Advances in Photodynamic Treatment of Precancerous and Cancerous Gynecological Diseases
Abstract
High mortality rates and poor quality of life result from the late-stage detection and frequent recurrence of gynecological neoplasms. Background/Objectives: The aim of this study was to conduct a systematic analysis of the energy parameters of photodynamic therapy (PDT) in the treatment of cervical and vulvar lesions, with a focus on stimulating immune responses leading to human papillomavirus (HPV) eradication and lesion regression without adverse effects, such as thermal damage. Methods: A total of 46 peer-reviewed studies published between January 2010 and April 2024 were analyzed. These studies focused on PDT applications for cervical and vulvar lesions, sourced from Google Scholar, Scopus, and Web of Science. Results: Although PDT shows promise, significant limitations exist, such as insufficient consideration of individual tumor characteristics, restricted treatment depths, and the heterogeneous distribution and low selectivity of photosensitizer (PS) accumulation in tumors. Tumor hypoxia further reduces PDT's effectiveness, and most studies overlook immune system activation, which is crucial for targeting HPV infections and improving antitumor responses. Conclusions: Advancing the research into PDT's molecular and cellular mechanisms, optimizing the immune response stimulation, and improving the PS and delivery methods could enhance the safety and effectiveness of cervical and vulvar neoplasm treatments. The use of personalized PDT parameters may reduce the side…
Read the paper
Related studies
- Chaos and quantum thermalization
- The Dalton quantum chemistry program system
- Quantum dots: synthesis, bioapplications, and toxicity
- Cord Blood Leptin and Adiponectin as Predictors of Adiposity in Children at 3 Years of Age: A Prospective Cohort Study
- A Guide to In Silico Drug Design
- Quantitative metabolomics by H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.