Smooth or Attached Solid Indeterminate Nodules Detected at Baseline CT Screening in the NELSON Study: Cancer Risk during 1 Year of Follow-up

Published Online:Jan 1 2009https://doi.org/10.1148/radiol.2493070847

Abstract

Purpose: To retrospectively determine whether baseline nodule characteristics at 3-month and 1-year volume doubling time (VDT) are predictive for lung cancer in solid indeterminate noncalcified nodules (NCNs) detected at baseline computed tomographic (CT) screening.

Materials and Methods: The study, conducted between April 2004 and May 2006, was institutional review board approved. Patient consent was waived for this retrospective evaluation. NCNs between 5 and 10 mm in diameter (n = 891) were evaluated at 3 months and 1 year to assess growth (VDT < 400 days). Baseline assessments were related to growth at 3 months and 1 year by using χ² and Mann-Whitney U tests. Baseline assessments and growth were related to the presence of malignancy by using univariate and multivariate logistic regression analyses.

Results: At 3 months and at 1 year, 8% and 1% of NCNs had grown, of which 15% and 50% were malignant, respectively. One-year growth was related to morphology (P < .01), margin (P < .0001), location (P < .001), and size (P < .01). All cancers were nonspherical and purely intraparenchymal, without attachment to vessels, the pleura, or fissures. In nonsmooth unattached nodules, a volume of 130 mm³ or larger was the only predictor for malignancy (odds ratio, 6.3; 95% confidence interval [CI]: 1.7, 23.0). After the addition of information on the 3-month VDT, large volume (odds ratio, 4.9; 95% CI: 1.2, 20.1) and 3-month VDT (odds ratio, 15.6; 95% CI: 4.5, 53.5) helped predict malignancy. At 1 year, only the 1-year growth remained (odds ratio, 213.3; 95% CI: 18.7, 2430.9) as predictor for malignancy.

Conclusion: In smooth or attached solid indeterminate NCNs, no malignancies were found at 1-year follow-up. In nonsmooth purely intraparenchymal NCNs, size is the main baseline predictor for malignancy. When follow-up data are available, growth is a strong predictor for malignancy, especially at 1-year follow-up.

References

1 Gohagan J, Marcus P, Fagerstrom R, Pinsky P, Kramer B, Prorok P. Baseline findings of a randomized feasibility trial of lung cancer screening with spiral CT scan vs chest radiograph: the Lung Screening Study of the National Cancer Institute. Chest 2004; 126: 114–121. Crossref, Medline, Google Scholar
2 Henschke CI, McCauley DI, Yankelevitz DF, et al. Early Lung Cancer Action Project: overall design and findings from baseline screening. Lancet 1999;354:99–105. Crossref, Medline, Google Scholar
3 Henschke CI, Yankelevitz DF, Naidich DP, et al. CT screening for lung cancer: suspiciousness of nodules according to size on baseline scans. Radiology 2004;231:164–168. Link, Google Scholar
4 Benjamin MS, Drucker EA, McLoud TC, Shepard JA. Small pulmonary nodules: detection at chest CT and outcome. Radiology 2003;226:489–493. Link, Google Scholar
5 Winer-Muram HT. The solitary pulmonary nodule. Radiology 2006;239:34–49. Link, Google Scholar
6 MacMahon H, Austin JH, Gamsu G, et al. Guidelines for management of small pulmonary nodules detected on CT scans: a statement from the Fleischner Society. Radiology 2005;237:395–400. Link, Google Scholar
7 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;231:453–458. Link, Google Scholar
8 van Iersel CA, de Koning HJ, Draisma G, 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 2007;120:868–874. Crossref, Medline, Google Scholar
9 Xu DM, Gietema H, de Koning H, et al. Nodule management protocol of the NELSON randomised lung cancer screening trial. Lung Cancer 2006;54:177–184. Crossref, Medline, Google Scholar
10 Suzuki K, Asamura H, Kusumoto M, Kondo H, Tsuchiya R. “Early” peripheral lung cancer: prognostic significance of ground glass opacity on thin-section computed tomographic scan. Ann Thorac Surg 2002;74:1635–1639. Crossref, Medline, Google Scholar
11 Gurney JW. Determining the likelihood of malignancy in solitary pulmonary nodules with Bayesian analysis. I. Theory. Radiology 1993;186:405–413. Google Scholar
12 Takashima S, Maruyama Y, Hasegawa M, et al. CT findings and progression of small peripheral lung neoplasms having a replacement growth pattern. AJR Am J Roentgenol 2003;180:817–826. Crossref, Medline, Google Scholar
13 Takashima S, Sone S, Li F, 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;180:955–964. Crossref, Medline, Google Scholar
14 Murakami T, Yasuhara Y, Yoshioka S, Uemura M, Mochizuki T, Ikezoe J. Pulmonary lesions detected in population-based CT screening for lung cancer: reliable findings of benign lesions. Radiat Med 2004;22:287–295. Medline, Google Scholar
15 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;180:1255–1263. Crossref, Medline, Google Scholar
16 Wang JC, Sone S, Feng L, et al. Rapidly growing small peripheral lung cancers detected by screening CT: correlation between radiological appearance and pathological features. Br J Radiol 2000;73:930–937. Crossref, Medline, Google Scholar
17 Jeong YJ, Lee KS, Jeong SY, et al. Solitary pulmonary nodule: characterization with combined wash-in and washout features at dynamic multi-detector row CT. Radiology 2005;237:675–683. Link, Google Scholar
18 Furuya K, Murayama S, Soeda H, et al. New classification of small pulmonary nodules by margin characteristics on high-resolution CT. Acta Radiol 1999;40:496–504. Crossref, Medline, Google Scholar
19 Erasmus JJ, Connolly JE, McAdams HP, Roggli VL. Solitary pulmonary nodules. I. Morphologic evaluation for differentiation of benign and malignant lesions. RadioGraphics 2000;20:43–58. Google Scholar
20 Hasegawa M, Sone S, Takashima S, et al. Growth rate of small lung cancers detected on mass CT screening. Br J Radiol 2000;73:1252–1259. Crossref, Medline, Google Scholar
21 Hyodo T, Kanazawa S, Dendo S, et al. Intrapulmonary lymph nodes: thin-section CT findings, pathological findings, and CT differential diagnosis from pulmonary metastatic nodules. Acta Med Okayama 2004;58:235–240. Medline, Google Scholar
22 Oshiro Y, Kusumoto M, Moriyama N, et al. Intrapulmonary lymph nodes: thin-section CT features of 19 nodules. J Comput Assist Tomogr 2002;26:553–557. Crossref, Medline, Google Scholar
23 Swensen SJ, Jett JR, Sloan JA, et al. Screening for lung cancer with low-dose spiral computed tomography. Am J Respir Crit Care Med 2002;165:508–513. Crossref, Medline, Google Scholar
24 Swensen SJ, Jett JR, Hartman TE, et al. CT screening for lung cancer: 5-year prospective experience. Radiology 2005;235:259–265. Link, Google Scholar
25 Thunnissen FB, Schuurbiers OC, den Bakker MA. A critical appraisal of prognostic and predictive factors for common lung cancers. Histopathology 2006;48:779–786. Crossref, Medline, Google Scholar
26 Revel MP, Merlin A, Peyrard S, et al. Software volumetric evaluation of doubling times for differentiating benign versus malignant pulmonary nodules. AJR Am J Roentgenol 2006;187:135–142. Crossref, Medline, Google Scholar

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Published in print: 2009

Vol. 250, No. 1

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