Department of Radiology, The Bishan Hospital of Chongqing, Bishan District, Chongqing 402760, China.
Department of Hepatobiliary Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
Biomed Res Int. 2020 Sep 28;2020:9549361. doi: 10.1155/2020/9549361. eCollection 2020.
To evaluate the diagnostic performance of apparent diffusion coefficient (ADC) histogram parameters for differentiating the genetic subtypes in lower-grade diffuse gliomas and explore which segmentation method (ROI-1, the entire tumor ROI; ROI2, the tumor ROI excluding cystic and necrotic portions) performs better.
We retrospectively evaluated 56 lower-grade diffuse gliomas and divided them into three categories: IDH-wild group (IDH, 16cases); IDH mutant with the intact 1p or 19q group (IDH/1p19q, 18cases); and IDH mutant with the 1p/19q codeleted group (IDH/1p19q, 22cases). Histogram parameters of ADC maps calculated with the two different ROI methods: ADCmean, min, max, mode, P5, P10, P25, P75, P90, P95, kurtosis, skewness, entropy, StDev, and inhomogenity were compared between these categories using the independent test or Mann-Whitney test. For statistically significant results, a receiver operating characteristic (ROC) curves were constructed, and the optimal cutoff value was determined by maximizing Youden's index. Area under the curve (AUC) results were compared using the method of Delong et al.
The inhomogenity from the two different ROI methods for distinguishing IDH gliomas from IDH gliomas both showed the biggest AUC (0.788, 0.930), the optimal cutoff value was 0.229 (sensitivity, 81.3%; specificity, 75.0%) for the ROI-1 and 0.186 (sensitivity, 93.8%; specificity, 82.5%) for the ROI-2, and the AUC of the inhomogenity from the ROI-2 was significantly larger than that from another segmentation, but no significant differences were identified between the AUCs of other same parameters from the two different ROI methods. For the differentiaiton of IDH/1p19q tumors and IDH/1p19q tumors, with the ROI-1, the ADCmode showed the biggest AUC (AUC: 0.784; sensitivity, 61.1%; specificity, 90.9%), with the ROI-2, and the skewness performed best (AUC, 0.821; sensitivity, 81.8%; specificity, 77.8%), but no significant differences were identified between the AUCs of the same parameters from the two different ROI methods.
ADC values analyzed by the histogram method could help to classify the genetic subtypes in lower-grade diffuse gliomas, no matter which ROI method was used. Extracting cystic and necrotic portions from the entire tumor lesions is preferable for evaluating the difference of the intratumoral heterogeneity and classifying IDH-wild tumors, but not significantly beneficial to predicting the 1p19q genotype in the lower-grade gliomas.
评估表观扩散系数(ADC)直方图参数在区分低级别弥漫性神经胶质瘤遗传亚型中的诊断性能,并探讨哪种分割方法(ROI-1,整个肿瘤 ROI;ROI2,不包括囊性和坏死部分的肿瘤 ROI)性能更好。
我们回顾性评估了 56 例低级别弥漫性神经胶质瘤,并将其分为三组:IDH 野生型组(IDH,16 例);IDH 突变伴完整 1p 或 19q 组(IDH/1p19q,18 例);和 IDH 突变伴 1p/19q 缺失组(IDH/1p19q,22 例)。使用两种不同 ROI 方法(ROI-1 和 ROI-2)计算 ADC 图的直方图参数:ADCmean、min、max、mode、P5、P10、P25、P75、P90、P95、峰度、偏度、熵、StDev 和异质性,并使用独立样本 t 检验或 Mann-Whitney 检验比较这些类别之间的差异。对于具有统计学意义的结果,构建了受试者工作特征(ROC)曲线,并通过最大化 Youden 指数确定最佳截断值。使用 Delong 等人的方法比较曲线下面积(AUC)结果。
两种不同 ROI 方法对区分 IDH 胶质瘤和 IDH 胶质瘤的异质性均显示出最大的 AUC(0.788、0.930),ROI-1 的最佳截断值为 0.229(灵敏度,81.3%;特异性,75.0%),ROI-2 的最佳截断值为 0.186(灵敏度,93.8%;特异性,82.5%),ROI-2 中异质性的 AUC 明显大于另一种分割方法,但两种 ROI 方法的相同参数的 AUC 之间没有显著差异。对于 IDH/1p19q 肿瘤和 IDH/1p19q 肿瘤的鉴别,使用 ROI-1,ADCmode 显示出最大的 AUC(AUC:0.784;灵敏度,61.1%;特异性,90.9%),使用 ROI-2,偏度表现最佳(AUC,0.821;灵敏度,81.8%;特异性,77.8%),但两种 ROI 方法的相同参数的 AUC 之间没有显著差异。
通过直方图方法分析的 ADC 值有助于对低级别弥漫性神经胶质瘤的遗传亚型进行分类,无论使用哪种 ROI 方法。从整个肿瘤病变中提取囊性和坏死部分对于评估肿瘤内异质性的差异和分类 IDH 野生型肿瘤是有利的,但对预测低级别神经胶质瘤中的 1p19q 基因型没有显著益处。