European Radiology

, Volume 25, Issue 4, pp 1040–1047 | Cite as

Interscan variation of semi-automated volumetry of subsolid pulmonary nodules

  • Ernst Th. Scholten
  • Pim A. de Jong
  • Colin Jacobs
  • Bram van Ginneken
  • Sarah van Riel
  • Martin J. Willemink
  • Rozemarijn Vliegenthart
  • Matthijs Oudkerk
  • Harry J. de Koning
  • Nanda Horeweg
  • Mathias Prokop
  • Willem P. Th. M. Mali
  • Hester A. Gietema
Computed Tomography

Abstract

Rationale

We aimed to test the interscan variation of semi-automatic volumetry of subsolid nodules (SSNs), as growth evaluation is important for SSN management.

Methods

From a lung cancer screening trial all SSNs that were stable over at least 3 months were included (N = 44). SSNs were quantified on the baseline CT by two observers using semi-automatic volumetry software for effective diameter, volume, and mass. One observer also measured the SSNs on the second CT 3 months later. Interscan variation was evaluated using Bland-Altman plots. Observer agreement was calculated as intraclass correlation coefficient (ICC). Data are presented as mean (± standard deviation) or median and interquartile range (IQR). A Mann-Whitney U test was used for the analysis of the influence of adjustments on the measurements.

Results

Semi-automatic measurements were feasible in all 44 SSNs. The interscan limits of agreement ranged from -12.0 % to 9.7 % for diameter, -35.4 % to 28.6 % for volume and -27.6 % to 30.8 % for mass. Agreement between observers was good with intraclass correlation coefficients of 0.978, 0.957, and 0.968 for diameter, volume, and mass, respectively.

Conclusion

Our data suggest that when using our software an increase in mass of 30 % can be regarded as significant growth.

Key Points

Recently, recommendations regarding subsolid nodules have stressed the importance of growth quantification.

Volumetric measurement of subsolid nodules is feasible with good interscan agreement.

Increase of mass of 30 % can be regarded as significant growth.

Keywords

Subsolid pulmonary nodules Computer-aided diagnosis Computed tomography Lung cancer Screening 

Notes

Acknowledgements

The scientific guarantor of this publication is Prof. Dr. W.P.Th.M.Mali. The authors of this manuscript declare relationships with the following companies: Prof. Dr. B. van Ginneken is affiliated with Fraunhofer MeVis, Bremen, Germany. The NELSON trial has received funding from Zorg Onderzoek Nederland-Medische Wetenschappen (ZonMw), KWF Kankerbestrijding, Stichting Centraal Fonds Reserves van Voormalig Vrijwillige Ziekenfondsverzekeringen (RvvZ), G. Ph. Verhagen Foundation, Rotterdam Oncologic Thoracic Study Group (ROTS) and Erasmus Trust Fund, Stichting tegen Kanker, Vlaamse Liga tegen Kanker, and LOGO Leuven and Hageland. One of the authors has significant statistical expertise. No complex statistical methods were necessary for this paper. Institutional review board approval was obtained. Written informed consent was obtained from all subjects (patients) in this study. Methodology: retrospective, observational, multicenter study/performed at one institution.

References

  1. 1.
    Hansell DM, Bankier AA, MacMahon H, McLoud TC, Muller NL, Remy J (2008) Fleischner society: glossary of terms for thoracic imaging. Radiology 246:697–722CrossRefPubMedGoogle Scholar
  2. 2.
    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
  3. 3.
    Kim HY, Shim YM, Lee KS, Han J, Yi CA, Kim YK (2007) Persistent pulmonary nodular ground-glass opacity at thin-section ct: histopathologic comparisons. Radiology 245:267–275CrossRefPubMedGoogle Scholar
  4. 4.
    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
  5. 5.
    de Hoop B, Gietema H, van de Vorst S, Murphy K, van Klaveren RJ, Prokop M (2010) Pulmonary ground-glass nodules: increase in mass as an early indicator of growth. Radiology 255:199–206CrossRefPubMedGoogle Scholar
  6. 6.
    Kuhnigk JM, Dicken V, Bornemann L et al (2006) Morphological segmentation and partial volume analysis for volumetry of solid pulmonary lesions in thoracic CT scans IEEE Trans. Med Imaging 25:417–434CrossRefGoogle Scholar
  7. 7.
    Park CM, Goo JM, Lee HJ et al (2010) Persistent pure ground-glass nodules in the lung: interscan variability of semiautomated volume and attenuation measurements. AJR Am J Roentgenol 195:408–414CrossRefGoogle Scholar
  8. 8.
    Kim H, Park CM, Woo S et al (2013) Pure and part-solid pulmonary ground-glass nodules: measurement variability of volume and mass in nodules with a solid portion less than or equal to 5 mm. Radiology 269:585–593CrossRefPubMedGoogle Scholar
  9. 9.
    Godoy MC, Naidich DP (2012) Overview and strategic management of subsolid pulmonary nodules. J Thorac Imaging 27:240–248CrossRefPubMedGoogle Scholar
  10. 10.
    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
  11. 11.
    Scholten ET, Jacobs C, van Ginneken B et al (2013) Computer aided segmentation and volumetry of artificial ground glass nodules on chest computed tomography. AJR Am J Roentgenol 201:295–300CrossRefPubMedGoogle Scholar
  12. 12.
    Scholten ET, de Hoop B, Jacobs C et al (2013) Semi-automatic quantification of subsolid pulmonary nodules: comparison with manual Measurements. PLoS One 21:8(11)Google Scholar

Copyright information

© European Society of Radiology 2014

Authors and Affiliations

  • Ernst Th. Scholten
    • 1
    • 2
  • Pim A. de Jong
    • 1
  • Colin Jacobs
    • 3
  • Bram van Ginneken
    • 3
    • 4
  • Sarah van Riel
    • 3
  • Martin J. Willemink
    • 1
  • Rozemarijn Vliegenthart
    • 5
    • 6
  • Matthijs Oudkerk
    • 6
  • Harry J. de Koning
    • 7
  • Nanda Horeweg
    • 7
    • 8
  • Mathias Prokop
    • 9
  • Willem P. Th. M. Mali
    • 1
  • Hester A. Gietema
    • 1
  1. 1.Department of RadiologyUniversity Medical CenterUtrechtThe Netherlands
  2. 2.Department of RadiologyKennemer GasthuisHaarlemThe Netherlands
  3. 3.Diagnostic Image Analysis GroupRadboud University Medical CenterNijmegenThe Netherlands
  4. 4.Fraunhofer MEVISBremenGermany
  5. 5.Department of RadiologyUniversity of Groningen, University Medical Center GroningenGroningenThe Netherlands
  6. 6.Center for Medical Imaging-North East NetherlandsUniversity of Groningen, University Medical Centre GroningenGroningenThe Netherlands
  7. 7.Department of Public HealthErasmus Medical CenterRotterdamThe Netherlands
  8. 8.Department of PulmonologyErasmus Medical CenterRotterdamThe Netherlands
  9. 9.Department of RadiologyRadboud University Medical CenterNijmegenThe Netherlands

Personalised recommendations