一个全面的放射病理学名图,用于预测胃癌的病理阶段,使用CT衍生和基于WSI的特征
Yang Tan1, Li-Juan Feng2, Ying-He Huang3
1Department of Pathology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, PR China.
Translational oncology
|December 23, 2023
概括
一种新的放射病理学名图准确地区分了早期 (I-II阶段) 和晚期 (III阶段) 的胃癌. 这种结合成像和病理学的方法有助于精确的胃癌分期.
科学领域:
- 在瘤学瘤学.
- 医疗成像医学成像
- 计算病理学计算病理学
背景情况:
- 胃癌的分期对于治疗计划至关重要.
- 准确区分早期 (I-II阶段) 和晚期 (III阶段) 的胃癌是必不可少的.
- 目前的分期方法可以通过综合数据分析来改进.
研究的目的:
- 开发和验证放射病理学模型,以区分胃癌的病理阶段.
- 结合CT扫描的放射学特征和来自组织病理学图像的病理学特征.
- 创建一个预测模型来区分I-II阶段和III阶段的胃癌.
主要方法:
- 200名胃癌患者被分为训练 (n=140) 和测试 (n=60) 队列.
- 从CT图像中提取了放射学特征;使用深度学习从整个幻灯片图像中提取了病理学特征.
- 使用机器学习算法 (SVM,LR,MLP) 构建和评估了放射学,病理学和综合放射病理学模型.
主要成果:
- 最佳放射学模型 (MLP_rad) 在测试队列中实现了0.797的AUC.
- 最佳病理学模型 (SVM_path) 在测试队列中实现了0.792的AUC.
- 综合放射病理学名图显示出卓越的性能,测试队列中的AUC为0.837.
结论:
- 一种新的放射病理学名图有效地区分了I-II期和III期胃癌.
- 这种综合方法利用手术前CT和组织病理学数据进行准确的分期.
- 该模型有可能在手术前预测胃癌的分期.
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