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.
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).


METHODS
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.
Department of medicine, School of Medicine, University of Zambia, ZAMBART Project, Lusaka, Zambia.
Monde
M
Muyoyeta
Diagnostic Image Analysis Group, Radboud University Medical Center, Nijmegen, The Netherlands.
Pragnya
P
Maduskar
Department of medicine, School of Medicine, University of Zambia, ZAMBART Project, Lusaka, Zambia.
Maureen
M
Moyo
Department of medicine, School of Medicine, University of Zambia, ZAMBART Project, Lusaka, Zambia.
Nkatya
N
Kasese
Department of medicine, School of Medicine, University of Zambia, ZAMBART Project, Lusaka, Zambia.
Deborah
D
Milimo
Department of medicine, School of Medicine, University of Zambia, ZAMBART Project, Lusaka, Zambia.
Rosanna
R
Spooner
National TB program, Ministry of Health, Lusaka, Zambia.
Nathan
N
Kapata
Diagnostic Image Analysis Group, Radboud University Medical Center, Nijmegen, The Netherlands.
Laurens
L
Hogeweg
Diagnostic Image Analysis Group, Radboud University Medical Center, Nijmegen, The Netherlands.
Bram
B
van Ginneken
Department of medicine, School of Medicine, University of Zambia, ZAMBART Project, Lusaka, Zambia; Clinical research department, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Helen
H
Ayles
D019540:Area Under Curve; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008400:Mass Chest X-Ray / Q000379:methods*; D008856:Microscopy, Fluorescence; D009169:Mycobacterium tuberculosis / Q000302:isolation & purification; D011237:Predictive Value of Tests; D012372:ROC Curve; D012680:Sensitivity and Specificity; D013183:Sputum / Q000382:microbiology; D014397:Tuberculosis, Pulmonary / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000453:epidemiology*; D015024:Zambia / Q000453:epidemiology