Wang Gang, Zhou Junlin
Department of Radiology, The First Hospital of Lanzhou University, Lanzhou, China.
Key Laboratory of Medical Imaging of Gansu Province, Lanzhou, China.
Front Oncol. 2023 May 16;13:1155162. doi: 10.3389/fonc.2023.1155162. eCollection 2023.
To investigate the value of whole-volume apparent diffusion coefficient (ADC) histogram analysis in preoperatively distinguishing intracranial solitary fibrous tumors (SFT) from transitional meningiomas (TM), thereby assisting the establishment of the treatment protocol.
Preoperative diffusion-weighted imaging datasets of 24 patients with SFT and 28 patients with TM were used to extract whole-volume ADC histogram parameters, including variance, skewness, kurtosis, and mean, as well as 1st (AP1), 10th (AP10), 50th (AP50), 90th (AP90), and 99th (AP99) percentiles of ADC using MaZda software. The independent -test or Mann-Whitney test was used to compare the differences between ADC histogram parameters of SFT and TM. Receiver operating characteristic (ROC) curves were generated to evaluate the performance of significant ADC histogram parameters. Spearman's correlation coefficients were calculated to evaluate correlations between these parameters and the Ki-67 expression levels.
SFT exhibited significantly higher variance, and lower AP1 and AP10 (all < 0.05) than TM. The best diagnostic performance was obtained by variance, with an area under the ROC curve of 0.848 (0.722-0.933). However, there was no significant difference in skewness, kurtosis, mean, or other percentiles of ADC between the two groups (all > 0.05). Significant correlations were also observed between the Ki-67 proliferation index and variance ( = 0.519), AP1 ( = -0.425), and AP10 ( = -0.372) (all < 0.05).
Whole-volume ADC histogram analysis is a feasible tool for non-invasive preoperative discrimination between intracranial SFT and TM, with variance being the most promising prospective parameter.
探讨全容积表观扩散系数(ADC)直方图分析在术前鉴别颅内孤立性纤维瘤(SFT)与过渡性脑膜瘤(TM)中的价值,从而辅助制定治疗方案。
利用24例SFT患者和28例TM患者的术前扩散加权成像数据集,使用MaZda软件提取全容积ADC直方图参数,包括方差、偏度、峰度和均值,以及ADC的第1百分位数(AP1)、第10百分位数(AP10)、第50百分位数(AP50)、第90百分位数(AP90)和第99百分位数(AP99)。采用独立样本t检验或曼-惠特尼U检验比较SFT和TM的ADC直方图参数差异。绘制受试者操作特征(ROC)曲线以评估显著ADC直方图参数的性能。计算Spearman相关系数以评估这些参数与Ki-67表达水平之间的相关性。
SFT表现出比TM显著更高的方差以及更低的AP1和AP10(均P<0.05)。方差具有最佳的诊断性能,ROC曲线下面积为0.848(0.722 - 0.933)。然而,两组之间的偏度、峰度、均值或ADC的其他百分位数均无显著差异(均P>0.05)。在Ki-67增殖指数与方差(r = 0.519)、AP1(r = -0.425)和AP10(r = -0.372)之间也观察到显著相关性(均P<0.05)。
全容积ADC直方图分析是术前无创鉴别颅内SFT和TM的可行工具,方差是最有前景的预测参数。