Evaluating InferVision's Computer-Aided Detection (CAD) algorithm for Tuberculosis (TB) screening, Lusaka, Zambia

在赞比亚卢萨卡评估 InferVision 的计算机辅助检测 (CAD) 算法在结核病 (TB) 筛查中的应用

阅读:2

Abstract

The objective of this study was to evaluate the diagnostic performance of InferRead DR Chest for tuberculosis (TB) screening in a high HIV and TB burden setting. The study assessed the performance of InferRead DR Chest using anonymized chest X-ray images from an active TB case finding study in Lusaka, Zambia, for individuals aged 15 and older. The Xpert MTB/RIF or MTB culture was the composite reference standard. Performance was evaluated using the Area Under the Receiver Operating Characteristic Curve (AUC), and a binary classification point was selected where the sensitivity aligned with the WHO target product profile for TB screening tools. Of the 1,890 chest X-ray images that met the inclusion criteria, 91.5% of participants reported at least one TB symptom. The median age was 38 years (IQR: 29-47), and 1,186 (62.8%) were male. From the study sample, 449 participants (23.8%) reported a history of previous TB, and 704 (37.2%) were HIV positive. Among the analyzed images, 289 (15.3%) were classified as TB positive based on the composite reference standard test results. The overall area under the curve (AUC) was 0.81 (95% CI: 0.78-0.83). Among individuals with a history of previous TB and those who were HIV positive, the AUCs were 0.71 (95% CI: 0.63-0.79) and 0.77 (95% CI: 0.72-0.82), respectively. At a sensitivity of 90.3% (95% CI: 86.3%-93.5%), InferRead DR Chest achieved a specificity of 39.2% (95% CI: 36.8%-41.7%) at TB score cut point of 0.12. InferRead DR Chest had acceptable performance in our population. Additional training and piloting of InferRead DR Chest in this population is recommended.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。