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DSC 和 DCE 直方图分析胶质瘤生物标志物,包括 IDH、MGMT 和 TERT,用于分化和生存。

DSC and DCE Histogram Analyses of Glioma Biomarkers, Including IDH, MGMT, and TERT, on Differentiation and Survival.

机构信息

Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen 518035, China.

Department of Radiology, The First Affiliated Hospital of Shenzhen University, Health Science Center, Shenzhen Second People's Hospital, 3002 SunGangXi Road, Shenzhen 518035, China.

出版信息

Acad Radiol. 2020 Dec;27(12):e263-e271. doi: 10.1016/j.acra.2019.12.010. Epub 2020 Jan 23.

DOI:10.1016/j.acra.2019.12.010
PMID:31983532
Abstract

RATIONALE AND OBJECTIVES

The World Health Organization 2016 classification of central nervous system tumors added the molecular classification of gliomas and has guiding significance for the operation and prognosis of glioma patients. At present, the perfusion technique plays an important role in judging the malignant degree of glioma. To evaluate the performance of dynamic susceptibility contrast (DSC)- and dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) histogram analyses in discriminating the states of molecular biomarkers and survival in glioma patients.

MATERIALS AND METHODS

Forty-three glioma patients who underwent DCE- and DSC-MRI were enrolled. Relevant molecular test results, including those on isocitrate dehydrogenase (IDH), O6-methylguanine-DNA methyltransferase (MGMT) and telomere reverse transcriptase (TERT), were collected. The mean relative cerebral blood volume of DSC-MRI and histogram parameters derived from DCE-MRI (volume transfer coefficient (K), fractional volume of the extravascular extracellular space (V), fractional blood plasma volume (V), rate constant between the extravascular extracellular space and blood plasma (K) and area under the curve (AUC)) were calculated. Differences in each parameter between gliomas with different expression states (IDH, MGMT, and TERT) were evaluated. The diagnostic efficiency of each parameter was analyzed. The overall survival of all patients was assessed.

RESULTS

The 10th percentile AUC (AUC = 0.830, sensitivity = 0.78, specificity = 0.80), the 90th percentile V (AUC = 0.816, sensitivity = 0.84, specificity = 0.79), and the mean K (AUC = 0.818, sensitivity = 0.76, specificity = 0.78) provided the highest differential efficiency for IDH, MGMT, and TERT, respectively. Kaplan-Meier curves showed a significant difference between subjects with a 10th percentile AUC higher or lower than 0.028 (log-rank = 7.535; p = 0.006) for IDH and between subjects with different 90th percentile V values (log-rank = 6.532; p = 0.011) for MGMT.

CONCLUSION

Histogram DCE-MRI demonstrates good diagnostic performance in identifying different molecular types and for the prognostic assessment of glioma.

摘要

背景与目的

世界卫生组织 2016 年中枢神经系统肿瘤分类增加了胶质瘤的分子分类,对胶质瘤患者的手术和预后具有指导意义。目前,灌注技术在判断胶质瘤恶性程度方面起着重要作用。本研究旨在评估动态对比增强磁共振灌注成像(DCE-MRI)和动态磁敏感对比磁共振灌注成像(DSC-MRI)直方图分析在鉴别胶质瘤患者分子标志物状态和生存中的性能。

材料与方法

纳入 43 例接受 DCE-MRI 和 DSC-MRI 检查的胶质瘤患者。收集了包括异柠檬酸脱氢酶(IDH)、O6-甲基鸟嘌呤-DNA 甲基转移酶(MGMT)和端粒逆转录酶(TERT)在内的相关分子检测结果。计算 DSC-MRI 的平均相对脑血容量和 DCE-MRI 的直方图参数(容积转移常数(K)、细胞外间隙的血管外分数(V)、血容量分数(V)、细胞外间隙与血容量的速率常数(K)和曲线下面积(AUC))。评估不同表达状态(IDH、MGMT 和 TERT)的胶质瘤之间各参数的差异。分析各参数的诊断效率。评估所有患者的总生存期。

结果

第 10 百分位数 AUC(AUC=0.830,敏感性=0.78,特异性=0.80)、第 90 百分位数 V(AUC=0.816,敏感性=0.84,特异性=0.79)和平均 K(AUC=0.818,敏感性=0.76,特异性=0.78)分别对 IDH、MGMT 和 TERT 具有最高的鉴别效率。Kaplan-Meier 曲线显示,AUC 值大于或小于 0.028 的第 10 百分位数(log-rank=7.535;p=0.006)的 IDH 患者和不同 90 百分位数 V 值(log-rank=6.532;p=0.011)的 MGMT 患者之间存在显著差异。

结论

直方图 DCE-MRI 在识别不同分子类型和评估胶质瘤的预后方面具有良好的诊断性能。

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