基于先进磁共振成像衍生的多参数对胶质瘤患者Ki-67标记指数进行无创评估。
Noninvasive assessment of Ki-67 labeling index in glioma patients based on multi-parameters derived from advanced MR imaging.
作者信息
Hu Ying, Zhang Kai
机构信息
Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.
West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
出版信息
Front Oncol. 2024 May 17;14:1362990. doi: 10.3389/fonc.2024.1362990. eCollection 2024.
PURPOSE
To investigate the predictive value of multi-parameters derived from advanced MR imaging for Ki-67 labeling index (LI) in glioma patients.
MATERIALS AND METHODS
One hundred and nine patients with histologically confirmed gliomas were evaluated retrospectively. These patients underwent advanced MR imaging, including dynamic susceptibility-weighted contrast enhanced MR imaging (DSC), MR spectroscopy imaging (MRS), diffusion-weighted imaging (DWI) and diffusion-tensor imaging (DTI), before treatment. Twenty-one parameters were extracted, including the maximum, minimum and mean values of relative cerebral blood flow (rCBF), relative cerebral blood volume (rCBV), relative mean transit time (rMTT), relative apparent diffusion coefficient (rADC), relative fractional anisotropy (rFA) and relative mean diffusivity (rMD) respectively, and ration of choline (Cho)/creatine (Cr), Cho/N-acetylaspartate (NAA) and NAA/Cr. Stepwise multivariate regression was performed to build multivariate models to predict Ki-67 LI. Pearson correlation analysis was used to investigate the correlation between imaging parameters and the grade of glioma. One-way analysis of variance (ANOVA) was used to explore the differences of the imaging parameters among the gliomas of grade II, III, and IV.
RESULTS
The multivariate regression showed that the model of five parameters, including rCBV (RC=0.282), rCBF (RC=0.151), rADC (RC= -0.14), rFA (RC=0.325) and Cho/Cr ratio (RC=0.157) predicted the Ki-67 LI with a root mean square (RMS) error of 0. 0679 (R = 0.8025).The regression check of this model showed that there were no multicollinearity problem (variance inflation factor: rCBV, 3.22; rCBF, 3.14; rADC, 1.96; rFA, 2.51; Cho/Cr ratio, 1.64), and the functional form of this model was appropriate (F test: p=0.682). The results of Pearson correlation analysis showed that the rCBV, rCBF, rFA, the ratio of Cho/Cr and Cho/NAA were positively correlated with Ki-67 LI and the grade of glioma, while the rADC and rMD were negatively correlated with Ki-67 LI and the grade of glioma.
CONCLUSION
Combining multiple parameters derived from DSC, DTI, DWI and MRS can precisely predict the Ki-67 LI in glioma patients.
目的
探讨高级磁共振成像（MR）多参数对胶质瘤患者Ki-67标记指数（LI）的预测价值。
材料与方法
回顾性评估109例经组织学确诊的胶质瘤患者。这些患者在治疗前接受了包括动态磁敏感加权对比增强磁共振成像（DSC）、磁共振波谱成像（MRS）、扩散加权成像（DWI）和扩散张量成像（DTI）在内的高级MR成像检查。提取了21个参数，分别包括相对脑血流量（rCBF）、相对脑血容量（rCBV）、相对平均通过时间（rMTT）、相对表观扩散系数（rADC）、相对分数各向异性（rFA）和相对平均扩散率（rMD）的最大值、最小值和平均值，以及胆碱（Cho）/肌酸（Cr）、Cho/N-乙酰天门冬氨酸（NAA）和NAA/Cr的比值。进行逐步多元回归以建立预测Ki-67 LI的多元模型。采用Pearson相关分析研究成像参数与胶质瘤分级之间的相关性。采用单因素方差分析（ANOVA）探讨II、III和IV级胶质瘤之间成像参数的差异。
结果
多元回归显示，包括rCBV（回归系数[RC]=0.282）、rCBF（RC=0.151）、rADC（RC=-0.14）、rFA（RC=0.325）和Cho/Cr比值（RC=0.157）在内共5个参数的模型预测Ki-67 LI的均方根（RMS）误差为0.0679（R=0.8025）。该模型的回归检验显示不存在多重共线性问题（方差膨胀因子：rCBV为3.22；rCBF为3.14；rADC为1.96；rFA为2.51；Cho/Cr比值为1.64），且该模型的函数形式合适（F检验：p=0.682）。Pearson相关分析结果显示，rCBV、rCBF、rFA、Cho/Cr和Cho/NAA比值与Ki-67 LI及胶质瘤分级呈正相关，而rADC和rMD与Ki-67 LI及胶质瘤分级呈负相关。
结论
结合DSC、DTI、DWI和MRS得出的多个参数能够精确预测胶质瘤患者的Ki-67 LI。
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