The role of medical imaging in translational research into early pulmonary tuberculosis

Early detection of tuberculosis (TB) is central to global efforts for TB care and prevention. Conventional symptom-based screening and sputum microbiology fail to identify a substantial proportion of cases, particularly those that are asymptomatic or have low bacillary burden. Non-invasive medical imaging offers a critical solution for visualizing pulmonary pathology before individuals with TB develop characteristic symptoms. Chest X-ray has long been central to community screening, and recent advances in computer-aided detection systems endorsed by the World Health Organization have improved scalability and reduced reliance on expert interpretation. However, limitations in sensitivity for the earliest stages of disease and reduced specificity in individuals with prior lung pathology persist, underscoring the need for further research to improve performance for early TB detection. High-resolution modalities, such as computed tomography, magnetic resonance imaging, and functional imaging approaches, such as positron emission tomography and single-photon emission computed tomography, provide unparalleled insights into lesion dynamics, disease activity, and treatment response. They can be utilized to benchmark the development of novel diagnostic tests for bacteriologically unconfirmed TB and define imaging correlates of early disease progression and resolution. Furthermore, emerging innovations in pathogen-specific radiotracers may enable localization of viable bacilli in vivo. As a result, these new high-resolution imaging technologies offer transformative potential to address key knowledge gaps in the natural history, pathogenesis, dissemination, and therapeutic approaches to early pulmonary TB. Together, clinical imaging provides a framework for the development and validation of clinically relevant biomarkers and quantitative readouts that capture early, asymptomatic TB pathology and disease activity before conventional microbiologic confirmation. Future work should focus on integrating advanced imaging with microbiology, host-response biomarkers, and artificial intelligence to define actionable imaging phenotypes that inform early diagnosis, risk stratification, and treatment decision-making across diverse settings.