Screening for Lung Cancer with Digital Chest Radiography: Sensitivity and Number of Secondary Work-up CT Examinations

Published Online:https://doi.org/10.1148/radiol.09091308

A high rate of detection of lung cancer can be achieved with digital chest radiography at a stage when lesions can be seen with CT screening, but only at the expense of a low specificity that results in an excessive number of work-up CT examinations.

Purpose

To estimate the performance of digital chest radiography for detection of lung cancer.

Materials and Methods

The study had ethics committee approval, and a nested case-control design was used and included 55 patients with lung cancer detected at computed tomography (CT) and confirmed with histologic examination and a sample of 72 of 4873 control subjects without nodules at CT. All patients underwent direct-detector digital chest radiography in two projections within 2 months of the screening CT. Four radiologists with varying experience identified and localized potential cancers on chest radiographs by using a confidence scale of level 1 (no lesion) to 5 (definite lesion). Localization receiver operating characteristic (ROC) analysis was performed. On the basis of the assumption that suspicious lesions seen at chest radiography would lead to further work-up with CT, the number of work-up CT examinations per detected cancer (CT examinations per cancer) was calculated at various confidence levels for the screening population (cancer rate in study population, 1.3%).

Results

Tumor size ranged from 6.8 to 50.7 mm (median, 11.8 mm). Areas under the localization ROC curve ranged from 0.52 to 0.69. Detection rates substantially varied with the observers’ experience and confidence level: At a confidence level of 5, detection rates ranged from 18% at one CT examination per cancer to 53% at 13 CT examinations per cancer. At a confidence level of 2 or higher, detection rates ranged from 94% at 62 CT examinations per cancer to 78% at 44 CT examinations per cancer.

Conclusion

A detection rate of 94% for lung tumors with a diameter of 6.8–50.7 mm found at CT screening was achievable with chest radiography only at the expense of a high false-positive rate and an excessive number of work-up CT examinations. Detection performance is strongly observer dependent.

© RSNA, 2010

References

  • 1 Flehinger BJ, Melamed MR. Current status of screening for lung cancer. Chest Surg Clin N Am 1994;4(1):1–15.
  • 2 Hennigs SP, Garmer M, Jaeger HJ, et al.. Digital chest radiography with a large-area flat-panel silicon X-ray detector: clinical comparison with conventional radiography. Eur Radiol 2001;11(9):1688–1696.
  • 3 Fink C, Hallscheidt PJ, Noeldge G, et al.. Clinical comparative study with a large-area amorphous silicon flat-panel detector: image quality and visibility of anatomic structures on chest radiography. AJR Am J Roentgenol 2002;178(2):481–486.
  • 4 Garmer M, Hennigs SP, Jäger HJ, et al.. Digital radiography versus conventional radiography in chest imaging: diagnostic performance of a large-area silicon flat-panel detector in a clinical CT-controlled study. AJR Am J Roentgenol 2000;174(1):75–80.
  • 5 Redlich U, Hoeschen C, Effenberger O, et al.. Comparison of four digital and one conventional radiographic image systems for the chest in a patient study with subsequent system optimization [in German]. Rofo 2005;177(2):272–278.
  • 6 Xu DM, Gietema H, de Koning H, et al.. Nodule management protocol of the NELSON randomised lung cancer screening trial. Lung Cancer 2006;54(2):177–184.
  • 7 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(4):868–874.
  • 8 Rabe KF, Hurd S, Anzueto A, et al.. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med 2007;176(6):532–555.
  • 9 Stahl M, Aach T, Dippel S. Digital radiography enhancement by nonlinear multiscale processing. Med Phys 2000;27(1):56–65.
  • 10 Biesheuvel CJ, Vergouwe Y, Oudega R, Hoes AW, Grobbee DE, Moons KG. Advantages of the nested case-control design in diagnostic research. BMC Med Res Methodol 2008;8:48.
  • 11 Swensson RG. Unified measurement of observer performance in detecting and localizing target objects on images. Med Phys 1996;23(10):1709–1725.
  • 12 Zheng B, Chakraborty DP, Rockette HE, Maitz GS, Gur D. A comparison of two data analyses from two observer performance studies using Jackknife ROC and JAFROC. Med Phys 2005;32(4):1031–1034.
  • 13 Chakraborty DP, Berbaum KS. Observer studies involving detection and localization: modeling, analysis, and validation. Med Phys 2004;31(8):2313–2330.
  • 14 van Klaveren RJ, Oudkerk M, Prokop M, et al.. Management of lung nodules detected by volume CT scanning. N Engl J Med 2009;361(23):2221–2229.
  • 15 National Lung Cancer Screening Trial. http://www.nci.nih.gov/nlst. 2008. Accessed July 2, 2009.
  • 16 Awai K, Murao K, Ozawa A, et al.. Pulmonary nodules at chest CT: effect of computer-aided diagnosis on radiologists’ detection performance. Radiology 2004;230(2):347–352.
  • 17 Sone S, Li F, Yang ZG, et al.. Characteristics of small lung cancers invisible on conventional chest radiography and detected by population based screening using spiral CT. Br J Radiol 2000;73(866):137–145.
  • 18 Quekel LG, Kessels AG, Goei R, van Engelshoven JM. Detection of lung cancer on the chest radiograph: a study on observer performance. Eur J Radiol 2001;39(2):111–116.
  • 19 Potchen EJ, Cooper TG, Sierra AE, et al.. Measuring performance in chest radiography. Radiology 2000;217(2):456–459.
  • 20 Gavelli G, Giampalma E. Sensitivity and specificity of chest X-ray screening for lung cancer: review article. Cancer 2000;89(11 suppl):2453–2456.
  • 21 Li F, Arimura H, Suzuki K, et al.. Computer-aided detection of peripheral lung cancers missed at CT: ROC analyses without and with localization. Radiology 2005;237(2):684–690.
  • 22 Toyoda Y, Nakayama T, Kusunoki Y, Iso H, Suzuki T. Sensitivity and specificity of lung cancer screening using chest low-dose computed tomography. Br J Cancer 2008;98(10):1602–1607.
  • 23 Monnier-Cholley L, Carrat F, Cholley BP, Tubiana JM, Arrivé L. Detection of lung cancer on radiographs: receiver operating characteristic analyses of radiologists’, pulmonologists’, and anesthesiologists’ performance. Radiology 2004;233(3):799–805.
  • 24 Samei E, Flynn MJ, Eyler WR. Detection of subtle lung nodules: relative influence of quantum and anatomic noise on chest radiographs. Radiology 1999;213(3):727–734.
  • 25 Egglin TK, Feinstein AR. Context bias. A problem in diagnostic radiology. JAMA 1996;276(21):1752–1755.

Article History

Received July 20, 2009; revision requested August 28; final revision received October 5; accepted October 27; final version accepted November 16.
Published online: Apr 8 2010
Published in print: May 2010