Advanced imaging tools could help detect tuberculosis earlier
24 Mar 2026
On World TB Day, new findings show that advanced imaging technologies can detect evidence of asymptomatic tuberculosis (TB) in the lungs years before symptoms appear or routine tests are positive. The study, published yesterday in The Lancet Respiratory Medicine, is the largest of its kind to follow high‑risk individuals with sensitive imaging over five years.
Global estimates suggest that up to one‑quarter of the world’s population has been infected by the bacteria Mycobacterium tuberculosis. However, this figure is based largely on inference from tests showing an immune response to the bacterium, not direct evidence of infection. Most people with a positive immune response never develop disease. Predicting who will progress to TB remains one of the most urgent gaps in TB prevention. “Identifying those most likely to develop TB is crucial if we want to prevent transmission and intervene earlier”, said study first author Professor Hanif Esmail from UCL.
In the study, researchers followed 250 HIV-negative, asymptomatic people in Khayelitsha, Cape Town, South Africa, who were household contacts of drug-resistant TB cases. Each participant received a PET‑CT scan as well as a digital chest X‑ray interpreted by artificial intelligence (AI) tools. Participants were monitored for up to five years.
During the follow‑up period, 18 individuals were diagnosed and treated for TB. Six were identified early through enhanced screening at the start of the study, five of whom would have been missed by routine rapid molecular testing, while the remaining 12 were diagnosed with TB after an average of three years. Many of these participants were still asymptomatic at the time bacteria were detected in their sputum, highlighting that transmission may occur before routine systems detect disease.
PET‑CT is the most sensitive imaging tool for research use and revealed a wide spectrum of lung abnormalities. However, those whose PET‑CT scans showed a specific set of abnormalities associated with TB at the start of the study were more than 28 times more likely to be diagnosed with TB during follow-up compared with individuals whose scans appeared normal. Thus, whilst 205 of the 250 showed an immune response to the bacterium, it was the 29 with lung abnormalities on the PET-CT scans that were at the highest risk of TB diagnosis.
“These findings position PET‑CT as a powerful research tool for understanding how TB progresses in the body. While the method is too costly and complex for large-scale public health use, its precision offers valuable insights for clinical research studies to develop improved diagnostics and therapeutics.”, said co-senior author Associate Professor Anna Coussens.
More immediately impactful, however, was the performance of AI‑interpreted chest X-rays. Although less sensitive than PET‑CT, the AI readings showed good alignment with PET‑CT predictions, suggesting significant promise for mass screening.
“AI-read chest X-rays could play a vital role in strengthening TB control strategies through mass-screening efforts.”, said co-senior author Professor Robert J Wilkinson.
The study highlights a critical advancement: the ability to identify people likely to have TB long before symptoms appear. With earlier detection comes the possibility of timely intervention, reducing transmission, preventing lung damage, and improving global TB prevention efforts.
The study was co-authored by over 30 researchers, including the following institutions: UCL, University of Cape Town, Walter and Eliza Hall Institute of Medical Research, Stellenbosch University, Rutgers University, Boston University, University of Pittsburgh, National Institute of Allergy and Infectious Diseases, Imperial College, and the Francis Crick Institute
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