Integrating Lung CAD and PACS Streamlining Day-to-Day Usability

Twitter icon
Facebook icon
LinkedIn icon
e-mail icon
Google icon
Philips’ xLNA CAD highlights three suspicious areas in a chest x-ray.

Fueled by promising clinical studies, computer-assisted detection (CAD) technology continues to improve early lung cancer detection: greater sensitivity, fewer false-positives. As developers work to refine CAD’s capabilities so as not to bog down image interpretation and accuracy, many radiologists are already successfully integrating lung CAD into day-to-day clinical practice, thanks to links with PACS. The future appears promising and we can anticipate a day when lung CAD moves from a “detection tool to a diagnostic tool.”

Since lung CAD’s debut on the market five years ago, clinicians and manufacturers have worked to refine and improve the technology to reach a level of sophistication that will speed CAD’s utilization to an everyday clinical tool that provides a greater level of clinical assuredness than previously available. Better and more efficient diagnosis of early stage lung cancer via CT and digital x-ray, that is what CAD is striving for. As refinements continue to be made, and clinical studies validate its effectiveness, lung CAD is moving its way into a part of the clinical routine for helping radiologists detect solid lung nodules earlier.

Integration into everyday workflow

For a new technology to be readily adopted into everyday practice, it is critical that it seamlessly blends into the existing clinical workflow, ?with minimal to non-existent disruptions.

At the department of radiology at RWTH Aachen University in Aachen, Germany, Siemens’ syngo Lung CAD is integrated into the PACS workstations, giving radiologists a second reader for interpreting complex chest CT data sets. It also aids in the detection of solid pulmonary nodules in thoracic CT studies.

The department also uses the CAD Server from Siemens. As long as a patient is not in the ICU, all thoracic CTs are sent to the server and CAD is used on the PACS workstation, according to Marco Das, MD, fellow in the department.

“We get preprocessed results from the CAD Server displayed in the PACS,” says Das. “We can then do direct comparison to the original data set and see if we missed anything.”

Prior to pairing Siemens’ syngo Lung CAD and server, CAD results had to be processed on a separate workstation, which required radiologists to interrupt workflow to move to a different workstation to process results. “Now with the CAD server and syngo Lung CAD, we have a solution that allows us to stay at the PACS station and have CAD results directly there to use for routine reading. This results in a decrease in image reading time and smoother workflow because the radiologist stays in one location.

Around the globe in Japan, CAD also is finding its way into the clinical routines of radiologists at Iwate Prefectural Central Hospital in Moroika.

For the last 10 months, radiologists have been using the xLNA Enterprise CAD from Philips (the OEM version of EDDA’s IQQA-Chest system) for visualizing, identifying, evaluating, and reporting of pulmonary lesions in digital chest x-rays. They’re benefitting from an increase in the diagnostic accuracy of detecting pulmonary nodules approximately 5 to 15 mm.

CAD systems are not perfect, but if they can be integrated into diagnostic workflow, it can be helpful in diagnosis, says Yasuo Sasaki, MD, PhD, director of radiology.

CAD, which is integrated into the hospital’s Kodak Carestream PACS Client Suite, has helped to streamline workflow. The software automatically loads when the chest image is selected and with a fast processing speed, “there seems to be no issue using the xLNA in daily clinical use,” Sasaki says, adding that staff use lung CAD on all chest x-rays taken in the hospital.

“As a doctor, it is always good to ask a second opinion, and we are able to get that with CAD,” Sasaki says.

Earning its spot, fueled by study results

Despite the significant advances made in imaging technology over the last few decades, the early detection of lung cancer remains a challenge. Neither the technologies nor the interpreters have reached the level of accuracy to make it an exact science, says Moulay Meziane, MD, section head of thoracic imaging at the Imaging Institute within the Cleveland Clinic.

Meziane has been evaluating how chest x-ray CAD can improve practical, early detection of lung cancer, as part of collaboration between Riverain Medical and Cleveland Clinic. Investigators conducted retrospective studies to evaluate the performance