Study on the Optimization of Precise Positioning Biopsy and Subsequent Treatment Strategy of Cervical Lesions under Hysteroscopy

Abstract

Cervical lesions remain a significant public health challenge due to their potential progression to cervical cancer, necessitating effective diagnostic and therapeutic approaches. This study focuses on the optimization of precise positioning biopsy and subsequent treatment strategies for cervical lesions under hysteroscopy, a minimally invasive diagnostic procedure. By leveraging advanced imaging modalities, such as narrow-band imaging (NBI) and artificial intelligence (AI)-assisted diagnostics, hysteroscopy offers unparalleled accuracy in detecting and sampling suspicious lesions. Comparative analyses reveal its superiority over traditional methods, including colposcopy, in enhancing diagnostic sensitivity and specificity.

Subsequent treatment strategies tailored to biopsy results emphasize minimally invasive techniques, fertility-preserving options, and emerging molecular therapies. High-grade lesions are addressed through targeted excisional or ablative procedures, while advanced cases benefit from multidisciplinary interventions, including immunotherapy and chemoradiation. The integration of AI in diagnostic workflows and the development of portable hysteroscopic systems represent promising avenues for improving accessibility and efficiency.

This study synthesizes existing advancements, identifies persistent gaps, and proposes innovative solutions to refine the diagnostic and therapeutic landscape of cervical lesion management. By addressing barriers such as procedural costs, training limitations, and variability in diagnostic accuracy, this research aims to contribute to the equitable and effective treatment of cervical lesions, ultimately reducing the global burden of cervical cancer.