An Algorithmic Approach to the Interpretation of Diffuse Lung Disease on Chest CT Imaging: A Theory of Almost Everything

Abstract

We propose an algorithmic approach to the interpretation of diffuse lung disease on high-resolution CT. Following an initial review of pertinent lung anatomy, the following steps are included. Step 1: a preliminary review of available chest radiographs, including the "scanogram" obtained at the time of the CT examination. Step 2: a review of optimal methods of data acquisition and reconstruction, emphasizing the need for contiguous high-resolution images throughout the entire thorax. Step 3: initial uninterrupted scrolling of contiguous high-resolution images throughout the chest to establish the quality of examination as well as an overview of the presence and extent of disease. Step 4: determination of one of three predominant categories - primarily reticular disease, nodular disease, or diseases associated with diffuse alteration in lung density. Based on this determination, one of the three following Steps are followed: Step 5: evaluation of cases primarily involving diffuse lung reticulation; Step 6: evaluation of cases primarily resulting in diffuse lung nodules; and Step 7: evaluation of cases with diffuse alterations in lung density including those with diffusely diminished lung density vs those with heterogenous or diffusely increased lung density, respectively. It is anticipated that this algorithmic approach will substantially enhance initial interpretations of a wide range of pulmonary disease.

Keywords: CT imaging; crazy paving; fibrotic lung disease; halo sign; lung nodules; mosaic attenuation.