Brown Matthew S, Goldin Jonathan G, Rogers Sarah, Kim Hyun J, Suh Robert D, McNitt-Gray Michael F, Shah Sumit K, Truong Dao, Brown Kathleen, Sayre James W, Gjertson David W, Batra Poonam, Aberle Denise R
Thoracic Imaging Section, David Geffen School of Medicine at UCLA, 10833 Le Conte Avenue, Los Angeles, CA 90095, USA.
Acad Radiol. 2005 Jun;12(6):681-6. doi: 10.1016/j.acra.2005.02.041.
The objective is to study the incremental effects of using a computer-aided lung nodule detection (CAD) system on the performance of a large pool of observers.
A set of eight thin-section computed tomographic data sets with limited longitudinal coverage, containing a total of 22 lung nodules, was analyzed by using the automated nodule detection system. When applied to all eight cases, the CAD system alone achieved a detection rate of 86.4%, with 2.64 false-positive results per case. This study included 202 observers at a national radiology meeting: 39 thoracic radiologists, 95 non-thoracic radiologists, and 68 non-radiologists. Each participant read from one to eight cases in random order, first without and then with CAD system output available. Observer performance in nodule detection was measured before and after CAD was made available. Differences in performance of groups of observers before and after CAD were tabulated by mean, median, and SD in detection rate and number of false-positive results and tested by using nonparametric methods.
In an analysis involving only the first randomly selected case read by all 202 participants, there were statistically significant increases in nodule detection rates and numbers of false-positive results for all types of observers. There was a significant difference in detection rates between radiologists and non-radiologists before CAD, but after CAD, there was no significant difference in detection rates between these observer types. In a second analysis involving 13 participants who read all eight cases, mean detection rates were 64.0% before CAD and 81.9% after CAD. Mean numbers of false-positive results were 0.144 per case before CAD and 0.173 after CAD.
In a large observer study, use of a CAD system for nodule detection resulted in an incremental increase in detection rate, but also led to an increase in number of false-positive results. Also, CAD appears to be an equalizer of detection rates between observers of different levels of experience.
目的是研究使用计算机辅助肺结节检测（CAD）系统对大量观察者表现的增量影响。
使用自动结节检测系统分析了一组八个纵向覆盖范围有限的薄层计算机断层扫描数据集，共包含22个肺结节。当应用于所有八个病例时，仅CAD系统的检测率为86.4%，每个病例有2.64个假阳性结果。本研究在一次全国放射学会议上纳入了202名观察者：39名胸放射科医生、95名非胸放射科医生和68名非放射科医生。每位参与者随机顺序阅读一至八个病例，先是在没有CAD系统输出的情况下，然后是在有CAD系统输出的情况下。在提供CAD前后测量观察者在结节检测方面的表现。通过检测率和假阳性结果数量的均值、中位数和标准差将CAD前后不同观察者组的表现差异制成表格，并使用非参数方法进行检验。
在一项仅涉及所有202名参与者随机选择阅读的第一个病例的分析中，所有类型的观察者在结节检测率和假阳性结果数量上均有统计学显著增加。在CAD之前，放射科医生和非放射科医生之间的检测率存在显著差异，但在CAD之后，这些观察者类型之间的检测率没有显著差异。在第二项涉及阅读所有八个病例的13名参与者的分析中，CAD之前的平均检测率为64.0%，CAD之后为81.9%。CAD之前每个病例的平均假阳性结果数量为0.144，CAD之后为0.173。
在一项大型观察者研究中，使用CAD系统进行结节检测导致检测率有增量提高，但也导致假阳性结果数量增加。此外，CAD似乎是不同经验水平观察者之间检测率的均衡器。
