从多参数MRI进行术前高风险前列腺癌预测的可解释性息地和周放射学:一项多机构研究
Mengxuan Yuan1,2,3, Di Chang4, Wanjun Lu5
1Department of Radiology, Jiangdu People's Hospital Affiliated to Yangzhou University, 100 Jiangzhou Road, Jiangdu district, Yangzhou, Jiangsu, 225200, PR China. 15895711125@yzu.edu.cn.
Journal of translational medicine
|February 14, 2026
概括
这项研究引入了一种先进的放射学框架,用于精确的术前前列腺癌风险评估. 综合模型利用息地和周分析,显著改善了高风险前列腺癌的预测.
科学领域:
- 放射学 放射学是一门学科.
- 在瘤学瘤学.
- 人工智能的人工智能
背景情况:
- 目前前前列腺癌的术前评估存在局限性,包括主观PI-RADS评分和诊断不确定性.
- 区分高风险前列腺癌与良性或低风险病变仍然具有挑战性.
研究的目的:
- 开发一个可解释的集体学习框架,用于术前高风险前列腺癌预测.
- 从多参数MRI中整合基于息地的放射学和周围分析.
主要方法:
- 在896名经遗传学证实前列腺病变的患者中进行了多机构的回顾性研究.
- 内息地分析使用K-means集群和周分析,使用1-5毫米的扩张环.
- 通过mRMR和LASSO回归,外部验证和SHAP分析来进行特征选择.
主要成果:
- 在外部验证中,综合息地和周放射学模型获得了优异的性能 (AUC: 0.860-0.876).
- 息地特征显著超过了内和临床特征.
- 来自ADC的特征,特别是来自息地区域H3的特征,是关键预测因素.
结论:
- 综合息地和周放射学为前列腺癌提供了强大的手术前风险分层.
- ADC衍生的息地特征在预测高风险前列腺癌方面表现出卓越的表现.
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