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A multi-country head-to-head accuracy comparison of automated chest X-ray algorithms for tuberculosis

Computer-aided detection algorithms for automated chest X-ray reading have been endorsed by the World Health Organization for tuberculosis triage, but independent, multi-country assessment of current products is needed to guide implementation.We included chest X-rays from adults who presented to out...

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Main Authors: Worodria, William (Author) , Castro, Robert (Author) , Kik, Sandra V (Author) , Dalay, Victoria (Author) , Derendinger, Brigitta (Author) , Festo, Charles (Author) , Nguyen, Thanh Quoc (Author) , Raberahona, Mihaja (Author) , Sudarsan, Swati (Author) , Andama, Alfred (Author) , Thangakunam, Balamugesh (Author) , Lyimo, Issa (Author) , Nguyen, Viet Nhung (Author) , Rakotoarivelo, Rivo (Author) , Theron, Grant (Author) , Yu, Charles (Author) , Denkinger, Claudia M. (Author) , Lapierre, Simon Grandjean (Author) , Cattamanchi, Adithya (Author) , Christopher, Devasahayam J (Author) , Jaganath, Devan (Author)
Format: Article (Journal)
Language:English
Published: May 2026
In: Annals of the American Thoracic Society
Year: 2026, Volume: 23, Issue: 5, Pages: 728-736
ISSN:2325-6621
DOI:10.1093/annalsats/aaoag011
Online Access:Verlag, kostenfrei, Volltext: https://doi.org/10.1093/annalsats/aaoag011
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Author Notes:William Worodria, Robert Castro, Sandra V Kik, Victoria Dalay, Brigitta Derendinger, Charles Festo, Thanh Quoc Nguyen, Mihaja Raberahona, Swati Sudarsan, Alfred Andama, Balamugesh Thangakunam, Issa Lyimo, Viet Nhung Nguyen, Rivo Rakotoarivelo, Grant Theron, Charles Yu, Claudia M. Denkinger, Simon Grandjean Lapierre, Adithya Cattamanchi, Devasahayam J Christopher, Devan Jaganath, and the R2D2 TB Network
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Summary:Computer-aided detection algorithms for automated chest X-ray reading have been endorsed by the World Health Organization for tuberculosis triage, but independent, multi-country assessment of current products is needed to guide implementation.We included chest X-rays from adults who presented to outpatient facilities with at least 2 weeks of cough in India, Madagascar, the Philippines, South Africa, Tanzania, Uganda, and Vietnam.We calculated and compared the accuracy overall and by country and key groups for 7 computer-aided detection algorithms: CAD4TB, qXR, INSIGHT CXR, DrAid, Genki, InferRead, and Radify. We determined if any computer-aided detection product could achieve the minimum target accuracy for a tuberculosis triage test (≥ 90% sensitivity and ≥ 70% specificity).Of 3901 individuals included, the median age was 41 years (IQR, 29-54 years), 12.9% were people living with HIV, 8.2% were living with diabetes, and 21.2% had a prior history of tuberculosis. Specificity ranged from 30.9% to 73.5% at 90% sensitivity. CAD4TB achieved the highest specificity at 90% sensitivity (73.5% specific [95% CI, 71.9%-75.1%]), although qXR and INSIGHT CXR also achieved the target 70% specificity. There was heterogeneity by country and subgroup that improved with population-specific thresholds, except for people living with HIV, 50 years and older, or with a history of tuberculosis.Multiple computer-aided detection algorithms achieved the minimum target accuracy for a tuberculosis triage test among symptomatic individuals with cough. Further efforts are needed to integrate computer-aided detection into routine tuberculosis case detection programs in high-burden communities.
Item Description:Veröffentlicht: 30. Januar 2026
Gesehen am 17.08.2026
Physical Description:Online Resource
ISSN:2325-6621
DOI:10.1093/annalsats/aaoag011

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