Purpose
High-Resolution chest CT (HRCT) is essential in the characterization of interstitial lung disease (ILD). The HRCT features of some diseases can be diagnostic. Longitudinal monitoring with HRCT can assess progression of ILD; 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 interrogate chest HRCT data, including retrospective processing of clinical CT scans and research data from the Lung Tissue Research Consortium (LTRC). Additional information including physiologic, pathologic and semi-quantitative radiologist assessment was available to allowcomparison of quantitative results with visual estimates of disease, physiologic parameters and measures of disease outcome.
Results
Quantitative analysis results were provided in regional volumetric quantities for statistical analysis as well as a graphical representation. Analysis suggests that quantitative HRCT analysis can serve as a biomarker with physiologic, pathologic and prognostic significance.
Conclusion
It is likely that quantitative analysis of HRCT can be used in clinical practice as a means to aid in identifying probable diagnosis, stratifying prognosis in early disease, and consistently determining progression of disease or response to therapy. Further optimization of quantitative techniques and longitudinal analysis of well-characterized subjects would be helpful to validate these methods.