Evaluation of an ultra-portable X-ray system with automated interpretation for tuberculosis active case finding in carceral settings: a diagnostic test accuracy study
Argita D. Salindri, José V. B. Bampi, Caroline Busatto, Alessandra M. da Silva, Andrea da Silva Santos, Isabella B. Gonçalves, Thais O. Gonçalves, Eunice A. T. Cunha, Daniel Tsuha, Everton Lemos, Roberto D. de Oliveira, Mariana Croda, Jason R. Andrews, Julio Croda

TL;DR
This study tested a portable X-ray system with automated analysis for detecting tuberculosis in prisons, showing high accuracy, especially among symptomatic individuals.
Contribution
The study evaluates a novel ultra-portable X-ray system with AI for TB screening in carceral settings, demonstrating its diagnostic accuracy.
Findings
The system achieved an AUC of 0.89 for TB detection, with higher accuracy in symptomatic individuals (AUC 0.93).
TB prevalence was 4.1% among 3399 screened individuals in a Brazilian prison.
The system enabled rapid screening with high diagnostic accuracy in a high-risk population.
Abstract
The World Health Organization recommends systematic active case finding for tuberculosis (TB) among high-risk populations, including incarcerated individuals; however, many prisons lack screening capacity. In this study, we aimed to evaluate the diagnostic performance of an ultra-portable digital chest radiography system paired with LunitTB, an automated interpretation algorithm, to detect TB disease. We conducted a diagnostic test accuracy study using data collected during a prospective active TB case finding effort TB in a Brazilian prison from February 2023 through May 2024. Eligible individuals included adults (≥18 years) without a history of TB in the past two years. A Fujifilm Digital Radiography (FDR) Xair paired with LunitTB algorithm (version v3.1.5.1) system was used to screen consented individuals for TB disease, irrespective of their TB symptoms. Area under curves (AUC) and…
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Taxonomy
TopicsCOVID-19 diagnosis using AI · Tuberculosis Research and Epidemiology · Image Processing Techniques and Applications
