Scholarlink

<p>Cancer screening can enable early detection and improve survival but a focus on single cancers limits cost-effectiveness. Here we present OMAFound (carcinOMA Finder foundation), a foundation model capable of simultaneous multi-cancer screening at both organ level and patient level using widely accessible non-contrast computed tomography (CT). The model was developed and tested on 325,197 CT volumes from 151,386 patients across 10 Chinese and international datasets, achieving performance comparable to mammography-based approaches for breast cancer detection and matching existing lung-specific models for lung cancer detection. In a prospective multi-centre cohort of 21,601 patients undergoing low-dose CT screening, OMAFound demonstrated balanced accuracy of 82.2% for breast cancer and 88.0% for lung cancer in females, while attaining 86.1% balanced accuracy for lung cancer detection in males. When assisted by OMAFound, 7 generalist radiologists showed improvement in sensitivity (mean increases of 38.9% for breast cancer, 16.0% for lung cancer and 21.3% at patient level), without compromising specificity. These findings highlight the potential of OMAFound as a multi-cancer screening tool to offer robust preventive medicine strategies with minimal costs.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A foundation model for breast and lung cancer screening using non-contrast computed tomography

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月5日

查看全文
  • Zhiying Liang,
  • Qingliang Niu,
  • Jinmei Wang,
  • Chunguang Han,
  • Qin Li,
  • Yiming Wu,
  • Baoxi Zhu,
  • Xipeng Han,
  • Zhaorui Wang,
  • Xia Wang,
  • Chenglu Hu,
  • Chongyan Liu,
  • Yu Zhao,
  • Jingjing Wang,
  • Zikang Wang,
  • Yongyi Ni,
  • Jing Pei,
  • Xuejun Qian

摘要

Cancer screening can enable early detection and improve survival but a focus on single cancers limits cost-effectiveness. Here we present OMAFound (carcinOMA Finder foundation), a foundation model capable of simultaneous multi-cancer screening at both organ level and patient level using widely accessible non-contrast computed tomography (CT). The model was developed and tested on 325,197 CT volumes from 151,386 patients across 10 Chinese and international datasets, achieving performance comparable to mammography-based approaches for breast cancer detection and matching existing lung-specific models for lung cancer detection. In a prospective multi-centre cohort of 21,601 patients undergoing low-dose CT screening, OMAFound demonstrated balanced accuracy of 82.2% for breast cancer and 88.0% for lung cancer in females, while attaining 86.1% balanced accuracy for lung cancer detection in males. When assisted by OMAFound, 7 generalist radiologists showed improvement in sensitivity (mean increases of 38.9% for breast cancer, 16.0% for lung cancer and 21.3% at patient level), without compromising specificity. These findings highlight the potential of OMAFound as a multi-cancer screening tool to offer robust preventive medicine strategies with minimal costs.