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预测肿瘤反应。

Predicting tumour response.

机构信息

Department of Radiology, Princess Alexandra Hospital, Brisbane, Australia; School of Medicine, University of Queensland, Southern Clinical School, Brisbane, Australia.

出版信息

Cancer Imaging. 2013 Sep 23;13(3):381-90. doi: 10.1102/1470-7330.2013.9039.

Abstract

Response prediction is an important emerging concept in oncologic imaging, with tailored, individualized treatment regimens increasingly becoming the standard of care. This review aims to define tumour response and illustrate the ways in which imaging techniques can demonstrate tumour biological characteristics that provide information on the likely benefit to be received by treatment. Two imaging approaches are described: identification of therapeutic targets and depiction of the treatment-resistant phenotype. The former approach is exemplified by the use of radionuclide imaging to confirm target expression before radionuclide therapy but with angiogenesis imaging and imaging correlates for genetic response predictors also demonstrating potential utility. Techniques to assess the treatment-resistant phenotype include demonstration of hypoperfusion with dynamic contrast-enhanced computed tomography and magnetic resonance imaging (MRI), depiction of necrosis with diffusion-weighted MRI, imaging of hypoxia and tumour adaption to hypoxia, and 99mTc-MIBI imaging of P-glycoprotein mediated drug resistance. To date, introduction of these techniques into clinical practice has often been constrained by inadequate cross-validation of predictive criteria and lack of verification against appropriate response end points such as survival. With further refinement, imaging predictors of response could play an important role in oncology, contributing to individualization of therapy based on the specific tumour phenotype. This ability to predict tumour response will have implications for improving efficacy of treatment, cost-effectiveness and omission of futile therapy.

摘要

肿瘤反应预测是肿瘤影像学中的一个新兴概念,越来越多的量身定制、个体化的治疗方案正在成为标准的治疗模式。本文旨在定义肿瘤反应,并举例说明影像学技术如何展示肿瘤的生物学特征,为治疗可能带来的获益提供信息。本文介绍了两种影像学方法:治疗靶点的识别和耐药表型的描述。前者的例子是放射性核素成像用于放射性核素治疗前确认靶标表达,但血管生成成像和针对遗传反应预测因子的影像学相关性也显示出潜在的应用价值。评估耐药表型的技术包括:用动态对比增强 CT 和 MRI 显示低灌注、用弥散加权 MRI 显示坏死、成像显示缺氧和肿瘤对缺氧的适应、99mTc-MIBI 成像显示 P-糖蛋白介导的药物耐药。迄今为止,这些技术在临床实践中的应用往往受到预测标准的交叉验证不足以及缺乏与适当的反应终点(如生存)相验证的限制。随着进一步的改进,肿瘤反应的影像学预测因子可能在肿瘤学中发挥重要作用,根据特定的肿瘤表型为治疗提供个体化方案。这种预测肿瘤反应的能力将对提高治疗效果、成本效益和避免无效治疗产生影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/85f5/3783115/6e284d749550/ci13903901.jpg

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