动态对比增强(DCE)、动态敏感性对比(DSC)和动脉自旋标记(ASL)灌注MRI对高级别和低级别胶质瘤鉴别的诊断价值

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Retrospective qualitative and quantitative assessment of MRP-derived parameters, including DCE-Ktrans, DCE-Ve, DCE-Vp, DSC-rCBV, DSC-rCBF, and ASL-rCBF were performed, and the diagnostic value of each parameter was determined using ROC analysis.\n\nResults: Of the 24 patients enrolled in the present study, which included 10 LGGs and 14 HGGs, DCE-derived Vp showed the best diagnostic performance for differentiating between HGGs and LGGs (AUC 0.833, cutoff >0.0002 mL/100 g, p=0.018, 100% sensitivity, 28.6% specificity), followed by DCE-derived Ktrans (AUC 0.75, cutoff >0.024 min⁻¹, p=0.011, 58.3% sensitivity, 100% specificity) and DSC-derived normalized rCBV (AUC 0.75, p=0.021, cutoff >1.15, 100% sensitivity, 37.5% specificity). 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引用次数: 0

摘要

目的:评价动态对比增强(DCE)、动态敏感性对比(DSC)和动脉自旋标记(ASL)衍生灌注磁共振成像(MRI)参数作为鉴别高级别胶质瘤(HGGs)和低级别胶质瘤(LGGs)的无创技术,并确定各参数的诊断价值。材料与方法:24例经组织病理学证实的HGGs或LGGs患者行DCE-、DSC-和asl -磁共振灌注(MRP)。对mrp衍生参数DCE-Ktrans、DCE-Ve、DCE-Vp、DSC-rCBV、DSC-rCBF、ASL-rCBF进行回顾性定性和定量评估,并采用ROC分析确定各参数的诊断价值。结果:在本研究纳入的24例患者中,10例LGGs和14例HGGs中,dce衍生Vp对HGGs和LGGs的鉴别诊断效果最好(AUC 0.833,临界值>0.0002 mL/100 g, p=0.018, 100%灵敏度,28.6%特异性),其次是dce衍生Ktrans (AUC 0.75,临界值>0.024 min - 1, p=0.011, 58.3%灵敏度,100%特异性)和dce衍生归一化rCBV (AUC 0.75, p=0.021,临界值>1.15,100%灵敏度,37.5%特异性)。asl衍生的归一化rCBF在hgg和lgg之间无统计学差异(AUC 0.457, p=0.757)。结论:dce衍生Vp、dce衍生Ktrans和dsc衍生rCBV是鉴别HGGs和LGGs的有用灌注MRI参数,其中dce衍生Vp在本研究中表现出最好的诊断效果。关键词:DCE;DSL;美国手语;灌注先生;神经胶质瘤
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Diagnostic Value of Dynamic Contrast-Enhanced (DCE), Dynamic Susceptibility Contrast (DSC) and Arterial Spin Labeling (ASL) Perfusion MRI for Differentiation of High-Grade and Low-Grade Gliomas
Objective: To evaluate dynamic contrast-enhanced (DCE), dynamic susceptibility contrast (DSC), and arterial spin labeling (ASL)-derived perfusion magnetic resonance imaging (MRI) parameters as a non-invasive technique for differentiating between high-grade gliomas (HGGs) and low-grade gliomas (LGGs), and to determine the diagnostic value of each parameter. Materials and Methods: Twenty-four patients with histopathologically confirmed HGGs or LGGs underwent DCE-, DSC-, and ASL-magnetic resonance perfusion (MRP). Retrospective qualitative and quantitative assessment of MRP-derived parameters, including DCE-Ktrans, DCE-Ve, DCE-Vp, DSC-rCBV, DSC-rCBF, and ASL-rCBF were performed, and the diagnostic value of each parameter was determined using ROC analysis. Results: Of the 24 patients enrolled in the present study, which included 10 LGGs and 14 HGGs, DCE-derived Vp showed the best diagnostic performance for differentiating between HGGs and LGGs (AUC 0.833, cutoff >0.0002 mL/100 g, p=0.018, 100% sensitivity, 28.6% specificity), followed by DCE-derived Ktrans (AUC 0.75, cutoff >0.024 min⁻¹, p=0.011, 58.3% sensitivity, 100% specificity) and DSC-derived normalized rCBV (AUC 0.75, p=0.021, cutoff >1.15, 100% sensitivity, 37.5% specificity). The ASL-derived normalized rCBF showed no statistically significant difference between HGGs and LGGs (AUC 0.457, p=0.757). Conclusion: DCE-derived Vp, DCE-derived Ktrans, and DSC-derived rCBV are helpful perfusion MRI parameters for differentiating HGGs and LGGs, with DCE-derived Vp showing the best diagnostic performance in the present study. Keywords: DCE; DSL; ASL; Perfusion MR; Glioma
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