| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH |
|
|
|
|||||||
|
|||||||||
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Thoracic Imaging |
1 From the Departments of Radiology (G.D.R., J.K.L., D.S.P., L.C.C., A.N.L., R.M., P.K.S.D., S.E.Z., S.N.) and Electrical Engineering (A.J.S.), Stanford University School of Medicine, 300 Pasteur Dr, S-072, Stanford, CA 94305-5105; and Department of Radiology, New York University School of Medicine, New York, NY (D.P.N.). Received March 31, 2004; revision requested June 8; revision received July 26; accepted August 19. Address correspondence to G.D.R. (e-mail: grubin@stanford.edu).
PURPOSE: To compare the performance of radiologists and of a computer-aided detection (CAD) algorithm for pulmonary nodule detection on thin-section thoracic computed tomographic (CT) scans.
MATERIALS AND METHODS: The study was approved by the institutional review board. The requirement of informed consent was waived. Twenty outpatients (age range, 15–91 years; mean, 64 years) were examined with chest CT (multi–detector row scanner, four detector rows, 1.25-mm section thickness, and 0.6-mm interval) for pulmonary nodules. Three radiologists independently analyzed CT scans, recorded the locus of each nodule candidate, and assigned each a confidence score. A CAD algorithm with parameters chosen by using cross validation was applied to the 20 scans. The reference standard was established by two experienced thoracic radiologists in consensus, with blind review of all nodule candidates and free search for additional nodules at a dedicated workstation for three-dimensional image analysis. True-positive (TP) and false-positive (FP) results and confidence levels were used to generate free-response receiver operating characteristic (ROC) plots. Double-reading performance was determined on the basis of TP detections by either reader.
RESULTS: The 20 scans showed 195 noncalcified nodules with a diameter of 3 mm or more (reference reading). Area under the alternative free-response ROC curve was 0.54, 0.48, 0.55, and 0.36 for CAD and readers 1–3, respectively. Differences between reader 3 and CAD and between readers 2 and 3 were significant (P < .05); those between CAD and readers 1 and 2 were not significant. Mean sensitivity for individual readings was 50% (range, 41%–60%); double reading resulted in increase to 63% (range, 56%–67%). With CAD used at a threshold allowing only three FP detections per CT scan, mean sensitivity was increased to 76% (range, 73%–78%). CAD complemented individual readers by detecting additional nodules more effectively than did a second reader; CAD-reader weighted 
values were significantly lower than reader-reader weighted values (Wilcoxon rank sum test, P < .05).
CONCLUSION: With CAD used at a level allowing only three FP detections per CT scan, sensitivity was substantially higher than with conventional double reading.
Supplemental material: radiology.rsnajnls.org/cgi/content/full/2341040589/DC1
© RSNA, 2004
This article has been cited by other articles:
|
|
 |
|
  M. C. Kang, C. H. Kang, H. J. Lee, J. M. Goo, Y. T. Kim, and J. H. Kim Accuracy of 16-channel multi-detector row chest computed tomography with thin sections in the detection of metastatic pulmonary nodules Eur. J. Cardiothorac. Surg., March 1, 2008; 33(3): 473 - 479. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 C. Beigelman-Aubry, P. Raffy, W. Yang, R. A. Castellino, and P. A. Grenier Computer-Aided Detection of Solid Lung Nodules on Follow-Up MDCT Screening: Evaluation of Detection, Tracking, and Reading Time Am. J. Roentgenol., October 1, 2007; 189(4): 948 - 955. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. E. Baker, L. Bogoni, N. A. Obuchowski, C. Dass, R. M. Kendzierski, E. M. Remer, D. M. Einstein, P. Cathier, A. Jerebko, S. Lakare, et al. Computer-aided Detection of Colorectal Polyps: Can It Improve Sensitivity of Less-Experienced Readers? Preliminary Findings Radiology, October 1, 2007; 245(1): 140 - 149. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. Suzuki, Y. Nakamoto, T. Terauchi, M. Kawamoto, Y. Okumura, Y. Suzuki, T. Sato, N. Takahashi, J. Lee, M. Senda, et al. Inter-observer Variations in FDG-PET Interpretation for Cancer Screening Jpn. J. Clin. Oncol., August 18, 2007; (2007) hym064v1. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
P. Peloschek, J. Sailer, M. Weber, C. J. Herold, M. Prokop, and C. Schaefer-Prokop Pulmonary Nodules: Sensitivity of Maximum Intensity Projection versus That of Volume Rendering of 3D Multidetector CT Data Radiology, May 1, 2007; 243(2): 561 - 569. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. Das, G. Muhlenbruch, A. H. Mahnken, T. G. Flohr, L. Gundel, S. Stanzel, T. Kraus, R. W. Gunther, and J. E. Wildberger Small Pulmonary Nodules: Effect of Two Computer-aided Detection Systems on Radiologist Performance. Radiology, November 1, 2006; 241(2): 564 - 571. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 T. K. Trow Clinical Year in Review I: Diagnostic Imaging, Asthma, Lung Transplantation, and Interventional Pulmonology Proceedings of the ATS, September 1, 2006; 3(7): 553 - 556. [Full Text] [PDF]
|
|
|
|
 |
|
 C. C. Jaffe Measures of Response: RECIST, WHO, and New Alternatives J. Clin. Oncol., July 10, 2006; 24(20): 3245 - 3251. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. B. Lobrano Partnerships in Oncology and Radiology: The Role of Radiology in the Detection, Staging, and Follow-up of Lung Cancer Oncologist, July 1, 2006; 11(7): 774 - 779. [Abstract] [Full Text] [PDF]
|
|
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH |
| RADIOLOGY | RADIOGRAPHICS | RSNA JOURNALS ONLINE |
