DOI QR코드

DOI QR Code

Digital Tomosynthesis for Evaluating Metastatic Lung Nodules: Nodule Visibility, Learning Curves, and Reading Times

  • Lee, Kyung Hee (Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center) ;
  • Goo, Jin Mo (Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center) ;
  • Lee, Sang Min (Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center) ;
  • Park, Chang Min (Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center) ;
  • Bahn, Young Eun (Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center) ;
  • Kim, Hyungjin (Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center) ;
  • Song, Yong Sub (Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center) ;
  • Hwang, Eui Jin (Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center)
  • 투고 : 2014.08.26
  • 심사 : 2014.11.30
  • 발행 : 2015.04.01

초록

Objective: To evaluate nodule visibility, learning curves, and reading times for digital tomosynthesis (DT). Materials and Methods: We included 80 patients who underwent computed tomography (CT) and DT before pulmonary metastasectomy. One experienced chest radiologist annotated all visible nodules on thin-section CT scans using computeraided detection software. Two radiologists used CT as the reference standard and retrospectively graded the visibility of nodules on DT. Nodule detection performance was evaluated in four sessions of 20 cases each by six readers. After each session, readers were unblinded to the DT images by revealing the true-positive markings and were instructed to self-analyze their own misreads. Receiver-operating-characteristic curves were determined. Results: Among 414 nodules on CT, 53.3% (221/414) were visible on DT. The main reason for not seeing a nodule on DT was small size (93.3%, ${\leq}5mm$). DT revealed a substantial number of malignant nodules (84.1%, 143/170). The proportion of malignant nodules among visible nodules on DT was significantly higher (64.7%, 143/221) than that on CT (41.1%, 170/414) (p < 0.001). Area under the curve (AUC) values at the initial session were > 0.8, and the average detection rate for malignant nodules was 85% (210/246). The inter-session analysis of the AUC showed no significant differences among the readers, and the detection rate for malignant nodules did not differ across sessions. A slight improvement in reading times was observed. Conclusion: Most malignant nodules > 5 mm were visible on DT. As nodule detection performance was high from the initial session, DT may be readily applicable for radiology residents and board-certified radiologists.

키워드

참고문헌

  1. Jung HN, Chung MJ, Koo JH, Kim HC, Lee KS. Digital tomosynthesis of the chest: utility for detection of lung metastasis in patients with colorectal cancer. Clin Radiol 2012;67:232-238 https://doi.org/10.1016/j.crad.2011.08.017
  2. Dobbins JT 3rd, McAdams HP. Chest tomosynthesis: technical principles and clinical update. Eur J Radiol 2009;72:244-251 https://doi.org/10.1016/j.ejrad.2009.05.054
  3. Yamada Y, Jinzaki M, Hasegawa I, Shiomi E, Sugiura H, Abe T, et al. Fast scanning tomosynthesis for the detection of pulmonary nodules: diagnostic performance compared with chest radiography, using multidetector-row computed tomography as the reference. Invest Radiol 2011;46:471-477 https://doi.org/10.1097/RLI.0b013e318217b838
  4. James TD, McAdams HP, Song JW, Li CM, Godfrey DJ, DeLong DM, et al. Digital tomosynthesis of the chest for lung nodule detection: interim sensitivity results from an ongoing NIH-sponsored trial. Med Phys 2008;35:2554-2557 https://doi.org/10.1118/1.2937277
  5. Vikgren J, Zachrisson S, Svalkvist A, Johnsson AA, Boijsen M, Flinck A, et al. Comparison of chest tomosynthesis and chest radiography for detection of pulmonary nodules: human observer study of clinical cases. Radiology 2008;249:1034-1041 https://doi.org/10.1148/radiol.2492080304
  6. Potchen EJ, Cooper TG, Sierra AE, Aben GR, Potchen MJ, Potter MG, et al. Measuring performance in chest radiography. Radiology 2000;217:456-459 https://doi.org/10.1148/radiology.217.2.r00nv14456
  7. Asplund S, Johnsson AA, Vikgren J, Svalkvist A, Boijsen M, Fisichella V, et al. Learning aspects and potential pitfalls regarding detection of pulmonary nodules in chest tomosynthesis and proposed related quality criteria. Acta Radiol 2011;52:503-512 https://doi.org/10.1258/ar.2011.100378
  8. Dachman AH, Kelly KB, Zintsmaster MP, Rana R, Khankari S, Novak JD, et al. Formative evaluation of standardized training for CT colonographic image interpretation by novice readers. Radiology 2008;249:167-177 https://doi.org/10.1148/radiol.2491080059
  9. Hock D, Ouhadi R, Materne R, Aouchria AS, Mancini I, Broussaud T, et al. Virtual dissection CT colonography: evaluation of learning curves and reading times with and without computer-aided detection. Radiology 2008;248:860-868 https://doi.org/10.1148/radiol.2482070895
  10. Otani H, Nitta N, Ikeda M, Nagatani Y, Tanaka T, Kitahara H, et al. Flat-panel detector computed tomography imaging: observer performance in detecting pulmonary nodules in comparison with conventional chest radiography and multidetector computed tomography. J Thorac Imaging 2012;27:51-57 https://doi.org/10.1097/RTI.0b013e31820321e2
  11. Monnier-Cholley L, Carrat F, Cholley BP, Tubiana JM, Arrive L. Detection of lung cancer on radiographs: receiver operating characteristic analyses of radiologists', pulmonologists', and anesthesiologists' performance. Radiology 2004;233:799-805 https://doi.org/10.1148/radiol.2333031478
  12. Kakeda S, Moriya J, Sato H, Aoki T, Watanabe H, Nakata H, et al. Improved detection of lung nodules on chest radiographs using a commercial computer-aided diagnosis system. AJR Am J Roentgenol 2004;182:505-510 https://doi.org/10.2214/ajr.182.2.1820505
  13. Hanley JA, McNeil BJ. A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology 1983;148:839-843 https://doi.org/10.1148/radiology.148.3.6878708
  14. Fischbach F, Knollmann F, Griesshaber V, Freund T, Akkol E, Felix R. Detection of pulmonary nodules by multislice computed tomography: improved detection rate with reduced slice thickness. Eur Radiol 2003;13:2378-2383 https://doi.org/10.1007/s00330-003-1915-7
  15. Goo JM. A computer-aided diagnosis for evaluating lung nodules on chest CT: the current status and perspective. Korean J Radiol 2011;12:145-155 https://doi.org/10.3348/kjr.2011.12.2.145
  16. Park EA, Goo JM, Lee JW, Kang CH, Lee HJ, Lee CH, et al. Efficacy of computer-aided detection system and thin-slab maximum intensity projection technique in the detection of pulmonary nodules in patients with resected metastases. Invest Radiol 2009;44:105-113 https://doi.org/10.1097/RLI.0b013e318190fcfc
  17. Quaia E, Baratella E, Cioffi V, Bregant P, Cernic S, Cuttin R, et al. The value of digital tomosynthesis in the diagnosis of suspected pulmonary lesions on chest radiography: analysis of diagnostic accuracy and confidence. Acad Radiol 2010;17:1267-1274 https://doi.org/10.1016/j.acra.2010.05.009
  18. Quaia E, Baratella E, Poillucci G, Kus S, Cioffi V, Cova MA. Digital tomosynthesis as a problem-solving imaging technique to confirm or exclude potential thoracic lesions based on chest X-ray radiography. Acad Radiol 2013;20:546-553 https://doi.org/10.1016/j.acra.2012.12.009
  19. Kim EY, Chung MJ, Choe YH, Lee KS. Digital tomosynthesis for aortic arch calcification evaluation: performance comparison with chest radiography with CT as the reference standard. Acta Radiol 2012;53:17-22 https://doi.org/10.1258/ar.2011.110347
  20. Rose SL, Tidwell AL, Bujnoch LJ, Kushwaha AC, Nordmann AS, Sexton R Jr. Implementation of breast tomosynthesis in a routine screening practice: an observational study. AJR Am J Roentgenol 2013;200:1401-1408 https://doi.org/10.2214/AJR.12.9672
  21. Lee G, Jeong YJ, Kim KI, Song JW, Kang DM, Kim YD, et al. Comparison of chest digital tomosynthesis and chest radiography for detection of asbestos-related pleuropulmonary disease. Clin Radiol 2013;68:376-382 https://doi.org/10.1016/j.crad.2012.05.022
  22. Quaia E, Baratella E, Cernic S, Lorusso A, Casagrande F, Cioffi V, et al. Analysis of the impact of digital tomosynthesis on the radiological investigation of patients with suspected pulmonary lesions on chest radiography. Eur Radiol 2012;22:1912-1922 https://doi.org/10.1007/s00330-012-2440-3
  23. Terzi A, Bertolaccini L, Viti A, Comello L, Ghirardo D, Priotto R, et al. Lung cancer detection with digital chest tomosynthesis: baseline results from the observational study SOS. J Thorac Oncol 2013;8:685-692 https://doi.org/10.1097/JTO.0b013e318292bdef
  24. Kim EY, Chung MJ, Lee HY, Koh WJ, Jung HN, Lee KS. Pulmonary mycobacterial disease: diagnostic performance of low-dose digital tomosynthesis as compared with chest radiography. Radiology 2010;257:269-277 https://doi.org/10.1148/radiol.10100303

피인용 문헌

  1. AN ANALYSIS OF THE POTENTIAL ROLE OF CHEST TOMOSYNTHESIS IN OPTIMISING IMAGING RESOURCES IN THORACIC RADIOLOGY vol.169, pp.1, 2015, https://doi.org/10.1093/rpd/ncw040
  2. Comparison of digital tomosynthesis and chest radiography for the detection of pulmonary nodules: systematic review and meta-analysis vol.89, pp.1068, 2015, https://doi.org/10.1259/bjr.20160421
  3. Detection of Acetabular and Proximal Femoral Radiographic Abnormalities Showed by Hip Digital Tomosynthesis in Special Functional Position Compared with Conventional Radiography vol.14, pp.1, 2015, https://doi.org/10.5812/iranjradiol.36009
  4. Detection and Characterization of Solid Pulmonary Nodules at Digital Chest Tomosynthesis: Data from a Cohort of the Pilot Swedish Cardiopulmonary Bioimage Study vol.287, pp.3, 2018, https://doi.org/10.1148/radiol.2018171481
  5. Surveillance of small, solid pulmonary nodules at digital chest tomosynthesis: data from a cohort of the pilot Swedish CArdioPulmonary bioImage Study (SCAPIS) vol.62, pp.3, 2021, https://doi.org/10.1177/0284185120923106
  6. Surveillance of small, solid pulmonary nodules at digital chest tomosynthesis: data from a cohort of the pilot Swedish CArdioPulmonary bioImage Study (SCAPIS) vol.62, pp.3, 2021, https://doi.org/10.1177/0284185120923106