Importance of patient DTI's to accurately model glioma growth using the reaction diffusion equation

E. Stretton, Ezequiel Geremia, Bjoern H Menze, H. Delingette, N. Ayache
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引用次数: 21

Abstract

Tumor growth models based on the FisherKolmogorov reaction-diffusion equation (FK) have shown convincing results in reproducing and predicting the invasion patterns of gliomas brain tumors. Diffusion tensor images (DTIs) were suggested to model the anisotropic diffusion of tumor cells in the brain white matter. However, clinical patient-DTIs are expensive and often acquired with low resolution, which compromises the accuracy of the tumor growth models. In this work, we used the traveling wave approximation model to describe the evolution of the visible boundary of the tumor modeled by the FK equation to investigate the impact of replacing the patient DTI by (i) an isotropic diffusion map or (ii) an anisotropic high-resolution DTI atlas formed by averaging DTIs of multiple patients. We quantify the impact of replacing the patient DTI using three metrics: the shape of the simulated glioma, the estimation of the tumor growth parameters, and the prediction performance on clinical cases.
患者DTI对使用反应扩散方程准确模拟胶质瘤生长的重要性
基于FisherKolmogorov反应扩散方程(FK)的肿瘤生长模型在再现和预测胶质瘤脑肿瘤的侵袭模式方面显示出令人信服的结果。采用弥散张量图像(DTIs)模拟肿瘤细胞在脑白质中的各向异性扩散。然而,临床患者- dti价格昂贵且通常分辨率较低,这损害了肿瘤生长模型的准确性。在这项工作中,我们使用行波近似模型来描述由FK方程建模的肿瘤可见边界的演变,以研究用(i)各向同性扩散图或(ii)由多个患者DTI平均形成的各向异性高分辨率DTI图谱代替患者DTI的影响。我们使用三个指标来量化替换患者DTI的影响:模拟胶质瘤的形状、肿瘤生长参数的估计以及对临床病例的预测性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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