Related Experiment Video

Updated: Sep 13, 2025

Diagnosing Pulmonary Tuberculosis with the Xpert MTB/RIF Test

Diagnosing Pulmonary Tuberculosis with the Xpert MTB/RIF Test

Published on: April 9, 2012

Evaluating the accuracy of artificial intelligence-powered chest X-ray diagnosis for paediatric pulmonary

Brekhna Aurangzeb¹, Dennis Robert², Cynthia Baard^3,4

¹Centre for International Health, Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.

|July 29, 2025

Insights

This study evaluates artificial intelligence (AI) for diagnosing childhood pulmonary tuberculosis (PTB) using chest X-rays (CXRs). AI shows potential to improve diagnostic accuracy in children, aiding faster and more reliable PTB detection.

Area of Science:

Pediatric Infectious Diseases
Medical Imaging Analysis
Artificial Intelligence in Healthcare

Background:

Diagnosing childhood pulmonary tuberculosis (PTB) is difficult due to subtle symptoms and challenges in microbiological confirmation.
Chest X-ray (CXR) interpretation is crucial for diagnosis and disease severity assessment in pediatric PTB.
While AI has shown promise in adult PTB diagnosis via CXR, its utility in children remains under-investigated.

Purpose of the Study:

To evaluate the sensitivity and specificity of an AI-CXR algorithm (qXR) for detecting PTB in children.
To assess the impact of AI assistance on the diagnostic performance of clinicians and radiologists interpreting pediatric CXRs.

Main Methods:

A prospective, two-stage study in South Africa and Pakistan involving children with presumed PTB.
Stage I: AI algorithm (qXR) processed CXRs against a radiologist-defined reference standard for PTB classification.
Stage II: A multi-reader study assessed AI's effect on diagnostic accuracy using a cross-over design.

Main Results:

The primary endpoint is the AI algorithm's sensitivity and specificity in identifying confirmed and unconfirmed PTB cases.
A secondary endpoint will assess AI's performance for microbiologically confirmed PTB cases.
Stage II will quantify the improvement in diagnostic performance with AI-assisted CXR interpretation.

Conclusions:

This research aims to establish the diagnostic value of AI in pediatric PTB detection through CXR analysis.
Findings will inform the potential integration of AI tools to enhance the diagnosis of PTB in children.
The study will contribute valuable data on AI's role in pediatric radiology and infectious disease diagnostics.

Read full analysis

Abstract

Introduction:

Diagnosing pulmonary tuberculosis (PTB) in children is challenging owing to paucibacillary disease, non-specific symptoms and signs and challenges in microbiological confirmation. Chest X-ray (CXR) interpretation is fundamental for diagnosis and classifying disease as severe or non-severe. In adults with PTB, there is substantial evidence showing the usefulness of artificial intelligence (AI) in CXR interpretation, but very limited data exist in children.

Methods And Analysis:

A prospective two-stage study of children with presumed PTB in three sites (one in South Africa and two in Pakistan) will be conducted. In stage I, eligible children will be enrolled and comprehensively investigated for PTB. A CXR radiological reference standard (RRS) will be established by an expert panel of blinded radiologists. CXRs will be classified into those with findings consistent with PTB or not based on RRS. Cases will be classified as confirmed, unconfirmed or unlikely PTB according to National Institutes of Health definitions. Data from 300 confirmed and unconfirmed PTB cases and 250 unlikely PTB cases will be collected. An AI-CXR algorithm (qXR) will be used to process CXRs. The primary endpoint will be sensitivity and specificity of AI to detect confirmed and unconfirmed PTB cases (composite reference standard); a secondary endpoint will be evaluated for confirmed PTB cases (microbiological reference standard). In stage II, a multi-reader multi-case study using a cross-over design will be conducted with 16 readers and 350 CXRs to assess the usefulness of AI-assisted CXR interpretation for readers (clinicians and radiologists). The primary endpoint will be the difference in the area under the receiver operating characteristic curve of readers with and without AI assistance in correctly classifying CXRs as per RRS.

Ethics And Dissemination:

The study has been approved by a local institutional ethics committee at each site. Results will be published in academic journals and presented at conferences. Data will be made available as an open-source database.

Study Registration Number:

PACTR202502517486411.

Keywords:

Artificial Intelligence Chest imaging Diagnostic radiology Paediatric infectious disease & immunisation Pulmonary Disease Tuberculosis

More Related Videos

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer

Author Spotlight: Advancing 3D Modeling for Enhanced Diagnosis and Treatment of Pulmonary Nodules in Early-Stage Lung Cancer

Published on: October 13, 2023

Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules

Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules

Published on: May 19, 2023

Related Concept Videos

Pulmonary Tuberculosis IV

Pulmonary Tuberculosis IV

Tuberculosis, more commonly referred to as TB, is an infectious disease stemming from Mycobacterium tuberculosis. While it primarily impacts the lungs, TB can also affect other body areas. Given its severity and global impact, timely and accurate diagnosis is crucial for controlling its spread and improving patient outcomes.
Several diagnostic approaches are used to detect TB. The conventional method is the Tuberculin Skin Test (TST), also known as the Mantoux test. However, this method has...

Pneumonia III: Complications and Assessment

Pneumonia III: Complications and Assessment

Pneumonia poses the potential for numerous complications that warrant consideration. These complications include the following:

Radiological Investigation I: X-ray and CT

Radiological Investigation I: X-ray and CT

Radiological investigations, including X-rays and computed tomography (CT) scans, are critical for diagnosing and evaluating various medical conditions. These imaging techniques provide valuable insights into the body's internal structures, aiding in the detection of abnormalities, assessment of disease progression, and development of treatment strategies. This article delves into two primary radiological investigations, chest X-rays and CT scans, outlining their purpose, procedures, and...

Pulmonary Tuberculosis V

Pulmonary Tuberculosis V

Medical management of tuberculosis (TB) patients involves a comprehensive approach that includes diagnosis, treatment, and monitoring. The specific strategies can vary depending on the type of tuberculosis (latent or active), the patient's overall health status, and other considerations.
Latent tuberculosis infection occurs when TB bacteria are present in a person's body, but are not causing illness or symptoms. It is not contagious, and preventive treatment is crucial to avoid the...

Pulmonary Tuberculosis III

Pulmonary Tuberculosis III

Tuberculosis (TB) is a contagious infection primarily affecting the lung parenchyma but which can also affect other body parts. TB can be classified based on disease development, presentation, and the affected anatomical site.
The first classification is based on the development of the disease, and it includes the following categories:

Pulmonary Tuberculosis I

Pulmonary Tuberculosis I

Tuberculosis, often called TB, is a contagious illness primarily caused by Mycobacterium tuberculosis. It mainly affects the lung parenchyma but can also impact other body parts.
Causative Organism
The primary infectious agent causing tuberculosis is Mycobacterium tuberculosis, a slow-growing, acid-fast, aerobic rod that exhibits sensitivity to heat and ultraviolet light. Instances of Mycobacterium bovis and Mycobacterium avium contributing to the development of TB infection are rare.
Mode of...

Articles linked to this work by shared authors, journal, and citation graph.

Long term outcome following pulmonary TB or lower respiratory tract illness in children: a prospective South African study.

EClinicalMedicine·2026

A meta-proteomics approach using autopsy material from the pre-antibiotic era from patients with untreated pulmonary tuberculosis to identify proteins present in early lesions of post-primary tuberculosis.

PloS one·2026

Factors Associated with Outcomes of Non-Invasive Ventilation in Acute Hypercapnic Respiratory Failure with Acidosis: A Study from a Tertiary Care Hospital in Pakistan.

Journal of clinical medicine·2026

Evaluating the Usefulness of Artificial Intelligence-based Chest X-Ray Screening in Improving Tuberculosis Detection Among the High-Risk Tribal Population of Chhattisgarh, India: A Prospective Multi-Centre Study.

Open forum infectious diseases·2026

Evaluation of the Performance of Stool Samples to Diagnose Pediatric Pulmonary Tuberculosis in Routine Care: A Cohort Study From Pakistan.

Open forum infectious diseases·2025

Development and internal validation of multimodal machine learning models for predicting eligibility for mechanical thrombectomy in suspected stroke patients using routinely collected clinical and imaging data.

PloS one·2025

See all related articles