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Computer-aided interpretation of chest radiography reveals the spectrum of tuberculosis in rural South Africa
npj Digital Medicine ( IF 12.4 ) Pub Date : 2021-07-02 , DOI: 10.1038/s41746-021-00471-y
Jana Fehr 1, 2 , Stefan Konigorski 2, 3 , Stephen Olivier 1 , Resign Gunda 1, 4, 5 , Ashmika Surujdeen 1 , Dickman Gareta 1 , Theresa Smit 1 , Kathy Baisley 1, 6 , Sashen Moodley 1 , Yumna Moosa 1 , Willem Hanekom 1, 5 , Olivier Koole 1, 6 , Thumbi Ndung'u 1, 5, 7, 8, 9 , Deenan Pillay 1, 5 , Alison D Grant 1, 4, 6, 10 , Mark J Siedner 1, 10, 11, 12 , Christoph Lippert 2, 3 , Emily B Wong 1, 11, 12, 13 ,
Affiliation  

Computer-aided digital chest radiograph interpretation (CAD) can facilitate high-throughput screening for tuberculosis (TB), but its use in population-based active case-finding programs has been limited. In an HIV-endemic area in rural South Africa, we used a CAD algorithm (CAD4TBv5) to interpret digital chest x-rays (CXR) as part of a mobile health screening effort. Participants with TB symptoms or CAD4TBv5 score above the triaging threshold were referred for microbiological sputum assessment. During an initial pilot phase, a low CAD4TBv5 triaging threshold of 25 was selected to maximize TB case finding. We report the performance of CAD4TBv5 in screening 9,914 participants, 99 (1.0%) of whom were found to have microbiologically proven TB. CAD4TBv5 was able to identify TB cases at the same sensitivity but lower specificity as a blinded radiologist, whereas the next generation of the algorithm (CAD4TBv6) achieved comparable sensitivity and specificity to the radiologist. The CXRs of people with microbiologically confirmed TB spanned a range of lung field abnormality, including 19 (19.2%) cases deemed normal by the radiologist. HIV serostatus did not impact CAD4TB’s performance. Notably, 78.8% of the TB cases identified during this population-based survey were asymptomatic and therefore triaged for sputum collection on the basis of CAD4TBv5 score alone. While CAD4TBv6 has the potential to replace radiologists for triaging CXRs in TB prevalence surveys, population-specific piloting is necessary to set the appropriate triaging thresholds. Further work on image analysis strategies is needed to identify radiologically subtle active TB.



中文翻译:

胸部 X 线摄影的计算机辅助解读揭示了南非农村地区的结核病谱

计算机辅助数字胸片判读 (CAD) 可以促进结核病 (TB) 的高通量筛查,但其在基于人群的主动病例发现计划中的使用受到限制。在南非农村的艾滋病毒流行地区,我们使用 CAD 算法 (CAD4TBv5) 来解释数字胸部 X 光片 (CXR),作为移动健康筛查工作的一部分。患有结核病症状或 CAD4TBv5 评分高于分类阈值的参与者被转介进行微生物痰液评估。在最初的试点阶段,选择了 25 的低 CAD4TBv5 分类阈值,以最大限度地提高结核病病例发现率。我们报告了 CAD4TBv5 在筛查 9,914 名参与者时的表现,其中 99 名 (1.0%) 被发现患有微生物学证明的结核病。CAD4TBv5 能够以与盲法放射科医生相同的灵敏度但较低的特异性来识别结核病例,而下一代算法 (CAD4TBv6) 实现了与放射科医生相当的灵敏度和特异性。经微生物学确诊的结核病患者的 CXR 表现出一系列肺野异常,其中 19 例 (19.2%) 病例被放射科医生视为正常。HIV 血清状态不会影响 CAD4TB 的性能。值得注意的是,在这项基于人群的调查中发现的结核病病例中有 78.8% 是无症状的,因此仅根据 CAD4TBv5 评分对痰液采集进行分类。虽然 CAD4TBv6 有可能取代放射科医生在结核病患病率调查中对 CXR 进行分类,但有必要针对特定​​人群进行试点,以设置适当的分类阈值。需要进一步研究图像分析策略来识别放射学上微妙的活动性结核病。

更新日期:2021-07-02
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