European Radiology

, Volume 26, Issue 9, pp 2915–2920 | Cite as

Magnetic resonance imaging of pulmonary nodules: accuracy in a granulomatous disease–endemic region

  • Natália Henz ConcattoEmail author
  • Guilherme Watte
  • Edson Marchiori
  • Klaus Irion
  • José Carlos Felicetti
  • José Jesus Camargo
  • Bruno Hochhegger
Magnetic Resonance



To estimate the diagnostic accuracy of signal intensity of the lesion-to-spinal cord ratio (LSR) and apparent diffusion coefficient (ADC) in diffusion-weighted (DW) magnetic resonance imaging of pulmonary nodules suspicious for lung cancer in granulomatous lung disease-endemic regions.


Forty-nine patients with indeterminate solitary pulmonary nodules detected by chest computed tomography and histopathologically confirmed diagnoses were included in the study. DW images were analysed semiquantitatively by focusing regions of interest on the lesion and spinal cord at the same level (for LSR calculation). ADCs were estimated from ratios of the two image signal intensities. Ratios of T1 and T2 signal intensity between nodules and muscle were calculated for comparison.


Mean ADCs ± standard deviations for lung cancer and benign lesions were 0.9 ± 0.2 and 1.3 ± 0.2 × 10-3 mm2/s, respectively. Mean LSRs were 1.4 ± 0.3 for lung cancer and 1 ± 0.1 for benign lesions. ADCs and LSRs differed significantly between malignant and benign lesions (P < 0.001). Mean T2 signal intensity ratios also differed significantly between benign and malignant lesions (0.8 ± 0.2 vs. 1.6 ± 0.2; P < 0.05).


DWI can help to differentiate malignant from benign lesions according to ADC and the LSR with good accuracy.

Key Points

DW imaging can help differentiate malignant from benign pulmonary nodules.

ADC and LSR signal intensities had only small overlap between malignant and benign pulmonary nodules.

Mean T2 signal intensity ratios differed significantly between benign and malignant lesions.


Magnetic resonance imaging Pulmonary nodules Granulomatous disease-endemic region Diffusion weighted Differentiation of malignant from benign lesions 



The authors thank Prof. Dr. Hans Ulrich Kauczor for his teachings, availability and great incentive to the development of magnetic resonance imaging of the chest in our country, without whom this study would not be possible. The scientific guarantor of this publication is Bruno Hochhegger. 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. The authors state that this work has not received any funding.

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. Methodology: cross sectional study, performed at one institution.


  1. 1.
    Santos MK, Elias J Jr, Mauad FM, Muglia VF, Trad CS (2011) Magnetic resonance imaging of the chest: current and new applications, with an emphasis on pulmonology. J Bras Pneumol 37:242–258CrossRefPubMedGoogle Scholar
  2. 2.
    Hochhegger B, Marchiori E, Irion K, Souza AS Jr, Volkart J, Rubin AS (2012) Magnetic resonance of the lung: a step forward in the study of lung disease. J Bras Pneumol 38:105–115CrossRefPubMedGoogle Scholar
  3. 3.
    Koyama H, Ohno Y, Seki S et al (2013) Magnetic resonance imaging for lung cancer. J Thorac Imaging 28:138–150CrossRefPubMedGoogle Scholar
  4. 4.
    Wang YX, Lo GG, Yuan J, Larson PE, Zhang X (2014) Magnetic resonance imaging for lung cancer screen. J Thorac Dis 6:1340–1348PubMedPubMedCentralGoogle Scholar
  5. 5.
    Luna A, Sánchez-Gonzalez J, Caro P (2011) Diffusion-weighted imaging of the chest. Magn Reson Imaging Clin N Am 19:69–94CrossRefPubMedGoogle Scholar
  6. 6.
    Liu H, Liu Y, Yu T, Ye N (2010) Usefulness of diffusion-weighted MR imaging in the evaluation of pulmonary lesions. Eur Radiol 20:807–815CrossRefPubMedGoogle Scholar
  7. 7.
    Uto T, Takehara Y, Nakamura Y et al (2009) Higher sensitivity and specificity for diffusion-weighted imaging of malignant lung lesions without apparent diffusion coefficient quantification. Radiology 252:247–254CrossRefPubMedGoogle Scholar
  8. 8.
    Kanauchi N, Oizumi H, Honma T et al (2009) Role of diffusion-weighted magnetic resonance imaging for predicting of tumor invasiveness for clinical stage IA non-small cell lung cancer. Eur J Cardiothorac Surg 35:706–710, discussion 710-1CrossRefPubMedGoogle Scholar
  9. 9.
    Kurihara Y, Matsuoka S, Yamashiro T et al (2014) MRI of pulmonary nodules. AJR Am J Roentgenol 202:W210–W216CrossRefPubMedGoogle Scholar
  10. 10.
    Li B, Li Q, Chen C, Guan Y, Liu S (2014) A systematic review and meta-analysis of the accuracy of diffusion-weighted MRI in the detection of malignant pulmonary nodules and masses. Acad Radiol 21:21–29CrossRefPubMedGoogle Scholar
  11. 11.
    Koyama H, Ohno Y, Seki S et al (2015) Value of diffusion-weighted MR imaging using various parameters for assessment and characterization of solitary pulmonary nodules. Eur J Radiol 84:509–515CrossRefPubMedGoogle Scholar
  12. 12.
    Ohno Y, Koyama H, Takenaka D et al (2008) Dynamic MRI, dynamic multidetector-row computed tomography (MDCT), and coregistered 2-[fluorine-18]-fluoro-2-deoxy-D-glucose-positron emission tomography (FDG-PET)/CT: comparative study of capability for management of pulmonary nodules. J Magn Reson Imaging 27:1284–1295CrossRefPubMedGoogle Scholar
  13. 13.
    Deppen SA, Blume JD, Kensinger CD et al (2014) Accuracy of FDG-PET to diagnose lung cancer in areas with infectious lung disease: a meta-analysis. JAMA 312:1227–1236CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Deppen S, Putnam JB Jr, Andrade G et al (2011) Accuracy of FDG-PET to diagnose lung cancer in a region of endemic granulomatous disease. Ann Thorac Surg 92:428–432, discussion 433CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    MacMahon H, Austin JH, Gamsu G et al (2005) Fleischner Society. Guidelines for management of small pulmonary nodules detected on CT scans: a statement from the Fleischner Society. Radiology 237:395–400CrossRefPubMedGoogle Scholar

Copyright information

© European Society of Radiology 2015

Authors and Affiliations

  • Natália Henz Concatto
    • 1
    • 7
    Email author
  • Guilherme Watte
    • 2
  • Edson Marchiori
    • 3
  • Klaus Irion
    • 4
  • José Carlos Felicetti
    • 5
  • José Jesus Camargo
    • 5
  • Bruno Hochhegger
    • 6
  1. 1.University of Caxias do SulCaxias do SulBrazil
  2. 2.Medical Imaging Research LaboratoryFederal University of Health Sciences of Porto AlegrePorto AlegreBrazil
  3. 3.Department of RadiologyFederal University of Rio de JaneiroRio de JaneiroBrazil
  4. 4.Department of RadiologyLiverpool Heart and Chest Hospital NHS Foundation TrustLiverpoolUK
  5. 5.Department of Thoracic SurgerySanta Casa Hospital ComplexPorto AlegreBrazil
  6. 6.Department of RadiologySanta Casa Hospital ComplexPorto AlegreBrazil
  7. 7.Caxias do SulBrazil

Personalised recommendations