肿瘤疾病放射诊断质量控制系统在放射组学中的作用

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现代医学成像方法可以定性和定量地评估肿瘤组织及其周围的空间。计算机科学的进步，特别是机器学习方法在医学图像分析中的参与，允许将任何放射学研究转变为可分析的数据集。在这些数据集中，可以寻找有统计学意义夫人相关性与临床事件，以便随后评估其预后意义和预测不同临床结果的能力。 这个概念在2012年首次被描述并称为»放射组学»。这对于肿瘤学特别重要，因为已知每种类型的肿瘤可以分为许多不同的分子遗传亚型，而仅仅是视觉特征已经不够了。在绝对非侵入性的情况下，放射组学能够为放射科医生提供有时只有活检材料的组织学检查才能提供的信息。然而，正如在任何基于使用大数据的方法中一样，存在关于初始数据信息的质量的尖锐问题，因为这可能直接影响分析的结果并给出不正确的诊断信息。

在文献综述中，我们分析了确保各个阶段研究质量的可能方法 - 从诊断设备状态的技术控制到提取肿瘤学中的成像标记并计算其与临床数据的相关性。

作者简介

Anna N. Khoruzhaya

Moscow Center for Diagnostics and Telemedicine

编辑信件的主要联系方式.
Email: a.khoruzhaya@npcmr.ru
ORCID iD: 0000-0003-4857-5404
SPIN 代码: 7948-6427

Junior Researcher, Department of Innovative Technologies

俄罗斯联邦, 28-1 Srednyaya Kalitnikovskaya str., 109029, Moscow

Ekaterina S. Ahkmad

Moscow Center for Diagnostics and Telemedicine

Email: e.ahkmad@npcmr.ru
ORCID iD: 0000-0002-8235-9361
SPIN 代码: 5891-4384
俄罗斯联邦, 28-1 Srednyaya Kalitnikovskaya str., 109029, Moscow

Dmitriy S. Semenov

Moscow Center for Diagnostics and Telemedicine

Email: d.semenov@npcmr.ru
ORCID iD: 0000-0002-4293-2514
SPIN 代码: 2278-7290
俄罗斯联邦, 28-1 Srednyaya Kalitnikovskaya str., 109029, Moscow

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2. 图 1放射诊断图像的放射组学分析图，说明质量控制系统的作用。

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3. 图 2在放射学中实施质量控制体系的理由。

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