» Articles » PMID: 37965525

Computer-aided Diagnostic Accuracy of Pulmonary Tuberculosis on Chest Radiography Among Lower Respiratory Tract Symptoms Patients

Overview
Specialty Public Health
Date 2023 Nov 15
PMID 37965525
Authors
Affiliations
Soon will be listed here.
Abstract

Even though the Gaza Strip is a low pulmonary tuberculosis (TB) burden region, it is well-known that TB is primarily a socioeconomic problem associated with overcrowding, poor hygiene, a lack of fresh water, and limited access to healthcare, which is the typical case in the Gaza Strip. Therefore, this study aimed at assessing the accuracy of the automatic software computer-aided detection for tuberculosis (CAD4TB) in diagnosing pulmonary TB on chest radiography and compare the CAD4TB software reading with the results of geneXpert. Using a census sampling method, the study was conducted in radiology departments in the Gaza Strip hospitals between 1 December 2022 and 31 March 2023. A digital X-ray, printer, and online X-ray system backed by CAD4TBv6 software were used to screen patients with lower respiratory tract symptoms. GeneXpert analysis was performed for all patients having a score > 40. A total of 1,237 patients presenting with lower respiratory tract symptoms participated in this current study. Chest X-ray readings showed that 7.8% ( = 96) were presumptive for TB. The CAD4TBv6 scores showed that 11.8% ( = 146) of recruited patients were presumptive for TB. GeneXpert testing on sputum samples showed that 6.2% ( = 77) of those with a score > 40 on CAD4TB were positive for pulmonary TB. Significant differences were found in chest X-ray readings, CAD4TBv6 scores, and GeneXpert results among sociodemographic and health status variables (-value < 0.05). The study showed that the incidence rate of TB in the Gaza Strip is 3.5 per 100,000 population in the Gaza strip. The sensitivity of the CAD4TBv6 score and the symptomatic review for tuberculosis with a threshold score of >40 is 80.2%, and the specificity is 94.0%. The positive Likelihood Ratio is 13.3%, Negative Likelihood Ratio is 0.2 with 7.8% prevalence. Positive Predictive Value is 52.7%, Negative Predictive Value is 98.3%, and accuracy is 92.9%. In a resource-limited country with a high burden of neglected disease, combining chest X-ray readings by CAD4TB and symptomatology is extremely valuable for screening a population at risk. CAD4TB is noticeably more efficient than other methods for TB screening and early diagnosis in people who would otherwise go undetected.

Citing Articles

Comparative effectiveness of chest ultrasound, chest X-ray and computer-aided diagnostic (CAD) for tuberculosis diagnosis in low-resource setting: study protocol for a cross-sectional study from Ethiopia.

Guido G, Nigussa W, Cotugno S, Kenate Sori B, Bobbio F, Gulo B Front Public Health. 2024; 12:1476866.

PMID: 39691654 PMC: 11650444. DOI: 10.3389/fpubh.2024.1476866.

References
1.
Nishtar T, Burki S, Ahmad F, Ahmad T . Diagnostic accuracy of computer aided reading of chest x-ray in screening for pulmonary tuberculosis in comparison with Gene-Xpert. Pak J Med Sci. 2022; 38(1):62-68. PMC: 8713241. DOI: 10.12669/pjms.38.1.4531. View

2.
Lakhani P, Sundaram B . Deep Learning at Chest Radiography: Automated Classification of Pulmonary Tuberculosis by Using Convolutional Neural Networks. Radiology. 2017; 284(2):574-582. DOI: 10.1148/radiol.2017162326. View

3.
Gautam S, Shrestha N, Mahato S, Nguyen T, Mishra S, Berg-Beckhoff G . Diabetes among tuberculosis patients and its impact on tuberculosis treatment in South Asia: a systematic review and meta-analysis. Sci Rep. 2021; 11(1):2113. PMC: 7822911. DOI: 10.1038/s41598-021-81057-2. View

4.
Fatima R, Qadeer E, Yaqoob A, Ul Haq M, Majumdar S, Shewade H . Extending 'Contact Tracing' into the Community within a 50-Metre Radius of an Index Tuberculosis Patient Using Xpert MTB/RIF in Urban, Pakistan: Did It Increase Case Detection?. PLoS One. 2016; 11(11):e0165813. PMC: 5127497. DOI: 10.1371/journal.pone.0165813. View

5.
Harris M, Qi A, Jeagal L, Torabi N, Menzies D, Korobitsyn A . A systematic review of the diagnostic accuracy of artificial intelligence-based computer programs to analyze chest x-rays for pulmonary tuberculosis. PLoS One. 2019; 14(9):e0221339. PMC: 6719854. DOI: 10.1371/journal.pone.0221339. View