Qiang Li PhD, Presenter: Patent agreement, General Electric Company Patent agreement, Toshiba Corporation Patent agreement, R2 Technology, Inc Patent agreement, Deus Technologies, LLC Patent agreement, Riverain Medical Patent agreement, MEDIAN Technologies Patent agreement, Mitsubishi Corporation Consultant, Riverain Medical

Feng Li MD, PhD, Abstract Co-Author: License agreement, Hologic, Inc (R2 Technology, Inc) License agreement, Deus Technologies, LLC License agreement, Riverain Medical License agreement, Mitsubishi Corporation License agreement, MEDIAN Technologies License agreement, General Electric Company License agreement, Toshiba Corporation

Kunio Doi PhD, Abstract Co-Author: Shareholder, Hologic, Inc (R2 Technology, Inc) License Agreement, Hologic, Inc (R2 Technology, Inc) License Agreement, Deus Technologies, LLC License Agreement, Riverain Medical License Agreement, Mitsubishi Corporation License Agreement, MEDIAN Technologies License Agreement, General Electric Company License Agreement, Toshiba Corporation Research Support, Deus Technologies, LLC Research Support, DuPont Research Support, Elbit Medical Imaging Ltd Research Support, Fuji Photo Film Co, Ltd Research Support, General Electric Company Research Support, Hitachi, Ltd Research Support, Eastman Kodak Company Research Support, Konica Minolta Group Research Support, Mitaya Manufacturing Co, Ltd Research Support, Mitsubishi Corporation Research Support, Koninklijke Philips Electronics NV Research Support, Hologic, Inc (R2 Technology, Inc) Research Support, Riverain Medical Research Support, Seiko Corporation Research Support, Siemens AG Research Support, 3M Company Research Support, Toshiba Corporation

To develop a computer-aided diagnostic (CAD) scheme for detection of lung nodules in CT and to investigate its performance levels for nodules in different size and pattern groups.

Our database consisted of 117 thin-slice CT scans with 153 nodules obtained at Shinshu University, Japan (85 scans, 91 nodules, including 41 cancers and 50 benign nodules) and the University of Chicago (32 scans, 62 nodules). There were 68 (44.4%) small, 52 (34.0%) medium-sized, and 33 (21.6%) large nodules; 101 (66.0%) solid and 52 (34.0%) nodules with ground glass opacity (GGO) in the combined database. Our CAD scheme consisted of lung segmentation, selective nodule enhancement, initial nodule detection, accurate nodule segmentation, and feature extraction and analysis techniques. The selective nodule enhancement filter was a key technique for significant enhancement of nodules and suppression of other normal anatomic structures such as blood vessels, which were the main source of false positives. We employed a case-based four-fold cross-validation method to evaluate the performance levels of our CAD scheme. The cross-validation testing method was repeated 10 times, and the average performance levels were determined for all nodules; for small, medium-sized, and large nodules; and for solid and GGO nodules.

Our CAD scheme achieved an overall sensitivity of 87% (small: 74%, medium-sized: 98%, large: 94%; solid: 85%, GGO: 90%) with 6.5 false positives per scan; an overall sensitivity of 82% (small: 68%, medium-sized: 94%, large: 91%; solid: 78%, GGO: 89%) with 2.8 false positives per scan; and an overall sensitivity of 77% (small: 63%, medium-sized: 90%, large: 89%; solid: 71%, GGO: 89%) with 1.5 false positives per scan. Our CAD scheme achieved a higher sensitivity for GGO nodules than for solid nodules, because most (82.4%) of small nodules, which were more difficult to detect than medium-sized and large nodules, were solid.

Our CAD scheme achieved a low false positive rate and a relatively high detection rate for nodules with a large variation in size and pattern.

Our CAD scheme achieved a good performance and would assist radiologists in the detection of lung nodules on thin-section CT.

Li, Q, Li, F, Doi, K, Development of Computerized Nodule Detection Scheme on Thin-slice CT: Effect of Nodule Size and Pattern Group on Its Performance.  Radiological Society of North America 2007 Scientific Assembly and Annual Meeting, November 25 - November 30, 2007 ,Chicago IL. http://archive.rsna.org/2007/5009607.html