Skip to main content
SpringerLink
Log in

Accuracy of automated volumetry of pulmonary nodules across different multislice CT scanners

  • Experimental
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

The purpose of this study was to compare the accuracy of an automated volumetry software for phantom pulmonary nodules across various 16-slice multislice spiral CT (MSCT) scanners from different vendors. A lung phantom containing five different nodule categories (intraparenchymal, around a vessel, vessel attached, pleural, and attached to the pleura), with each category comprised of 7–9 nodules (total, n = 40) of varying sizes (diameter 3–10 mm; volume 6.62 mm3–525 mm3), was scanned with four different 16-slice MSCT scanners (Siemens, GE, Philips, Toshiba). Routine and low-dose chest protocols with thin and thick collimations were applied. The data from all scanners were used for further analysis using a dedicated prototype volumetry software. Absolute percentage volume errors (APE) were calculated and compared. The mean APE for all nodules was 8.4% (±7.7%) for data acquired with the 16-slice Siemens scanner, 14.3% (±11.1%) for the GE scanner, 9.7% (±9.6%) for the Philips scanner and 7.5% (±7.2%) for the Toshiba scanner, respectively. The lowest APEs were found within the diameter size range of 5–10 mm and volumes >66 mm3. Nodule volumetry is accurate with a reasonable volume error in data from different scanner vendors. This may have an important impact for intraindividual follow-up studies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Wormanns D, Ludwig K, Beyer F, Heindel W, Diederich S (2005) Detection of pulmonary nodules at multirow-detector CT: effectiveness of double reading to improve sensitivity at standard-dose and low-dose chest CT. Eur Radiol 15:14–22

    Article  PubMed  Google Scholar 

  2. Valencia R, Denecke T, Lehmkuhl L, Fischbach F, Felix R, Knollmann F (2006) Value of axial and coronal maximum intensity projection (MIP) images in the detection of pulmonary nodules by multislice spiral CT: comparison with axial 1-mm and 5-mm slices. Eur Radiol 16:325–332

    Article  PubMed  Google Scholar 

  3. Takashima S, Sone S, Li F, Maruyama Y, Hasegawa M, Kadoya M (2003) Indeterminate solitary pulmonary nodules revealed at population-based CT screening of the lung: using first follow-up diagnostic CT to differentiate benign and malignant lesions. AJR Am J Roentgenol 180:1255–1263

    PubMed  Google Scholar 

  4. Tan BB, Flaherty KR, Kazerooni EA, Iannettoni MD (2003) The solitary pulmonary nodule. Chest 123:89S–96S

    Article  PubMed  Google Scholar 

  5. Diederich S, Wormanns D, Semik M et al (2002) Screening for early lung cancer with low-dose spiral CT: prevalence in 817 asymptomatic smokers. Radiology 222:773–781

    Article  PubMed  Google Scholar 

  6. Henschke CI, McCauley DI, Yankelevitz DF et al (1999) Early Lung Cancer Action Project: overall design and findings from baseline screening. Lancet 354:99–105

    Article  PubMed  CAS  Google Scholar 

  7. Henschke CI, Naidich DP, Yankelevitz DF et al (2001) Early lung cancer action project: initial findings on repeat screenings. Cancer 92:153–159

    Article  PubMed  CAS  Google Scholar 

  8. Sone S, Takashima S, Li F et al (1998) Mass screening for lung cancer with mobile spiral computed tomography scanner. Lancet 351:1242–1245

    Article  PubMed  CAS  Google Scholar 

  9. Swensen SJ, Jett JR, Hartman TE et al (2003) Lung cancer screening with CT: Mayo Clinic experience. Radiology 226:756–761

    Article  PubMed  Google Scholar 

  10. Diederich S, Hansen J, Wormanns D (2005) Resolving small pulmonary nodules: CT features. Eur Radiol 15:2064–2069

    Article  PubMed  CAS  Google Scholar 

  11. 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 237:395–400

    Article  PubMed  Google Scholar 

  12. Bogot NR, Kazerooni EA, Kelly AM, Quint LE, Desjardins B, Nan B (2005) Interobserver and intraobserver variability in the assessment of pulmonary nodule size on CT using film and computer display methods. Acad Radiol 12:948–956

    Article  PubMed  Google Scholar 

  13. Marten K, Auer F, Schmidt S, Kohl G, Rummeny EJ, Engelke C (2006) Inadequacy of manual measurements compared to automated CT volumetry in assessment of treatment response of pulmonary metastases using RECIST criteria. Eur Radiol 16:781–790

    Article  PubMed  Google Scholar 

  14. Marten K, Engelke C, Grabbe E, Rummeny EJ (2004) [Flat-panel detector-based computed tomography: accuracy of experimental growth rate assessment in pulmonary nodules]. Rofo 176:752–757

    PubMed  CAS  Google Scholar 

  15. Marten K, Funke M, Engelke C (2004) Flat panel detector-based volumetric CT: prototype evaluation with volumetry of small artificial nodules in a pulmonary phantom. J Thorac Imaging 19:156–163

    Article  PubMed  Google Scholar 

  16. Wiemker R, Rogalla P, Blaffert T et al (2005) Aspects of computer-aided detection (CAD) and volumetry of pulmonary nodules using multislice CT. Br J Radiol 78 Spec No:S46–S56

    Article  PubMed  Google Scholar 

  17. Wormanns D, Kohl G, Klotz E et al (2004) Volumetric measurements of pulmonary nodules at multi-row detector CT: in vivo reproducibility. Eur Radiol 14:86–92

    Article  PubMed  Google Scholar 

  18. Yankelevitz DF, Reeves AP, Kostis WJ, Zhao B, Henschke CI (2000) Small pulmonary nodules: volumetrically determined growth rates based on CT evaluation. Radiology 217:251–256

    PubMed  CAS  Google Scholar 

  19. Boll DT, Gilkeson RC, Fleiter TR, Blackham KA, Duerk JL, Lewin JS (2004) Volumetric assessment of pulmonary nodules with ECG-gated MDCT. AJR Am J Roentgenol 183:1217–1223

    PubMed  Google Scholar 

  20. Mullally W, Betke M, Wang J, Ko JP (2004) Segmentation of nodules on chest computed tomography for growth assessment. Med Phys 31:839–848

    Article  PubMed  Google Scholar 

  21. Bolte H, Riedel C, Jahnke T et al (2006) Reproducibility of computer-aided volumetry of artificial small pulmonary nodules in ex vivo porcine lungs. Invest Radiol 41:28–35

    Article  PubMed  Google Scholar 

  22. Goo JM, Tongdee T, Tongdee R, Yeo K, Hildebolt CF, Bae KT (2005) Volumetric measurement of synthetic lung nodules with multi-detector row CT: effect of various image reconstruction parameters and segmentation thresholds on measurement accuracy. Radiology 235:850–856

    Article  PubMed  Google Scholar 

  23. Ko JP, Rusinek H, Jacobs EL et al (2003) Small pulmonary nodules: volume measurement at chest CT-phantom study. Radiology 228:864–870

    Article  PubMed  Google Scholar 

  24. Shin HO, Blietz M, Frericks B, Baus S, Savellano D, Galanski M (2006) Insertion of virtual pulmonary nodules in CT data of the chest: development of a software tool. Eur Radiol 16:2567–2574 Nov

    Article  PubMed  Google Scholar 

  25. Benjamin MS, Drucker EA, McLoud TC, Shepard JA (2003) Small pulmonary nodules: detection at chest CT and outcome. Radiology 226:489–493

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Diagnostic Radiology, RWTH Aachen University, Pauwelsstrasse 30, 52072, Aachen, Germany

    Marco Das, Georg Mühlenbruch, Andreas H. Mahnken, Markus Katoh, Rolf W. Günther & Joachim E. Wildberger

  2. Department of Radiology, German Cancer Research Center, Heidelberg, Germany

    Julia Ley-Zaporozhan & Hans-Ulrich Kauczor

  3. Department of Diagnostic Radiology, University Hospital Utrecht, Utrecht, The Netherlands

    H. A. Gietema & Mathias Prokop

  4. Department of Diagnostic Radiology, Marienhospital Düsseldorf, Düsseldorf, Germany

    Andre Czech & Stefan Diederich

  5. CT Division, Siemens Medical Solutions, Forchheim, Germany

    Annemarie Bakai

  6. CAD Applications, Siemens Medical Solutions, Malvern, PA, USA

    Marcos Salganicoff

Authors
  1. Marco Das
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Julia Ley-Zaporozhan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. H. A. Gietema
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Andre Czech
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Georg Mühlenbruch
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Andreas H. Mahnken
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Markus Katoh
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Annemarie Bakai
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Marcos Salganicoff
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Stefan Diederich
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Mathias Prokop
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Hans-Ulrich Kauczor
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Rolf W. Günther
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Joachim E. Wildberger
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Marco Das.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Das, M., Ley-Zaporozhan, J., Gietema, H.A. et al. Accuracy of automated volumetry of pulmonary nodules across different multislice CT scanners. Eur Radiol 17, 1979–1984 (2007). https://doi.org/10.1007/s00330-006-0562-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-006-0562-1

Keywords

Search

Navigation