European Radiology

, Volume 25, Issue 3, pp 792–799 | Cite as

The impact of radiologists’ expertise on screen results decisions in a CT lung cancer screening trial

  • Marjolein A. Heuvelmans
  • Matthijs Oudkerk
  • Pim A. de Jong
  • Willem P. Mali
  • Harry J. M. Groen
  • Rozemarijn VliegenthartEmail author



To evaluate the impact of radiological expertise on screen result decisions in a CT lung cancer screening trial.


In the NELSON lung cancer screening trial, the baseline CT result was based on the largest lung nodule’s volume. The protocol allowed radiologists to manually adjust screen results in cases of high suspicion of benign or malignant nodule nature. Participants whose baseline CT result was based on a solid or part-solid nodule were included in this study. Adjustments by radiologists at baseline were evaluated. Histology was the reference for diagnosis or to confirm benignity and stability on subsequent CT examinations.


A total of 3,318 participants (2,796 male, median age 58.0 years) were included. In 195 participants (5.9 %) the initial baseline screen result was adjusted by the radiologist. Adjustment was downwards from positive or indeterminate to negative in two and 119 participants, respectively, and from positive to indeterminate in 65 participants. None of these nodules turned out to be malignant. In 9/195 participants (4.6 %) the screen result was adjusted upwards from negative to indeterminate or indeterminate to positive; two nodules were malignant.


In one in 20 cases of baseline lung cancer screening, nodules were reclassified by the radiologist, leading to a reduction of false-positive screen results.

Key Points

The NELSON study allowed radiologists to manually adjust the screen result

At baseline, radiologists adjusted the result in about one in 20 cases (95.4 % downwards)

Radiologists’ adjustments led to a 22 % reduction of false-positive screen results

Radiologists’ expertise can improve nodule classification in addition to a nodule protocol


Pulmonary nodule Lung neoplasms Mass screening Protocol compliance Computed tomography 



Computed tomography


Interquartile range


National Lung Screening Trial


Volume-doubling time



The scientific guarantor of this publication is Prof. Dr. M. Oudkerk. The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article. This study has received funding by The NELSON trial was sponsored by: Netherlands Organisation for Health Research and Development (ZonMw); Dutch Cancer Society Koningin Wilhelmina Fonds (KWF); Stichting Centraal Fonds Reserves van Voormalig Vrijwillige Ziekenfondsverzekeringen (RvvZ); Siemens Germany; Rotterdam Oncologic Thoracic Steering committee (ROTS); G.Ph.Verhagen Trust, Flemish League Against Cancer, Foundation Against Cancer and Erasmus Trust Fund. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. One of the authors has significant statistical expertise. Institutional review board approval was obtained. Written informed consent was obtained from all subjects (patients) in this study. Some study subjects or cohorts have been previously reported (N Engl J Med 361:2221–2229, 2009). Other substudies were published in Radiology, European Radiology, Am J Respir Crit Care Med and Eur Resp Journal amongst others. Methodology: retrospective, randomised controlled trial, multicenter study. The work was performed at the following institutions: University of Groningen / University Medical Center Groningen, Groningen, The Netherlands; University Medical Center Utrecht, Utrecht, The Netherlands; Kennemer Gasthuis, Haarlem, The Netherlands; University Hospital Gasthuisberg Leuven, Leuven, Belgium.


  1. 1.
    National Lung Screening Trial Research Team, Aberle DR, Adams AM et al (2011) Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med 365:395–409CrossRefGoogle Scholar
  2. 2.
    (USPSTF) TUSPSTF (2013) Screening for lung cancer: U.S. preventive services task force recommendation statement. 2013Google Scholar
  3. 3.
    Jaklitsch MT, Jacobson FL, Austin JH et al (2012) The American Association for Thoracic Surgery guidelines for lung cancer screening using low-dose computed tomography scans for lung cancer survivors and other high-risk groups. J Thorac Cardiovasc Surg 144:33–38CrossRefPubMedGoogle Scholar
  4. 4.
    Detterbeck FC, Mazzone PJ, Naidich DP, Bach PB (2013) Screening for lung cancer: diagnosis and management of lung cancer, 3rd edn. American College of Chest Physicians evidence-based clinical practice guidelines. Chest 143:e78S–e92SCrossRefPubMedCentralPubMedGoogle Scholar
  5. 5.
    Wender R, Fontham ET, Barrera E Jr et al (2013) American Cancer Society lung cancer screening guidelines. CA Cancer J Clin 63:107–117CrossRefPubMedCentralPubMedGoogle Scholar
  6. 6.
    American Lung Association (2012) Providing guidance on CT lung cancer screening to patients and physicians. 2013Google Scholar
  7. 7.
    Humphrey LL, Deffebach M, Pappas M et al (2013) Screening for lung cancer with low-dose computed tomography: a systematic review to update the US Preventive Services Task Force recommendation. Ann Intern Med. doi: 10.7326/0003-4819-159-6-201309170-00690 Google Scholar
  8. 8.
    Xu DM, Gietema H, de Koning H et al (2006) Nodule management protocol of the NELSON randomised lung cancer screening trial. Lung Cancer 54:177–184CrossRefPubMedGoogle Scholar
  9. 9.
    van Klaveren RJ, Oudkerk M, Prokop M et al (2009) Management of lung nodules detected by volume CT scanning. N Engl J Med 361:2221–2229CrossRefPubMedGoogle Scholar
  10. 10.
    Christe A, Leidolt L, Huber A et al (2013) Lung cancer screening with CT: evaluation of radiologists and different computer assisted detection software (CAD) as first and second readers for lung nodule detection at different dose levels. Eur J Radiol 82:e873–e878CrossRefPubMedGoogle Scholar
  11. 11.
    Zhao Y, de Bock GH, Vliegenthart R et al (2012) Performance of computer-aided detection of pulmonary nodules in low-dose CT: comparison with double reading by nodule volume. Eur Radiol 22:2076–2084CrossRefPubMedCentralPubMedGoogle Scholar
  12. 12.
    Kakinuma R, Ashizawa K, Kobayashi T et al (2012) Comparison of sensitivity of lung nodule detection between radiologists and technologists on low-dose CT lung cancer screening images. Br J Radiol 85:e603–e608CrossRefPubMedCentralPubMedGoogle Scholar
  13. 13.
    van Iersel CA, de Koning HJ, Draisma G et al (2007) Risk-based selection from the general population in a screening trial: selection criteria, recruitment and power for the Dutch-Belgian randomised lung cancer multi-slice CT screening trial (NELSON). Int J Cancer 120:868–874CrossRefPubMedGoogle Scholar
  14. 14.
    Horeweg N, van der Aalst CM, Vliegenthart R et al (2013) Volumetric computer tomography screening for lung cancer: three rounds of the NELSON trial. Eur Respir J. doi: 10.1183/09031936.00197712 PubMedGoogle Scholar
  15. 15.
    CBO (2004) Guideline - non-small cell lung cancer: staging and treatment. Van Zuiden Communications BV, Alphen aan de Rijn, the NetherlandsGoogle Scholar
  16. 16.
    Xu DM, van der Zaag-Loonen HJ, Oudkerk M et al (2009) Smooth or attached solid indeterminate nodules detected at baseline CT screening in the NELSON study: cancer risk during 1 year of follow-up. Radiology 250:264–272CrossRefPubMedGoogle Scholar
  17. 17.
    MacMahon H, Austin JH, Gamsu G et al (2005) Guidelines for management of small pulmonary nodules detected on CT scans: a statement from the Fleischner Society. Radiology 237:395–400CrossRefPubMedGoogle Scholar
  18. 18.
    Gould MK, Donington J, Lynch WR et al (2013) Evaluation of individuals with pulmonary nodules: when is it lung cancer? Diagnosis and management of lung cancer, 3rd edn: American College of Chest Physicians evidence-based clinical practice guidelines. Chest 143:e93S–e120SCrossRefPubMedCentralPubMedGoogle Scholar
  19. 19.
    Gurney JW, Lyddon DM, McKay JA (1993) Determining the likelihood of malignancy in solitary pulmonary nodules with Bayesian analysis. Part II. Application. Radiology 186:415–422CrossRefPubMedGoogle Scholar
  20. 20.
    Takashima S, Sone S, Li F et al (2003) Small solitary pulmonary nodules (< or =1 cm) detected at population-based CT screening for lung cancer: reliable high-resolution CT features of benign lesions. AJR Am J Roentgenol 180:955–964CrossRefPubMedGoogle Scholar
  21. 21.
    Zhao YR, Heuvelmans MA, Dorrius MD et al (2014) Features of resolving and nonresolving indeterminate pulmonary nodules at follow-up CT: The NELSON study. Radiology 270:872–879CrossRefPubMedGoogle Scholar
  22. 22.
    Henschke CI, Yankelevitz DF, Mirtcheva R et al (2002) CT screening for lung cancer: frequency and significance of part-solid and nonsolid nodules. AJR Am J Roentgenol 178:1053–1057CrossRefPubMedGoogle Scholar
  23. 23.
    Brewer NT, Salz T, Lillie SE (2007) Systematic review: the long-term effects of false-positive mammograms. Ann Intern Med 146:502–510CrossRefPubMedGoogle Scholar
  24. 24.
    van den Bergh KA, Essink-Bot ML, Bunge EM et al (2008) Impact of computed tomography screening for lung cancer on participants in a randomized controlled trial (NELSON trial). Cancer 113:396–404CrossRefPubMedGoogle Scholar
  25. 25.
    Ahn MI, Gleeson TG, Chan IH et al (2010) Perifissural nodules seen at CT screening for lung cancer. Radiology 254:949–956CrossRefPubMedGoogle Scholar
  26. 26.
    de Hoop B, van Ginneken B, Gietema H, Prokop M (2012) Pulmonary perifissural nodules on CT scans: rapid growth is not a predictor of malignancy. Radiology 265:611–616CrossRefPubMedGoogle Scholar
  27. 27.
    Li F, Sone S, Abe H, Macmahon H, Doi K (2004) Malignant versus benign nodules at CT screening for lung cancer: comparison of thin-section CT findings. Radiology 233:793–798CrossRefPubMedGoogle Scholar
  28. 28.
    Zwirewich CV, Vedal S, Miller RR, Muller NL (1991) Solitary pulmonary nodule: high-resolution CT and radiologic-pathologic correlation. Radiology 179:469–476CrossRefPubMedGoogle Scholar
  29. 29.
    Wang Y, van Klaveren RJ, van der Zaag-Loonen HJ et al (2008) Effect of nodule characteristics on variability of semiautomated volume measurements in pulmonary nodules detected in a lung cancer screening program. Radiology 248:625–631CrossRefPubMedGoogle Scholar
  30. 30.
    Naidich DP, Bankier AA, MacMahon H et al (2013) Recommendations for the management of subsolid pulmonary nodules detected at CT: a statement from the Fleischner Society. Radiology 266:304–317CrossRefPubMedGoogle Scholar

Copyright information

© European Society of Radiology 2014

Authors and Affiliations

  • Marjolein A. Heuvelmans
    • 1
    • 2
  • Matthijs Oudkerk
    • 1
  • Pim A. de Jong
    • 3
  • Willem P. Mali
    • 3
  • Harry J. M. Groen
    • 4
  • Rozemarijn Vliegenthart
    • 1
    • 2
    Email author
  1. 1.Center for Medical Imaging – North East NetherlandsUniversity of Groningen, University Medical Center GroningenGroningenThe Netherlands
  2. 2.Department of RadiologyUniversity of Groningen / University Medical Center GroningenGroningenThe Netherlands
  3. 3.Department of RadiologyUniversity Medical Center UtrechtUtrechtThe Netherlands
  4. 4.Department of PulmonologyUniversity of Groningen, University Medical Center GroningenGroningenThe Netherlands

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