Molecular and functional imaging in cancer-targeted therapy: current applications and future directions

分子成像 靶向治疗 医学 磁共振成像 癌症治疗 实体瘤疗效评价标准 癌症 模式 正电子发射断层摄影术 医学物理学 病理 临床试验 放射科 内科学 生物 社会科学 社会学 生物技术 体内 临床研究阶段
作者
Junwei Bai,Siqi Qiu,Guojun Zhang
出处
期刊:Signal Transduction and Targeted Therapy [Springer Nature]
卷期号:8 (1) 被引量:21
标识
DOI:10.1038/s41392-023-01366-y
摘要

Targeted anticancer drugs block cancer cell growth by interfering with specific signaling pathways vital to carcinogenesis and tumor growth rather than harming all rapidly dividing cells as in cytotoxic chemotherapy. The Response Evaluation Criteria in Solid Tumor (RECIST) system has been used to assess tumor response to therapy via changes in the size of target lesions as measured by calipers, conventional anatomically based imaging modalities such as computed tomography (CT), and magnetic resonance imaging (MRI), and other imaging methods. However, RECIST is sometimes inaccurate in assessing the efficacy of targeted therapy drugs because of the poor correlation between tumor size and treatment-induced tumor necrosis or shrinkage. This approach might also result in delayed identification of response when the therapy does confer a reduction in tumor size. Innovative molecular imaging techniques have rapidly gained importance in the dawning era of targeted therapy as they can visualize, characterize, and quantify biological processes at the cellular, subcellular, or even molecular level rather than at the anatomical level. This review summarizes different targeted cell signaling pathways, various molecular imaging techniques, and developed probes. Moreover, the application of molecular imaging for evaluating treatment response and related clinical outcome is also systematically outlined. In the future, more attention should be paid to promoting the clinical translation of molecular imaging in evaluating the sensitivity to targeted therapy with biocompatible probes. In particular, multimodal imaging technologies incorporating advanced artificial intelligence should be developed to comprehensively and accurately assess cancer-targeted therapy, in addition to RECIST-based methods.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
英俊的十三完成签到,获得积分20
刚刚
王彤彤发布了新的文献求助10
刚刚
深情安青应助娄某采纳,获得10
刚刚
沐沐发布了新的文献求助20
刚刚
Owen应助烂漫的闭月采纳,获得10
1秒前
艾尔文团长完成签到,获得积分10
1秒前
1秒前
熊儒恒完成签到,获得积分10
2秒前
神勇紫易完成签到,获得积分10
3秒前
科研狗应助谦让凌晴采纳,获得10
4秒前
hanahuang发布了新的文献求助30
4秒前
4秒前
molihuakai应助rr采纳,获得10
4秒前
图南发布了新的文献求助10
4秒前
4秒前
达不溜发布了新的文献求助10
5秒前
5秒前
5秒前
肖子涵完成签到,获得积分10
6秒前
鬼王神完成签到,获得积分10
7秒前
无忧应助陈龙采纳,获得10
8秒前
tester_gater发布了新的文献求助10
8秒前
地球发布了新的文献求助10
8秒前
科目三应助jagger采纳,获得10
8秒前
8秒前
无忧应助糯米多多采纳,获得10
8秒前
8秒前
沫栀发布了新的文献求助10
9秒前
科研狗应助谦让凌晴采纳,获得30
9秒前
武元彤完成签到,获得积分10
10秒前
yyljc完成签到,获得积分10
10秒前
科研通AI6.1应助花露水采纳,获得10
10秒前
烂漫的闭月完成签到,获得积分10
10秒前
ww完成签到,获得积分10
11秒前
11秒前
酷波er应助杨柳采纳,获得10
11秒前
肖恒完成签到,获得积分20
11秒前
11秒前
小流星完成签到,获得积分10
11秒前
super完成签到,获得积分10
12秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
The Organometallic Chemistry of the Transition Metals 800
Chemistry and Physics of Carbon Volume 18 800
The Organometallic Chemistry of the Transition Metals 800
The formation of Australian attitudes towards China, 1918-1941 640
Signals, Systems, and Signal Processing 610
全相对论原子结构与含时波包动力学的理论研究--清华大学 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6442770
求助须知:如何正确求助?哪些是违规求助? 8256642
关于积分的说明 17583261
捐赠科研通 5501353
什么是DOI,文献DOI怎么找? 2900675
邀请新用户注册赠送积分活动 1877632
关于科研通互助平台的介绍 1717328