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在常规乳房MRI中以AI为基础对胸前大动脉动脉瘤进行查

Dimitrios Bounias^1,2, Tobit Führes³, Luise Brock³

¹German Cancer Research Center (DKFZ) Heidelberg, Division of Medical Image Computing, Im Neuenheimer Feld 280, Heidelberg, Germany.

Nature communications

|June 12, 2025

概括

人工神经网络 (ANN) 管道可以在乳房MRI扫描上检测胸前大动脉动脉瘤,提高检测率3.5倍. 这项技术可以同时对乳腺癌和大动脉动脉瘤进行查,从而有可能改善患者的治疗结果.

科学领域:

放射学放射学是一门学科.
人工智能的人工智能
心血管成像 - 心血管成像

背景情况:

胸前动脉动脉瘤 (TAA) 在女性中预后较差.
磁共振成像 (MRI) 越来越多地用于乳腺癌查.
在乳房MRI中同时检测TAA可以改善早期诊断.

研究的目的:

验证一个全自动的人工神经网络 (ANN) 管道,用于在乳腺MRI检查中检测TAA.
评估ANN的表现与地面真相细分,临床报告和专家读者的表现.
评估乳腺癌和TAA综合查的潜力.

主要方法:

从公共和内部数据集中对5057个乳腺MRI扫描进行ANN管道的回顾性验证.
使用3D基准真实细分,临床报告和多读者面板进行ANN性能基准测试.
评估不同MRI供应商和现场强度的技术稳定性.

主要成果:

该ANN管道表现出高的技术稳定性,子/clDice得分为0.88-0.91/0.97-0.99.
与常规临床读数相比,ANN辅助的TAA检测率高3.5倍.
在有乳腺癌史的女性中观察到TAA的更高几率比率 (OR=2.29).

结论:

一个完全自动化的ANN管道在乳房MRI扫描上有效检测胸前大动脉动脉瘤.
这项技术显著提高了TAA检测率,为改善早期诊断和患者结果提供了潜力.
对乳腺癌和TAA的综合同时评估可能会带来额外的好处,特别是对于有乳腺癌病史的女性.

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