Pattern analysis of dynamic susceptibility contrast-enhanced MR imaging demonstrates peritumoral tissue heterogeneity.
Pattern analysis of dynamic susceptibility contrast-enhanced MR imaging demonstrates peritumoral tissue heterogeneity.
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DOI：
10.1148/radiol.14132458
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发表时间：
2014-11
期刊：
影响因子：
19.7
通讯作者：
Davatzikos C
中科院分区：
文献类型：
--
作者：
Akbari H;Macyszyn L;Da X;Wolf RL;Bilello M;Verma R;O'Rourke DM;Davatzikos C
本研究的目的是增强动态磁敏感对比MRI（DSC-MRI）的分析，以揭示独特的组织特征，通过更好地了解胶质母细胞瘤患者的瘤周区域，可能有助于制定治疗计划。本研究获得了机构审查委员会的批准，并放弃了对医疗记录进行回顾性审查的知情同意书。获得79例患者的DSC-MRI数据，并对灌注信号进行主成分分析（PCA）。前六个主成分（PC）足以表征所有感兴趣区域中血液灌注的时间动态中超过99%的方差。随后将PC与支持向量机（SVM）分类器结合使用，以创建肿瘤周围区域内的异质性图，该图的方差作为异质性评分。计算的PC允许可能高度浸润的组织与不太可能浸润有肿瘤的组织接近完美的分离。使用PC创建的异质性图显示了SVM判断为高度浸润的体素与随后复发之间的明确关系。结果表明异质性评分与患者生存率之间存在显著相关性（r=0.46，p<0.0001）。根据中位异质性评分，高异质性评分和低异质性评分患者之间的风险比为2.23（95% CI，1.4-3.6，p <0.01）。使用PCA分析DSC-MRI数据可以识别成像变量，这些变量随后可以用于评估胶质母细胞瘤中的瘤周区域。这些变量是潜在的肿瘤浸润的指示，并可能成为有用的工具，在指导治疗以及个性化治疗。
The aim of this study is to augment the analysis of dynamic susceptibility contrast MRI (DSC-MRI) to uncover unique tissue characteristics that could potentially facilitate treatment planning through a better understanding of the peritumoral region of patients with glioblastoma. IRB approval was obtained for this study with waiver of informed consent for retrospective review of medical records. DSC-MRI data was obtained for 79 patients and principal component analysis (PCA) was applied to the perfusion signal. The first six principal components (PCs) were sufficient to characterize more than 99% of variance in the temporal dynamics of blood perfusion in all regions of interest. The PCs were subsequently used in conjunction with a support vector machine (SVM) classifier to create a map of heterogeneity within the peritumoral region and the variance of this map served as the heterogeneity score. The calculated PCs allowed near perfect separability of tissue that was likely highly infiltrated from tissue that was unlikely infiltrated with tumor. The heterogeneity map created using the PCs showed a clear relationship between voxels judged by the SVM to be highly infiltrated and subsequent recurrence. The results demonstrated a significant correlation (r=0.46, p<0.0001) between the heterogeneity score and patient survival. The hazard ratio was 2.23 (95% CI, 1.4-3.6, p <0.01) between high and low heterogeneity score patients based on the median heterogeneity score. Analysis of DSC-MRI data using PCA can identify imaging variables that can be subsequently utilized to evaluate the peritumoral region in glioblastoma. These variables are potentially indicative of tumor infiltration and may become useful tools in guiding therapy as well as individualized prognostication.
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影响因子：
10.6
作者：
Sled, JG;Zijdenbos, AP;Evans, AC
通讯作者：
Evans, AC
影响因子：
4.8
作者：
Smith, SM
通讯作者：
Smith, SM
影响因子：
7.5
作者：
CORTES, C;VAPNIK, V
通讯作者：
VAPNIK, V
影响因子：
2.6
作者：
Thompson, G.;Mills, S. J.;Jackson, A.
通讯作者：
Jackson, A.
DOI：
10.1016/j.ijrobp.2006.12.009
发表时间：
2007-05-01
影响因子：
7
作者：
Chang, Eric L.;Akyurek, Serap;Maor, Moshe H.
通讯作者：
Maor, Moshe H.