Studies presented at the Annual RSNA Meeting demonstrate value of chest CT CAD

Chicago 30 November 2003The impact of computer-aided detection (CAD) on the evaluation of chest CT exams is the focus of seven research papers accepted for presentation at the 89th Scientific Assembly and Annual Meeting of the Radiological Society of North America (RSNA), November 30-December 4. According to R2 Technology, the developer of the only commercially available CAD system for use with chest multi-detector CT (MDCT), these papers join a growing body of research demonstrating the value of CAD technology that can improve radiologist accuracy and efficiency in interpreting these studies.

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One of these papers examined the potential benefit of CAD analysis of MDCT images: "The purpose of our study was to assess the prevalence of additional findings yielded by computer-aided detection (CAD) in high-resolution MDCT chest exams that were interpreted as normal at routine clinical reading. What we found was that the ImageChecker CT CAD system found lesions of clinical significance, meaning they required surveillance or work-up, in nearly a quarter of the cases originally interpreted as normal", stated Kersten Peldschus, M.D., Department of Radiology - Division of Thoracic Imaging, Brigham and Women's Hospital.

"The conclusion we have to draw from these results is that lung lesions with potential impact on patient management are missed at clinical interpretation of chest CT studies, but may be detected if CAD is used to assist the radiologist", noted Dr. Peldschus.

Several of the studies looked at the performance of radiologists when using CAD when reading MDCT chest exams, rates for lung nodule detection, and the potential benefits of CAD for detecting actionable lung nodules in these exams. Other research concluded that the use of CAD integrated into an enhanced workstation improves the accuracy and efficiency of identifying lung nodules on thin slice MDCT.

Research also looked at CAD performance for automated detection of pulmonary emboli in MDCT data sets. Results showed that CAD may increase diagnostic accuracy by detecting isolated peripheral pulmonary emboli and may contribute to the radiologist's accuracy in the interpretation of large volume MDCT pulmonary angiography studies.

Introduced commercially in Europe in March 2003, the ImageChecker CT CAD system with OmniCAD technology is a comprehensive lung nodule detection and analysis system. The CAD algorithms automatically detect potential areas of interest to increase physician accuracy by decreasing observational oversights, as well as provide work flow enhancing tools, including automatic measurement and characterization information of the detected lung nodules. Combined, the integrated system is designed to improve radiologist efficiency and aid in making clinical decisions.

R2 Technology's proprietary CAD technology provides detection of nodules in chest CT exams taken for any clinical indication, not just for lung cancer screening studies. R2 Technology has conducted extensive clinical trials to demonstrate that the use of the ImageChecker CT CAD system improves radiologists' performance in the detection of lung nodules on MDCT exams. In the United States, R2 received 510(k) clearance for the work flow enhancing tools of the ImageChecker CT LN-500 system from the United States Food and Drug Administration (FDA) in November 2002. The ImageChecker CT LN-1000, which includes the CAD software, is pending FDA approval.

According to the World Health Organization (WHO), lung cancer is the world's most common cancer, accounting for more than 1,2 million new cases annually. Lung cancer, often presenting as lung nodules, can be difficult to detect in its early stages. The American Cancer Society (ACS) reports that many early stage lung cancers are diagnosed incidentally, as a result of imaging studies requested for an unrelated medical condition.

In 2000, the five-year survival rate for all stages of lung cancer was 14 percent. If lung cancer is found and treated while it is localized, however, the ACS reports that the five-year survival rates increase to 42 percent. Only about 15 percent of lung cancers are found in the early stages. Improving the early detection of lung cancer could help improve the survival rate for this deadly disease.

R2 Technology Inc., headquartered in Sunnyvale, California, is a recognized expert in the development and commercialization of computer-aided detection (CAD), an innovative technology that assists radiologists in the early detection of breast cancer and other abnormalities. As a medical software company, R2 is developing CAD systems for a variety of imaging modalities and disease states.


Leslie Versweyveld

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