首页|人工智能辅助的MRI影像组学在前列腺癌诊疗中的进展

人工智能辅助的MRI影像组学在前列腺癌诊疗中的进展

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前列腺癌(PCa)目前是全球男性第2大常见癌症,也是导致男性癌症死亡的第5大原因.MRI在检测PCa方面具有很高的灵敏度和特异性,是目前用于肿瘤定位和癌症分期最广泛的成像技术.MRI在新发肿瘤患者的风险分层、低风险患者的主动监测以及治疗后的复发监测方面发挥着关键作用.影像组学是一种新兴的、前景广阔的工具,通过将数字图像转换为可挖掘的高维数据,可对图像中的肿瘤进行定量评估.影像组学的目的是增加可用于检测PCa的特征、避免不必要的活检、确定肿瘤的侵袭性以及监测治疗后的复发.利用人工智能(AI)整合影像组学数据,包括不同的成像模式(如PET-CT)以及其他临床和组织病理学数据,可提高对肿瘤侵袭性的预测并指导临床决策和患者管理.本综述旨在介绍目前AI辅助下的影像组学在PCa MRI图像上的研究应用.
Advances in artificial intelligence-assisted MRI radiomics in the diagnosis and treatment of prostate cancer
Prostate cancer(PCa)is the second most common cancer worldwide and the fifth leading cause of cancer deaths in men.Magnetic resonance imaging(MRI),with its high sensitivity and specificity in detecting PCa,is currently the most widely used imaging technique for tumor localization and staging.MRI plays a significant role in risk stratification of patients with neoplasm,sur-veillance of low-risk patients,and monitoring of recurrence after treatment.Radiomics is an emerging and promising tool that allows quantitative assessment of tumors in images by converting digital images into mineable high-dimensional data.Imaging histology aims to increase the number of features that can be used to detect PCa,avoid unnecessary biopsies,determine tumor aggressiveness and moni-tor recurrence after treatment.Artificial intelligence integration of imaging histology data,including those of different imaging modalities(e.g.,PET-CT)as well as other clinical and histopathological data,can improve the prediction of tumor aggressiveness and guide clinical decision-making and patient management.The aim of this review is to present current research applications of AI-assisted ra-diomics in PCa MRI images.

prostate cancermagnetic resonance imagingradiomicsartificial intelligence

梁梓淳、孙超、陈明

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东南大学附属中大医院泌尿外科,江苏南京 210096

前列腺癌 MRI 影像组学 人工智能

国家自然科学基金

81871157

2024

中华男科学杂志
南京军区南京总医院

中华男科学杂志

CSTPCD
影响因子:1.052
ISSN:1009-3591
年,卷(期):2024.30(1)
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