基于 T2*-加权的脑胶质瘤分级药代动力学成像的直方图分析。
Histogram analysis of T2*-based pharmacokinetic imaging in cerebral glioma grading.
机构信息
School of Biomedical Engineering, College of Biomedical Engineering, Taipei Medical University, Taipei, Taiwan; International Ph.D. Program in Biomedical Engineering, College of Biomedical Engineering, Taipei Medical University, Taipei, Taiwan; Research Center of Translational Imaging, College of Medicine, Taipei Medical University, Taipei, Taiwan; Radiogenomic Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan.
Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan; Department of Radiology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.
出版信息
Comput Methods Programs Biomed. 2018 Mar;155:19-27. doi: 10.1016/j.cmpb.2017.11.011. Epub 2017 Nov 15.
BACKGROUND AND OBJECTIVE
To investigate the feasibility of histogram analysis of the T2*-based permeability parameter volume transfer constant (K) for glioma grading and to explore the diagnostic performance of the histogram analysis of K and blood plasma volume (v).
METHODS
We recruited 31 and 11 patients with high- and low-grade gliomas, respectively. The histogram parameters of K and v, derived from the first-pass pharmacokinetic modeling based on the T2* dynamic susceptibility-weighted contrast-enhanced perfusion-weighted magnetic resonance imaging (T2* DSC-PW-MRI) from the entire tumor volume, were evaluated for differentiating glioma grades.
RESULTS
Histogram parameters of K and v showed significant differences between high- and low-grade gliomas and exhibited significant correlations with tumor grades. The mean K derived from the T2* DSC-PW-MRI had the highest sensitivity and specificity for differentiating high-grade gliomas from low-grade gliomas compared with other histogram parameters of K and v.
CONCLUSIONS
Histogram analysis of T2*-based pharmacokinetic imaging is useful for cerebral glioma grading. The histogram parameters of the entire tumor K measurement can provide increased accuracy with additional information regarding microvascular permeability changes for identifying high-grade brain tumors.
背景与目的
探讨基于 T2*-加权渗透性参数容积转移常数（K）直方图分析对脑胶质瘤分级的可行性，并探讨 K 和血容量（v）直方图分析的诊断性能。
方法
我们分别招募了 31 例和 11 例高级别和低级别胶质瘤患者。基于整个肿瘤体积的 T2动态磁敏感对比增强灌注加权磁共振成像（T2 DSC-PW-MRI）的首过药代动力学建模，评估了 K 和 v 的直方图参数，以区分胶质瘤级别。
结果
高级别和低级别胶质瘤之间的 K 和 v 的直方图参数存在显著差异，并且与肿瘤分级显著相关。与其他 K 和 v 的直方图参数相比，来自 T2* DSC-PW-MRI 的平均 K 对区分高级别胶质瘤和低级别胶质瘤具有最高的敏感性和特异性。
结论
基于 T2*-加权药代动力学成像的直方图分析有助于脑胶质瘤分级。整个肿瘤 K 测量的直方图参数可提供更高的准确性，并提供有关微血管通透性变化的附加信息，以识别高级别脑肿瘤。
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