Abstract: Microbial keratitis (MK) is a significant cause of corneal blindness worldwide, necessitating accurate and timely diagnosis for effective treatment. Traditional diagnostic techniques, such as corneal scraping for staining and culture, have limitations in sensitivity, specificity, and result time. This review analyzed peer-reviewed PubMed articles to explore emerging diagnostic modalities that address these challenges, focusing on molecular diagnostics, imaging techniques, and artificial intelligence (AI). Polymerase chain reaction and next-generation sequencing offer rapid and sensitive detection of the causative pathogen, although limitations include cost and false positives. Imaging technologies, such as in vivo confocal microscopy and anterior segment optical coherence tomography, allow for visualization of corneal pathology and may be useful for some etiologies. The emergence of AI with these imaging techniques has demonstrated significant success in classifying pathogens, which can be used to tailor antimicrobial treatment. The integration of these advanced diagnostic tools into clinical practice has the potential to significantly improve the management and outcomes of MK by enabling precise and rapid pathogen identification, guiding more effective treatment strategies, and ultimately reducing the morbidity associated with this condition. As these technologies continue to evolve and become more accessible, they are poised to transform the diagnostic approach to MK.
Vought et al. (Wed,) studied this question.
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