专题社论：基于成像的前列腺癌诊断——最新技术水平
Editorial for Special Topics: Imaging-Based Diagnosis for Prostate Cancer-State of the Art.
作者信息
Mayer Rulon, Choyke Peter L, Simone Ii Charles B
机构信息
Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
Oncoscore, Garrett Park, MD 20896, USA.
出版信息
Diagnostics (Basel). 2024 Sep 12;14(18):2016. doi: 10.3390/diagnostics14182016.
Abstract
This Special Topics Issue, "Imaging-based Diagnosis of Prostate Cancer-State of the Art", of compiles 10 select articles [...].
摘要
本期专题“基于成像的前列腺癌诊断——最新技术”汇集了10篇精选文章[...]。
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本文引用的文献
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Biparametric vs. Multiparametric MRI in the Detection of Cancer in Transperineal Targeted-Biopsy-Proven Peripheral Prostate Cancer Lesions Classified as PI-RADS Score 3 or 3+1: The Added Value of ADC Quantification.双参数磁共振成像与多参数磁共振成像在经会阴靶向活检证实的PI-RADS评分3或3+1的外周前列腺癌病变中检测癌症的比较：表观扩散系数定量的附加价值
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Relationship between Eccentricity and Volume Determined by Spectral Algorithms Applied to Spatially Registered Bi-Parametric MRI and Prostate Tumor Aggressiveness: A Pilot Study.应用于空间配准双参数磁共振成像的谱算法测定的偏心率与体积之间的关系及前列腺肿瘤侵袭性：一项初步研究。
Diagnostics (Basel). 2023 Oct 17;13(20):3238. doi: 10.3390/diagnostics13203238.
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Machine Learning CT-Based Automatic Nodal Segmentation and PET Semi-Quantification of Intraoperative Ga-PSMA-11 PET/CT Images in High-Risk Prostate Cancer: A Pilot Study.基于机器学习的高危前列腺癌术中镓-PSMA-11 PET/CT图像的自动淋巴结分割及PET半定量分析：一项初步研究
Diagnostics (Basel). 2023 Sep 21;13(18):3013. doi: 10.3390/diagnostics13183013.
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MRI-Based Surrogate Imaging Markers of Aggressiveness in Prostate Cancer: Development of a Machine Learning Model Based on Radiomic Features.基于MRI的前列腺癌侵袭性替代成像标志物：基于放射组学特征的机器学习模型的开发
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Cardiac Metastasis from Prostate Cancer: A Case Study Underlying the Crucial Role of the PSMA PET/CT.前列腺癌的心脏转移：一项病例研究揭示PSMA PET/CT的关键作用
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The Impact of Prostate Volume on the Prostate Imaging and Reporting Data System (PI-RADS) in a Real-World Setting.在实际临床环境中前列腺体积对前列腺影像报告和数据系统（PI-RADS）的影响。
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Application of Spectral Algorithm Applied to Spatially Registered Bi-Parametric MRI to Predict Prostate Tumor Aggressiveness: A Pilot Study.应用光谱算法于空间配准双参数磁共振成像以预测前列腺肿瘤侵袭性的初步研究
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