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Sensitivity and Specificity of a CAD Solution for Lung Nodule Detection on Chest Radiograph with CTA Correlation

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Abstract

The objective of this research was to determine the sensitivity and specificity of a commercially available computer-aided detection (CAD) system for detection of lung nodule on posterior–anterior (PA) chest radiograph in a varied patient population who are referred to computed tomographic angiogram (CTA) of the chest as a reference standard. Patients who had a PA chest radiograph with concomitant CTA of the chest were included in this retrospective study. The PA chest radiograph was analyzed by a CAD device, and results were recorded. A qualitative assessment of the CAD results was performed using a 5-point Likert scale. The CTA was then reviewed to determine if there were correlative nodules. The presence of a correlative nodule between 0.5 cm and 1.5 cm was considered a positive result. The baseline sensitivity of the system was determined to be 0.707 (95% CI = 0.52–0.86), with a specificity of 0.50 (95% CI = 0.38–0.76). Positive predictive value was 0.30 (95% CI = 0.24–0.49), with a negative predictive value of 0.858 (95% CI = 0.82–0.95), and accuracy of 0.555 (95% CI = 0.40–0.66). When excluding nodules that were qualitatively determined by a thoracic radiologist to be false positives, the specificity was 0.781 (95% CI = 0.764–0.839), the positive predictive value was 0.564 (95% CI = 0.491–0.654), the negative predictive value was 0.829 (95% CI = 0.819–0.878), and the accuracy was 0.737 (95% CI = 0.721–0.801). The use of CAD for lung nodule detection on chest radiograph, when used in conjunction with an experienced radiologist, has a very good sensitivity, specificity, and accuracy.

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References

  1. American Cancer Society: Cancer Facts and Figures 2007. Atlanta, GA, American Cancer Society, 2007

  2. Levi F, Lucchini F, Negri E, La Vecchia C: Worldwide patterns of cancer mortality: 1990–1994. Eur J Cancer Prev 8:381–400, 1999

    Article  PubMed  CAS  Google Scholar 

  3. The international Early Lung cancer Action program Investigators: Survival of patients with stage 1 lung cancer detected on CT screening. NEJM 355:1763–1771, 2006

    Article  Google Scholar 

  4. National Institutes of Standards and Technology, an agency of the U.S. Commerce Department’s Technology Administration

  5. McLoud TC, Davis SD, Aquino SD, Batra PV, Goodman PC, Haramati LB, Khan A, Leung AN, Rosado de Chritenson ML, Rozenshtein A, White CS, Kaiser LR, Raoof S: Expert Panel on Thoracic Imaging. Routine admission and preoperative chest radiography. [online publication]. Reston (VA): American College of Radiology (ACR), 2006

  6. Austin JH, Romney BM, Goldmith LS: Missed bronchogenic carcinoma: radiographic findings in 27 patients with a potentially resectable lesion evident in retrospect. Radiology 182:115–122, 1992

    PubMed  CAS  Google Scholar 

  7. Kakeda S, Moriya J, Sato H, et al: Improved detection of lung nodules on chest radiographs using a commericial computer-aided diagnosis system. AJR 182:505–510, 2004

    PubMed  Google Scholar 

  8. Giger ML, Doi K, MacMahon H, Metz CE, Yin FF: Pulmonary nodules: computer-aided detection in digital chest images. Radio Graphics 10:41–51, 1990

    CAS  Google Scholar 

  9. Kobayashi T, Xu XW, MacMahon H, et al: Effect of a computer-aided diagnosis scheme on radiologists’ performance in detection of lung nodules on radiographs. Radiology 199:843–848, 1996

    PubMed  CAS  Google Scholar 

  10. Reeves AP, Kostis WJ: Computer-aided diagnosis for lung cancer. Radiol Clin North Am 38:497–509, 2000

    Article  PubMed  CAS  Google Scholar 

  11. Freedman MT, Lo SCB, Lure F, et al: Computer aided detection of lung cancer on chest radiographs: algorithm performance vs. radiologists’ performance by size of cancer. Prop SPIE 4319:150–159, 2001

    Article  Google Scholar 

  12. Freedman MT, Lo SCB, Osicka T, et al: Computer-aided detection of lung cancer on chest radiographs: effect of machine CAD false-positive locations on radiologists’ behavior. Prop SPIE 4684:1311–1319, 2002

    Article  Google Scholar 

  13. Giger ML, Doi K, MacMahon H: Image feature analysis and computer-aided diagnosis in digital radiography. III. Automated detection of nodules in peripheral lung field. Med Phys 15:158–166, 1988

    Article  PubMed  CAS  Google Scholar 

  14. Kakeda S, Moriya J, Sato H, et al: Improved detection of lung nodules on chest radiographs using a commercial computer-aided diagnosis system. AJR 182:505–510, 2004

    PubMed  Google Scholar 

  15. Jin Z, Ma D, Song W, Fan L, et al: Improving radiological interpretation of chest digital radiograph images using a real-time interactive pulmonary nodule analysis system: a cross-center study, RSNA, Chicago, November, 2005

  16. van Beek E, Mullan B, Thompson B: Evaluation of a real-time interactive pulmonary nodule analysis system on chest digital radiographic images: a prospective study, RSNA, Chicago, November, 2006

  17. Kakeda S, Moriya J, Sato H, et al: Improved detection of lung nodules on chest radiographs using a commercial computer-aided diagnosis system. AJR 182:505–510, 2004

    PubMed  Google Scholar 

  18. Van Beek E: Evaluation of a real-time interactive pulmonary nodule analysis system on chest digital radiographic images: a prospective study. Acad Rad 15(5):571–575, 2008

    Article  Google Scholar 

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Correspondence to William Moore.

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Moore, W., Ripton-Snyder, J., Wu, G. et al. Sensitivity and Specificity of a CAD Solution for Lung Nodule Detection on Chest Radiograph with CTA Correlation. J Digit Imaging 24, 405–410 (2011). https://doi.org/10.1007/s10278-010-9284-7

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  • DOI: https://doi.org/10.1007/s10278-010-9284-7

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