Xuefang Cao, Boxuan Feng, Bin Zhang, Dakuan Wang, Jiang Du, Yijun He, Tonglei Guo, Shouguo Pan, Zisen Liu, Jiaoxia Yan, Qi Jin, Lei Gao, Henan Xin
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引用次数: 0
Abstract
Background
Computer-aided detection (CAD) software has been introduced to automatically interpret digital chest X-rays. This study aimed to evaluate the performance of CAD software (JF CXR-1 v3.0, which was developed by a domestic Hi-tech enterprise) in tuberculosis (TB) case finding in China.
Methods
In 2019, we conducted an internal evaluation of the performance of JF CXR-1 v3.0 by reading standard images annotated by a panel of experts. In 2020, using the reading results of chest X-rays by a panel of experts as the reference standard, we conducted an on-site prospective study to evaluate the performance of JF CXR-1 v3.0 and local radiologists in TB case finding in 13 township health centers in Zhongmu County, Henan Province.
Results
Internal assessment results based on 277 standard images showed that JF CXR-1 v3.0 had a sensitivity of 85.94% (95% confidence interval [CI]: 77.42%, 94.45%) and a specificity of 74.65% (95% CI: 68.81%, 80.49%) to distinguish active TB from other imaging conditions. In the on-site evaluation phase, images from 3705 outpatients who underwent chest X-ray detection were read by JF CXR-1 v3.0 and local radiologists in parallel. The imaging diagnosis of local radiologists for active TB had a sensitivity of 32.89% (95% CI: 22.33%, 43.46%) and a specificity of 99.28% (95% CI: 99.01%, 99.56%), while JF CXR-1 v3.0 showed a significantly higher sensitivity of 92.11% (95% CI: 86.04%, 98.17%) (p < 0.05) and maintained high specificity at 94.54% (95% CI: 93.81%, 95.28%).
Conclusions
CAD software could play a positive role in improving the TB case finding capability of township health centers.
期刊介绍：
This journal aims to promote progress from basic research to clinical practice and to provide a forum for communication among basic, translational, and clinical research practitioners and physicians from all relevant disciplines. Chronic diseases such as cardiovascular diseases, cancer, diabetes, stroke, chronic respiratory diseases (such as asthma and COPD), chronic kidney diseases, and related translational research. Topics of interest for Chronic Diseases and Translational Medicine include Research and commentary on models of chronic diseases with significant implications for disease diagnosis and treatment Investigative studies of human biology with an emphasis on disease Perspectives and reviews on research topics that discuss the implications of findings from the viewpoints of basic science and clinical practic.
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