The optimization and application of photodynamic diagnosis and autofluorescence imaging in tumor diagnosis and guided surgery: current status and future prospects.

Photodynamic diagnosis (PDD) and autofluorescence imaging (AFI) are emerging cancer diagnostic technologies that offer significant advantages over traditional white-light endoscopy in detecting precancerous lesions and early-stage cancers; moreover, they hold promising potential in fluorescence-guided surgery (FGS) for tumors. However, their shortcomings have somewhat hindered the clinical application of PDD and AFI. Therefore, it is imperative to enhance the efficacy of PDD and AFI, thereby maximizing their potential for practical clinical use. This article reviews the principles, characteristics, current research status, and advancements of PDD and AFI, focusing on analyzing and discussing the optimization strategies of PDD and AFI in tumor diagnosis and FGS scenarios. Considering the practical and technical feasibility, optimizing PDD and AFI may result in an effective real-time diagnostic tool to guide clinicians in tumor diagnosis and surgical guidance to achieve the best results.