The aim of this study was to prospectively assess the accuracy gain of Bayesian analysis-based computeraided diagnosis(CAD) vs human judgment alone in characterizing solitary pulmonary nodules(SPNs) at computed tomogr...The aim of this study was to prospectively assess the accuracy gain of Bayesian analysis-based computeraided diagnosis(CAD) vs human judgment alone in characterizing solitary pulmonary nodules(SPNs) at computed tomography(CT). The study included 100 randomly selected SPNs with a definitive diagnosis. Nodule features at first and follow-up CT scans as well as clinical data were evaluated individually on a 1 to 5 points risk chart by 7 radiologists, firstly blinded then aware of Bayesian Inference Malignancy Calculator(BIMC) model predictions. Raters' predictions were evaluated by means of receiver operating characteristic(ROC) curve analysis and decision analysis. Overall ROC area under the curve was 0.758 before and 0.803 after the disclosure of CAD predictions(P = 0.003). A net gain in diagnostic accuracy was found in 6 out of 7 readers. Mean risk class of benign nodules dropped from 2.48 to 2.29, while mean risk class of malignancies rose from 3.66 to 3.92. Awareness of CAD predictions also determined a significant drop on mean indeterminate SPNs(15 vs 23.86 SPNs) and raised the mean number of correct and confident diagnoses(mean 39.57 vs 25.71 SPNs). This study provides evidence supporting the integration of the Bayesian analysis-based BIMC model in SPN characterization.展开更多
Objective: Large cell carcinoma of lung is a very rare tumor. The clinical characteristics and CT imaging feature of large cell carcinoma of lung were discussed in this article. Methods: Eight cases of large cell carc...Objective: Large cell carcinoma of lung is a very rare tumor. The clinical characteristics and CT imaging feature of large cell carcinoma of lung were discussed in this article. Methods: Eight cases of large cell carcinoma of lung proven by post-operational pathology were retrospectively analyzed from 2000 to 2005 and the literature on it was reviewed. Results: All 8 cases were men. The average age of patients was 64.88 years. Seven cases were smokers. Six cases had obvious chest stuffy, short breath, thrill dry cough. Hereinto 3 cases had cardinal red blood sputum. CT images of large cell carcinoma of lung were represented as single and peripheral mass or nodule. The distribution of large cell carcinoma of lung was short of some rule. 75% focus had clear finitude. One case showed internal calcification and 2 cases showed cavity. They did not show internal fat density. Conclusion: Large cell carcinoma of lung is difficult to be diagnosed before operation. Its CT finding is nonspecific.展开更多
文摘The aim of this study was to prospectively assess the accuracy gain of Bayesian analysis-based computeraided diagnosis(CAD) vs human judgment alone in characterizing solitary pulmonary nodules(SPNs) at computed tomography(CT). The study included 100 randomly selected SPNs with a definitive diagnosis. Nodule features at first and follow-up CT scans as well as clinical data were evaluated individually on a 1 to 5 points risk chart by 7 radiologists, firstly blinded then aware of Bayesian Inference Malignancy Calculator(BIMC) model predictions. Raters' predictions were evaluated by means of receiver operating characteristic(ROC) curve analysis and decision analysis. Overall ROC area under the curve was 0.758 before and 0.803 after the disclosure of CAD predictions(P = 0.003). A net gain in diagnostic accuracy was found in 6 out of 7 readers. Mean risk class of benign nodules dropped from 2.48 to 2.29, while mean risk class of malignancies rose from 3.66 to 3.92. Awareness of CAD predictions also determined a significant drop on mean indeterminate SPNs(15 vs 23.86 SPNs) and raised the mean number of correct and confident diagnoses(mean 39.57 vs 25.71 SPNs). This study provides evidence supporting the integration of the Bayesian analysis-based BIMC model in SPN characterization.
文摘Objective: Large cell carcinoma of lung is a very rare tumor. The clinical characteristics and CT imaging feature of large cell carcinoma of lung were discussed in this article. Methods: Eight cases of large cell carcinoma of lung proven by post-operational pathology were retrospectively analyzed from 2000 to 2005 and the literature on it was reviewed. Results: All 8 cases were men. The average age of patients was 64.88 years. Seven cases were smokers. Six cases had obvious chest stuffy, short breath, thrill dry cough. Hereinto 3 cases had cardinal red blood sputum. CT images of large cell carcinoma of lung were represented as single and peripheral mass or nodule. The distribution of large cell carcinoma of lung was short of some rule. 75% focus had clear finitude. One case showed internal calcification and 2 cases showed cavity. They did not show internal fat density. Conclusion: Large cell carcinoma of lung is difficult to be diagnosed before operation. Its CT finding is nonspecific.
