摘要
胰腺神经内分泌肿瘤具有高度异质性,准确的术前分级对临床决策至关重要。人工智能驱动的无创性预测方法为评估胰腺神经内分泌肿瘤的病理学分级及侵袭性提供了新的技术手段和研究方向。本文通过对人工智能结合不同影像学检查方法在预测胰腺神经内分泌肿瘤病理学分级中的应用现状作一综述,旨在为临床管理方案的制订及肿瘤的综合评估提供多模态影像学依据,并为后续研究指明方向。
Pancreatic neuroendocrine neoplasms(pNENs)are highly heterogeneous,making accurate preoperative grading crucial for clinical decision-making.Artificial intelligence(AI)-driven noninvasive predictive methods offer novel technical approaches and perspectives for assessing the pathological grade and aggressiveness of pNENs.This review aims to provide a multimodal imaging basis for formulating clinical management strategies and comprehensive tumor assessment,while also identifying directions for future research.
作者
张月
李浩博
王法颖
姬琳琳
李现军
ZHANG Yue;LI Haobo;WANG Faying;JI Linlin;LI Xianjun(School of Medical Imaging,Shandong Second Medical University,Weifang 261053,China;Department of Nuclear Medicine,Weifang People's Hospital,Shandong Second Medical University,Weifang 261041,China)
出处
《分子影像学杂志》
2026年第2期263-269,共7页
Journal of Molecular Imaging
基金
潍坊市科技发展计划项目(2023YX010)。
关键词
胰腺
神经内分泌肿瘤
人工智能
影像学
分级
pancreas
neuroendocrine neoplasms
artificial intelligence
medical imaging
grading
