist, or clinician. Quantitative analysis of thoracic HRCT has the potential to determine the extent of disease reproducibly, classify the types of abnormalities, and automate the diagnostic process. Materials and Methods: Novel software that utilizes histogram signatures to characterize pulmonary parenchyma was used to analyze chest HRCT data, including retrospective processing of clinical CT scans and research data from the Lung Tissue Research Consortium. Additional information including physiological, pathologic, and semiquantitative radiologist assessment was available to allow comparison of quantitative results, with visual estimates of the disease, physiological parameters, and measures of disease outcome. Results: Quantitative analysis results were provided in regional volumetric quantities for statistical analysis and a graphical representation. These results suggest that quantitative HRCT analysis can serve as a biomarker with physiological, pathologic, and prognostic significance. Conclusions: It is likely that quantitative analysis of HRCT can be used in clinical practice as a means to aid in identifying a probable diagnosis, stratifying prognosis in early disease, and consistently determining progression of the disease or response to therapy. Further optimization of quantitative techniques and longitudinal analysis of well-characterized subjects would be helpful in validating these methods.

Although usual interstitial pneumonia (UIP) appears to portend better survival when associated with connective tissue disease (CTD-UIP), little is known about the presenting clinical, radiologic, and pathologic features that differentiate pathologically confirmed UIP with CTD from idiopathic pulmonary fibrosis (IPF). In patients with atypical radiologic and clinical features, what specific findings predict underlying IPF vs. CTD-UIP diagnosis and their respective long term survival? A large retrospective cohort analysis was done of consecutive patients seen from 1995 through 2010 with biopsy confirmed UIP completed or reviewed at our institution. CTD-UIP was defined by independent rheumatology consultation with exclusion of all other secondary causes of lung fibrosis. Primary clinical data was collected and compared for IPF and CTD-UIP along with logistic regression performed for predictors of disease likelihood and Cox proportional hazards analysis for predictors of survival. Six hundred and twenty five patients were included in the study of which 89 had diagnosed CTD-UIP representing 7 disease entities. Survival was better among those with CTD-UIP except in UIP associated with rheumatoid arthritis, which had similar presenting features and survival to IPF. Predictors of underlying CTD included female gender, younger age, positive autoimmune serology, and inconsistent presenting radiologic findings. Only age and forced vital capacity corrected for a priori covariates were predictive of survival in CTD-UIP. UIP pathology occurs frequently among patients with atypically presenting clinical and radiologic features, and may represent IPF or CTD-UIP with improved prognosis if underlying CTD is diagnosed. Presenting radiologic and pathologic features alone are not predictive of underlying secondary cause or survival between the two groups.