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利用功能成像描绘肿瘤异质性,并量化高危肿瘤体积以实现对治疗效果的早期预测:以宫颈癌为例。

Characterizing tumor heterogeneity with functional imaging and quantifying high-risk tumor volume for early prediction of treatment outcome: cervical cancer as a model.

机构信息

Department of Radiation Oncology, Ohio State University, Columbus, OH 43210, USA.

出版信息

Int J Radiat Oncol Biol Phys. 2012 Jul 1;83(3):972-9. doi: 10.1016/j.ijrobp.2011.08.011. Epub 2011 Dec 28.

Abstract

PURPOSE

Treatment response in cancer has been monitored by measuring anatomic tumor volume (ATV) at various times without considering the inherent functional tumor heterogeneity known to critically influence ultimate treatment outcome: primary tumor control and survival. This study applied dynamic contrast-enhanced (DCE) functional MRI to characterize tumors' heterogeneous subregions with low DCE values, at risk for treatment failure, and to quantify the functional risk volume (FRV) for personalized early prediction of treatment outcome.

METHODS AND MATERIALS

DCE-MRI was performed in 102 stage IB(2)-IVA cervical cancer patients to assess tumor perfusion heterogeneity before and during radiation/chemotherapy. FRV represents the total volume of tumor voxels with critically low DCE signal intensity (<2.1 compared with precontrast image, determined by previous receiver operator characteristic analysis). FRVs were correlated with treatment outcome (follow-up: 0.2-9.4, mean 6.8 years) and compared with ATVs (Mann-Whitney, Kaplan-Meier, and multivariate analyses).

RESULTS

Before and during therapy at 2-2.5 and 4-5 weeks of RT, FRVs >20, >13, and >5 cm(3), respectively, significantly predicted unfavorable 6-year primary tumor control (p = 0.003, 7.3 × 10(-8), 2.0 × 10(-8)) and disease-specific survival (p = 1.9 × 10(-4), 2.1 × 10(-6), 2.5 × 10(-7), respectively). The FRVs were superior to the ATVs as early predictors of outcome, and the differentiating power of FRVs increased during treatment.

DISCUSSION

Our preliminary results suggest that functional tumor heterogeneity can be characterized by DCE-MRI to quantify FRV for predicting ultimate long-term treatment outcome. FRV is a novel functional imaging heterogeneity parameter, superior to ATV, and can be clinically translated for personalized early outcome prediction before or as early as 2-5 weeks into treatment.

摘要

目的

在癌症治疗中,通过在不同时间测量解剖肿瘤体积(ATV)来监测治疗反应,而没有考虑到已知对最终治疗结果具有关键影响的固有功能肿瘤异质性:原发性肿瘤控制和生存。本研究应用动态对比增强(DCE)功能磁共振成像来描述具有低 DCE 值的肿瘤异质亚区,这些亚区存在治疗失败的风险,并量化功能风险体积(FRV),以实现治疗结果的个体化早期预测。

方法和材料

对 102 例 IB(2)-IVA 期宫颈癌患者进行 DCE-MRI 检查,以评估放疗/化疗前后肿瘤灌注异质性。FRV 代表具有临界低 DCE 信号强度的肿瘤体素的总体积(<2.1,与之前的接收器操作特征分析确定的对比前图像相比)。FRV 与治疗结果相关(随访:0.2-9.4 年,平均 6.8 年),并与 ATV 进行比较(Mann-Whitney、Kaplan-Meier 和多变量分析)。

结果

在放疗的 2-2.5 周和 4-5 周时,FRVs>20、>13 和>5 cm(3)分别显著预测了 6 年原发性肿瘤控制不良(p=0.003,7.3×10(-8),2.0×10(-8))和疾病特异性生存(p=1.9×10(-4),2.1×10(-6),2.5×10(-7))。FRVs 作为结果的早期预测指标优于 ATV,并且在治疗过程中,FRVs 的区分能力增加。

讨论

我们的初步结果表明,功能肿瘤异质性可以通过 DCE-MRI 进行特征描述,以量化 FRV 来预测最终的长期治疗结果。FRV 是一种新的功能成像异质性参数,优于 ATV,可以在治疗前或治疗后 2-5 周内进行个体化早期结果预测,并进行临床转化。

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