Computer-aided interpretation of chest radiography reveals the spectrum of tuberculosis in rural South Africa
Abstract 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 int...
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2021
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oai:doaj.org-article:624d734c5cfd44b79ddb5c726f170c9c2021-12-02T16:32:00ZComputer-aided interpretation of chest radiography reveals the spectrum of tuberculosis in rural South Africa10.1038/s41746-021-00471-y2398-6352https://doaj.org/article/624d734c5cfd44b79ddb5c726f170c9c2021-07-01T00:00:00Zhttps://doi.org/10.1038/s41746-021-00471-yhttps://doaj.org/toc/2398-6352Abstract 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.Jana FehrStefan KonigorskiStephen OlivierResign GundaAshmika SurujdeenDickman GaretaTheresa SmitKathy BaisleySashen MoodleyYumna MoosaWillem HanekomOlivier KooleThumbi Ndung’uDeenan PillayAlison D. GrantMark J. SiednerChristoph LippertEmily B. Wongthe Vukuzazi TeamNature PortfolioarticleComputer applications to medicine. Medical informaticsR858-859.7ENnpj Digital Medicine, Vol 4, Iss 1, Pp 1-10 (2021) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
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Computer applications to medicine. Medical informatics R858-859.7 |
| spellingShingle |
Computer applications to medicine. Medical informatics R858-859.7 Jana Fehr Stefan Konigorski Stephen Olivier Resign Gunda Ashmika Surujdeen Dickman Gareta Theresa Smit Kathy Baisley Sashen Moodley Yumna Moosa Willem Hanekom Olivier Koole Thumbi Ndung’u Deenan Pillay Alison D. Grant Mark J. Siedner Christoph Lippert Emily B. Wong the Vukuzazi Team Computer-aided interpretation of chest radiography reveals the spectrum of tuberculosis in rural South Africa |
| description |
Abstract 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. |
| format |
article |
| author |
Jana Fehr Stefan Konigorski Stephen Olivier Resign Gunda Ashmika Surujdeen Dickman Gareta Theresa Smit Kathy Baisley Sashen Moodley Yumna Moosa Willem Hanekom Olivier Koole Thumbi Ndung’u Deenan Pillay Alison D. Grant Mark J. Siedner Christoph Lippert Emily B. Wong the Vukuzazi Team |
| author_facet |
Jana Fehr Stefan Konigorski Stephen Olivier Resign Gunda Ashmika Surujdeen Dickman Gareta Theresa Smit Kathy Baisley Sashen Moodley Yumna Moosa Willem Hanekom Olivier Koole Thumbi Ndung’u Deenan Pillay Alison D. Grant Mark J. Siedner Christoph Lippert Emily B. Wong the Vukuzazi Team |
| author_sort |
Jana Fehr |
| title |
Computer-aided interpretation of chest radiography reveals the spectrum of tuberculosis in rural South Africa |
| title_short |
Computer-aided interpretation of chest radiography reveals the spectrum of tuberculosis in rural South Africa |
| title_full |
Computer-aided interpretation of chest radiography reveals the spectrum of tuberculosis in rural South Africa |
| title_fullStr |
Computer-aided interpretation of chest radiography reveals the spectrum of tuberculosis in rural South Africa |
| title_full_unstemmed |
Computer-aided interpretation of chest radiography reveals the spectrum of tuberculosis in rural South Africa |
| title_sort |
computer-aided interpretation of chest radiography reveals the spectrum of tuberculosis in rural south africa |
| publisher |
Nature Portfolio |
| publishDate |
2021 |
| url |
https://doaj.org/article/624d734c5cfd44b79ddb5c726f170c9c |
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