集成磁共振成像技术在前列腺癌中的研究进展  

Research progress of synthetic magnetic resonance imaging in prostate cancer

作  者:贝明洁 祝新[1] BEI Mingjie;ZHU Xin(Department of Radiology,Jiangsu Province Hospital of Chinese Medicine,Affiliated Hospital of Nanjing University of Chinese Medicine,Nanjing 210029,China)

机构地区:[1]南京中医药大学附属江苏省中医院放射科,南京210029

出  处:《磁共振成像》2025年第2期210-214,共5页Chinese Journal of Magnetic Resonance Imaging

基  金:江苏省中医院院内基金项目(编号:Y2021ZR30)。

摘  要:集成磁共振成像(synthetic magnetic resonance imaging,SyMRI)是一种新型快速定量MRI技术,能通过短时间扫描获得多种定量图谱和对比加权图像,无创性地获得组织客观定量参数,从微观角度提供更多组织成分信息。该技术获得的纵向弛豫时间T1、横向弛豫时间T2和质子密度(proton density,PD)在前列腺癌的鉴别诊断、侵袭性预测和预后评价等方面发挥了重要作用。本文通过阐述SyMRI技术基本原理,就现有文献对SyMRI在前列腺癌中的相关应用进行综述,旨在提高对前列腺癌的早期诊断,并为前列腺癌治疗提供额外信息。此外,本文就该技术在前列腺癌的应用现状,探讨其未来发展方向,以期为后续的研究提供参考。Synthetic MRI(SyMRI)is a new type of rapid quantitative MRI technique,which can obtain multiple quantitative maps and contrast-weighted images in a short scanning time,and can non-invasively obtain objective quantitative parameters of tissues and provide more information about tissue composition from a microscopic perspective.The longitudinal relaxation time T1,transverse relaxation time T2 and proton density(PD)obtained by Synthetic MRI(SyMRI)play an important role in the differential diagnosis,prediction of aggressiveness and prognosis of prostate cancer.This paper describes the basic principles of SyMRI technology and reviews the existing literature on the application of integrated MRI technology in prostate cancer,aiming to improve the early diagnosis of prostate cancer and provide more additional information for prostate cancer treatment.In addition,this paper discusses the future development direction of this technology based on the current application of prostate cancer,hoping to provide a reference for subsequent research.

关 键 词:前列腺癌 骨转移 集成磁共振成像 鉴别诊断 侵袭性 GLEASON分级 预后 

分 类 号:R445.2[医药卫生—影像医学与核医学] R737.25[医药卫生—诊断学]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象