Object

To develop new imaging biomarkers of therapeutic efficacy through the quantification of intratumoral microvascular heterogeneity.

Materials and methods

The described method was a combination of non-supervised clustering and extraction of intratumoral complexity features (ICF): number of non-connected objects, volume fraction. It was applied to a set of 3D DCE-MRI K^trans maps acquired previously on tumor bearing mice prior to and on day 4 of anti-angiogenic treatment. Evolutions of ICF were compared to conventional summary statistics (CSS) and to heterogeneity related whole tumor texture features (TF) on treated (n = 9) and control (n = 6) mice.

Results

Computed optimal number of clusters per tumor was 4. Several intratumoral features extracted from the clusters were able to monitor a therapy effect. Whereas no feature significantly changed for the control group, 6 features significantly changed for the treated group (4 ICF, 2 CSS). Among these, 5 also significantly differentiated the two groups (3 ICF, 2 CSS). TF failed in demonstrating differences within and between the two groups.

Discussion

ICF are potential imaging biomarkers for anti-angiogenic therapy assessment. The presented method may be expected to have advantages with respect to texture analysis-based methods regarding interpretability of results and setup of standardized image analysis protocols.

中文翻译：

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量化肿瘤内异质性的新方法：临床前 DCE-MRI Ktrans 图的可行性研究

目的

通过量化肿瘤内微血管异质性，开发新的治疗效果成像生物标志物。

材料和方法

所描述的方法是非监督聚类和肿瘤内复杂性特征 (ICF) 提取的组合：非连接对象的数量、体积分数。它被应用于先前在抗血管生成治疗之前和第 4 天在荷瘤小鼠身上获得的一组 3D DCE-MRI K ^trans图。将 ICF 的演变与常规汇总统计 (CSS) 和与治疗 ( n  = 9) 和对照 ( n  = 6) 小鼠的异质性相关的整个肿瘤纹理特征 (TF) 进行比较。

结果

计算出的每个肿瘤的最佳簇数为 4。从簇中提取的几个肿瘤内特征能够监测治疗效果。对照组的特征没有显着变化，而治疗组的 6 个特征发生了显着变化（4 个 ICF，2 个 CSS）。其中，5个也显着区分了两组（3个ICF，2个CSS）。TF 未能证明两组内部和之间的差异。

讨论

ICF 是用于抗血管生成治疗评估的潜在成像生物标志物。在结果的可解释性和标准化图像分析协议的设置方面，所提出的方法有望在基于纹理分析的方法方面具有优势。