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Apparent diffusion coefficient values and non-homogeneity of diffusion in brain tumors in diffusion-weighted MRI

机译:扩散加权MRI脑肿瘤中脑肿瘤中脑肿瘤的表观扩散系数值和非均匀性

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Background The values that have been received from apparent diffusion coefficient (ADC) maps of diffusion-weighted magnetic resonance imaging (DW-MRI) might play a vital role in evaluating tumors and their grading scale. Purpose To investigate the predictive role of this heterogeneity in brain tumor pathologies and its correlation with Ki-67. Material and Methods A total of 124 patients with brain tumors underwent brain MRI with gadolinium injection. ADC and standard deviation of each lesion have been obtained from manual localization of the region of interest on the ADC map. A receiver operating characteristic analysis was conducted to determine the minimum cut-off values of the mean ADC and mean standard deviation of ADC maps having the highest sensitivity and specificity to differentiate high-grade and low-grade tumors. Results Mean ADC values in the region of interest were significantly lower for malignant tumors (grade IV and metastasis) than grade I brain tumors, while a higher mean standard deviation was observed. In a more detailed comparison of tumor groups, the mean standard deviation of the ADC for glioblastoma multiform was significantly higher than meningioma grade I (P < 0.001) and metastasis was significantly higher than grade III and IV astrocytic tumors (P = 0.004). The analysis of Ki-67 proliferation index and mean ADC values in gliomas showed a significant inverse correlation between the parameters (r = -0.0429, P < 0.001) and direct correlation between Ki-67 and mean standard deviation of the ADC (r = 0.551, P < 0.001). As an index for the ADC to differentiate high-grade and low-grade tumors, the cut-off values of 1.40*10(-3) mm(2)/s for mean ADC and 45*10(-3) mm(2)/s for mean standard deviation have the highest combination of sensitivity, specificity, and area under the curve. Conclusion The mean value and standard deviation of the ADC could be considered for differentiating between low-grade and high-grade brain tumors, as two available non-invasive methods.
机译:背景技术从漫反应加权磁共振成像(DW-MRI)的表观扩散系数(ADC)地图中接收的值可能在评估肿瘤及其分级规模方面发挥至关重要的作用。目的探讨这种异质性在脑肿瘤病理中的预测作用及其与KI-67的相关性。材料和方法共124例脑肿瘤患者接受脑MRI与钆注射。已经从ADC地图上的感兴趣区域的手动定位获得了ADC和每个病变的标准偏差。进行接收器操作特征分析以确定平均ADC的最小截止值,并且ADC地图的平均标准偏差具有最高的敏感性和特异性,以区分高级和低等级的肿瘤。结果对恶性肿瘤(IV等级和转移)的感兴趣区域中的ADC值显着降低,而不是I级脑肿瘤,而观察到更高的平均标准偏差。在肿瘤基团的更详细比较中,ADC用于胶质母细胞瘤的平均标准偏差显着高于脑膜瘤I(P <0.001),并且转移显着高于III级和IV星形细胞肿瘤(P = 0.004)。 KI-67增殖指数的分析和胶质瘤中的平均ADC值显示参数(R = -0.0429,P <0.001)与KI-67之间的直接相关性和ADC的平均标准偏差之间的显着逆相关(R = 0.551 ,p <0.001)。作为ADC的指标,以区分高档和低级肿瘤,为平均ADC和45×10(-3)mm(2 )/ s对于平均标准偏差具有曲线下的敏感性,特异性和面积的最高组合。结论ADC的平均值和标准偏差可以考虑区分低级和高等脑肿瘤,作为两种可用的非侵入性方法。

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