相关实验视频

Updated: Jul 16, 2025

Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy

Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy

Published on: April 9, 2019

基于MRI的代理成像,前列腺癌中的侵略性标记:基于放射性特征的机器学习模型的开发

Ignacio Dominguez¹, Odette Rios-Ibacache^2,3, Paola Caprile^2,4

¹Department of Radiology, School of Medicine, Pontificia Universidad Católica de Chile, Santiago 8320000, Chile.

Diagnostics (Basel, Switzerland)

|September 9, 2023

概括

使用MRI放射学和临床数据的新机器学习模型准确地识别了西班牙裔男性的侵袭性前列腺癌 (csPCa). 这种非侵入性方法与PI-RADS等现有方法相比,显示出更高的性能.

科学领域:

放射学放射学是一门学科.
在瘤学瘤学.
机器学习机器学习

背景情况:

前列腺癌 (PCa) 诊断依赖于侵入性方法.
准确识别临床显著的PCa (csPCa) 对于治疗决策至关重要.
需要非侵入性生物标志物来评估PCa的攻击性.

研究的目的:

开发和验证一种非侵入性机器学习 (ML) 模型,用于在西班牙裔男性中识别csPCa (格莱森分数≥7).
用双参数MRI (bpMRI) 放射特征和临床数据来评估模型的性能.
将ML模型的准确性与PI-RADS和前列腺特异性抗原密度 (PSA-D) 进行比较.

主要方法:

对86名患有PCa的西班牙裔男性进行了预视镜,3T核磁共振.
两名观察员在T2WI/ADC图像中对病变的二维细分.
使用放射性和临床特征 (PV,PSA-D) 的递归特征消除 (RFE) 进行多变量ML模型开发.
对csPCa (GS ≥ 7) 与非csPCa (GS = 6) 的分类.
分层列车/测试 (80%) 和验证 (20%) 套件.

主要成果:

来自T2WI/ADC图像的放射性特征与PCa患者的格里森分数 (GS) 有关.
最好的多变量ML模型将T2WI/ADC放射性特征与临床数据 (PV,PSA-D) 整合在一起.
该模型在csPCa检测方面实现了0.80的曲线下的验证面积 (AUC),超过PI-RADS (AUC:0.71) 和PSA-D (AUC:0.78).

结论:

开发的多变量ML模型准确地对csPCa进行分类,超过PI-RADS v2.1和PSA-D.
磁力共振成像衍生放射学 (T2WI/ADC) 显示出作为评估PCa攻击性的强大的生物标志物的潜力.
这种非侵入性方法为西班牙裔人口中PCa管理提供了有希望的工具.

关键词:

格里森得分格里森得分这是bpMRI.机器学习是机器学习.前列腺癌是前列腺癌.无线电学 (radiomics) 是一种无线电学.质地分析,质地分析.

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

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

相关概念视频

Magnetic Resonance Imaging

Magnetic Resonance Imaging

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...

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,...