Pulmonary nodules: estimation of malignancy at thin-section helical CT--effect of computer-aided diagnosis on performance of radiologists

Radiology. 2006 Apr;239(1):276-84. doi: 10.1148/radiol.2383050167. Epub 2006 Feb 7.

Abstract

Purpose: To evaluate the effect of a computer-aided diagnosis (CAD) system on the diagnostic performance of radiologists for the estimation of the malignancy of pulmonary nodules on thin-section helical computed tomographic (CT) scans.

Materials and methods: The institutional review board approved use of the CT database; informed specific study-related consent was waived. The institutional review board approved participation of radiologists; informed consent was obtained from all observers. Thirty-three (18 malignant, 15 benign) pulmonary nodules of less than 3.0 cm in maximal diameter were evaluated. Receiver operating characteristic (ROC) analysis with a continuous rating scale was used to compare observer performance for the estimation of the likelihood of malignancy first without and then with the CAD system. The participants were 10 board-certified radiologists and nine radiology residents.

Results: For all 19 participants, the mean area under the best-fit ROC curve (A(z)) values achieved without and with the CAD system were 0.843 +/- 0.097 (standard deviation) and 0.924 +/- 0.043, respectively. The difference was significant (P = .021). The mean A(z) values achieved without and with the CAD system were 0.910 +/- 0.052 and 0.944 +/- 0.040, respectively, for the 10 board-certified radiologists (P = .190) and 0.768 +/- 0.078 and 0.901 +/- 0.036, respectively, for the nine radiology residents (P = .009).

Conclusion: Use of the CAD system significantly (P = .009) improved the diagnostic performance of radiology residents for assessment of the malignancy of pulmonary nodules; however, it did not improve that of board-certified radiologists.

MeSH terms

  • Adenocarcinoma / diagnostic imaging*
  • Adult
  • Aged
  • Diagnosis, Computer-Assisted* / statistics & numerical data
  • Diagnostic Errors
  • Female
  • Humans
  • Lung Neoplasms / diagnostic imaging*
  • Male
  • Middle Aged
  • Observer Variation
  • Tomography, X-Ray Computed* / methods
  • Tomography, X-Ray Computed* / statistics & numerical data