Shamsunder Saritha, Mishra Archana, Kumar Anita, Kolte Sachin
Gynecology Department, Safdarjung Hospital, New Delhi 110029, India.
Department of Pathology, VMMC and Safdarjung Hospital, New Delhi 110029, India.
Diagnostics (Basel). 2023 Sep 28;13(19):3085. doi: 10.3390/diagnostics13193085.
In low-resource settings, a point-of-care test for cervical cancer screening that can give an immediate result to guide management is urgently needed. A transvaginal digital device, "Smart Scope" (SS), with an artificial intelligence-enabled auto-image-assessment (SS-AI) feature, was developed. In a single-arm observational study, eligible consenting women underwent a Smart Scope-aided VIA-VILI test. Images of the cervix were captured using SS and categorized by SS-AI in four groups (green, amber, high-risk amber (HRA), red) based on risk assessment. Green and amber were classified as SS-AI negative while HRA and red were classified as SS-AI positive. The SS-AI-positive women were advised colposcopy and guided biopsy. The cervix images of SS-AI-negative cases were evaluated by an expert colposcopist (SS-M); those suspected of being positive were also recommended colposcopy and guided biopsy. Histopathology was considered a gold standard. Data on 877 SS-AI, 485 colposcopy, and 213 histopathology were available for analysis. The SS-AI showed high sensitivity (90.3%), specificity (75.3%), accuracy (84.04%), and correlation coefficient (0.670, = 0.0) in comparison with histology at the CINI+ cutoff. In conclusion, the AI-enabled Smart Scope test is a good alternative to the existing screening tests as it gives a real-time accurate assessment of cervical health and an opportunity for immediate triaging with visual evidence.
在资源匮乏地区，迫切需要一种能够即时给出结果以指导治疗的宫颈癌筛查即时检验方法。一种具有人工智能自动图像评估（SS-AI）功能的经阴道数字设备“智能镜”（SS）被研发出来。在一项单臂观察性研究中，符合条件并同意参与的女性接受了智能镜辅助的醋酸肉眼观察-碘试验（VIA-VILI）。使用智能镜采集宫颈图像，并由SS-AI根据风险评估将其分为四组（绿色、琥珀色、高危琥珀色（HRA）、红色）。绿色和琥珀色被分类为SS-AI阴性，而HRA和红色被分类为SS-AI阳性。建议SS-AI阳性的女性进行阴道镜检查并引导活检。SS-AI阴性病例的宫颈图像由专业阴道镜医师（SS-M）进行评估；那些疑似阳性的病例也被建议进行阴道镜检查并引导活检。组织病理学被视为金标准。共有877例SS-AI、485例阴道镜检查和213例组织病理学数据可供分析。与CINI+临界值时的组织学相比，SS-AI显示出高灵敏度（90.3%）、特异性（75.3%）、准确性（84.04%）和相关系数（0.670，P = 0.0）。总之，具有人工智能功能的智能镜检测是现有筛查检测的良好替代方法，因为它能实时准确评估宫颈健康状况，并提供基于视觉证据进行即时分流的机会。
