Cited by 35Tuberculosis Research and EpidemiologyAI in cancer detectionCOVID-19 diagnosis using AI

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Computer-assisted chest radiography reading for tuberculosis screening in people living with diabetes mellitus

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Abstract

BACKGROUND: Diabetes mellitus is a significant risk factor for tuberculosis (TB). We evaluated the performance of computer-aided detection for tuberculosis (CAD4TB) in people living with diabetes mellitus (PLWD) in Indonesia. METHODS: PLWD underwent symptom screening and chest X-ray (CXR); sputum was examined in those with positive symptoms and/or CXR. Digital CXRs were scored using CAD4TB and analysed retrospectively using clinical and microbiological diagnosis as a reference. The area under the receiver operator curve (AUC) of CAD4TB scores was determined, and an optimal threshold score established. Agreement between CAD4TB and the radiologist's reading was determined. RESULTS: Among 346 included PLWD, seven (2.0%) had microbiologically confirmed and two (0.6%) had clinically diagnosed TB. The highest agreement of CAD4TB with radiologist reading was achieved using a threshold score of 70 (κ = 0.41, P < 0.001). The AUC for CAD4TB was 0.89 (95%CI 0.73-1.00). A threshold score of 65 for CAD4TB resulted in a sensitivity, specificity, positive predictive value and negative predictive value of respectively 88.9% (95%CI 51.8-99.7), 88.5% (95%CI 84.6-91.7), 17.0% (95%CI 7.6-30.8) and 99.6% (95%CI 98.2-100). With this threshold, 48 (13.9%) individuals needed microbiological examination and no microbiologically confirmed cases were missed. CONCLUSIONS: CAD4TB has potential as a triage tool for TB screening in PLWD, thereby significantly reducing the need for microbiological examination.

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Crossref · 10.5588/ijtld.17.0827

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Metadata

Authors
Koesoemadinata, R. C., Kranzer, K., Livia, R., Susilawati, N., Annisa, J., Soetedjo, N. N. M., Ruslami, R., Philipsen, R., van Ginneken, B., Soetikno, R. D., van Crevel, R., Alisjahbana, B., & Hill, P. C.
Affiliations
  • Padjadjaran University (ID)
  • London School of Hygiene & Tropical Medicine (GB)
  • Infectious Disease Research Centre
  • Dr. Hasan Sadikin General Hospital (ID)
  • Radboud University Medical Center (NL)
  • University of Otago (NZ)
Venue
The International Journal of Tuberculosis and Lung Disease
Published
2018-09-01
Volume
22
Issue
9
Pages
1088-1094
ISSN
1027-3719 (ISSN-L)
OpenAlex
W2886671133
Cited by
35
References
2
Citations by year
2026: 2 · 2025: 3 · 2024: 7 · 2023: 5 · 2022: 7 · 2021: 6 · 2020: 3 · 2019: 2
FWCI
2.09
Type
journal article
Language
en
Open access
Licence
other-oa
Locations
  • The International Journal of Tuberculosis and Lung Disease (publishedVersion)
  • PubMed (publishedVersion)
  • Radboud Repository (Radboud University) (submittedVersion)
  • Radboud Repository (Radboud University) (submittedVersion, other-oa)
Topics
  • Health Sciences › Medicine › Infectious Diseases › Tuberculosis Research and Epidemiology
  • Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › COVID-19 diagnosis using AI
Keywords
tuberculosis screening, diabetes mellitus, computer-aided detection, CAD4TB, chest radiography, triage tool, diagnostic accuracy, threshold scores, Indonesia
MeSH terms
Aged, Female, Humans, Image Processing, Computer-Assisted, Indonesia, Male, Mass Chest X-Ray, Middle Aged, Retrospective Studies, Sensitivity and Specificity, Sputum, Tuberculosis, Pulmonary, Area Under Curve, Diabetes Complications

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