Influence of lung nodule margin on volume- and diameter-based reader variability in cT lung cancer screening

British Journal of Radiology

Volumn 91, Issue 1090, 2018, Pages

  Han, Daiwei ^a   Heuvelmans, Marjolein A ^a,b   Vliegenthart, Rozemarijn ^a   Rook, Mieneke ^a   Dorrius, Monique D ^a   De Jonge, Gonda J ^a   Walter, Joan E ^a   Van Ooijen, Peter M A ^a   De Koning, Harry J ^c   Oudkerk, Matthijs ^a  

^a UNIVERSITY MEDICAL CENTER GRONINGEN   (Netherlands)

^b MEDISCH SPECTRUM TWENTE   (Netherlands)

^c ERASMUS MEDICAL CENTER   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER ASSISTED DIAGNOSIS; DIAGNOSTIC IMAGING; HUMAN; LUNG NODULE; LUNG TUMOR; MIDDLE AGED; PATHOLOGY; PROCEDURES; RADIATION DOSE; X-RAY COMPUTED TOMOGRAPHY;

HUMANS; LUNG NEOPLASMS; MIDDLE AGED; RADIATION DOSAGE; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; SOLITARY PULMONARY NODULE; TOMOGRAPHY, X-RAY COMPUTED;

EID: 85046279056     PISSN: 00071285     EISSN: 1748880X     Source Type: Journal    
DOI: 10.1259/bjr.20170405     Document Type: Article

References (33)

1. National Lung Screening Trial Research Team, Aberle DR, Adams AM, Berg CD, Black WC, Clapp JD, et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med 2011; 365: 395-409. doi: https://doi.org/10.1056/ NEJMoa1102873
2. Pinsky PF, Gierada DS, Nath PH, Kazerooni E, Amorosa J. National lung screening trial: variability in nodule detection rates in chest CT studies. Radiology 2013; 268: 865-73. doi: https://doi.org/10.1148/radiol.13121530
3. Callister ME, Baldwin DR, Akram AR, Barnard S, Cane P, Draffan J, et al. British Thoracic Society guidelines for the investigation and management of pulmonary nodules. Thorax 2015; 70(Suppl 2): ii1-ii54. doi: https://doi.org/10.1136/thoraxjnl-2015-207168
4. Lung CT Screening Reporting and Data System (Lung-RADSTM). American College of Radiology. 2016. Available from: http://www.acr.org/Quality-Safety/Resources/LungRADS [cited 10 August 2016].
5. MacMahon H, Naidich DP, Goo JM, Lee KS, Leung ANC, Mayo JR, et al. Guidelines for management of incidental pulmonary nodules detected on CT images: from the fleischner society 2017. Radiology 2017; 284: 228-43. doi: https://doi.org/10.1148/radiol.2017161659
6. van Klaveren RJ, Oudkerk M, Prokop M, Scholten ET, Nackaerts K, Vernhout R, et al. Management of lung nodules detected by volume CT scanning. N Engl J Med 2009; 361: 2221-9. doi: https://doi.org/10.1056/ NEJMoa0906085
7. Pedersen JH, Ashraf H, Dirksen A, Bach K, Hansen H, Toennesen P, et al. The Danish randomized lung cancer CT screening trial-overall design and results of the prevalence round. J Thorac Oncol Off Publ Int Assoc Study Lung Cancer 2009; 4: 608-14. doi: https://doi.org/10.1097/JTO. 0b013e3181a0d98f
8. Xie X, Zhao Y, Snijder RA, van Ooijen PM, de Jong PA, Oudkerk M, et al. Sensitivity and accuracy of volumetry of pulmonary nodules on low-dose 16- and 64-row multi-detector CT: an anthropomorphic phantom study. Eur Radiol 2013; 23: 139-47. doi: https://doi.org/10.1007/s00330-012-2570-7
9. Zhang L, Yankelevitz DF, Henschke CI, Jirapatnakul AC, Reeves AP, Carter D. Zone of transition: a potential source of error in tumor volume estimation. Radiology 2010; 256: 633-9. doi: https://doi.org/10.1148/radiol.10090924
10. Das M, Ley-Zaporozhan J, Gietema HA, Czech A, Mühlenbruch G, Mahnken AH, et al. Accuracy of automated volumetry of pulmonary nodules across different multislice CT scanners. Eur Radiol 2007; 17: 1979-84. doi: https://doi.org/10.1007/ s00330-006-0562-1
11. Marten K, Funke M, Engelke C. Flat panel detector-based volumetric CT: prototype evaluation with volumetry of small artificial nodules in a pulmonary phantom. J Thorac Imaging 2004; 19: 156-63.
12. Tao P, Griess F, Lvov Y, Mineyev M, Zhao B, Levin D, et al. Characterization of small nodules by automatic segmentation of X-ray computed tomography images. J Comput Assist Tomogr 2004; 28: 372-7.
13. Way TW, Chan HP, Goodsitt MM, Sahiner B, Hadjiiski LM, Zhou C, et al. Effect of CT scanning parameters on volumetric measurements of pulmonary nodules by 3D active contour segmentation: a phantom study. Phys Med Biol 2008; 53: 1295-312. doi: https://doi.org/10.1088/0031-9155/53/5/009
14. Yankelevitz DF, Reeves AP, Kostis WJ, Zhao B, Henschke CI. Small pulmonary nodules: volumetrically determined growth rates based on CT evaluation. Radiology 2000; 217: 251-6. doi: https://doi.org/10.1148/radiology.217.1.r00oc33251
15. Xu DM, van Klaveren RJ, de Bock GH, Leusveld A, Zhao Y, Wang Y, et al. Limited value of shape, margin and CT density in the discrimination between benign and malignant screen detected solid pulmonary nodules of the NELSON trial. Eur J Radiol 2008; 68: 347-52. doi: https://doi.org/10.1016/j.ejrad.2007.08.027
16. Xu DM, van der Zaag-Loonen HJ, Oudkerk M, Wang Y, Vliegenthart R, Scholten ET, et al. Smooth or attached solid indeterminate nodules detected at baseline CT screening in the NELSON study: cancer risk during 1 year of follow-up. Radiology 2009; 250: 264-72. doi: https://doi.org/10.1148/radiol.2493070847
17. Xu DM, Gietema H, de Koning H, Vernhout R, Nackaerts K, Prokop M, et al. Nodule management protocol of the NELSON randomised lung cancer screening trial. Lung Cancer 2006; 54: 177-84. doi: https://doi.org/10.1016/j.lungcan.2006.08. 006
18. van Iersel CA, de Koning HJ, Draisma G, Mali W, Scholten ET, Nackaerts K, et al. Risk-based selection from the general population in a screening trial: selection criteria, recruitment and power for the Dutch-Belgian randomised lung cancer multi-slice CT screening trial (NELSON). Int J Cancer J Int Cancer 2007; 120: 868-74.
19. Li K, Yip R, Avila R, Henschke C, Yankelevitz D. P1.03-052 the effect of rounding on rate of positive results on CT screening for Lung Cancer. J Thorac Oncol 2017; 12: S575. doi: https://doi.org/10.1016/j.jtho.2016.11.723
20. Takashima S, Sone S, Li F, Maruyama Y, Hasegawa M, Matsushita T, et al. Small solitary pulmonary nodules (< or =1 cm) detected at population-based CT screening for lung cancer: reliable high-resolution CT features of benign lesions. AJR Am J Roentgenol 2003; 180: 955-64.
21. Takashima S, Sone S, Li F, Maruyama Y, Hasegawa M, Kadoya M. 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 2003; 180: 1255-63. doi: https://doi.org/10.2214/ajr.180.5.1801255
22. Jones M, Dobson A, O'Brian S. A graphical method for assessing agreement with the mean between multiple observers using continuous measures. Int J Epidemiol 2011; 40: 1308-13. doi: https://doi.org/10.1093/ije/ dyr109
23. Gietema HA, Wang Y, Xu D, van Klaveren RJ, de Koning H, Scholten E, et al. Pulmonary nodules detected at lung cancer screening: interobserver variability of semiautomated volume measurements. Radiology 2006; 241: 251-7. doi: https://doi.org/10.1148/radiol. 2411050860
24. Hayes AF, Krippendorff K. Answering the call for a standard reliability measure for coding data. Commun Methods Meas 2007; 1: 77-89.
25. Krippendorff K. Reliability in content analysis: some common misconceptions and recommendations. Hum Commun Res 2004;: 411-33.
26. Siegelman SS, Khouri NF, Leo FP, Fishman EK, Braverman RM, Zerhouni EA. Solitary pulmonary nodules: CT assessment. Radiology 1986; 160: 307-12. doi: https://doi. org/10.1148/radiology.160.2.3726105
27. Zerhouni EA, Stitik FP, Siegelman SS, Naidich DP, Sagel SS, Proto AV, et al. CT of the pulmonary nodule: a cooperative study. Radiology 1986; 160: 319-27. doi: https://doi.org/10.1148/radiology.160.2.3726107
28. Zwirewich CV, Vedal S, Miller RR, Müller NL. Solitary pulmonary nodule: high-resolution CT and radiologic-pathologic correlation. Radiology 1991; 179: 469-76. doi: https://doi.org/10.1148/radiology.179.2. 2014294
29. Zhao YR, Heuvelmans MA, Dorrius MD, van Ooijen PM, Wang Y, de Bock GH, et al. Features of resolving and nonresolving indeterminate pulmonary nodules at followup CT: the NELSON study. Radiology 2014; 270: 872-9. doi: https://doi.org/10.1148/radiol.13130332
30. Revel MP, Bissery A, Bienvenu M, Aycard L, Lefort C, Frija G. Are two-dimensional CT measurements of small noncalcified pulmonary nodules reliable? Radiology 2004; 231: 453-8. doi: https://doi.org/10.1148/radiol.2312030167
31. Petrick N, Kim HJ, Clunie D, Borradaile K, Ford R, Zeng R, et al. Comparison of 1D, 2D, and 3D nodule sizing methods by radiologists for spherical and complex nodules on thoracic CT phantom images. Acad Radiol 2014; 21: 30-40. doi: https://doi.org/10.1016/j.acra.2013.09.020
32. Zhao YR, van Ooijen PMA, Dorrius MD, Heuvelmans M, de Bock GH, Vliegenthart R, et al. Comparison of three software systems for semi-automatic volumetry of pulmonary nodules on baseline and follow-up CT examinations. Acta Radiol Stockh Swed 1987. 2014; 55: 691-8.
33. de Hoop B, Gietema H, van Ginneken B, Zanen P, Groenewegen G, Prokop M. A comparison of six software packages for evaluation of solid lung nodules using semiautomated volumetry: what is the minimum increase in size to detect growth in repeated CT examinations. Eur Radiol 2009; 19: 800-8. doi: https://doi.org/10.1007/s00330-008-1229-x