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Automated measurement of lymph nodes: a phantom study

  • Oncology
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Abstract

The purpose of this study was to assess the accuracy of automated nodal quantification in a phantom. MDCT of a phantom with 17 synthetic lymph nodes of different sizes (diameter 6.0–30.0 mm) was performed at varying tube currents, reconstruction kernels and slice thicknesses. RECIST diameter and volume were measured using an automated software tool. Results were compared with the reference diameter and volume by calculating the absolute percentage error (APE). Degree of agreement between software and reference measurements was evaluated by computing corresponding concordance correlation coefficients (CCC). Under varying tube currents the mean APE (CCC) varied between 5.18% and 10.12% (0.95–0.99) for RECIST diameter and between 7.22% and 16.21% (0.94–1.00) for the volume. At different reconstruction kernels the mean APE values ranged between 7.20% and 7.55% (0.99) (RECIST) and between 8.96% and 14.42% (1.00) (volume). With different slice thicknesses the mean APE values differed from 5.81% to 9.20% (0.97–0.99) (RECIST) and from 8.16% to 22.66% (0.99–1.00) (volume). Regarding RECIST criteria and volume, automated evaluation of lymph nodes in a phantom demonstrated a high accuracy under varying MDCT parameters.

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References

  1. Golder WA (2004) Lymph node diagnosis in oncologic imaging: a dilemma still waiting to be solved. Onkologie 27:194–199

    Article  PubMed  CAS  Google Scholar 

  2. Barrett T, Choyke PL, Kobayashi H (2006) Imaging of the lymphatic system: new horizons. Contrast Media Mol Imaging 1:230–245

    Article  PubMed  CAS  Google Scholar 

  3. Kwee TC, Kwee RM, Nievelstein RA (2008) Imaging in staging of malignant lymphoma: a systematic review. Blood 111:504–516

    Article  PubMed  CAS  Google Scholar 

  4. Miller AB, Hoogstraten B, Staquet M et al (1981) Reporting results of cancer treatment. Cancer 47:207–214

    Article  PubMed  CAS  Google Scholar 

  5. James K, Eisenhauer E, Christian M et al (1999) Measuring response in solid tumors: unidimensional versus bidimensional measurement. J Natl Cancer Inst 91:523–528

    Article  PubMed  CAS  Google Scholar 

  6. Therasse P, Arbuck SG, Eisenhauer EA et al (2000) New guidelines to evaluate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada. J Natl Cancer Inst 92:205–216

    Article  PubMed  CAS  Google Scholar 

  7. Prasad SR, Jhaveri KS, Saini S et al (2002) CT tumor measurement for therapeutic response assessment: comparison of unidimensional, bidimensional, and volumetric techniques initial observations. Radiology 225:416–419

    Article  PubMed  Google Scholar 

  8. Heussel CP, Meier S, Wittelsberger S et al (2007) Follow-up CT measurement of liver malignoma according to RECIST and WHO vs. volumetry. Fortschr Röntgenstr 179:958–964

    Article  CAS  Google Scholar 

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

    Article  PubMed  Google Scholar 

  10. Marten K, Auer F, Schmidt S et al (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 

  11. Keil S, Behrendt FF, Stanzel S et al (2008) Semi-automated measurement of hyperdense, hypodense and heterogeneous hepatic metastasis on standard MDCT slices. Comparison of semi-automated and manual measurement of RECIST and WHO criteria. Eur Radiol 18(11):2456–2465

    Article  PubMed  Google Scholar 

  12. Fabel M, von Tengg-Kobligk H, Giesel FL et al (2008) Semi-automated volumetric analysis of lymph node metastases in patients with malignant melanoma stage III/IV—a feasibility study. Eur Radiol 18:1114–1122

    Article  PubMed  CAS  Google Scholar 

  13. 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 25:417–434

    Article  PubMed  Google Scholar 

  14. Bornemann L, Dicken V, Kuhnigk JM et al (2007) OncoTREAT: a software assistant for cancer therapy monitoring. Int J Comput Assist Radiol Surg 1:231–242

    Article  Google Scholar 

  15. Goo JM, Tongdee T, Tongdee R et al (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 

  16. Lin LIK (1989) A concordance correlation coefficient to evaluate reproducibility. Biometrics 45:255–268

    Article  PubMed  CAS  Google Scholar 

  17. Yankelevitz DF, Gupta R, Zhao B et al (1999) Small pulmonary nodules: evaluation with repeat CT-preliminary experience. Radiology 212:561–566

    PubMed  CAS  Google Scholar 

  18. 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 

Download references

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Authors and Affiliations

  1. Department of Diagnostic Radiology, University Hospital, RWTH Aachen University, Pauwelsstrasse 30, 52074, Aachen, Germany

    Sebastian Keil, Cedric Plumhans, Florian F. Behrendt, Georg Mühlenbruch, Andreas H. Mahnken, Rolf W. Günther & Marco Das

  2. Institute of Medical Statistics, University Hospital, RWTH Aachen University, Aachen, Germany

    Sven Stanzel

  3. Siemens Medical Solutions, Forchheim, Germany

    Michael Suehling

Authors
  1. Sebastian Keil
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  2. Cedric Plumhans
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  3. Florian F. Behrendt
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  4. Sven Stanzel
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  5. Michael Suehling
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  6. Georg Mühlenbruch
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  7. Andreas H. Mahnken
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  8. Rolf W. Günther
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  9. Marco Das
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Correspondence to Sebastian Keil.

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Keil, S., Plumhans, C., Behrendt, F.F. et al. Automated measurement of lymph nodes: a phantom study. Eur Radiol 19, 1079–1086 (2009). https://doi.org/10.1007/s00330-008-1254-9

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  • DOI: https://doi.org/10.1007/s00330-008-1254-9

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