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Performance of Computer-Aided Detection Software in Tuberculosis Case Finding in Township Health Centers in China

Performance of Computer-Aided Detection Software in Tuberculosis Case Finding in Township Health Centers in China

摘要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.

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abstractsBackground::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.

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作者 Cao Xuefang [1] Feng Boxuan [1] Zhang Bin [2] Wang Dakuan [2] Du Jiang [1] He Yijun [1] Guo Tonglei [1] Pan Shouguo [2] Liu Zisen [2] Yan Jiaoxia [2] Jin Qi [1] Gao Lei [1] Xin Henan [1] 学术成果认领
作者单位 NHC Key Laboratory of Systems Biology of Pathogens, National Institute of Pathogen Biology, and Center for Tuberculosis Research, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China [1] Center for Disease Control and Prevention of Zhongmu County, Zhengzhou, Henan, China [2]
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DOI 10.1002/cdt3.70001
发布时间 2026-01-27(万方平台首次上网日期,不代表论文的发表时间)
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