Advertisement

European Radiology

, Volume 17, Issue 12, pp 3148–3156 | Cite as

Pulmonary nodule detection on MDCT images: evaluation of diagnostic performance using thin axial images, maximum intensity projections, and computer-assisted detection

  • A. JankowskiEmail author
  • T. Martinelli
  • J. F. Timsit
  • C. Brambilla
  • F. Thony
  • M. Coulomb
  • G. Ferretti
Chest
First Online:

Abstract

This study aimed at evaluating the diagnostic benefits of maximum intensity projections (MIP) and a commercially available computed-assisted detection system (CAD) for the detection of pulmonary nodules on MDCT as compared with standard 1-mm images on lung cancer screening material. Thirty subjects were randomly selected from our database. Three radiologists independently reviewed three types of images: axial 1-mm images, axial MIP slabs, and CAD system detections. Two independent experienced chest radiologists decided which were true-positive nodules. Two hundred eighty-five nodules ≥1 mm were identified as true-positive by consensus of two independent chest radiologists. The detection rates of the three independent observers with 1-mm axial images were 22 ± 4.8%, 30 ± 5.3%, and 47 ± 2.8%; with MIP: 33 ± 5.4%, 39 ± 5.7%, and 45 ± 5.8%; and with CAD: 35 ± 5.6%, 36 ± 5.6%, and 36 ± 5.6%. There was a reading technique effect on the observers’ sensitivity for nodule detection: sensitivities with MIP were higher than with 1-mm images or CAD for all nodules (F-values = 0.046). For nodules ≥3 mm, readers’ sensitivities were higher with 1-mm images or MIP than with CAD (p < 0.0001). CAD was the most and MIP the less time-consuming technique (p < 0.0001). MIP and CAD reduced the number of overlooked small nodules. As MIP is more sensitive and less time consuming than the CAD we used, we recommend viewing MIP and 1-mm images for the detection of pulmonary nodules.

Keywords

Multislice computed tomography Computer-aided diagnosis Maximum intensity projection (MIP) Pulmonary nodules 
This is a preview of subscription content, log in to check access.

References

  1. 1.
    Henschke CI, McCauley DI, Yankelevitz DF et al (2001) Early lung cancer action project: a summary of the findings on baseline screening. Oncologist 6:147–152PubMedCrossRefGoogle Scholar
  2. 2.
    Sone S, Li F, Yang ZG et al (2000) Characteristics of small lung cancers invisible on conventional chest radiography and detected by population based screening using spiral CT. Br J Radiol 73:137–145PubMedGoogle Scholar
  3. 3.
    Kaneko M, Eguchi K, Ohmatsu H et al (1996) Peripheral lung cancer: screening and detection with low-dose spiral CT versus radiography. Radiology 201:798–802PubMedGoogle Scholar
  4. 4.
    Sone S, Takashima S, Li F et al (1998) Mass screening for lung cancer with mobile spiral computed tomography scanner. Lancet 351:1242–1245PubMedCrossRefGoogle Scholar
  5. 5.
    Swensen SJ, Jett JR, Hartman TE et al (2005) CT screening for lung cancer: five-year prospective experience. Radiology 235:259–265PubMedCrossRefGoogle Scholar
  6. 6.
    Naidich DP, Rusinek H, McGuinness G, Leitman B, McCauley DI, Henschke CI (1993) Variables affecting pulmonary nodule detection with computed tomography: evaluation with three-dimensional computer simulation. J Thorac Imaging 8:291–299PubMedCrossRefGoogle Scholar
  7. 7.
    Fischbach F, Knollmann F, Griesshaber V, Freund T, Akkol E, Felix R (2003) Detection of pulmonary nodules by multislice computed tomography: improved detection rate with reduced slice thickness. Eur Radiol 13:2378–2383PubMedCrossRefGoogle Scholar
  8. 8.
    Seltzer SE, Judy PF, Adams DF et al (1995) Spiral CT of the chest: comparison of cine and film-based viewing. Radiology 197:73–78PubMedGoogle Scholar
  9. 9.
    Tillich M, Kammerhuber F, Reittner P, Riepl T, Stoeffler G, Szolar DH (1997) Detection of pulmonary nodules with helical CT: comparison of cine and film-based viewing. AJR Am J Roentgenol 169:1611–1614PubMedGoogle Scholar
  10. 10.
    Wormanns D, Ludwig K, Beyer F, Heindel W, Diederich S (2005) Detection of pulmonary nodules at multirow-detector CT: effectiveness of double reading to improve sensitivity at standard-dose and low-dose chest CT. Eur Radiol 15:14–22PubMedCrossRefGoogle Scholar
  11. 11.
    Wormanns D, Beyer F, Diederich S, Ludwig K, Heindel W (2004) Diagnostic performance of a commercially available computer-aided diagnosis system for automatic detection of pulmonary nodules: comparison with single and double reading. Eur Radiol 176:953–958Google Scholar
  12. 12.
    Gruden JF, Ouanounou S, Tigges S, Norris SD, Klausner TS (2002) Incremental benefit of maximum-intensity-projection images on observer detection of small pulmonary nodules revealed by multidetector CT. AJR Am J Roentgenol 179:149–157PubMedGoogle Scholar
  13. 13.
    Diederich S, Lentschig MG, Overbeck TR, Wormanns D, Heindel W (2001) Detection of pulmonary nodules at spiral CT: comparison of maximum intensity projection sliding slabs and single-image reporting. Eur Radiol 11:1345–1350PubMedCrossRefGoogle Scholar
  14. 14.
    Coakley FV, Cohen MD, Johnson MS, Gonin R, Hanna MP (1998) Maximum intensity projection images in the detection of simulated pulmonary nodules by spiral CT. Br J Radiol 71:135–140PubMedGoogle Scholar
  15. 15.
    Eibel R, Turk TR, Kulinna C, Herrmann K, Reiser MF (2001) [Multidetector-row CT of the lungs: Multiplanar reconstructions and maximum intensity projections for the detection of pulmonary nodule]. Rofo 173:815–821Google Scholar
  16. 16.
    Valencia R, Denecke T, Lehmkuhl L, Fischbach F, Felix R, Knollmann F (2006) Value of axial and coronal maximum intensity projection (MIP) images in the detection of pulmonary nodules by multislice spiral CT: comparison with axial 1-mm and 5-mm slices. Eur Radiol 16:325–332PubMedCrossRefGoogle Scholar
  17. 17.
    Armato SG 3rd, Li F, Giger ML, MacMahon H, Sone S, Doi K (2002) Lung cancer: performance of automated lung nodule detection applied to cancers missed in a CT screening program. Radiology 225:685–692PubMedCrossRefGoogle Scholar
  18. 18.
    Armato SG 3rd, Giger ML, MacMahon H (2001) Automated detection of lung nodules in CT scans: preliminary results. Med Phys 28:1552–1561PubMedCrossRefGoogle Scholar
  19. 19.
    Brown MS, McNitt-Gray MF, Goldin JG, Suh RD, Sayre JW, Aberle DR (2001) Patient-specific models for lung nodule detection and surveillance in CT images. IEEE Trans Med Imaging 20:1242–1250PubMedCrossRefGoogle Scholar
  20. 20.
    Gurcan MN, Sahiner B, Petrick N et al (2002) Lung nodule detection on thoracic computed tomography images: preliminary evaluation of a computer-aided diagnosis system. Med Phys 29:2552–2558PubMedCrossRefGoogle Scholar
  21. 21.
    Lee Y, Hara T, Fujita H, Itoh S, Ishigaki T (2001) Automated detection of pulmonary nodules in helical CT images based on an improved template-matching technique. IEEE Trans Med Imaging 20:595–604PubMedCrossRefGoogle Scholar
  22. 22.
    Wormanns D, Fiebich M, Saidi M, Diederich S, Heindel W (2002) Automatic detection of pulmonary nodules at spiral CT: clinical application of a computer-aided diagnosis system. Eur Radiol 12:1052–1057PubMedCrossRefGoogle Scholar
  23. 23.
    Rubin GD, Lyo JK, Paik DS et al (2005) Pulmonary nodules on multi-detector row CT scans: performance comparison of radiologists and computer-aided detection. Radiology 234:274–283PubMedCrossRefGoogle Scholar
  24. 24.
    Awai K, Murao K, Ozawa A et al (2004) Pulmonary nodules at chest CT: effect of computer-aided diagnosis on radiologists’ detection performance. Radiology 230:347–352PubMedCrossRefGoogle Scholar
  25. 25.
    Lee IJ, Gamsu G, Czum J, Wu N, Johnson R, Chakrapani S (2005) Lung nodule detection on chest CT: evaluation of a computer-aided detection (CAD) system. Korean J Radiol 6:89–93PubMedCrossRefGoogle Scholar
  26. 26.
    Marten K, Seyfarth T, Auer F et al (2004) Computer-assisted detection of pulmonary nodules: performance evaluation of an expert knowledge-based detection system in consensus reading with experienced and inexperienced chest radiologists. Eur Radiol 14:1930–1938PubMedCrossRefGoogle Scholar
  27. 27.
    Marten K, Engelke C, Seyfarth T, Grillhosl A, Obenauer S, Rummeny EJ (2005) Computer-aided detection of pulmonary nodules: influence of nodule characteristics on detection performance. Clin Radiol 60:196–206PubMedCrossRefGoogle Scholar
  28. 28.
    Armato SG 3rd, Giger ML, Moran CJ, Blackburn JT, Doi K, MacMahon H (1999) Computerized detection of pulmonary nodules on CT scans. Radiographics 19:1303–1311PubMedGoogle Scholar
  29. 29.
    Giger ML, Bae KT, MacMahon H (1994) Computerized detection of pulmonary nodules in computed tomography images. Invest Radiol 29:459–465PubMedCrossRefGoogle Scholar
  30. 30.
    Ko JP, Betke M (2001) Chest CT: automated nodule detection and assessment of change over time-preliminary experience. Radiology 218:267–273PubMedGoogle Scholar
  31. 31.
    Brown MS, Goldin JG, Suh RD, McNitt-Gray MF, Sayre JW, Aberle DR (2003) Lung micronodules: automated method for detection at thin-section CT—initial experience. Radiology 226:256–262PubMedCrossRefGoogle Scholar
  32. 32.
    Marten K, Grillhösl A, Seyfarth T, Obenauer S, Rimmeny EJ, Engelke C (2005) Computer-assisted detection of pulmonary nodules: evaluation of diagnostic performance using an expert knowledge-based detection system with variable reconstruction slice thickness settings. Eur Radiol 15:203–212PubMedCrossRefGoogle Scholar
  33. 33.
    Marten K, Engelke C (2007) Computer-aided detection and automated CT volumetry of pulmonary nodules. Eur Radiol 17(4):888–901PubMedCrossRefGoogle Scholar
  34. 34.
    Das M, Mühlenbruch G, Mahnken AH et al (2006) Small pulmonary nodules: effect of two computer-aided detection systems on radiologist performance. Radiology 241(2):564–571PubMedCrossRefGoogle Scholar
  35. 35.
    Yuan R, Vos PM, Cooperberg PL. Compuer-aided detection in screening CT for pulmonary nodules. Am J Roentgenol 186:1280–1287Google Scholar
  36. 36.
    Diederich S, Wormanns D, Semik M et al (2002) Screening for early lung cancer with low-dose spiral CT: prevalence in 817 asymptomatic smokers. Radiology 222:773–781PubMedCrossRefGoogle Scholar
  37. 37.
    Henschke CI (2005) Computed tomography screening for lung cancer: principles and results. Clin Cancer Res 11:4984s–4987sPubMedCrossRefGoogle Scholar
  38. 38.
    Midthun DE, Swense SJ, Jett JR, Hartman TE (2003) Evaluation of nodules detected by screening for lung cancer with low dose spiral computed tomography. Lung Cancer 41(suppl 2):S40CrossRefGoogle Scholar
  39. 39.
    MacMahonH, Austin JHM, Gamsu G, Herold CJ, Jett JR, Naidich DP, Patz EF, Swensen SJ (2005) Guidelines for management of small pulmonary nodules detected on CT scans: a statement of the Fleischner society. Radiology 237:395–400PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • A. Jankowski
    • 1
    Email author
  • T. Martinelli
    • 1
  • J. F. Timsit
    • 2
    • 3
  • C. Brambilla
    • 3
    • 4
  • F. Thony
    • 1
  • M. Coulomb
    • 1
  • G. Ferretti
    • 1
    • 3
  1. 1.Service Central de Radiologie et d’Imagerie MédicaleGrenoble Cedex 09France
  2. 2.Réanimation médicale et soins intensifs d’urgenceGrenoble Cedex 09France
  3. 3.INSERM U 823, Institut Albert Bonnot, Rond-point de la ChantourneLa Tronche CedexFrance
  4. 4.Pneumologie, Département de Médecine aigue spécialiséeGrenoble Cedex 09France

Personalised recommendations

Cite article

Buy options