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Variability of Semiautomated Lung Nodule Volumetry on Ultralow-Dose CT: Comparison with Nodule Volumetry on Standard-Dose CT

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Abstract

The study investigates the effect of a substantial dose reduction on the variability of lung nodule volume measurements by assessing and comparing nodule volumes using a dedicated semiautomated segmentation software on ultralow-dose computed tomography (ULD-CT) and standard-dose computed tomography (SD-CT) data. In 20 patients, thin-slice chest CT datasets (1 mm slice thickness; 20% reconstruction overlap) were acquired at ultralow-dose (120 kV, 5 mAs) and at standard-dose (120 kV, 75 mAs), respectively, and analyzed using the segmentation software OncoTREAT (MeVis, Bremen, Germany; version 1.3). Interobserver variability of volume measurements of 202 solid pulmonary nodules (mean diameter 11 mm, range 3.2–44.5 mm) was calculated for SD-CT and ULD-CT. With respect to interobserver variability, the 95% confidence interval for the relative differences in nodule volume in the intrascan analysis was measured with −9.7% to 8.3% (mean difference −0.7%) for SD-CT and with −12.6% to 12.4% (mean difference −0.2%) for ULD-CT. In the interscan analysis, the 95% confidence intervals for the differences in nodule volume ranged with −25.1% to −23.4% and 26.2% to 28.9% (mean difference 1.4% to 2.1%) dependent on the combination of readers and scans. Intrascan interobserver variability of volume measurements was comparable for ULD-CT and SD-CT data. The calculated variability of volume measurements in the interscan analysis was similar to the data reported in the literature for CT data acquired with equal radiation dose. Thus, the evaluated segmentation software provides nodule volumetry that appears to be independent of the dose level with which the CT source dataset is acquired.

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References

  1. Watanabe H, Yamamoto S, Kunitoh H, et al: Tumor response to chemotherapy: the validity and reproducibility of RECIST guidelines in NSCLC patients. Cancer Sci 94(11):1015–1020, 2003

    Article  CAS  PubMed  Google Scholar 

  2. Yankelevitz DF, Reeves AP, Kostis WJ, Zhao B, Henschke CI: Small pulmonary nodules: volumetrically determined growth rates based on CT evaluation. Radiology 217(1):251–256, 2000

    CAS  PubMed  Google Scholar 

  3. Winer-Muram HT, Jennings SG, Meyer CA, et al: Effect of varying CT section width on volumetric measurement of lung tumors and application of compensatory equations. Radiology 229(1):184–194, 2003

    Article  PubMed  Google Scholar 

  4. Ko JP, Rusinek H, Jacobs EL, et al: Small pulmonary nodules: volume measurement at chest CT—phantom study. Radiology 228(3):864–870, 2003

    Article  PubMed  Google Scholar 

  5. Revel MP, Lefort C, Bissery A, Bienvenu M, Aycard L, Chatellier G, Frija G: Pulmonary nodules: preliminary experience with three-dimensional evaluation. Radiology 231(2):459–466, 2004

    Article  PubMed  Google Scholar 

  6. Ko JP, Chang J, Bomsztyk E, Babb JS, Naidich DP, Rusinek H: Effect of CT image compression on computer-assisted lung nodule volume measurement. Radiology 237(1):83–88, 2005

    Article  PubMed  Google Scholar 

  7. Bolte H, Riedel C, Knoss N, et al: Computed tomography-based lung nodule volumetry—do optimized reconstructions of routine protocols achieve similar accuracy, reproducibility and interobserver variability to that of special volumetry protocols? Rofo 179(3):276–281, 2007

    CAS  PubMed  Google Scholar 

  8. Das M, Muhlenbruch G, Katoh M, et al: Automated volumetry of solid pulmonary nodules in a phantom: accuracy across different CT scanner technologies. Invest Radiol 42(5):297–302, 2007

    Article  PubMed  Google Scholar 

  9. Bolte H, Jahnke T, Schafer FK, et al: Interobserver-variability of lung nodule volumetry considering different segmentation algorithms and observer training levels. Eur J Radiol 64(2):285–295, 2007

    Article  CAS  PubMed  Google Scholar 

  10. Ravenel JG, Leue WM, Nietert PJ, et al: Pulmonary nodule volume: effects of reconstruction parameters on automated measurements—a phantom study. Radiology 247(2):400–408, 2008

    PubMed  Google Scholar 

  11. Larici AR, Storto ML, Torge M, et al: Automated volumetry of pulmonary nodules on multidetector CT: influence of slice thickness, reconstruction algorithm and tube current. Preliminary results. Radiol Med (Torino) 113(1):29–42, 2008

    Article  CAS  Google Scholar 

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

    Article  PubMed  Google Scholar 

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

    Article  PubMed  Google Scholar 

  14. Gietema HA, Wang Y, Xu D, et al: Pulmonary nodules detected at lung cancer screening: interobserver variability of semiautomated volume measurements. Radiology 241(1):251–257, 2006

    Article  PubMed  Google Scholar 

  15. Wormanns D, Kohl G, Klotz E, et al: Volumetric measurements of pulmonary nodules at multi-row detector CT: in vivo reproducibility. Eur Radiol 14(1):86–92, 2004

    Article  PubMed  Google Scholar 

  16. Goodman LR, Gulsun M, Washington L, Nagy PG, Piacsek KL: Inherent variability of CT lung nodule measurements in vivo using semiautomated volumetric measurements. AJR Am J Roentgenol 186(4):989–994, 2006

    Article  PubMed  Google Scholar 

  17. Bornemann L, Kuhnigk JM, Dicken V, et al: Informatics in radiology (infoRAD): new tools for computer assistance in thoracic CT part 2. Therapy monitoring of pulmonary metastases. Radiographics 25(3):841–848, 2005

    Article  PubMed  Google Scholar 

  18. Kuhnigk JM, Dicken V, Bornemann L, et al: Fast automated segmentation and reproducible volumetry of pulmonary metastases in CT-scans for therapy monitoring. IEEE Trans Med Imaging 25(4):417–434, 2006

    Article  PubMed  Google Scholar 

  19. Wormanns D, Diederich S, Lentschig MG, Winter F, Heindel W: Spiral CT of pulmonary nodules: interobserver variation in assessment of lesion size. Eur Radiol 10(5):710–713, 2000

    Article  CAS  PubMed  Google Scholar 

  20. Erasmus JJ, Gladish GW, Broemeling L, et al: Interobserver and intraobserver variability in measurement of non-small-cell carcinoma lung lesions: implications for assessment of tumor response. J Clin Oncol 21(13):2574–2582, 2003

    Article  PubMed  Google Scholar 

  21. Revel MP, Bissery A, Bienvenu M, Aycard L, Lefort C, Frija G: Are two-dimensional CT measurements of small noncalcified pulmonary nodules reliable? Radiology 231(2):453–458, 2004

    Article  PubMed  Google Scholar 

  22. Goo JM, Tongdee T, Tongdee R, Yeo K, Hildebolt CF, Bae KT: 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(3):850–856, 2005

    Article  PubMed  Google Scholar 

  23. Boll DT, Gilkeson RC, Fleiter TR, Blackham KA, Duerk JL, Lewin JS: Volumetric assessment of pulmonary nodules with ECG-gated MDCT. AJR Am J Roentgenol 183(5):1217–1223, 2004

    PubMed  Google Scholar 

  24. Volterrani L, Mazzei MA, Scialpi M, et al: Three-dimensional analysis of pulmonary nodules by MSCT with Advanced Lung Analysis (ALA1) software. Radiol Med (Torino) 111(3):343–354, 2006

    Article  CAS  Google Scholar 

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Correspondence to Patrick A. Hein.

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Hein, P.A., Romano, V.C., Rogalla, P. et al. Variability of Semiautomated Lung Nodule Volumetry on Ultralow-Dose CT: Comparison with Nodule Volumetry on Standard-Dose CT. J Digit Imaging 23, 8–17 (2010). https://doi.org/10.1007/s10278-008-9157-5

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  • DOI: https://doi.org/10.1007/s10278-008-9157-5

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