“Maps” based on lung CTs could aid COPD diagnosis, treatment
A technique for analyzing CT lung scans, originally developed to show the response of brain tumors to treatment, could help physicians better assess patients with chronic obstructive pulmonary disease (COPD), according to a paper published online in Nature Medicine.

Researchers from the University of Michigan Medical School reported that parametric response mapping (PRM) allows them to better distinguish between early-stage damage to small airways in the lungs and the more severe damage of emphysema.

“Essentially, with the PRM technique, we’ve been able to tell sub-types of COPD apart, distinguishing functional small airway disease…from emphysema and normal lung function,” Brian Ross, PhD, senior author of the paper, said in a release. “We believe this offers a new path to more precise diagnosis and treatment planning, and a useful tool for precisely assessing the impact of new medications and other treatments.”

The researchers used PRM to identify COPD-specific changes in 3D lung regions over time by overlaying a CT scan taken during a full inhalation with an image taken during a full exhalation. Density of healthy lung tissue will change more between the two images than the density of diseased lung tissue based on the ability of the lung to push air out of the small sacs. The differences between scans allows for the creation of a 3D “map” of the patient’s lungs, with small voxels color-coded green for healthy, yellow for reduced ability and red for severely reduced ability.

Using scans of patients with COPD who took part in the national COPDGene study funded by the National Heart, Lung and Blood Institute, Ross and colleagues have shown that the severity of disease measured with PRM matches closely with the patient’s performance on standard lung tests of breathing ability.

The authors also indicated that PRM could help track COPD progression over time or its response to treatment, but more longitudinal data are needed to show the technique’s effectiveness for this long-term tracking.