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The Sensitivity and Specificity of Using a Computer Aided Diagnosis Program for Automatically Scoring Chest X-Rays of Presumptive TB Patients Compared with Xpert MTB/RIF in Lusaka Zambia

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Muyoyeta, Monde, Maduskar, Pragnya, Moyo, Maureen, Kasese, Nkatya, Milimo, Deborah, Spooner, Rosanna, Kapata, Nathan, Hogeweg, Laurens +2 more·2014·PLoS ONE
DOI 10.1371/journal.pone.0093757PMC PMC3976315
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Abstract

OBJECTIVE: To determine the sensitivity and specificity of a Computer Aided Diagnosis (CAD) program for scoring chest x-rays (CXRs) of presumptive tuberculosis (TB) patients compared to Xpert MTB/RIF (Xpert). METHOD: Consecutive presumptive TB patients with a cough of any duration were offered digital CXR, and opt out HIV testing. CXRs were electronically scored as normal (CAD score ≤ 60) or abnormal (CAD score > 60) using a CAD program. All patients regardless of CAD score were requested to submit a spot sputum sample for testing with Xpert and a spot and morning sample for testing with LED Fluorescence Microscopy-(FM). RESULTS: Of 350 patients with evaluable data, 291 (83.1%) had an abnormal CXR score by CAD. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of CXR compared to Xpert were 100% (95%CI 96.2-100), 23.2% (95%CI 18.2-28.9), 33.0% (95%CI 27.6-38.7) and 100% (95% 93.9-100), respectively. The area under the receiver operator curve (AUC) for CAD was 0.71 (95%CI 0.66-0.77). CXR abnormality correlated with smear grade (r = 0.30, p<0.0001) and with Xpert CT(r = 0.37, p<0.0001). CONCLUSIONS: To our knowledge this is the first time that a CAD program for TB has been successfully tested in a real world setting. The study shows that the CAD program had high sensitivity but low specificity and PPV. The use of CAD with digital CXR has the potential to increase the use and availability of chest radiography in screening for TB where trained human resources are scarce.

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  • We expected a lower CAD specificity in our setting as CXR is known to be less sensitive in immunocompromised patients with pulmonary TB.

    “We therefore expected a lower CAD specificity in our setting as CXR is known to be less sensitive in immunocompromised patients with pulmonary TB [38–41].”

    From Accuracy of computer-aided chest X-ray in community-based tuberculosis screening: Lessons from the 2016 Kenya National Tuberculosis Prevalence Survey (2022) · cites this paper as [41]

    The Discussion (page unavailable) reports significantly lower CAD specificity in HIV-positive than HIV-negative patients and attributes it to nonspecific CXR changes that can mimic TB. It does not say that CXR is less sensitive in immunocompromised patients with pulmonary TB; instead, it describes CAD sensitivity in the study as high. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

  • The majority of studies reporting on CAD threshold determination only included individuals who met criteria for microbiological testing.

    “The majority of studies reporting on CAD threshold determination only included individuals who met some criteria for microbiological testing, such as having symptoms and/or abnormal chest radiographs [8, 16–27].”

    From Computer-aided detection thresholds for digital chest radiography interpretation in tuberculosis diagnostic algorithms. (2024) · cites this paper as [21]

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Authors
Muyoyeta, M., Maduskar, P., Moyo, M., Kasese, N., Milimo, D., Spooner, R., Kapata, N., Hogeweg, L., van Ginneken, B., & Ayles, H.
Affiliations
  • University of Zambia (ZM)
  • Radboud University Medical Center (NL)
  • Ministry of Health (ZM)
Corresponding author
Muyoyeta, Monde
ORCID
Venue
PLoS ONE
Publisher
Public Library of Science (PLoS)
Published
2014-04-04
Volume
9
Issue
4
Pages
e93757
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0093757
PMC
PMC3976315
OpenAlex
W2164703398
Cited by
98
References
2
Citations by year
2026: 2 · 2025: 4 · 2024: 9 · 2023: 10 · 2022: 6 · 2021: 10 · 2020: 10 · 2019: 10 · 2018: 13 · 2017: 5 · 2016: 5 · 2015: 12 · 2014: 2
FWCI
5.62
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Radboud Repository (Radboud University) (submittedVersion)
  • Radboud Repository (Radboud University) (submittedVersion, other-oa)
Funders
World Health Organization
Topics
  • Health Sciences › Medicine › Infectious Diseases › Tuberculosis Research and Epidemiology
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › COVID-19 diagnosis using AI
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Diagnosis and Treatment
Keywords
computer-aided diagnosis, chest radiography, tuberculosis, presumptive tuberculosis, Xpert MTB/RIF, diagnostic accuracy, sensitivity and specificity, tuberculosis screening, digital radiography, smear-negative tuberculosis
MeSH terms
Humans, Image Interpretation, Computer-Assisted, Mass Chest X-Ray, Microscopy, Fluorescence, Mycobacterium tuberculosis, Predictive Value of Tests, ROC Curve, Sensitivity and Specificity, Sputum, Tuberculosis, Pulmonary, Zambia, Area Under Curve

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