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Cervical cancer related to high-risk human papillomavirus (HR-HPV) is the second female cancer in Mauritania (Northwest Sahelian Africa). We assessed the distribution of HPV genotypes in Mauritanian women with high-grade cervical intraepithelial neoplasia (CIN2/3) or invasive cervical cancer (ICC). A prospective study was conducted in the Centre Hospitalier National, Nouakchott, Mauritania, to collect cervical biopsies among women suspected of CIN2/3 or cancer. HPV DNA detection and genotyping were carried out from formalin-fixed, paraffin-embedded biopsies using multiplex PCR (Human Papillomavirus Genotyping Real-Time PCR Kit, Bioperfectus Technologies Co., Taizhou, China). Fifty biopsies were included from women (mean age: 56.7 years) suffering from CIN2/3 (28.0%) and ICC (72.0%) which corresponded to 32 (64.0%) squamous cell carcinomas (SCC) and 4 (8.0%) adenocarcinomas (ADC). HPV DNA detection was successful in 47 (94.0%) samples. The most prevalent HR-HPV genotypes were HPV-45 (40.4%), HPV-16 (38.3%), HPV-39 and HPV-52 (23.4%), HPV-33 (17.0%), HPV-18 (14.9%), HPV-35 (4.2%), and HPV-56 (2.1%). The majority (93.6%) of HPV-positive biopsies contained at least one HPV type covered by the 9-valent Gardasil-9® vaccine, and 40.9% were infected by multiple vaccine HPV genotypes. To eradicate cervical cancer in Mauritania, prophylactic HPV vaccination must be combined with primary molecular screening of cervical HR-HPV infection. [ABSTRACT FROM AUTHOR]

The rising global incidence of cervical cancer is estimated to have affected more than 600,000 women, and nearly 350,000 women are predicted to have died from the disease in 2020 alone. Novel advances in cancer prevention, screening, diagnosis and treatment have all but reduced the burden of cervical cancer in developed nations. Unfortunately, cervical cancer is still the number one gynecological cancer globally. A limiting factor in managing cervical cancer globally is access to healthcare systems and trained medical personnel. Any methodology or procedure that may simplify or assist cervical cancer screening is desirable. Herein, we assess the use of artificial intelligence (AI)-assisted colposcopy in a tertiary hospital cervical diagnostic pathology unit. The study group consisted of 48 women (mean age 34) who were referred to the clinic for a routine colposcopy by their gynecologist. Cervical images were taken by an EVA-Visualcheck TM colposcope and run through an AI algorithm that gave real-time binary results of the cervical images as being either normal or abnormal. The primary endpoint of the study assessed the AI algorithm's ability to correctly identify histopathology results of CIN2+ as being abnormal. A secondary endpoint was a comparison between the AI algorithm and the clinical assessment results. Overall, we saw lower sensitivity of AI (66.7%; 12/18) compared with the clinical assessment (100%; 18/18), and histopathology results as the gold standard. The positive predictive value (PPV) was comparable between AI (42.9%; 12/28) and the clinical assessment (41.8%; 18/43). The specificity, however, was higher in the AI algorithm (46.7%; 14/30) compared to the clinical assessment (16.7%; 5/30). Comparing the congruence between the AI algorithm and histopathology results showed agreement 54.2% of the time and disagreement 45.8% of the time. A trained colposcopist was in agreement 47.9% and disagreement 52.1% of the time. Assessing these results, there is currently no added benefit of using the AI algorithm as a tool of speeding up diagnosis. However, given the steady improvements in the AI field, we believe that AI-assisted colposcopy may be of use in the future. [ABSTRACT FROM AUTHOR]