Dual-energy subtraction chest radiography improves lung cancer detection

Dual-energy subtraction chest radiography has the potential to improve radiologists' performance for the detection of small missed lung cancers, according to a study published in the April issue of the American Journal of Roentology.

Feng Li and colleagues, from the department of radiology at the University of Chicago, selected 19 patients with previously missed nodular cancers, in which the radiology report did not mention a nodule that was visible in retrospect.

Dual-energy subtraction radiographs of 19 patients with cancer and 16 patients without cancer were used for an observer study, the authors wrote. Also, the researchers said that six radiologists indicated their confidence level regarding the presence of a lung cancer and, if they thought a cancer was present, marked the most likely position for each lung, first using standard posteroanterior and lateral chest radiographs and then using both soft-tissue and bone dual-energy subtraction images along with standard radiographs.

The researchers also analyzed the indicated locations of cancers and false-positives.

The investigators reported that the average area under the ROC curve value for the six radiologists was improved from 0.718 to 0.816, a statistically significant amount, and the average sensitivity (correct localizations) for 19 previously missed cancers was also significantly improved from 40 percent to 59 percent with the aid of dual-energy subtraction images.

Li and colleagues found that the average number of false-positive localizations on 70 lungs was 10 without and nine with dual-energy subtraction images.

Around the web

The new technology shows early potential to make a significant impact on imaging workflows and patient care. 

Richard Heller III, MD, RSNA board member and senior VP of policy at Radiology Partners, offers an overview of policies in Congress that are directly impacting imaging.
 

The two companies aim to improve patient access to high-quality MRI scans by combining their artificial intelligence capabilities.