Tuberculosis Diagnosis: Current, Ongoing, and Future Approaches

• Published in: Diseases Vol. 12; no. 9; p. 202
• Main Authors: Bartolomeu-Gonçalves, Guilherme, Souza, Joyce Marinho de, Fernandes, Bruna Terci, Spoladori, Laís Fernanda Almeida, Correia, Guilherme Ferreira, Castro, Isabela Madeira de, Borges, Paulo Henrique Guilherme, Silva-Rodrigues, Gislaine, Tavares, Eliandro Reis, Yamauchi, Lucy Megumi, Pelisson, Marsileni, Perugini, Marcia Regina Eches, Yamada-Ogatta, Sueli Fumie
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 03.09.2024; MDPI
• Subjects: Accuracy; Artificial intelligence; BCG; BCG vaccines; Cavitation; Deep learning; Diagnosis; diagnostic techniques; Disease; Disease transmission; Drug resistance; Forecasts and trends; Gene amplification; HIV; Human immunodeficiency virus; Infectious diseases; Innovations; Laboratories; Methods; Microscopy; molecular techniques; Mycobacterium tuberculosis; Polymerase chain reaction; pulmonary tuberculosis diagnosis; Radiography; Review; Reviews; Sputum; Stains & staining; Tuberculosis; Brazil; Israel; Massachusetts; China; Germany; India; Mycobacterium tuberculosis; pulmonary tuberculosis diagnosis; molecular techniques; diagnostic techniques
• ISSN: 2079-9721; 2079-9721
• DOI: 10.3390/diseases12090202

Tuberculosis (TB) remains an impactful infectious disease, leading to millions of deaths every year. causes the formation of granulomas, which will determine, through the host-pathogen relationship, if the infection will remain latent or evolve into active disease. Early TB diagnosis is life-saving, especially among immunocompromised individuals, and leads to proper treatment, preventing transmission. This review addresses different approaches to diagnosing TB, from traditional methods such as sputum smear microscopy to more advanced molecular techniques. Integrating these techniques, such as polymerase chain reaction (PCR) and loop-mediated isothermal amplification (LAMP), has significantly improved the sensitivity and specificity of identification. Additionally, exploring novel biomarkers and applying artificial intelligence in radiological imaging contribute to more accurate and rapid diagnosis. Furthermore, we discuss the challenges of existing diagnostic methods, including limitations in resource-limited settings and the emergence of drug-resistant strains. While the primary focus of this review is on TB diagnosis, we also briefly explore the challenges and strategies for diagnosing non-tuberculous mycobacteria (NTM). In conclusion, this review provides an overview of the current landscape of TB diagnostics, emphasizing the need for ongoing research and innovation. As the field evolves, it is crucial to ensure that these advancements are accessible and applicable in diverse healthcare settings to effectively combat tuberculosis worldwide.