Kliniken Nordoberpfalz AG, Klinikum Weiden, Department of Neurosurgery, Weiden, Germany.
Brain Center Rudolf Magnus, University Medical Center, Utrecht, The Netherlands.
World Neurosurg. 2020 Oct;142:e10-e17. doi: 10.1016/j.wneu.2020.04.134. Epub 2020 Apr 28.
In this study we present the nature and characteristic of the fluctuation of blood oxygen level-dependent (BOLD) signals measured from brain tumors.
Supratentorial astrocytomas, which were neither operated nor previously managed with chemotherapy or radiotherapy, were segmented, and the time series of the BOLD signal fluctuations were extracted. The mean (across patients) power spectra were plotted for the different World Health Organization tumor grades. One-way analysis of variance (ANOVA) was performed to identify significant differences between the power spectra of different tumor grades. Results were considered significant at P < 0.05.
A total of 58 patients were included in the study. This group of patients included 1 patient with grade I glioma; 15 with grade II; 12 with grade III; and 30 with grade IV. The power spectra of the tumor time series were individually inspected, and all tumors exhibited high peaks at the lower frequency signals, but these were more pronounced in high-grade tumors. ANOVA showed a significant difference in power spectra between groups (P = 0.000). Post hoc analysis with Bonferroni correction showed a significant difference between grade II and grade III (P = 0.012) and grade IV (P = 0.000). There was no significant power spectra difference between grade III and IV tumors (P = 1).
The power spectra of BOLD signals from tumor tissue showed fluctuations in the low-frequency signals and were significantly correlated with tumor grade. These signals could have a misleading effect when analyzing resting state functional magnetic resonance imaging and could be also viewed as a potential method of tumor characterization.
本研究旨在展示从脑肿瘤测量得到的血氧水平依赖(BOLD)信号波动的性质和特征。
对未接受手术、未接受化疗或放疗的幕上星形细胞瘤进行分割,并提取 BOLD 信号波动的时间序列。绘制不同世界卫生组织肿瘤分级的平均(跨患者)功率谱。采用单因素方差分析(ANOVA)来识别不同肿瘤分级之间的功率谱差异。结果 P < 0.05 时认为差异有统计学意义。
本研究共纳入 58 例患者。该组患者包括 1 例 I 级胶质瘤患者;15 例 II 级;12 例 III 级;30 例 IV 级。单独检查肿瘤时间序列的功率谱,所有肿瘤在较低频率信号处均表现出较高的峰值,但在高级别肿瘤中更为明显。ANOVA 显示组间功率谱差异有统计学意义(P = 0.000)。Bonferroni 校正后检验显示,II 级和 III 级(P = 0.012)和 IV 级(P = 0.000)之间有显著差异。III 级和 IV 级肿瘤之间的功率谱差异无统计学意义(P = 1)。
肿瘤组织 BOLD 信号的功率谱显示低频信号波动,与肿瘤分级显著相关。这些信号在分析静息状态功能磁共振成像时可能会产生误导,也可以作为肿瘤特征化的潜在方法。