期刊文献+

Radiomics in Antineoplastic Agents Development:Application and Challenge in Response Evaluation

影像组学在抗肿瘤药物临床试验疗效评估中的应用和挑战
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摘要 The recent spring up of the antineoplastic agents and the prolonged survival bring both challenge and chance to radiological practice.Radiological methods including CT,MRI and PET play an increasingly important role in evaluating the efficacy of these antineoplastic drugs.However,different antineoplastic agents potentially induce different radiological signs,making it a challenge for radiological response evaluation,which depends mainly on one-sided morphological response evaluation criteria in solid tumors(RECIST)in the status quo of clinical practice.This brings opportunities for the development of radiomics,which is promising to serve as a surrogate for response evaluations of anti-tumor treatments.In this article,we introduce the basic concepts of radiomics,review the state-of-art radiomics researches with highlights of radiomics application in predictions of molecular biomarkers,treatment response,and prognosis.We also provide in-depth analyses on major obstacles and future direction of this new technique in clinical investigations on new antineoplastic agents.
作者 Jiazheng Li Lei Tang 李佳铮;唐磊(北京大学肿瘤医院医学影像科,北京市肿瘤防治研究所,恶性肿瘤发病机制及转化研究教育部重点实验室,北京100142)
出处 《Chinese Medical Sciences Journal》 CAS CSCD 2021年第3期187-195,共9页 中国医学科学杂志(英文版)
基金 北京自然科学基金(Z180001,Z200015) 北大百度基金资助项目(2020BD027) 国家自然科学基金重大研究计划(91959205)。
关键词 radiomics deep learning machine learning antineoplastic agents response evaluation 影像组学 深度学习 机器学习 抗肿瘤药物 疗效评价
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