在转移性疾病中对病变特异性全身治疗反应的基于放射性预测
Caryn Geady1, Farnoosh Abbas-Aghababazadeh2, Andres Kohan2
1Princess Margaret Cancer Centre, University Health Network, Toronto, Canada; Medical Biophysics, University of Toronto, Toronto, Canada.
概括
放射性生物标志物可以预测leiomyosarcoma患者个体肺转移的治疗耐药性. 这种方法解释了瘤的多样性,可能改善转移性疾病的治疗策略.
科学领域:
- 在瘤学瘤学.
- 放射学 放射学是一门学科.
- 医疗成像医学成像
背景情况:
- 转移性患者的个体瘤可以表现出不同的特征和治疗敏感性,即使具有相同的组织学分类.
- 了解病变特异性治疗耐药性对于优化多转移环境中的抗癌疗法至关重要.
研究的目的:
- 研究放射性生物标志物的实用性,以预测多转移性乳腺肉瘤患者肺转移 (LM) 中的病变特异性治疗耐药性.
- 开发和评估用于预测个体LM进展的放射性模型.
主要方法:
- 利用80名患者202例肺转移 (LM) 的数据集,分析了1648例治疗前计算机断层扫描 (CT) 放射学特征.
- 开发了一种放射性模型,以基于CT数据预测病变进展,并评估不同LM体积组的表现.
- 通过删除与体积相关的特征来控制LM体积的影响.
主要成果:
- 与无技能分类器相比,病变特定的放射性模型显示预测能力显著增加 (高达4.5倍).
- 在最精确的模型中,精度回忆曲线下的面积为0.70 (错误发现率=0.05).
- 预测精度根据所服用的药物和LM体积而异,体积效应因特征选择而减轻.
结论:
- 放射性特征可以预测多转移性线性肌肉肉瘤的病变特异性治疗反应.
- 这种新的策略承认转移性亚克隆中的生物多样性.
- 它可以促进管理策略,包括在全身疗法期间选择性废除耐药克隆.
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