背景:胶质瘤和孤立性脑转移(SBM)的分化,需要活检或多学科诊断,在临床上仍然很复杂。MR扩散或分子成像的直方图分析尚未得到充分的鉴别研究,可能有改善它的潜力。
方法:共纳入65例新诊断的胶质瘤或转移瘤患者。所有患者均接受DWI,IVIM,和APTW,以及T1W,T2W,T2FLAIR,和对比增强T1W成像。DWI的表观扩散系数(ADC)的直方图特征,慢扩散系数(Dslow),灌注分数(压裂),来自IVIM的快速扩散系数(Dfast),从肿瘤实质中提取APTWI的MTRasym@3.5ppm,并在胶质瘤和SBM之间进行比较。用logistics回归和接受者算子曲线对差异显著的参数进行分析,探索最优模型,比较差异化表现。
结果:较高的ADCkurtosis(P=0.022),峰度(P<0.001),并且在神经胶质瘤中发现了分形(P<0.001),而较高(MTRasym@3.5ppm)10(P=0.045),frac10(P<0.001),frac90(P=0.001),分形均值(P<0.001),观察到SBM的分形熵(P<0.001)。错乱(OR=0.431,95CI0.256~0.723,P=0.002)是SBM分化的独立影响因素。结合(MTRasym@3.5ppm)10,frac10和frackurtosis的模型显示AUC为0.857(灵敏度:0.857,特异性:0.750),而结合frac10和Frackurtosis的模型的AUC为0.824(敏感性:0.952,特异性:0.591)。来自两个模型的AUC之间没有统计学上的显著差异。(Z=-1.14,P=0.25)。
结论:增强肿瘤区域的frac10和frackurtosis可用于区分神经胶质瘤和SBM,(MTRasym@3.5ppm)10有助于提高分化特异性。
BACKGROUND: Differentiation of glioma and solitary brain metastasis (SBM), which requires biopsy or multi-disciplinary diagnosis, remains sophisticated clinically. Histogram analysis of MR diffusion or molecular imaging hasn\'t been fully investigated for the differentiation and may have the potential to improve it.
METHODS: A total of 65 patients with newly diagnosed glioma or metastases were enrolled. All patients underwent DWI, IVIM, and APTW, as well as the T1W, T2W, T2FLAIR, and contrast-enhanced T1W imaging. The histogram features of apparent diffusion coefficient (ADC) from DWI, slow diffusion coefficient (Dslow), perfusion fraction (frac), fast diffusion coefficient (Dfast) from IVIM, and MTRasym@3.5ppm from APTWI were extracted from the tumor parenchyma and compared between glioma and SBM. Parameters with significant differences were analyzed with the logistics regression and receiver operator curves to explore the optimal model and compare the differentiation performance.
RESULTS: Higher ADCkurtosis (P = 0.022), frackurtosis (P<0.001),and fracskewness (P<0.001) were found for glioma, while higher (MTRasym@3.5ppm)10 (P = 0.045), frac10 (P<0.001),frac90 (P = 0.001), fracmean (P<0.001), and fracentropy (P<0.001) were observed for SBM. frackurtosis (OR = 0.431, 95%CI 0.256-0.723, P = 0.002) was independent factor for SBM differentiation. The model combining (MTRasym@3.5ppm)10, frac10, and frackurtosis showed an AUC of 0.857 (sensitivity: 0.857, specificity: 0.750), while the model combined with frac10 and frackurtosis had an AUC of 0.824 (sensitivity: 0.952, specificity: 0.591). There was no statistically significant difference between AUCs from the two models. (Z = -1.14, P = 0.25).
CONCLUSIONS: The frac10 and frackurtosis in enhanced tumor region could be used to differentiate glioma and SBM and (MTRasym@3.5ppm)10 helps improving the differentiation specificity.