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Gynecol Oncol ; 154(3): 558-564, 2019 09.
Artigo em Inglês | MEDLINE | ID: mdl-31288949

RESUMO

OBJECTIVE: Cervical cancer rates in the United States have declined since the 1940's, however, cervical cancer incidence remains elevated in medically-underserved areas, especially in the Rio Grande Valley (RGV) along the Texas-Mexico border. High-resolution microendoscopy (HRME) is a low-cost, in vivo imaging technique that can identify high-grade precancerous cervical lesions (CIN2+) at the point-of-care. The goal of this study was to evaluate the performance of HRME in medically-underserved areas in Texas, comparing results to a tertiary academic medical center. METHODS: HRME was evaluated in five different outpatient clinical settings, two in Houston and three in the RGV, with medical providers of varying skill and training. Colposcopy, followed by HRME imaging, was performed on eligible women. The sensitivity and specificity of traditional colposcopy and colposcopy followed by HRME to detect CIN2+ were compared and HRME image quality was evaluated. RESULTS: 174 women (227 cervical sites) were included in the final analysis, with 12% (11% of cervical sites) diagnosed with CIN2+ on histopathology. On a per-site basis, a colposcopic impression of low-grade precancer or greater had a sensitivity of 84% and a specificity of 45% to detect CIN2+. While there was no significant difference in sensitivity (76%, p = 0.62), the specificity when using HRME was significantly higher than that of traditional colposcopy (56%, p = 0.01). There was no significant difference in HRME image quality between clinical sites (p = 0.77) or medical providers (p = 0.33). CONCLUSIONS: HRME imaging increased the specificity for detecting CIN2+ when compared to traditional colposcopy. HRME image quality remained consistent across different clinical settings.


Assuntos
Colonoscopia/economia , Colonoscopia/métodos , Área Carente de Assistência Médica , Lesões Pré-Cancerosas/diagnóstico por imagem , Neoplasias do Colo do Útero/diagnóstico por imagem , Feminino , Humanos , Processamento de Imagem Assistida por Computador , Gradação de Tumores , Lesões Pré-Cancerosas/economia , Estudos Prospectivos , Sensibilidade e Especificidade , Texas , Estados Unidos , Neoplasias do Colo do Útero/patologia , Displasia do Colo do Útero/diagnóstico por imagem , Displasia do Colo do Útero/economia
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