相关实验视频

Updated: Jul 24, 2026

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Published on: December 15, 2014

基于动态对比增强MRI的深度学习框架来分层诺丁汉组织学二级乳腺瘤

Roham Hadidchi¹, Anchita Agrawal¹, Michael Z Liu¹

¹Department of Radiology, Montefiore Health System and Albert Einstein College of Medicine, Bronx, NY, USA.

European radiology

|December 17, 2025

概括

使用MRI的深度学习模型可以区分中等级 (诺丁汉史学级2) 乳腺瘤. 这种人工智能工具可以识别具有不同复发风险的子组,帮助进行针对乳腺癌的个性化治疗决策.

科学领域:

放射学和医学成像学医学成像学
在瘤学瘤学.
人工智能在医学中的应用

背景情况:

诺丁汉组织学等级 (NHG) 对乳腺癌的预后和治疗至关重要.
NHG2瘤表现出显著的生物异质性,使治疗决策复杂化,并导致潜在的过度治疗或治疗不足.

研究的目的:

开发和验证一个深度学习模型 (DeepRadGrade) 来分层NHG2乳腺瘤.
评估该模型在预测无复发生存期 (RFS) 中的临床实用性.

主要方法:

一个卷积神经网络 (CNN) 在动态对比增强 (DCE) MRI 数据上受训,以区分NHG1和NHG3瘤.
经过训练的模型将456个NHG2瘤分为NHG1-样 (DRG2-) 和NHG3-样 (DRG2+) 亚组.
使用卡普兰-梅尔和考克斯模型分析了无复发存活率,并对标准预后因素进行了调整.

主要成果:

在训练,测试和外部验证数据集 (AUC从0.82到0.84) 中,DeepRadGrade (DRG) 在区分瘤等级方面表现强.
在NHG2瘤中,315个被归类为DRG2-和131个被归类为DRG2+.
患有DRG2+瘤的患者显示RFS明显恶化 (调整后危险比=2.39,p=0.0059),表明复发风险更高.
纳入DRG分类提高了考克斯模型的预测准确度 (C指数从0.68增加到0.73).

结论:

应用到常规DCEMRI的深度学习可以有效地根据复发风险将NHG2乳腺瘤分为临床上有意义的子组.
这种人工智能驱动的方法提供了一种具有成本效益的方法,用于在中度乳腺癌中个性化风险分层.
这些发现表明,DRG分类可以帮助优化治疗策略,最大限度地减少治疗不足和过度治疗.

关键词:

乳腺新生体的形成.动态对比增强增强的动态对比.磁共振成像技术磁共振成像技术诺丁汉组织学等级的诺丁汉组织学等级.风险分层是指风险的分层.

更多相关视频

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

Industrialized, Artificial Intelligence-guided Laser Microdissection for Microscaled Proteomic Analysis of the Tumor Microenvironment

Published on: June 3, 2022

相关概念视频

Imaging Studies I: CT and MRI

Imaging Studies I: CT and MRI

Introduction: MRI and CT scans are crucial advancements in medical imaging techniques, playing a vital role in diagnosing conditions related to the gastrointestinal (GI) system. Each scan serves distinct purposes, targets specific areas, and requires unique nursing duties.
Description of the Procedures
Computed Tomography (CT) scan:
Computed Tomography (CT) scans use X-ray technology to generate detailed images of bones, organs, and tissues. During the scan, the patient lies on a moving table...

Imaging Studies IV: Magnetic Resonance Imaging

Imaging Studies IV: Magnetic Resonance Imaging

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,...