Diagnostic Schema for Typical Computed Tomography Findings of Diffuse Pulmonary Diseases



Diagnostic Schema for Typical Computed Tomography Findings of Diffuse Pulmonary Diseases






As in an identification guide, differential diagnosis of diffuse parenchymal lung diseases is presented on the basis of typical patterns of findings. This enables rapid orientation and quickly leads to the first suspected diagnosis. However, this overview is not a substitute for complete differential diagnosis tables on the various image patterns.

The differential diagnoses are presented in relation to a main finding. Further differentiation is made via an additionally present second image pattern that is less dominant than the main finding.

First, the main finding must be identified, as illustrated with different color backgrounds in ▶Fig. 24.1. The respective color leads the way to another table that queries the existence of an additional image pattern. This thus often narrows differential diagnosis down to a few diseases; some findings are even pathognomonic.

For nodules, a further differentiation into interstitial and airspace nodules is needed. Deviating from the normal procedure (i.e., an additional image pattern), differential diagnosis of interstitial nodules is based on their predominant distribution pattern.

To narrow the differential diagnosis sufficiently, inclusion of an additional image pattern is not enough for highly ambiguous main findings, such as ground-glass opacities. Other characteristic constellations of findings may in this case additionally point to potential diagnoses.







Fig. 24.1 Main finding on CT for diffuse pulmonary diseases.



24.1 Main Finding: Interlobular Septal Thickening

Fig. 24.2 illustrates the differential diagnoses for the main finding: interlobular septal thickening.






Fig. 24.2 Main finding: interlobular septal thickening.


Apr 12, 2020 | Posted by in CARDIOVASCULAR IMAGING | Comments Off on Diagnostic Schema for Typical Computed Tomography Findings of Diffuse Pulmonary Diseases

Full access? Get Clinical Tree

Get Clinical Tree app for offline access