多转移性环境中的基于放射性方法:定量审查
Caryn Geady1,2, Hemangini Patel3, Jacob Peoples4
1Medical Biophysics, University of Toronto, Toronto, ON, Canada. caryn.geady@mail.utoronto.ca.
BMC cancer
|March 26, 2025
概括
结合多种病变的放射性特征的最佳方法取决于特定的癌症和病变数量. 这项研究评估了各种方法来改进多病变放射性分析,以便更好地预测患者的结果.
科学领域:
- 医学成像分析分析 医学成像分析
- 定量成像成像技术的使用.
- 无线电学 (Radiomics) 是一种辐射学.
背景情况:
- 传统的放射学专注于单个病变,在转移性疾病中可能缺少病变间异质性.
- 没有标准化的方法可以将多种病变的放射性特征结合起来,这导致了多样化和不一致的方法.
- 本综述解决了在多损伤放射性分析中对各种数据集的最佳实践的需求.
研究的目的:
- 量化审查和评估整合多种病变放射性数据的方法.
- 评估现有的多损伤放射性分析方法的可复制性.
- 提供见解和指导未来的研究,以建立在这个领域的最佳实践.
主要方法:
- 进行了全面的文献搜索,以确定多损伤放射性数据集成的方法.
- 使用作者代码或基于纸张的重建复制识别的方法.
- 在三个不同的转移性数据集中应用和比较这些方法.
主要成果:
- 对比了10种数学方法,用于在3,930名患者的16,894个病变中结合放射性特征.
- 性能因数据集和损伤负担而异;没有一种方法是普遍优越的.
- 平均方法在结直肠肝转移,软组织肉瘤连接和头癌的总瘤体积方面表现出色.
结论:
- 放射性特征的有效选择或组合可以预测多转移患者的结果.
- 多病变放射性分析的最佳方法取决于特定的转移性设置.
- 这项研究提供了对多转移性疾病放射性分析的挑战和有效策略的关键见解.
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