Conte Gian Marco, Castellano Antonella, Altabella Luisa, Iadanza Antonella, Cadioli Marcello, Falini Andrea, Anzalone Nicoletta
Neuroradiology Unit and CERMAC, San Raffaele Scientific Institute and Vita-Salute San Raffaele University, via Olgettina 60, 20132, Milan, Mi, Italy.
Department of Medical Physics, San Raffaele Scientific Institute, via Olgettina 60, 20132, Milan, Mi, Italy.
Radiol Med. 2017 Apr;122(4):294-302. doi: 10.1007/s11547-016-0720-8. Epub 2017 Jan 9.
Dynamic susceptibility contrast MRI (DSC) and dynamic contrast-enhanced MRI (DCE) are useful tools in the diagnosis and follow-up of brain gliomas; nevertheless, both techniques leave the open issue of data reproducibility. We evaluated the reproducibility of data obtained using two different commercial software for perfusion maps calculation and analysis, as one of the potential sources of variability can be the software itself.
DSC and DCE analyses from 20 patients with gliomas were tested for both the intrasoftware (as intraobserver and interobserver reproducibility) and the intersoftware reproducibility, as well as the impact of different postprocessing choices [vascular input function (VIF) selection and deconvolution algorithms] on the quantification of perfusion biomarkers plasma volume (Vp), volume transfer constant (K ) and rCBV. Data reproducibility was evaluated with the intraclass correlation coefficient (ICC) and Bland-Altman analysis.
For all the biomarkers, the intra- and interobserver reproducibility resulted in almost perfect agreement in each software, whereas for the intersoftware reproducibility the value ranged from 0.311 to 0.577, suggesting fair to moderate agreement; Bland-Altman analysis showed high dispersion of data, thus confirming these findings. Comparisons of different VIF estimation methods for DCE biomarkers resulted in ICC of 0.636 for K and 0.662 for Vp; comparison of two deconvolution algorithms in DSC resulted in an ICC of 0.999.
The use of single software ensures very good intraobserver and interobservers reproducibility. Caution should be taken when comparing data obtained using different software or different postprocessing within the same software, as reproducibility is not guaranteed anymore.
动态磁敏感对比增强磁共振成像(DSC)和动态对比增强磁共振成像(DCE)是脑胶质瘤诊断和随访中的有用工具;然而,这两种技术都存在数据可重复性的问题。我们评估了使用两种不同商业软件进行灌注图计算和分析所获得数据的可重复性,因为软件本身可能是变异性的潜在来源之一。
对20例胶质瘤患者的DSC和DCE分析进行了软件内(作为观察者内和观察者间可重复性)和软件间可重复性测试,以及不同后处理选择[血管输入函数(VIF)选择和去卷积算法]对灌注生物标志物血浆容积(Vp)、容积转移常数(K)和相对脑血容量(rCBV)定量的影响。使用组内相关系数(ICC)和布兰德-奥特曼分析评估数据可重复性。
对于所有生物标志物,观察者内和观察者间的可重复性在每个软件中几乎完全一致,而软件间可重复性的值范围为0.311至0.577,表明一致性为中等;布兰德-奥特曼分析显示数据分散性高,从而证实了这些发现。DCE生物标志物不同VIF估计方法的比较得出K的ICC为0.636,Vp的ICC为0.662;DSC中两种去卷积算法的比较得出ICC为0.999。
使用单一软件可确保非常好的观察者内和观察者间可重复性。在比较使用不同软件或同一软件内不同后处理获得的数据时应谨慎,因为不再保证可重复性。