CerS-Path 宫颈病理诊断系统发表：14万张切片预训练 五中心3173例验证筛查敏感度99.38%
《自然·通讯》11月14日发表一项宫颈病理诊断研究，推出名为 CerS-Path 的宫颈亚专科病理诊断系统。该系统采用自监督学习框架，面向宫颈癌病理诊断任务构建。
据论文摘要，CerS-Path 以约14万张组织切片、1.9亿个组织切片块进行自监督预训练，并以250万个图文对做多模态增强，具备筛查、分级、亚型分类、定量、罕见癌分类、预测建模、多模态问答与自动报告生成八项诊断功能。研究指出，基础模型在宫颈癌筛查方面有应用前景，但在临床部署上仍存在重要限制，CerS-Path 正是针对宫颈组织病理的亚专科诊断需求设计。
在前瞻性验证中，CerS-Path 在5个中心共3173例病例上完成评估，筛查敏感度达到99.38%。据论文摘要，该系统在功能范围与临床适用性上超过先前的基础模型。
论文题为《由自监督学习驱动的亚专科诊断系统用于宫颈组织病理》，作者包括 Yizhi Wang、Li Chen、Qiang Huang、Tian Guan 等，参与机构包括清华大学深圳国际研究生院与宁波市临床病理诊断中心等。
CerS-Path Cervical Pathology System Published: Pretrained on 140,000 Slides, 99.38% Screening Sensitivity in 3,173 Prospective Cases Across Five Centers
Nature Communications on November 14 published a cervical histopathology study introducing CerS-Path, a Cervical Subspecialty Pathology diagnostic system built on a self-supervised learning framework for cervical cancer pathology.
According to the abstract, CerS-Path was pretrained in a self-supervised manner on about 190 million tissue patches drawn from roughly 140,000 whole-slide images, with multimodal enhancement from 2.5 million image-text pairs. It provides eight diagnostic functions: screening, grading, subtyping, quantification, rare-cancer classification, predictive modeling, multimodal question answering and automated report generation. The authors note that foundation models are promising for cervical cancer screening but face important limits in clinical deployment, and CerS-Path was designed for subspecialty diagnostic work in cervical histopathology.
In prospective validation across five centers covering 3,173 cases, CerS-Path achieved a screening sensitivity of 99.38 percent. According to the abstract, the system surpasses prior foundation models in scope and clinical applicability.
The paper, 'A subspecialty diagnostic system powered by self-supervised learning for cervical histopathology', is authored by Yizhi Wang, Li Chen, Qiang Huang, Tian Guan and colleagues, with participating institutions including Tsinghua Shenzhen International Graduate School and the Ningbo Clinical Pathology Diagnosis Center.
来源：《自然·通讯》
发布：GSM·美国（发布链接）
图片来源：图：宫颈鳞状细胞癌的组织病理图像（资料图）。来源：Li H 等，Wikimedia Commons，CC BY 4.0。 / Photo: Histopathology image of cervical squamous cell carcinoma (file image). Source: Li H et al., Wikimedia Commons, CC BY 4.0.
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