Shape matters: morphological metrics of glioblastoma imaging abnormalities as biomarkers of prognosis.
Shape matters: morphological metrics of glioblastoma imaging abnormalities as biomarkers of prognosis.
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DOI：
10.1038/s41598-021-02495-6
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发表时间：
2021-12-01
影响因子：
4.6
通讯作者：
Swanson KR
中科院分区：
文献类型：
--
作者：
Curtin L;Whitmire P;White H;Bond KM;Mrugala MM;Hu LS;Swanson KR
空隙性（一种形状如何填充空间的定量形态学测量）和分形维数（一种像素排列复杂性的形态学测量）已经显示出与各种癌症结果的关系。然而，这些指标在胶质母细胞瘤（GBM），一种非常侵袭性的原发性脑肿瘤中的应用还没有得到充分的探讨。在这个项目中，我们在临床标准磁共振成像（MRI）上计算了gbm引起的异常的间隙和分形维数值。在我们的患者队列（n = 402）中，我们将预处理MRI计算的这些形态学指标与GBM患者的生存率联系起来。我们计算了坏死区域的腔洞和分形维数（n = 390）， T1Gd MRI上的所有异常（n = 402）和T2/FLAIR MRI上的异常（n = 257）。我们还探讨了这些指标与诊断年龄以及异常体积之间的关系。我们发现，我们测试的所有三个成像区域的结果与统计上显著相关，T2/FLAIR异常的形状通常与水肿相关，与总生存率的关系最强。形态学和生存指标之间的这种联系可能是由潜在的生物现象、肿瘤位置或微环境因素驱动的，这些因素应该进一步探索。
Lacunarity, a quantitative morphological measure of how shapes fill space, and fractal dimension, a morphological measure of the complexity of pixel arrangement, have shown relationships with outcome across a variety of cancers. However, the application of these metrics to glioblastoma (GBM), a very aggressive primary brain tumor, has not been fully explored. In this project, we computed lacunarity and fractal dimension values for GBM-induced abnormalities on clinically standard magnetic resonance imaging (MRI). In our patient cohort (n = 402), we connect these morphological metrics calculated on pretreatment MRI with the survival of patients with GBM. We calculated lacunarity and fractal dimension on necrotic regions (n = 390), all abnormalities present on T1Gd MRI (n = 402), and abnormalities present on T2/FLAIR MRI (n = 257). We also explored the relationship between these metrics and age at diagnosis, as well as abnormality volume. We found statistically significant relationships to outcome for all three imaging regions that we tested, with the shape of T2/FLAIR abnormalities that are typically associated with edema showing the strongest relationship with overall survival. This link between morphological and survival metrics could be driven by underlying biological phenomena, tumor location or microenvironmental factors that should be further explored.
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