Medicsight demonstrates CAD products for colon and lung

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Medicsight highlighted studies demonstrating the effectiveness of CAD in the detection of various stages and types of colon cancer and shared its ColonCAD and LungCAD products last month in Chicago at the 93rd scientific assembly and annual meeting of the Radiological Society of North America (RSNA).

Data presented by Stuart Taylor, MD, consultant radiologist at University College Hospital, London, showed that in two different symptomatic study populations, Medicsight’s ColonCAD  is effective for the localization morphologically flat early colonic cancerous lesions that are often difficult to detect, as well as later stage colorectal cancers. Previous data have supported CAD’s role in highlighting areas of abnormality with CT colonography in asymptomatic patients, and this new data supports ColonCAD’s use in symptomatic patient populations,” Taylor said, “The results are interesting because CT colonography is well established for the detection of adenomatous polyps in asymptomatic patients and the role of CAD is becoming increasingly established, but the potential for computer-aided cancer detection in symptomatic patients has been relatively neglected.  The results show that ColonCAD effectively aids the detection of colon cancer in symptomatic patients, in particular bringing the difficult to detect, morphologically flat lesions to the attention of the radiologist.” 
   
One of the studies involved 30 symptomatic patients who had undergone a diagnostic colonoscopy and who were undergoing cancer staging. Their tumors were all endoscopically classified as having a flat morphology and were located and characterized by three independent radiologists in conjunction with the endoscopic reports and imaging. Medicsight’s ColonCAD software was then applied at three different settings of sphericity. The analysis showed ColonCAD detected 83.3 percent of the morphologically flat cancers present. This type of lesion has historically been difficult to detect with CT colonography.
   
The second larger study included 59 symptomatic patients with already proven cancers. ColonCAD was used at four different filter settings and results based on the sensitivity and specificity at the different settings showed ColonCAD to be effective for the detection of these later stage cancers. In addition, results showed that in the detection of polyps, optimal results for CAD detection of these cancers requires scans to be performed in both supine and prone CT acquisitions.
   
Medicsight’s ColonCAD and LungCAD software use an advanced CAD algorithm to analyze CT scans of the colon and lung and automatically highlight suspicious areas that may be indicators of disease. CAD may highlight areas easily overlooked by the reviewing radiologist, such as small lesions or regions that are hidden from view behind folds in the colon or normal structures and surrounding tissue in the lung. Both CAD products integrate with advanced 3D visualization platforms.

ColonCAD’s is used in symptomatic patient populations. Taylor said, “These results are interesting because CT colonography is well established for the detection of adenomatous polyps in asymptomatic patients and the role of CAD is becoming increasingly established, but the potential for computer-aided cancer detection in symptomatic patients has been relatively neglected. The results show that ColonCAD effectively aids the detection of colon cancer in symptomatic patients, in particular bringing the difficult to detect, morphologically flat lesions to the attention of the radiologist.”