A novel, one stop, affordable, point of care and artificial intelligence supported system of screening, triage and treatment selection for cervical cancer and precancer in the LMICs

复活节应用程序标识符1161104 摘要报表 人工智能(AI)已经渗透到包括医学在内的许多科学学科中。人工智能正在快速发展 被誉为宫颈癌筛查的极具前景的解决方案。基于人工智能的宫颈病变检测 肿瘤被美国NCI命名为自动视觉检查(AVE)。尽管有有效的 宫颈癌前病变的筛查、分流和治疗方法，宫颈癌的消除仍然难以捉摸 大多数疾病流行的低收入和中等收入国家(LMIC)。我们建议 开发和评估一种用于筛查和分诊妇女的新型人工智能系统的性能特征 以及在治疗决策方面的帮助。人工智能将分析来自尿液的红外光谱信号 未经筛查的妇女样本中是否存在高危人乳头瘤病毒(hr-HPV)。我们的预赛 研究表明，光谱学可以检测出尿液中的人乳头瘤病毒。对于屏幕积极的女性，人工智能将解读 用高质量专用摄像机拍摄的一组宫颈图像检测高级别宫颈癌前病变 并确定转化区(TZ)的类型(有助于治疗决策)。这个 我们已经开发了图像采集原型装置和人工智能算法。这些技术将 在第一阶段(最初两年)得到进一步改进，并在第二阶段(随后三年)得到验证。期间阶段 1，我们将分析从津巴布韦多个筛查诊所收集的2000名妇女的尿样 利用光谱学检测人乳头瘤病毒的存在，并利用产生的信号来改进AI算法。在……里面 在这一阶段，我们还将评估尿样中人乳头瘤病毒检测的一致性。 使用有效的HPV检测进行光谱分析和宫颈HPV检测。一种宫颈图像识别装置， 在第一阶段，人工智能算法将进一步改进，收集更多来自hr-hpv阳性的图像。 和消极的女人。AI还将接受解释宫颈图像的培训，以确定TZ类型。在……里面 津巴布韦第二阶段共3800名妇女将接受人工智能支持的尿液光谱分析 检测hrHPV和有效的HPV检测，以评估和比较它们检测的敏感性和特异性 组织学-证实为高级别的宫颈癌前病变和癌症。人工智能支持的敏感性和特异性 宫颈图像上宫颈肿瘤的检测将被评估为对HPV阳性妇女进行分类。这个 人工智能判断TZ类型的准确性将与专家意见进行比较。在现场验证阶段 (第二阶段)，我们还将进行成本分析，并将我们方法的成本与当前标准进行比较 津巴布韦的做法。国际癌症研究机构(世卫组织癌症研究 组织)与美国特拉华州的Neo Sense矢量公司(NSV)合作(行业)， 兰开斯特大学工程系，英国兰开斯特，津巴布韦大学，学院 津巴布韦哈拉雷健康科学公司将实施这项研究，重点放在创新上，这将对 在全球消除宫颈癌，这是世卫组织的一项优先事项。

EASTER Application identifier 1161104 Summary statement Artificial intelligence (AI) has penetrated many scientific disciplines, including medicine. AI is fast gaining reputation as a highly promising solution for cervical cancer screening. AI-based detection of cervical neoplasias is named automated visual exam (AVE) by the US NCI. Despite the availability of effective screening, triage and treatment methods for cervical pre-cancer, cervical cancer elimination is still elusive in low and middle income countries (LMICs) where the great majority of disease prevails. We propose to develop and evaluate the performance characteristics of a novel AI system to both screen and triage women as well as help in treatment decision making. AI will analyse infrared spectroscopic signals derived from urine samples of unscreened women for the presence of high-risk Human Papillomavirus (hr-HPV). Our preliminary study has shown that spectroscopy can detect hr-HPV in urine. For screen-positive women the AI will interpret a set of cervical images captured with a high-quality devoted camera to detect high grade cervical precancers and cancers and to determine the type of transformation zone (TZ) (helps in treatment decision). The prototype device for image capture and the AI algorithms are already developed by us. The technologies will be further improved in phase 1 (initial 2 years) and validated in phase 2 (subsequent 3 years). During phase 1, we will analyse urine samples collected from 2000 women at multiple screening clinics in Zimbabwe for the presence of hr-HPV using spectroscopy and use the signals generated to improve the AI algorithm. In this phase we will also assess the concordance between hr-HPV detection in urine samples using spectroscopy and cervical HPV detection using a validated HPV test. The cervical image recognition device and the AI algorithm will be further improved during phase 1 by collecting more images from hr-HPV positive and negative women. AI will also be trained to interpret the cervical images to determine the TZ type. In phase 2 total 3800 women will be screened in Zimbabwe with AI-supported spectroscopic analysis of urine to detect hrHPV and a validated HPV test to evaluate and compare their sensitivity and specificity to detect histology-proved high grade cervical precancers and cancers. The sensitivity and specificity of AI-supported detection of cervical neoplasias on cervical images will be evaluated to triage the HPV positive women. The accuracy of AI to determine TZ type will be compared with expert opinion. During the field validation phase (phase 2), we will also conduct a cost analysis and compare cost of our approach to current standard Zimbabwean practice. The International Agency for Research on Cancer (WHO cancer research organization) has partnered with The Neo Sense Vector Company (NSV), Delaware, USA (industry), The Engineering Department, Lancaster University, Lancaster, UK and The University of Zimbabwe, College of Health Sciences, Harare, Zimbabwe to implement this study focusing on innovation that will greatly contribute to the global elimination of cervical cancer, a WHO priority.