ehealth digital library

Digital library of
the Tanzania
health
community

Diagnostic Accuracy of Computer-Aided Detection of Pulmonary Tuberculosis in Chest Radiographs: A Validation Study from Sub-Saharan Africa.

Breuninger, M., van Ginneken, B., Philipsen, R. H. H. M., Mhimbira, F., Hella, J. J., Lwilla, F., van den Hombergh, J., Ross, A., Jugheli, L., Wagner, D. and Reither, K. (2014) Diagnostic Accuracy of Computer-Aided Detection of Pulmonary Tuberculosis in Chest Radiographs: A Validation Study from Sub-Saharan Africa. PloS one, 9 (9). e106381. ISSN 1932-6203

[img]
Preview
PDF
Marianne_Breuninger.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial.

Download (963kB)

Abstract

Chest radiography to diagnose and screen for pulmonary tuberculosis has limitations, especially due to inter-reader variability. Automating the interpretation has the potential to overcome this drawback and to deliver objective and reproducible results. The CAD4TB software is a computer-aided detection system that has shown promising preliminary findings. Evaluation studies in different settings are needed to assess diagnostic accuracy and practicability of use. CAD4TB was evaluated on chest radiographs of patients with symptoms suggestive of pulmonary tuberculosis enrolled in two cohort studies in Tanzania. All patients were characterized by sputum smear microscopy and culture including subsequent antigen or molecular confirmation of Mycobacterium tuberculosis (M.tb) to determine the reference standard. Chest radiographs were read by the software and two human readers, one expert reader and one clinical officer. The sensitivity and specificity of CAD4TB was depicted using receiver operating characteristic (ROC) curves, the area under the curve calculated and the performance of the software compared to the results of human readers. Of 861 study participants, 194 (23%) were culture-positive for M.tb. The area under the ROC curve of CAD4TB for the detection of culture-positive pulmonary tuberculosis was 0.84 (95% CI 0.80-0.88). CAD4TB was significantly more accurate for the discrimination of smear-positive cases against non TB patients than for smear-negative cases (p-value<0.01). It differentiated better between TB cases and non TB patients among HIV-negative compared to HIV-positive individuals (p<0.01). CAD4TB significantly outperformed the clinical officer, but did not reach the accuracy of the expert reader (p = 0.02), for a tuberculosis specific reading threshold. CAD4TB accurately distinguished between the chest radiographs of culture-positive TB cases and controls. Further studies on cost-effectiveness, operational and ethical aspects should determine its place in diagnostic and screening algorithms.

Item Type: Article
Keywords: Pulmonary Tuberculosis, Chest Radiographs, Computer, CAD4TB software, Mycobacterium tuberculosis, Tanzania
Subjects: Tuberculosis > Diagnosis
Divisions: Ifakara Health Institute > Biomedical
Depositing User: Mr Joseph Madata
Date Deposited: 15 Sep 2014 06:01
Last Modified: 15 Sep 2014 06:01
URI: http://ihi.eprints.org/id/eprint/2859

Actions (login required)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics