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一个基于前列腺成像报告和数据系统2.1版本的预测模型,用于临床上显著的前列腺癌诊断
David G Gelikman1, William S Azar2, Enis C Yilmaz1
1Molecular Imaging Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
BJU international
|December 10, 2024
概括
一个新的前列腺成像报告和数据系统 (PI-RADS) 2.1 版本的模型整合了多参数MRI,显著改善了临床上显著的前列腺癌检测,并减少了与单独临床数据相比不必要的活检.
科学领域:
- 放射学 放射学是一门学科.
- 在瘤学瘤学.
- 泌尿器科 泌尿器科 泌尿器科 泌尿器科
背景情况:
- 前列腺癌的诊断依赖于准确的风险分层.
- 多参数磁共振成像 (mpMRI) 与前列腺成像报告和数据系统 (PI-RADS) 评分提高了检测.
- 需要验证的预测模型来整合临床和成像数据以进行最佳决策.
研究的目的:
- 开发和验证基于PI-RADS v2.1的临床显著前列腺癌 (csPCa) 的预测模型.
- 整合临床和mpMRI数据以提高诊断准确度.
- 将新型模型的性能与现有的临床和基于MRI的算法进行比较.
主要方法:
- 对1319名接受mpMRI和活检的患者的回顾性分析 (2019年4月至2023年12月).
- 开发一个"临床基线"模型 (人口统计,实验室) 和一个"MRI添加"模型 (包括PI-RADS v2.1分数,前列腺体积).
- 模型的内部和外部验证;使用AUC和决策曲线分析与以前的算法进行比较.
主要成果:
- "MRI添加"模型显示显著改善了区分能力 (AUC内部0.88,AUC外部0.79) 与"临床基线"模型 (AUC内部0.75,AUC外部0.68) 相比.
- 在25%的风险值下",MRI Added"模型减少了27% (内部) 和10% (外部) 的不必要活检.
- 在预测能力或活检减少方面,新模型和比较PI-RADS v2/v1模型之间没有发现显著差异.
结论:
- 基于PI-RADS v2.1的mpMRI模型显著提高了csPCa预测的准确性.
- 这种综合方法有效地减少了不必要的活检,改善了患者管理.
- 该模型对不同人群具有前景,为前列腺癌检测提供了更新的战略.
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