New Tool May Assist in Earlier Detection of Asbestos-Related Diseases

The new technology, developed by Carmen Endress, M.D., associate professor of radiology at Wayne State University School of Medicine and radiologist at NCVAC, involves taking images obtained on the 64-slice high resolution CT scan and enhancing them using the Vitrea imaging software program.

"It's my sincere hope that with this new approach and enhanced technology we will help reduce the death rate caused by asbestos-related diseases, reduce the suffering by patients and their loved ones, and make a significant contribution to medicine,” Endress said.

3-D Detail

Michael Harbut, M.D., MPH, co-director of NCVAC at the Barbara Ann Karmanos Cancer Institute in Detroit and chief of the Center for Occupational and Environmental Medicine Wayne State University, said this technology will “allow us to visualize lesions caused by asbestos exposure in three-dimensional detail and often at a much earlier stage than that of the current standard radiographic techniques.”

According to Harbut, the benefits of this new approach include the possibility of earlier detection; better differentiation between patients with scarring on the lungs and other diseases; assistance in determining why some people who have thickening on the covering of the lungs have uncontrolled, unrelenting pain; and potentially increased success in the overall diagnosis and treatment of asbestos-related disease.

Harbut also said this approach could also have a significant public-health impact.

"If we can identify the 'sentinel' or first cases of asbestosis or lung cancer at an early stage, then we can help identify asbestos exposures in places where it might not have previously been suspected,” he said. “Such identification of early detection could help to reduce the death rate from asbestos-related diseases."

Harbut added that this new technology approach to chest radiography also could help reduce cases of fraud, which have been reported in asbestos litigation, due to the clarity and sophistication of the images that can help identify which cases are asbestos-related and which are not.