Computer-aided interpretation of chest radiography reveals the spectrum of tuberculosis in rural South Africa
Authors: Fehr Jana , Konigorski Stefan , Olivier Stephen , Gunda Resign , Surujdeen Ashmika , Gareta Dickman , Smit Theresa , Baisley Kathy , Moodley Sashen , Moosa Yumna , Hanekom Willem , Koole Olivier , Ndung’u Thumbi , Pillay Deenan , Grant Alison D. , Siedner Mark J. , Lippert Christoph , Wong Emily B. ,   the Vukuzazi Team, Ramnanan Anand , Mkhwanazi Anele , Rapulana Antony , Singh Anupa , Govender Ashentha , Zungu Ayanda , Mfolo Boitsholo , Magwaza Bongani , Ndlovu Bongumenzi , Mavimbela Clive , Criticos Costa , Munatsi Day , Kalyan Dilip , Mlambo Doctar , Mfeka Fezeka , Mabetlela Freddy , Ording-Jespersen Gregory , Keal Hannah , Dlamini Hlengiwe , Khathi Hlengiwe , Chonco Hlobisile , Gumede Hlobisile , Khumalo Hlolisile , Ngubane Hloniphile , Shen Hollis , Kambonde Hosea , Mpofana Innocentia , Kwinda Jabu , Dreyer Jaco , Cousins Jade , Kalideen Jaikrishna , Seeley Janet , Chetty Kandaseelan , Brien Kayleen , Nyamande Kennedy , Moropane Kgaugelo , Malomane Khabonina , Khan Khadija , Buthelezi Khanyisani , Perumal Kimeshree , Herbst Kobus , Mthembu Lindani , Pillay Logan , Dlamini Mandisi , Zikhali Mandlakayise , Mbuyisa Mbali , Mofokeng Mbuti , Sibiya Melusi , Dube Mlungisi , Suleman Mosa , Steto Mpumelelo , Buthelezi Mzamo , Padayachi Nagavelli , Gqaleni Nceba , Mhlongo Ngcebo , Ntshakala Nokukhanya , Majozi Nomathamsanqa , Zondi Nombuyiselo , Luthuli Nomfundo , Ngema Nomfundo , Buthelezi Nompilo , Mfeka Nonceba , Khuluse Nondumiso , Mabaso Nondumiso , Zitha Nondumiso , Mfekayi Nonhlanhla , Mzimela Nonhlanhla , Mbonambi Nozipho , Mkhwanazi Ntombiyenhlanhla , Ntombela Ntombiyenkosi , Ramkalawon Pamela , Tshivase Pfarelo , Mkhwanazi Phakamani , Mathews Philippa , Mthethwa Phumelele , Ngcobo Phumla , Jackpersad Ramesh , Zondo Raynold , Singh Rochelle , Myeni Rose , Bucibo Sanah , Mthembu Sandile , Harilall Sashin , Makhari Senamile , Mchunu Seneme , Mkhwanazi Senzeni , Gumbi Sibahle , Nene Siboniso , Mhlongo Sibusiso , Mkhwanazi Sibusiso , Nsibande Sibusiso , Ntshangase Simphiwe , Dlamini Siphephelo , Ngcobo Sithembile , Nsibande Siyabonga , Nxumalo Siyabonga , Ndlela Sizwe , Mthombeni Skhumbuzo , Zulu Smangaliso , Mthembu Sphiwe Clement , Ntuli Sphiwe , Ntimbane Talente , Zondi Thabile , Khoza Thandeka , Nkosi Thengokwakhe , Bhengu Thokozani , Simelane Thokozani , Modise Tshwaraganang , Madolo Tumi , Vellem Velile , Mthembu Welcome Petros , Mkhize Xolani , Mbatha Zamashandu , Buthelezi Zinhle , Mthembu Zinhle , Sikhosana Zizile 
Published: July 2021

AbstractComputer-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.