Mixture distribution analysis of a computer assisted diagnostic method for the evaluation of pulmonary nodules on computed tomography scan.

Rationale And Objectives: To compare the effectiveness of a new computational scheme for pulmonary nodule detection in computed tomography images against human observers.

Materials And Methods: The study involved evaluation of 81 potential nodules by four radiologists. Each radiologist separately evaluated the potential nodules and provided a confidence level for the presence of pulmonary nodules. Their performance was compared with that of the new computational scheme by mixture distribution analysis.

Results: Mixture distribution analysis of the results of the four radiologists demonstrated a relative proportion agreement of 0.84. The kappa statistic was used to compare the agreement of the computational scheme with the results of the four radiologists. A kappa value of .65 (se = .11) was shown to be significantly different from chance (P = .99).

Conclusion: The new computational scheme correlates well with the radiologists' subjective rankings of pulmonary nodules on computed tomography scans and may prove a useful tool in the evaluation of algorithms for the screening and diagnosis of lung cancer.