Microendoscopy in vivo for the pathological diagnosis of cervical precancerous lesions and early cervical cancer

Abstract

Abstract Background Cervical cancer is an important public health problem. Conventional colposcopy is inefficient in the diagnosis of cervical lesions and massive biopsies result in trauma. There is an urgent need for a new clinical strategy to triage women with abnormal cervical screening results immediately and effectively. In this study, the high-resolution microendoscopy combined with methylene blue cell staining technology was used to perform real-time in vivo imaging of the cervix for the first time. Methods A total of 41 patients were enrolled in the study. All patients underwent routine colposcopy and cervical biopsy, and high-resolution images of methylene blue-stained cervical lesions were obtained in vivo using microendoscopy. The cell morphological features of benign and neoplastic cervical lesions stained with methylene blue under microendoscopy were analyzed and summarized. The microendoscopy and histopathology findings of the high-grade squamous intraepithelial lesion (HSIL) and more severe lesions were compared. Results The overall consistency of microendoscopy diagnosis with pathological diagnosis was 95.12% (39/41). Diagnostic cell morphological features of cervicitis, low-grade squamous intraepithelial lesion (LSIL), HSIL, adenocarcinoma in situ, and invasive cancer were clearly demonstrated in methylene blue stained microendoscopic images. In HSIL and more severe lesions, microendoscopic methylene blue cell staining technology can show the microscopic diagnostic features consistent with histopathology. Conclusions This study was an initial exercise in the application of the microendoscopy imaging system combined with methylene blue cell staining technology to cervical precancerous lesions and cervical cancer screening. The results provided the basis for a novel clinical strategy for triage of women with abnormal cervical screening results using in vivo non-invasive optical diagnosis technology.