Advertisement

Journal of Cancer Research and Clinical Oncology

, Volume 144, Issue 1, pp 117–125 | Cite as

Lung cancer screening with MRI: results of the first screening round

  • Michael Meier-Schroers
  • Rami Homsi
  • Dirk Skowasch
  • Jens Buermann
  • Matthias Zipfel
  • Hans Heinz Schild
  • Daniel Thomas
Original Article – Clinical Oncology

Abstract

Purpose

To evaluate the suitability of MRI for lung cancer screening in a high-risk population.

Materials and methods

A 5-year lung cancer screening program comparing MRI and low-dose CT (LDCT) in a high-risk population was initiated. 224 subjects were examined with MRI and LDCT. Acquired MRI sequences were T2w MultiVane XD, balanced steady-state-free precession, 3D T1w GRE, and DWI with a maximum in-room-time of 20 min. Categorization and management of nodules were based on Lung-RADS. MRI findings were correlated with LDCT as a reference. Here, we report on the first screening round.

Results

MRI accurately detected 61 of 88 nodules 4–5 mm, 20 of 21 nodules 6–7 mm, 12 of 12 nodules 8–14 mm, 4 of 4 nodules ≥ 15 mm (solid nodules), and 8 of 11 subsolid nodules. Sensitivity/specificity of MRI for nodule detection was 69.3/96.4% for 4–5 mm, 95.2/99.6% for 6–7 mm, 100/99.6% for 8–14 mm, 100/100% for ≥ 15 mm (solid nodules), and 72.7/99.2% for subsolid nodules. The early recall rate was 13.8% for MRI and 12.5% for LDCT. Following Lung-RADS recommendations and based on interdisciplinary consensus, histology was obtained in eight subjects. The biopsy rate was 3.6% for MRI and 3.4% for LDCT. In all of these eight cases, the nodules were carcinomas, and all of them were accurately detected by MRI.

Conclusion

The results of the first screening round suggest that MRI is suitable for lung cancer screening with an excellent sensitivity and specificity for nodules ≥ 6 mm.

Keywords

Lung cancer Screening MRI 

Abbreviations

DWI

Diffusion-weighted imaging

LDCT

Low-dose computed tomography

Lung-RADS

Lung screening reporting and data system

MVXD

MultiVane XD (Philips Healthcare, Best, The Netherlands)

SENSE

Sensitivity encoding (Philips Healthcare, Best, The Netherlands)

STIR

Short tau inversion recovery

THRIVE

T1 high-resolution isotropic volume excitation (Philips Healthcare, Best, The Netherlands)

UTE

Ultrashort echo time

Notes

Acknowledgements

We would like to address special thanks to our study nurse Olga Ramig. This study would not have been achievable without her ambition.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

References

  1. Alberg AJ, Brock MV, Ford JG, Samet JM, Spivack SD (2013) Epidemiology of lung cancer. Chest 143(5 suppl):e1S–e29SCrossRefPubMedPubMedCentralGoogle Scholar
  2. Alper F, Kurt AT, Aydin Y, Ozgokce M, Akgun M (2013) The role of dynamic magnetic resonance imaging in the evaluation of pulmonary nodules and masses. Med Princ Pract 22(1):80–86CrossRefPubMedGoogle Scholar
  3. American College of Radiology (2017) Lung CT screening reporting and data system (Lung-RADS). Available at: http://www.acr.org/Quality-Safety/Resources/LungRADS. Accessed 31 March 2017
  4. Becker N, Motsch E, Gross ML et al (2012) Randomized study on early detection of lung cancer with MSCT in Germany: study design and results of the first screening round. J Cancer Res Clin Oncol 138:1475–1486CrossRefPubMedGoogle Scholar
  5. Biederer J, Beer M, Hirsch W, Wild J, Fabel M, Puderbach M, Van Beek EJ (2012) MRI of the lung (2/3). Why … when … how? Insights Imaging 3(4):355–371CrossRefPubMedPubMedCentralGoogle Scholar
  6. Biederer J, Ohno Y, Hatabu H, Schiebler ML, van Beek EJ, Vogel-Claussen J, Kauczor HU (2017) Screening for lung cancer: does MRI have a role? Eur J Radiol 86:353–360CrossRefPubMedGoogle Scholar
  7. Bieri O (2013) Ultra-fast steady state free precession and its application to in vivo (1)H morphological and functional lung imaging at 1.5 tesla. Magn Reson Med 70(3):657–663CrossRefPubMedGoogle Scholar
  8. Brenner DJ (2004) Radiation risks potentially associated with low-dose CT screening of adult smokers for lung cancer. Radiology 231(2):440–445CrossRefPubMedGoogle Scholar
  9. Carney PA, Sickles EA, Monsees BS et al (2010) Identifying minimally acceptable interpretive performance criteria for screening mammography. Radiology 255(2):354–361CrossRefPubMedPubMedCentralGoogle Scholar
  10. Chen L, Zhang J, Bao J et al (2013) Meta-analysis of diffusion-weighted MRI in the differential diagnosis of lung lesions. J Magn Reson Imaging 37(6):1351–1358CrossRefPubMedGoogle Scholar
  11. Cieszanowski A, Lisowska A, Dabrowska M, Korczynski P, Zukowska M, Grudzinski IP, Pacho R, Rowinski O, Krenke R (2016) MR imaging of pulmonary nodules: detection rate and accuracy of size estimation in comparison to computed tomography. PLoS One 11(6):e0156272CrossRefPubMedPubMedCentralGoogle Scholar
  12. Deng Y, Li X, Lei Y, Liang C, Liu Z (2016) Use of diffusion-weighted magnetic resonance imaging to distinguish between lung cancer and focal inflammatory lesions: a comparison of intravoxel incoherent motion derived parameters and apparent diffusion coefficient. Acta Radiol 57(11):1310–1317CrossRefPubMedGoogle Scholar
  13. Horeweg N, van Rosmalen J, Heuvelmans MA et al (2014) Lung cancer probability in patients with CT-detected pulmonary nodules: a prespecified analysis of data from the NELSON trial of low-dose CT screening. Lancet Oncol 15(12):1332–1341CrossRefPubMedGoogle Scholar
  14. Howington JA, Blum MG, Chang AC, Balekian AA, Murthy SC (2013) Treatment of stage I and II non-small cell lung cancer. Chest 143(5 suppl):e278S–e313SCrossRefPubMedGoogle Scholar
  15. Jett JR, Schild SE, Kesler KA, Kalemkerian GP (2013) Treatment of small cell lung cancer. Chest 143(5 suppl):e400S–e419SCrossRefPubMedGoogle Scholar
  16. Kono R, Fujimoto K, Terasaki H, Müller NL, Kato S, Sadohara J, Hayabuchi N, Takamori S (2007) Dynamic MRI of solitary pulmonary nodules: comparison of enhancement patterns of malignant and benign small peripheral lung lesions. AJR Am J Roentgenol 188(1):26–36CrossRefPubMedGoogle Scholar
  17. Koyama H, Ohno Y, Kono A, Takenaka D, Maniwa Y, Nishimura Y, Ohbayashi C, Sugimura K (2008) Quantitative and qualitative assessment of non-contrast-enhanced pulmonary MR imaging for management of pulmonary nodules in 161 subjects. Eur Radiol 18:2120–2131CrossRefPubMedGoogle Scholar
  18. Koyama H, Ohno Y, Aoyama N, Onishi Y, Matsumoto K, Nogami M, Takenaka D, Nishio W, Ohbayashi C, Sugimura K (2010) Comparison of STIR turbo SE imaging and diffusion-weighted imaging of the lung: capability for detection and subtype classification of pulmonary adenocarcinomas. Eur Radiol 20:790–800CrossRefPubMedGoogle Scholar
  19. Koyama H, Ohno Y, Seki S, Nishio M, Yoshikawa T, Matsumoto S, Sugimura K (2013) Magnetic resonance imaging for lung cancer. J Thorac Imaging 28(3):138–150CrossRefPubMedGoogle Scholar
  20. Lung cancer (2012) Estimated incidence, mortality and prevalence worldwide in 2012. Available at http://globocan.iarc.fr/Pages/fact_sheets_cancer.aspx. Accessed 31 March 2017
  21. MacMahon H, Naidich DP, Goo JM et al (2017) Guidelines for management of incidental pulmonary nodules detected on CT images: from the Fleischner Society 2017. Radiology 284(1):228–243CrossRefPubMedGoogle Scholar
  22. McWilliams A, Tammemagi MC, Mayo JR et al (2013) Probability of cancer in pulmonary nodules detected on first screening CT. N Engl J Med 369(10):910–919CrossRefPubMedPubMedCentralGoogle Scholar
  23. Meier-Schroers M, Kukuk G, Homsi R, Skowasch D, Schild HH, Thomas D (2016) MRI of the lung using the PROPELLER technique: artifact reduction, better image quality and improved nodule detection. Eur J Radiol 85(4):707–713CrossRefPubMedGoogle Scholar
  24. National Collaborating Centre for Cancer (UK) (2011) The diagnosis and treatment of lung cancer (Update). Cardiff (UK): National Collaborating Centre for Cancer (UK). NICE Clinical Guidelines, No. 121Google Scholar
  25. National Lung Screening Trial Research Team, Aberle DR, Adams AM, Berg CD, Black WC, Clapp JD, Fagerstrom RM, Gareen IF, Gatsonis C, Marcus PM, Sicks JD (2011) Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med 365(5):395–409CrossRefGoogle Scholar
  26. Ohno Y, Koyama H, Yoshikawa T, Seki S, Takenaka D, Yui M, Lu A, Miyazaki M, Sugimura K (2016) Pulmonary high-resolution ultrashort TE MR imaging: comparison with thin-section standard- and low-dose computed tomography for the assessment of pulmonary parenchyma diseases. J Magn Reson Imaging 43(2):512–532CrossRefPubMedGoogle Scholar
  27. Rajaram S, Swift AJ, Capener D, Telfer A, Davies C, Hill C, Condliffe R, Elliot C, Hurdman J, Kiely DG, Wild JM (2012) Lung morphology assessment with balanced steady-state free precession MR imaging compared with CT. Radiology 263:569–577CrossRefPubMedGoogle Scholar
  28. Schroeder T, Ruehm SG, Debatin JF, Ladd ME, Barkhausen J, Goehde SC (2005) Detection of pulmonary nodules using a 2D HASTE MR sequence: comparison with MDCT. AJR Am J Roentgenol 185:979–984CrossRefPubMedGoogle Scholar
  29. Sommer G, Tremper J, Koenigkam-Santos M, Delorme S, Becker N, Biederer J, Kauczor HU, Heussel CP, Schlemmer HP, Puderbach M (2014) Lung nodule detection in a high-risk population: comparison of magnetic resonance imaging and low-dose computed tomography. Eur J Radiol 83(3):600–605CrossRefPubMedGoogle Scholar
  30. 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
  31. Wielpütz M, Kauczor HU (2012) MRI of the lung: state of the art. Diagn Interv Radiol 18(4):344–353PubMedGoogle Scholar
  32. Wild JM, Marshall H, Bock M, Schad LR, Jakob PM, Puderbach M, Molinari F, Van Beek EJ, Biederer J (2012) MRI of the lung (1/3): methods. Insights Imaging 3(4):345–353CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Department of RadiologyUniversity of BonnBonnGermany
  2. 2.Department of Cardiology, Pneumology and AngiologyUniversity of BonnBonnGermany
  3. 3.Department of SurgeryUniversity of BonnBonnGermany
  4. 4.Department of Oncology, Hematology, Immunooncology and RheumatologyUniversity of BonnBonnGermany

Personalised recommendations