Gurney J W, Lyddon D M, McKay J A
Department of Radiology, University Hospital, Omaha, NE 68198.
Radiology. 1993 Feb;186(2):415-22. doi: 10.1148/radiology.186.2.8421744.
Four board-certified radiologists estimated the probability of malignancy in 66 cases of solitary pulmonary nodules. Two other radiologists evaluated the same nodules according to various radiographic and clinical findings. These findings were then used to estimate the probability of malignancy by using previously derived likelihood ratios and the Bayes theorem. The readers using Bayesian analysis performed significantly better than the expert readers (P < .05) when individual radiographs were considered and when all radiologic studies were combined. In addition, the readers using Bayesian analysis misclassified fewer malignant nodules as benign (mean, 6.5) than did the expert readers (mean, 6.5) than did the expert readers (mean, 16.5). The authors conclude that Bayesian analysis may be a useful aid in the evaluation of solitary pulmonary nodules.
四位具有专业资质认证的放射科医生评估了66例孤立性肺结节的恶性概率。另外两位放射科医生根据各种影像学和临床检查结果对相同的结节进行了评估。然后,利用先前得出的似然比和贝叶斯定理,这些检查结果被用于估计恶性概率。当考虑单张X光片以及综合所有放射学检查结果时,采用贝叶斯分析的阅片者表现明显优于专家阅片者(P < .05)。此外,采用贝叶斯分析的阅片者将恶性结节误判为良性的数量(平均6.5个)少于专家阅片者(平均16.5个)。作者得出结论,贝叶斯分析在评估孤立性肺结节时可能是一种有用的辅助手段。