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Assessment of non-tuberculosis abnormalities on digital chest x-rays with high CAD4TB scores from a tuberculosis prevalence survey in Zambia and South Africa

BACKGROUND: Chest X-rays (CXRs) have traditionally been used to aid the diagnosis of TB-suggestive abnormalities. Using Computer-Aided Detection (CAD) algorithms, TB risk is quantified to assist with diagnostics. However, CXRs capture all other structural abnormalities. Identification of non-TB abno...

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Autores principales: Ngosa, Dennis, Moonga, Given, Shanaube, Kwame, Jacobs, Choolwe, Ruperez, Maria, Kasese, Nkatya, Klinkenberg, Eveline, Schaap, Ab, Mureithi, Linda, Floyd, Sian, Fidler, Sarah, Sichizya, Veronica, Maleya, Adrian, Ayles, Helen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10408069/
https://www.ncbi.nlm.nih.gov/pubmed/37553658
http://dx.doi.org/10.1186/s12879-023-08460-0
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author Ngosa, Dennis
Moonga, Given
Shanaube, Kwame
Jacobs, Choolwe
Ruperez, Maria
Kasese, Nkatya
Klinkenberg, Eveline
Schaap, Ab
Mureithi, Linda
Floyd, Sian
Fidler, Sarah
Sichizya, Veronica
Maleya, Adrian
Ayles, Helen
author_facet Ngosa, Dennis
Moonga, Given
Shanaube, Kwame
Jacobs, Choolwe
Ruperez, Maria
Kasese, Nkatya
Klinkenberg, Eveline
Schaap, Ab
Mureithi, Linda
Floyd, Sian
Fidler, Sarah
Sichizya, Veronica
Maleya, Adrian
Ayles, Helen
author_sort Ngosa, Dennis
collection PubMed
description BACKGROUND: Chest X-rays (CXRs) have traditionally been used to aid the diagnosis of TB-suggestive abnormalities. Using Computer-Aided Detection (CAD) algorithms, TB risk is quantified to assist with diagnostics. However, CXRs capture all other structural abnormalities. Identification of non-TB abnormalities in individuals with CXRs that have high CAD scores but don’t have bacteriologically confirmed TB is unknown. This presents a missed opportunity of extending novel CAD systems’ potential to simultaneously provide information on other non-TB abnormalities alongside TB. This study aimed to characterize and estimate the prevalence of non-TB abnormalities on digital CXRs with high CAD4TB scores from a TB prevalence survey in Zambia and South Africa. METHODOLOGY: This was a cross-sectional analysis of clinical data of participants from the TREATS TB prevalence survey conducted in 21 communities in Zambia and South Africa. The study included individuals aged ≥ 15 years who had high CAD4TB scores (score ≥ 70), but had no bacteriologically confirmed TB in any of the samples submitted, were not on TB treatment, and had no history of TB. Two consultant radiologists reviewed the images for non-TB abnormalities. RESULTS: Of the 525 CXRs reviewed, 46.7% (245/525) images were reported to have non-TB abnormalities. About 11.43% (28/245) images had multiple non-TB abnormalities, while 88.67% (217/245) had a single non-TB abnormality. The readers had a fair inter-rater agreement (r = 0.40). Based on anatomical location, non-TB abnormalities in the lung parenchyma (19%) were the most prevalent, followed by Pleura (15.4%), then heart & great vessels (6.1%) abnormalities. Pleural effusion/thickening/calcification (8.8%) and cardiomegaly (5%) were the most prevalent non-TB abnormalities. Prevalence of (2.7%) for pneumonia not typical of pulmonary TB and (2.1%) mass/nodules (benign/ malignant) were also reported. CONCLUSION: A wide range of non-TB abnormalities can be identified on digital CXRs among individuals with high CAD4TB scores but don’t have bacteriologically confirmed TB. Adaptation of AI systems like CAD4TB as a tool to simultaneously identify other causes of abnormal CXRs alongside TB can be interesting and useful in non-faculty-based screening programs to better link cases to appropriate care. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-023-08460-0.
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spelling pubmed-104080692023-08-09 Assessment of non-tuberculosis abnormalities on digital chest x-rays with high CAD4TB scores from a tuberculosis prevalence survey in Zambia and South Africa Ngosa, Dennis Moonga, Given Shanaube, Kwame Jacobs, Choolwe Ruperez, Maria Kasese, Nkatya Klinkenberg, Eveline Schaap, Ab Mureithi, Linda Floyd, Sian Fidler, Sarah Sichizya, Veronica Maleya, Adrian Ayles, Helen BMC Infect Dis Research BACKGROUND: Chest X-rays (CXRs) have traditionally been used to aid the diagnosis of TB-suggestive abnormalities. Using Computer-Aided Detection (CAD) algorithms, TB risk is quantified to assist with diagnostics. However, CXRs capture all other structural abnormalities. Identification of non-TB abnormalities in individuals with CXRs that have high CAD scores but don’t have bacteriologically confirmed TB is unknown. This presents a missed opportunity of extending novel CAD systems’ potential to simultaneously provide information on other non-TB abnormalities alongside TB. This study aimed to characterize and estimate the prevalence of non-TB abnormalities on digital CXRs with high CAD4TB scores from a TB prevalence survey in Zambia and South Africa. METHODOLOGY: This was a cross-sectional analysis of clinical data of participants from the TREATS TB prevalence survey conducted in 21 communities in Zambia and South Africa. The study included individuals aged ≥ 15 years who had high CAD4TB scores (score ≥ 70), but had no bacteriologically confirmed TB in any of the samples submitted, were not on TB treatment, and had no history of TB. Two consultant radiologists reviewed the images for non-TB abnormalities. RESULTS: Of the 525 CXRs reviewed, 46.7% (245/525) images were reported to have non-TB abnormalities. About 11.43% (28/245) images had multiple non-TB abnormalities, while 88.67% (217/245) had a single non-TB abnormality. The readers had a fair inter-rater agreement (r = 0.40). Based on anatomical location, non-TB abnormalities in the lung parenchyma (19%) were the most prevalent, followed by Pleura (15.4%), then heart & great vessels (6.1%) abnormalities. Pleural effusion/thickening/calcification (8.8%) and cardiomegaly (5%) were the most prevalent non-TB abnormalities. Prevalence of (2.7%) for pneumonia not typical of pulmonary TB and (2.1%) mass/nodules (benign/ malignant) were also reported. CONCLUSION: A wide range of non-TB abnormalities can be identified on digital CXRs among individuals with high CAD4TB scores but don’t have bacteriologically confirmed TB. Adaptation of AI systems like CAD4TB as a tool to simultaneously identify other causes of abnormal CXRs alongside TB can be interesting and useful in non-faculty-based screening programs to better link cases to appropriate care. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-023-08460-0. BioMed Central 2023-08-08 /pmc/articles/PMC10408069/ /pubmed/37553658 http://dx.doi.org/10.1186/s12879-023-08460-0 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Ngosa, Dennis
Moonga, Given
Shanaube, Kwame
Jacobs, Choolwe
Ruperez, Maria
Kasese, Nkatya
Klinkenberg, Eveline
Schaap, Ab
Mureithi, Linda
Floyd, Sian
Fidler, Sarah
Sichizya, Veronica
Maleya, Adrian
Ayles, Helen
Assessment of non-tuberculosis abnormalities on digital chest x-rays with high CAD4TB scores from a tuberculosis prevalence survey in Zambia and South Africa
title Assessment of non-tuberculosis abnormalities on digital chest x-rays with high CAD4TB scores from a tuberculosis prevalence survey in Zambia and South Africa
title_full Assessment of non-tuberculosis abnormalities on digital chest x-rays with high CAD4TB scores from a tuberculosis prevalence survey in Zambia and South Africa
title_fullStr Assessment of non-tuberculosis abnormalities on digital chest x-rays with high CAD4TB scores from a tuberculosis prevalence survey in Zambia and South Africa
title_full_unstemmed Assessment of non-tuberculosis abnormalities on digital chest x-rays with high CAD4TB scores from a tuberculosis prevalence survey in Zambia and South Africa
title_short Assessment of non-tuberculosis abnormalities on digital chest x-rays with high CAD4TB scores from a tuberculosis prevalence survey in Zambia and South Africa
title_sort assessment of non-tuberculosis abnormalities on digital chest x-rays with high cad4tb scores from a tuberculosis prevalence survey in zambia and south africa
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10408069/
https://www.ncbi.nlm.nih.gov/pubmed/37553658
http://dx.doi.org/10.1186/s12879-023-08460-0
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