基于多模式的MRI模型用于结肠直肠肝转移的预测:将放射学,深度学习和临床特征与SHAP解释集成
Xin Yan1, Furui Duan2, Lu Chen1
1Department of Radiology, The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China.
Current oncology (Toronto, Ont.)
|August 27, 2025
概括
这项研究开发了一种可解释的多模式MRI模型,用于预测结直肠癌肝转移 (CRLM). 综合模型结合了放射学和深度学习,实现了高精度,有助于对CRLM风险评估的临床决策.
科学领域:
- 癌症学
- 放射学
- 医学成像
- 机器学习
背景情况:
- 预测结直肠癌的肝转移对于患者的预后至关重要.
- 多参数MRI提供了非侵入性CRLM评估的潜力.
研究的目的:
- 开发和验证可解释的多模式机器学习框架,使用多参数MRI进行CRLM预测.
- 使用SHapley添加式扩展 (SHAP) 和深度学习可视化来增强模型的解释性.
主要方法:
- 在463名结肠直肠癌患者中进行的多中心回顾性研究.
- 从T2WI和DWI中提取放射学特征,并使用ResNet101进行深度学习特征.
- 使用LASSO逻辑回归的临床,放射学,深度学习和组合模型的开发.
主要成果:
- 综合模型实现了高AUC (0. 889培训,0. 838内部,0. 822外部验证),表现优于单一模式.
- SHAP分析确定了T2WI纹理和CA19-9作为关键预测因素;Grad-CAM证实了深度学习对瘤区域的关注.
- 决策曲线分析显示,综合模型的临床净益增加.
结论:
- 为非侵入性CRLM预测开发了一个强大的,可解释的多参数MRI模型.
- 将放射学和深度学习功能与SHAP/Grad-CAM集成可以提高预测性能和临床相关性.
- 该模型显示了作为个人化结直肠癌管理的决策支持工具的潜力.
更多相关视频
04:09Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
Published on: October 10, 2018
8.3K
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025
193
相关概念视频
01:24Magnetic Resonance Imaging
7.6K
Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
7.6K
01:27Imaging Studies IV: Magnetic Resonance Imaging
427
Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...
427