A Multiparametric Model for Mapping Cellularity in Glioblastoma Using Radiographically Localized Biopsies
A Multiparametric Model for Mapping Cellularity in Glioblastoma Using Radiographically Localized Biopsies
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DOI：
10.3174/ajnr.a5112
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发表时间：
2017-05-01
影响因子：
3.5
通讯作者：
Canoll, P.
中科院分区：
文献类型：
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作者：
Chang, P. D.;Malone, H. R.;Canoll, P.
背景和目的：胶质母细胞瘤复杂的MRI表现与潜在的组织病理学异质性有关。更好地了解这些相关性，特别是浸润性胶质瘤细胞和血管源性水肿对T2和非强化区弥散信号的影响，对这些患者的治疗具有重要意义。通过局部活检，这项研究的目的是建立一个模型，能够预测整个肿瘤体积内每个体素的细胞密度作为信号强度的函数，从而提供一种量化肿瘤向周围脑组织渗透的方法。材料和方法：从36例胶质母细胞瘤患者中获得91例局部活检。通过使用自动配准算法，从T1-增强后减影、T2-FLAIR和ADC序列中获得与这些样本对应的信号强度。使用自动细胞计数算法计算每个样本的细胞密度。结果：T2-FLAIR(r=-0.61)和ADC(r=-0.63)序列与细胞密度呈负相关。增强后T1减影与细胞密度呈正相关(r=0.69)。将这些关系结合在一起，得到了一个具有改进的相关性的多参数模型(r=0.74)，表明每个序列提供了不同的和互补的信息。结论：使用局部活检，我们建立了一个模型，说明了MR信号和细胞密度之间的定量和显著关系。将这种关系投射到整个肿瘤体积，可以绘制出肿瘤内对比度增强的肿瘤核心和非增强边缘的胶质母细胞瘤的异质性图，并可用于指导扩大手术切除、局部活检和放射野标测。
BACKGROUND AND PURPOSE: The complex MR imaging appearance of glioblastoma is a function of underlying histopathologic heterogeneity. A better understanding of these correlations, particularly the influence of infiltrating glioma cells and vasogenic edema on T2 and diffusivity signal in nonenhancing areas, has important implications in the management of these patients. With localized biopsies, the objective of this study was to generate a model capable of predicting cellularity at each voxel within an entire tumor volume as a function of signal intensity, thus providing a means of quantifying tumor infiltration into surrounding brain tissue.MATERIALS AND METHODS: Ninety-one localized biopsies were obtained from 36 patients with glioblastoma. Signal intensities corresponding to these samples were derived from T1-postcontrast subtraction, T2-FLAIR, and ADC sequences by using an automated coregistration algorithm. Cell density was calculated for each specimen by using an automated cell-counting algorithm. Signal intensity was plotted against cell density for each MR image.RESULTS: T2-FLAIR (r = -0.61) and ADC (r = -0.63) sequences were inversely correlated with cell density. T1-postcontrast (r = 0.69) subtraction was directly correlated with cell density. Combining these relationships yielded a multiparametric model with improved correlation (r = 0.74), suggesting that each sequence offers different and complementary information.CONCLUSIONS: Using localized biopsies, we have generated a model that illustrates a quantitative and significant relationship between MR signal and cell density. Projecting this relationship over the entire tumor volume allows mapping of the intratumoral heterogeneity in both the contrast-enhancing tumor core and nonenhancing margins of glioblastoma and may be used to guide extended surgical resection, localized biopsies, and radiation field mapping.