辐射诱发心脏病建模路线图。

IF 2.2 4区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Samuel C Zhang, Andriana P Nikolova, Mitchell Kamrava, Raymond H Mak, Katelyn M Atkins
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引用次数: 0

摘要

随着癌症筛查和治疗的不断进步,癌症死亡率持续下降,因此降低心脏风险是改善癌症幸存者预后的重中之重。半数以上的成年癌症患者将接受放射治疗(RT),因此制定一个评估和预测辐射诱发心脏病(RICD)的框架至关重要。从历史上看,RICD 的建模仅使用平均心脏剂量等全心指标。然而,过去十年的数据发现,心脏亚结构在预测重大心脏事件方面优于全心脏指标。此外,非转录因子因素(如原有的心血管风险因素和其他疗法的毒性)也会导致未来发生心脏事件的风险。在本综述中,我们旨在讨论预测 RICD 的现有证据和知识差距,并为基于以下三个相互关联的组成部分开发综合模型提供路线图:(1)基线心血管风险评估;(2)与心脏特异性结果相关的心脏亚结构辐射剂量测量;(3)新型生物标记物的开发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A roadmap for modelling radiation-induced cardiac disease.

Cardiac risk mitigation is a major priority in improving outcomes for cancer survivors as advances in cancer screening and treatments continue to decrease cancer mortality. More than half of adult cancer patients will be treated with radiotherapy (RT); therefore it is crucial to develop a framework for how to assess and predict radiation-induced cardiac disease (RICD). Historically, RICD was modelled solely using whole heart metrics such as mean heart dose. However, data over the past decade has identified cardiac substructures which outperform whole heart metrics in predicting for significant cardiac events. Additionally, non-RT factors such as pre-existing cardiovascular risk factors and toxicity from other therapies contribute to risk of future cardiac events. In this review, we aim to discuss the current evidence and knowledge gaps in predicting RICD and provide a roadmap for the development of comprehensive models based on three interrelated components, (1) baseline CV risk assessment, (2) cardiac substructure radiation dosimetry linked with cardiac-specific outcomes and (3) novel biomarker development.

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来源期刊
CiteScore
3.30
自引率
6.20%
发文量
133
审稿时长
6-12 weeks
期刊介绍: Journal of Medical Imaging and Radiation Oncology (formerly Australasian Radiology) is the official journal of The Royal Australian and New Zealand College of Radiologists, publishing articles of scientific excellence in radiology and radiation oncology. Manuscripts are judged on the basis of their contribution of original data and ideas or interpretation. All articles are peer reviewed.
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