Emphasis shifts from detection to diagnosis

Computer-aided detection and diagnosis tools continue to advance and could at some point become superior to radiologists, presenters from Germany said during a special session at the European Congress of Radiology in Vienna in March.

The potential of CAD in breast imaging was first noted back in 1967, said Prof. Ulrich Bick, a professor of radiology at the Charité Medical University of Berlin. CAD algorithms have evolved considerably since then, leading to a steady improvement in performance. Bick showed data from a 2008 study revealing 100% sensitivity for breast CAD in detecting microcalcifications and 91% sensitivity for malignant masses.

"Masses are easy to see but difficult to interpret," he said. "Basically, the entire breast parenchyma is made up of masses. So it is very difficult to tell which are cancers and which are not."

Bick predicts that future breast CAD systems will be equipped with intelligent workstations that can help determine if lesions are malignant. This will be done by comparing key features seen on the mammogram with those in a database

.

Radiologists must learn to use the technology appropriately. Given the large number of false-positive readings generated by breast CAD, caution is necessary.

Bick suggests that radiologists will gradually come to regard CAD asa trusted second reader for screening mammography, rather than as a "spellchecker." No one is yet obliged to use CAD when reading screening mammograms, but if future data demonstrate that CAD can reduce the mortality of breast cancer, then this issue may need to be revisited.

"At some stage, CAD will be superior to radiologists," he said.

Chest imaging is another area in which CAD is used at present, but it has the potential to do much more, according to Prof. Hans-Ulrich Kauczor, chair of radiology at University Hospital Heidelberg.

CAD helps radiologists find pulmo­nary nodules and early signs of lung cancer on CT, but detection in itself is not enough, he said. The ideal CAD system should also be able to perform accurate volume measurements. Suspicious lesions can then be monitored to see if they change in size and, if so, by how much.

"You want to measure the tumor doubling time," he said. "But we also have to be aware that there is a significant error in making volumetry measurements. You have to demonstrate an increase in volume of more than 30% or 40% to be really sure that a nodule is actually growing."

Kauczor would like to see chest CAD used to assess a far greater spectrum of diseases related to smoking. He envisages computerized systems that could evaluate chronic obstructive pulmonary disease.

Other advances forecast by Kauc­zor include a greater use of CAD for emphysema and the inclusion of vascular imaging tools in chest CT workup.

Prof. Heinz-Otto Peitgen of the Centre for Medical Diagnostics and Visualization (MeVis) in Bremen described a variety of state-of-the-art tools that may assist liver imaging and intervention. His presentation explored different aspects of computer-aided diagnosis and therapy: response evaluation in chemotherapy, surgical planning, and radio­frequency ablation.

Detection rather than diagnosis will remain the primary role for CAD in the colon, said Prof. Andrik Aschoff, an associate professor of radiology at the University of Ulm. Early identification and removal of polyps promises to reduce the rate of colon cancer. But if this type of screening is to be performed with CT colonography, then CAD may be needed to reduce variations in reader sensitivity.

Aschoff outlined three paradigms for using CAD: as an initial reader to filter out "normal" cases, as an aid to the reporting radiologist, and as an independent second reader.

"CAD is very promising in CT co­lonography. If we do CTC on our patients, we want to give them the assurance that they have no large polyps and are not going to develop colorectal cancer," Aschoff said.