European Radiology

, Volume 27, Issue 7, pp 2802–2809 | Cite as

Predictive factors for malignancy in incidental pulmonary nodules detected in breast cancer patients at baseline CT

  • Mark M. Hammer
  • Eduardo J. Mortani BarbosaJr.



Pulmonary nodules are commonly encountered at staging CTs in patients with extrathoracic malignancies, but their significance on a per-patient basis remains uncertain.


We undertook a retrospective analysis of pulmonary nodules identified in patients with a diagnosis of breast cancer from 2010 – 2015, evaluating nodules present at a baseline CT (i.e. prevalent nodules). We reviewed 211 patients with 248 individual nodules.


The rate of malignancy in prevalent nodules is low, approximately 13 %. Variables associated with metastasis include pleural studding, hilar lymphadenopathy and the presence of extrapulmonary metastasis, as well as number of nodules, nodule size and nodule shape. Using a combination of these factors, we have developed an evidence-based multivariate decision tree to predict which nodules are malignant in these patients, which is 91 % accurate and 100 % sensitive for metastasis.


We propose a simplified clinical prediction algorithm to guide radiologists and oncologists in managing patients with breast cancer and incidental pulmonary nodules.

Key points

Incidental pulmonary nodules are common on computed tomography in breast cancer patients.

Nodules present at baseline have a lower malignancy risk than incident nodules.

We present an evidence-based decision algorithm predicting which nodules are likely malignant.

This algorithm can help direct patient management.


Breast cancer Significance of lung nodules Prediction algorithm Incident lung nodule Prevalent lung nodule 



The scientific guarantor of this publication is Eduardo Barbosa. 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. The authors have significant statistical expertise. Institutional Review Board approval was obtained. Written informed consent was waived by the Institutional Review Board. Methodology: retrospective, diagnostic study, performed at one institution. Author contributions: MMH collected the data. MMH and EB analysed the data and wrote the manuscript.

Supplementary material

330_2016_4627_Fig5_ESM.gif (60 kb)

(GIF 59 kb)

330_2016_4627_MOESM1_ESM.eps (2.7 mb)
High resolution image (EPS 2760 kb)


  1. 1.
    Yip R, Henschke CI, Yankelevitz DF, Smith JP (2014) CT screening for lung cancer: alternative definitions of positive test result based on the national lung screening trial and international early lung cancer action program databases. Radiology 273:591–596CrossRefPubMedGoogle Scholar
  2. 2.
    MacMahon H, Austin JHM, 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
  3. 3.
    Brader P, Abramson SJ, Price AP et al (2011) Do characteristics of pulmonary nodules on computed tomography in children with known osteosarcoma help distinguish whether the nodules are malignant or benign? J Pediatr Surg 46:729–735CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Chang ST, Nguyen DC, Raptis C et al (2015) Natural history of preoperative subcentimeter pulmonary nodules in patients with resectable pancreatic adenocarcinoma: a retrospective cohort study. Ann Surg 261:970–975CrossRefPubMedGoogle Scholar
  5. 5.
    Griffiths SN, Shaikh I, Tam E, Wegstapel H (2012) Characterisation of indeterminate pulmonary nodules in colorectal cancer. Int J Surg Lond Engl 10:575–577CrossRefGoogle Scholar
  6. 6.
    Hanamiya M, Aoki T, Yamashita Y et al (2012) Frequency and significance of pulmonary nodules on thin-section CT in patients with extrapulmonary malignant neoplasms. Eur J Radiol 81:152–157CrossRefPubMedGoogle Scholar
  7. 7.
    Khokhar S, Vickers A, Moore MS et al (2006) Significance of non-calcified pulmonary nodules in patients with extrapulmonary cancers. Thorax 61:331–336CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Kim CH, Huh JW, Kim HR, Kim YJ (2015) Indeterminate pulmonary nodules in colorectal cancer: follow-up guidelines based on a risk predictive model. Ann Surg 261:1145–1152CrossRefPubMedGoogle Scholar
  9. 9.
    Lee B, Lim A, Lalvani A et al (2008) The clinical significance of radiologically detected silent pulmonary nodules in early breast cancer. Ann Oncol 19:2001–2006CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Madani A, Spicer J, Alcindor T et al (2014) Clinical significance of incidental pulmonary nodules in esophageal cancer patients. J Gastrointest Surg Off J Soc Surg Aliment Tract 18:226–232, discussion 232–233CrossRefGoogle Scholar
  11. 11.
    Mano R, Vertosick E, Sankin AI et al (2015) Subcentimeter pulmonary nodules are not associated with disease progression in patients with renal cell carcinoma. J Urol 193:776–782CrossRefPubMedGoogle Scholar
  12. 12.
    Munden RF, Erasmus JJ, Wahba H, Fineberg NS (2010) Follow-up of small (4 mm or less) incidentally detected nodules by computed tomography in oncology patients: a retrospective review. J Thorac Oncol Off Publ Int Assoc Study Lung Cancer 5:1958–1962Google Scholar
  13. 13.
    Murrell Z, Dickie B, Dasgupta R (2011) Lung nodules in pediatric oncology patients: a prediction rule for when to biopsy. J Pediatr Surg 46:833–837CrossRefPubMedGoogle Scholar
  14. 14.
    Nordholm-Carstensen A, Wille-Jørgensen PA, Jorgensen LN, Harling H (2013) Indeterminate pulmonary nodules at colorectal cancer staging: a systematic review of predictive parameters for malignancy. Ann Surg Oncol 20:4022–4030CrossRefPubMedGoogle Scholar
  15. 15.
    Quint LE, Park CH, Iannettoni MD (2000) Solitary pulmonary nodules in patients with extrapulmonary neoplasms. Radiology 217:257–261CrossRefPubMedGoogle Scholar
  16. 16.
    Quyn AJ, Matthews A, Daniel T et al (2012) The clinical significance of radiologically detected indeterminate pulmonary nodules in colorectal cancer. Colorectal Dis Off J Assoc Coloproctology G B Irel 14:828–831Google Scholar
  17. 17.
    Smyth EC, Hsu M, Panageas KS, Chapman PB (2012) Histology and outcomes of newly detected lung lesions in melanoma patients. Ann Oncol 23:577–582CrossRefPubMedGoogle Scholar
  18. 18.
    Varol Y, Varol U, Karaca B et al (2012) The frequency and significance of radiologically detected indeterminate pulmonary nodules in patients with colorectal cancer. Med Princ Pract Int J Kuwait Univ Health Sci Cent 21:457–461Google Scholar
  19. 19.
    Surveillance Research Program, NCI’s Division of Cancer Control and Population Sciences SEER Stat Fact Sheets: Female Breast Cancer. Accessed 6 Feb 2016
  20. 20.
    National Comprehensive Cancer Network Breast Cancer Panel (2016) NCCN clinical practice guidelines in oncology. Breast CancerGoogle Scholar
  21. 21.
    Moher D, Schulz KF, Altman DG, CONSORT GROUP (Consolidated Standards of Reporting Trials) (2001) The CONSORT statement: revised recommendations for improving the quality of reports of parallel-group randomized trials. Ann Intern Med 134:657–662CrossRefPubMedGoogle Scholar
  22. 22.
    American Joint Committee on Cancer (2009) Breast cancer stagingGoogle Scholar
  23. 23.
    Harris PA, Taylor R, Thielke R et al (2009) Research Electronic Data Capture (REDCap) - A metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 42:377–381CrossRefPubMedGoogle Scholar
  24. 24.
    Hall M, Frank E, Holmes G et al (2009) The WEKA data mining software: an update. SIGKDD Explor Newsl 11:10–18CrossRefGoogle Scholar
  25. 25.
    Quinlan JR (1993) C4.5: programs for machine learning. Morgan Kaufmann Publishers Inc, San FranciscoGoogle Scholar
  26. 26.
    Iqbal J, Ginsburg O, Rochon PA et al (2015) DIfferences in breast cancer stage at diagnosis and cancer-specific survival by race and ethnicity in the united states. JAMA 313:165–173CrossRefPubMedGoogle Scholar
  27. 27.
    Oshiro Y, Kusumoto M, Moriyama N et al (2002) Intrapulmonary lymph nodes: thin-section CT features of 19 nodules. J Comput Assist Tomogr 26:553–557CrossRefPubMedGoogle Scholar
  28. 28.
    Ahn MI, Gleeson TG, Chan IH et al (2010) Perifissural nodules seen at CT screening for lung cancer. Radiology 254:949–956CrossRefPubMedGoogle Scholar
  29. 29.
    Takashima S, Sone S, Li F et al (2003) Small solitary pulmonary nodules (≤1 cm) detected at population-based CT screening for lung cancer: reliable high-resolution CT features of benign lesions. Am J Roentgenol 180:955–964CrossRefGoogle Scholar

Copyright information

© European Society of Radiology 2016

Authors and Affiliations

  • Mark M. Hammer
    • 1
  • Eduardo J. Mortani BarbosaJr.
    • 1
  1. 1.Division of Cardiothoracic Imaging, Department of Radiology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaUSA

Personalised recommendations