The Future of MR-Guided Radiation Therapy

被引：8

作者：

Guckenberger, Matthias ^{[1
,3
]}

Andratschke, Nicolaus ^{[1
]}

Chung, Caroline ^{[2
]}

Fuller, Dave ^{[2
]}

Tanadini-Lang, Stephanie ^{[1
]}

Jaffray, David A. ^{[2
]}

机构：

[1] Univ Zurich, Univ Hosp Zurich, Dept Radiat Oncol, Zurich, Switzerland

[2] Univ Texas MD Anderson Canc Ctr, Div Radiat Oncol, Houston, TX USA

[3] Univ Zurich, Univ Hosp Zurich, Dept Radiat Oncol, Raemistr 100, CH-8091 Zurich, Switzerland

来源：

SEMINARS IN RADIATION ONCOLOGY | 2024年 / 34卷 / 01期

关键词：

SYNTHETIC COMPUTED-TOMOGRAPHY; MV RADIOTHERAPY ACCELERATOR; ARTIFICIAL-INTELLIGENCE; MAGNETIC-FIELD; ONCOLOGY; PATIENT; REPRODUCIBILITY; RECOMMENDATIONS; PHASE-3; QUALITY;

D O I：

10.1016/j.semradonc.2023.10.015

中图分类号：

R73 [肿瘤学];

学科分类号：

100214 ;

摘要：

Magnetic resonance image guided radiation therapy (MRIgRT) is a relatively new technology that has already shown outcomes benefits but that has not yet reached its clinical potential. The improved soft-tissue contrast provided with MR, coupled with the immediacy of image acquisition with respect to the treatment, enables expansion of on-table adaptive protocols, currently at a cost of increased treatment complexity, use of human resources, and longer treatment slot times, which translate to decreased throughput. Many approaches are being investigated to meet these challenges, including the development of artificial intelligence (AI) algorithms to accelerate and automate much of the workflow and improved technology that parallelizes workflow tasks, as well as improvements in image acquisition speed and quality. This article summarizes limitations of current available integrated MRIgRT systems and gives an outlook about scientific developments to further expand the use of MRIgRT. (C) 2023 The Authors. Published by Elsevier Inc.

引用

页码：135 / 144

页数：10

共 115 条

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