The Performance of Computer-Aided Detection Digital Chest X-ray Reading Technologies for Triage of Active Tuberculosis Among Persons With a History of Previous Tuberculosis

被引:13
|
作者
Kagujje, Mary [1 ]
Kerkhoff, Andrew D. [2 ]
Nteeni, Mutinta [3 ]
Dunn, Ian [4 ]
Mateyo, Kondwelani [5 ]
Muyoyeta, Monde [1 ]
机构
[1] Ctr Infect Dis Res Zambia, TB Dept, Lusaka, Zambia
[2] Univ Calif San Francisco, Div HIV Infect Dis & Global Med Zuckerberg San Fr, San Francisco Gen Hosp & Trauma Ctr, San Francisco, CA 94143 USA
[3] Levy Mwanawasa Univ, Dept Radiol, Teaching Hosp, Lusaka, Zambia
[4] Univ British Columbia, Dept Radiol, Vancouver, BC, Canada
[5] Univ Teaching Hosp, Dept Internal Med, Lusaka, Zambia
关键词
tuberculosis; computer-aided detection; prior TB; CXR; triage; PULMONARY TUBERCULOSIS; DIAGNOSTIC-ACCURACY;
D O I
10.1093/cid/ciac679
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
Among adults with presumptive tuberculosis in Zambia, at a fixed abnormality threshold that achieves 90% sensitivity, the specificity of 2 computer-aided detection systems for reading digital chest X-rays for active tuberculosis was substantially reduced in persons with previous tuberculosis. Background Digital chest X-ray (dCXR) computer-aided detection (CAD) technology uses lung shape and texture analysis to determine the probability of tuberculosis (TB). However, many patients with previously treated TB have sequelae, which also distort lung shape and texture. We evaluated the diagnostic performance of 2 CAD systems for triage of active TB in patients with previously treated TB. Methods We conducted a retrospective analysis of data from a cross-sectional active TB case finding study. Participants >= 15 years, with >= 1 current TB symptom and complete data on history of previous TB, dCXR, and TB microbiological reference (Xpert MTB/RIF) were included. dCXRs were evaluated using CAD4TB (v.7.0) and qXR (v.3.0). We determined the diagnostic accuracy of both systems, overall and stratified by history of TB, using a single threshold for each system that achieved 90% sensitivity and maximized specificity in the overall population. Results Of 1884 participants, 452 (24.0%) had a history of previous TB. Prevalence of microbiologically confirmed TB among those with and without history of previous TB was 12.4% and 16.9%, respectively. Using CAD4TB, sensitivity and specificity were 89.3% (95% CI: 78.1-96.0%) and 24.0% (19.9-28.5%) and 90.5% (86.1-93.3%) and 60.3% (57.4-63.0%) among those with and without previous TB, respectively. Using qXR, sensitivity and specificity were 94.6% (95% CI: 85.1-98.9%) and 22.2% (18.2-26.6%) and 89.7% (85.1-93.2%) and 61.8% (58.9-64.5%) among those with and without previous TB, respectively. Conclusions The performance of CAD systems as a TB triage tool is decreased among persons previously treated for TB.
引用
收藏
页码:E894 / E901
页数:8
相关论文
共 25 条
  • [1] Digital Chest X-Ray with Computer-aided Detection for Tuberculosis Screening within Correctional Facilities
    Velen, Kavindhran
    Sathar, Farzana
    Hoffmann, Christopher J.
    Hausler, Harry
    Fononda, Amanda
    Govender, Sharlene
    Lerefolo, Matsie
    Govender, Ashley
    Charalambous, Salome
    ANNALS OF THE AMERICAN THORACIC SOCIETY, 2022, 19 (08) : 1313 - 1319
  • [2] Diagnostic Accuracy of Chest X-ray Computer-Aided Detection Software for Detection of Prevalent and Incident Tuberculosis in Household Contacts
    Macpherson, Liana
    Kik, Sandra, V
    Quartagno, Matteo
    Lakay, Francisco
    Jaftha, Marche
    Yende, Nombuso
    Galant, Shireen
    Aziz, Saalikha
    Daroowala, Remy
    Court, Richard
    Taliep, Arshad
    Serole, Keboile
    Goliath, Rene T.
    Davies, Nashreen Omar
    Jackson, Amanda
    Douglass, Emily
    Sossen, Bianca
    Mukasa, Sandra
    Thienemann, Friedrich
    Song, Taeksun
    Ruhwald, Morten
    Wilkinson, Robert J.
    Coussens, Anna K.
    Esmail, Hanif
    Imaging of TB Household Contacts Grp, Clifton E.
    CLINICAL INFECTIOUS DISEASES, 2024, : 626 - 636
  • [3] Breaking the threshold: Developing multivariable models using computer-aided chest X-ray analysis for tuberculosis triage
    Geric, Coralie
    Tavaziva, Gamuchirai
    Breuninger, Marianne
    Dheda, Keertan
    Esmail, Ali
    Scott, Alex
    Kagujje, Mary
    Muyoyeta, Monde
    Reither, Klaus
    Khan, Aamir J.
    Benedetti, Andrea
    Khan, Faiz Ahmad
    INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES, 2024, 147
  • [4] Computer-aided detection of pulmonary tuberculosis on digital chest radiographs: a systematic review
    Pande, T.
    Cohen, C.
    Pai, M.
    Khan, F. Ahmad
    INTERNATIONAL JOURNAL OF TUBERCULOSIS AND LUNG DISEASE, 2016, 20 (09) : 1226 - 1230
  • [5] Accuracy of computer-aided chest x-ray interpretation for tuberculosis screening in people with diabetes mellitus: A systematic review
    Emoru, Reagan Daniel
    Mrema, Lucy Elauteri
    Ntinginya, Nyanda Elias
    Biraro, Irene Andia
    van Crevel, Reinout
    Critchley, Julia A.
    TROPICAL MEDICINE & INTERNATIONAL HEALTH, 2025, : 323 - 331
  • [6] Early user perspectives on using computer-aided detection software for interpreting chest X-ray images to enhance access and quality of care for persons with tuberculosis
    Jacob Creswell
    Luan Nguyen Quang Vo
    Zhi Zhen Qin
    Monde Muyoyeta
    Marco Tovar
    Emily Beth Wong
    Shahriar Ahmed
    Shibu Vijayan
    Stephen John
    Rabia Maniar
    Toufiq Rahman
    Peter MacPherson
    Sayera Banu
    Andrew James Codlin
    BMC Global and Public Health, 1 (1):
  • [7] Computer-Aided detection of tuberculosis from X-ray images using CNN and PatternNet classifier
    Abraham, Bejoy
    Mohan, Jesna
    John, Shinu Mathew
    Ramachandran, Sivakumar
    JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY, 2023, 31 (04) : 699 - 711
  • [8] Comprehensive Computer-Aided Decision Support Framework to Diagnose Tuberculosis From Chest X-Ray Images: Data Mining Study
    Owais, Muhammad
    Arsalan, Muhammad
    Mahmood, Tahir
    Kim, Yu Hwan
    Park, Kang Ryoung
    JMIR MEDICAL INFORMATICS, 2020, 8 (12)
  • [9] Diagnostic accuracy of computer aided reading of chest x-ray in screening for pulmonary tuberculosis in comparison with Gene-Xpert
    Nishtar, Tahira
    Burki, Shamsullah
    Ahmad, Fatima Sultan
    Ahmad, Tabish
    PAKISTAN JOURNAL OF MEDICAL SCIENCES, 2022, 38 (01) : 62 - 68
  • [10] Targeted active screening for tuberculosis in Zimbabwe: are field digital chest X-ray ratings reliable?
    Timire, C.
    Sandy, C.
    Ngwenya, M.
    Woznitza, N.
    Kumar, A. M., V
    Takarinda, K. C.
    Sengai, T.
    Harries, A. D.
    PUBLIC HEALTH ACTION, 2019, 9 (03): : 96 - 101