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经专家验证的MNI图谱脑脊液分割提高了虚拟胶质瘤生长模式的准确性。

Expert-validated CSF segmentation of MNI atlas enhances accuracy of virtual glioma growth patterns.

作者信息

Amelot A, Stretton E, Delingette H, Ayache N, Froelich S, Mandonnet E

机构信息

Neurosurgery Department, Hôpital Lariboisière, Paris, France.

出版信息

J Neurooncol. 2015 Jan;121(2):381-7. doi: 10.1007/s11060-014-1645-5. Epub 2014 Nov 5.

Abstract

Biomathematical modeling of glioma growth has been developed to optimize treatments delivery and to evaluate their efficacy. Simulations currently make use of anatomical knowledge from standard MRI atlases. For example, cerebrospinal fluid (CSF) spaces are obtained by automatic thresholding of the MNI atlas, leading to an approximate representation of real anatomy. To correct such inaccuracies, an expert-revised CSF segmentation map of the MNI atlas was built. Several virtual glioma growth patterns of different locations were generated, with and without using the expert-revised version of the MNI atlas. The adequacy between virtual and radiologically observed growth patterns was clearly higher when simulations were based on the expert-revised atlas. This work emphasizes the need for close collaboration between clinicians and researchers in the field of brain tumor modeling.

摘要

已开发出胶质瘤生长的生物数学模型,以优化治疗方案的实施并评估其疗效。目前的模拟利用了标准MRI图谱的解剖学知识。例如,通过对MNI图谱进行自动阈值处理来获得脑脊液(CSF)空间,从而得到真实解剖结构的近似表示。为了纠正这种不准确性,构建了经专家修订的MNI图谱的CSF分割图。生成了不同位置的几种虚拟胶质瘤生长模式,分别使用和不使用经专家修订的MNI图谱版本。当模拟基于专家修订的图谱时,虚拟生长模式与放射学观察到的生长模式之间的匹配度明显更高。这项工作强调了脑肿瘤建模领域临床医生和研究人员密切合作的必要性。

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