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临床研究
Sy-MRI联合DWI在预测胶质瘤MGMT甲基化中的应用
马文富 葛鑫 党佩 黄雪莹 吕瑞瑞 郑佳瑞 张伟 王晓东

Cite this article as: MA W F, GE X, DANG P, et al. Application of Sy-MRI combined with DWI in predicting MGMT methylation in glioma[J]. Chin J Magn Reson Imaging, 2023, 14(7): 18-24, 48.本文引用格式:马文富, 葛鑫, 党佩, 等. Sy-MRI联合DWI在预测胶质瘤MGMT甲基化中的应用[J]. 磁共振成像, 2023, 14(7): 18-24, 48. DOI:10.12015/issn.1674-8034.2023.07.004.


[摘要] 目的 探讨集成MRI(synthetic MRI, Sy-MRI)联合扩散加权成像(diffusion weighted imaging, DWI)在预测胶质瘤O6-甲基鸟嘌呤-DNA甲基转移酶(O6-methylguanine-DNA methyltransferase, MGMT)启动子甲基化状态中的应用价值。材料与方法 前瞻性纳入2020年10月至2021年12月在宁夏医科大学总医院行肿瘤切除术并具有完整病理结果及免疫组化的胶质瘤患者47例,所有患者术前均在GE Architect 3.0 T超导型磁共振扫描仪接受Sy-MRI及DWI序列扫描,根据术后MGMT启动子甲基化的病理结果分为甲基化组和非甲基化组。对增强前后的Sy-MRI各参数图(pre-T1、post-T1、pre-T2、post-T2、pre-PD及post-PD)与基于DWI的表观扩散系数(apparent diffusion coefficient, ADC)图进行配准,随后测量胶质瘤实质部分在上述参数图的信号。采用独立样本t检验或Mann-Whitney U检验对比MGMT启动子甲基化组和非甲基化组各参数的差异,对差异有统计学意义的参数采用多因素logistic回归分析。采用受试者工作特征(receiver operating characteristic, ROC)曲线评估各参数独立及其联合诊断MGMT启动子甲基化的效能,并采用 DeLong检验对比ROC曲线下面积(area under the curve, AUC)的差异。结果 MGMT启动子甲基化组post-T1、pre-T2、post-T2、post-PD值低于非甲基化组,差异有统计学意义(P<0.05),pre-T1、pre-PD值两组间差异无统计学意义(P>0.05),甲基化组ADC值低于非甲基化组,差异有统计学意义(P<0.05)。多因素logistic回归分析显示,pre-T2 [OR=1.031,95%置信区间(confidence interval, CI):1.002~1.062,P=0.038]、post-T1(OR=1.003,95% CI:1.001~1.007,P=0.015)、ADC(OR=1.041,95% CI:1.008~1.072,P=0.047)是预测胶质瘤MGMT甲基化的独立影响因素。ROC曲线分析结果显示,pre-T2、post-T1及ADC值独立诊断MGMT启动子甲基化的AUC值分别为0.722、0.808及0.685,上述三参数联合模型诊断MGMT启动子甲基化的AUC为0.815。DeLong检验结果显示联合参数模型的诊断效能高于ADC值,差异有统计学意义(P=0.03),pre-T2、post-T1与联合参数模型的AUC值差异无统计学意义(P>0.05)。结论 Sy-MRI技术能够良好地诊断胶质瘤MGMT启动子甲基化,诊断效能显著高于DWI。当Sy-MRI参数联合DWI的ADC值时诊断效能更高。
[Abstract] Objective To investigate the value of synthetic MRI (Sy-MRI) combined with diffusion weighted imaging (DWI) in predicting the methylation status of O6-methylguanine DNA methyltransferase (MGMT) promoter in glioma.Materials and Methods Forty-seven patients with gliomas who underwent tumor resection in the General Hospital of Ningxia Medical University from October 2020 to December 2021 were prospectively collected. All patients were scanned by Sy-MRI and DWI sequence at the GE Architect 3.0 T superconducting MR scanner before operation. According to the pathological results of MGMT promoter methylation after the operation, they were divided into methylation group and non-methylation group. The pre-and post-enhanced Sy-MRI parameter maps (pre-T1, post-T1, pre-T2, post-T2, pre-PD and post-PD) were registered with the DWI-based apparent diffusion coefficient (ADC) map, and then the signal of the glioma parenchyma in the above parameter map was measured. The independent sample student's t-test or Mann-Whitney U test was used to compare the differences between the parameters of the methylation group and the non-methylation group of MGMT promoter. Receiver operating characteristic (ROC) curve was used to evaluate the efficacy of independent and combined diagnosis of MGMT promoter methylation, and the DeLong test was used to compare the difference of area under ROC curve (AUC).Results The values of post-T1, pre-T2, post-T2, and post-PD in the MGMT promoter methylation group were lower than those in the non-methylation group, with a statistically significant difference (P<0.05). The values of pre-T1 and pre-PD had no statistically significant difference between the two groups (P>0.05). The ADC values in the methylation group were lower than those in the non-methylation group, with a statistically significant difference (P<0.05). Multivariate logistic regression analysis showed that pre-T2 [OR=1.031, 95% confidence interval (CI): 1.002-1.062, P=0.038], post-T1 (OR=1.003, 95% CI: 1.001-1.007, P=0.015) and ADC (OR=1.041, 95% CI: 1.008-1.072, P=0.047) values were independent factors for predicting MGMT methylation in gliomas. The results of ROC curve analysis showed that the AUC values of pre-T2, post-T1 and ADC for independent diagnosis of MGMT promoter methylation were 0.722, 0.808 and 0.685 respectively, and the AUC of MGMT promoter methylation diagnosed by the combined model of the above three parameters was 0.815. The results of the DeLong test showed that the diagnostic efficacy of the combined parameter model was higher than that of the ADC value, and the difference was statistically significant (P=0.03). There was no significant difference between pre-T2, post-T1 and the AUC value of the combined parameter model (P>0.05).Conclusions Sy-MRI can well diagnose the methylation of the MGMT promoter in gliomas, and the diagnostic efficiency is significantly higher than that of traditional DWI. The diagnostic efficiency is higher when the Sy-MRI parameter is combined with the ADC value of DWI.
[关键词] 胶质瘤;磁共振成像;集成磁共振成像;扩散加权成像;O6-甲基鸟嘌呤-DNA甲基转移酶;甲基化;预测;诊断
[Keywords] glioma;magnetic resonance imaging;synthetic magnetic resonance imaging;diffusion weighted imaging;O6-methylguanine DNA methyltransferase;methylation;predict;diagnosis

马文富 1   葛鑫 2   党佩 3   黄雪莹 3   吕瑞瑞 1   郑佳瑞 1   张伟 3   王晓东 3*  

1 宁夏医科大学临床医学院,银川 750004

2 兰州大学第二临床医学院,兰州 730030

3 宁夏医科大学总医院放射科,银川 750004

通信作者:王晓东,E-mail:xdw80@yeah.net

作者贡献声明:马文富、葛鑫、党佩、黄雪莹、吕瑞瑞、郑佳瑞、张伟、王晓东均参与选题和试验设计;王晓东设计本研究的方案,对稿件重要的智力内容进行了修改;马文富起草和撰写稿件,获取、分析或解释本研究的数据;葛鑫、党佩、黄雪莹、吕瑞瑞、郑佳瑞、张伟获取、分析或解释本研究的数据,对稿件重要的智力内容进行了修改;王晓东获得宁夏回族自治区自然科学基金的资助;党佩获得宁夏回族自治区卫生健康系统科研课题的基金资助;全体作者都同意发表最后的修改稿,同意对本研究的所有方面负责,确保本研究的准确性和诚信。


基金项目: 宁夏回族自治区自然科学基金 2023AAC03557 宁夏回族自治区卫生健康系统科研课题 2023-NWKYP-046
收稿日期:2022-12-20
接受日期:2023-06-25
中图分类号:R445.2  R730.264 
文献标识码:A
DOI: 10.12015/issn.1674-8034.2023.07.004
本文引用格式:马文富, 葛鑫, 党佩, 等. Sy-MRI联合DWI在预测胶质瘤MGMT甲基化中的应用[J]. 磁共振成像, 2023, 14(7): 18-24, 48. DOI:10.12015/issn.1674-8034.2023.07.004.

0 前言

       脑胶质瘤是颅内最常见的恶性原发肿瘤,具有高侵袭性、高复发性及高死亡率的特点,预后很差,胶质母细胞瘤的五年生存率仅为0.05%~4.70%,世界卫生组织(World Health Organization, WHO)Ⅱ级和WHO Ⅲ级胶质瘤的中位生存期分别为78.1和38.6个月,星形细胞瘤、少突胶质细胞瘤的中位生存期分别为5.2年和7.2年[1, 2]。胶质瘤手术切除后替莫唑胺(temozolomide, TMZ)化疗是胶质瘤治疗的基本治疗手段,TMZ是一种能穿透血脑屏障的口服DNA烷化剂,具有广谱抗肿瘤活性,吸收快且具有良好的安全性,TMZ联合靶向治疗对于改善间变性神经胶质瘤患者的预后具有重要意义[3, 4]。近几年来,关于胶质瘤的分子诊断越来越受到重视[5]。O6-甲基鸟嘌呤-DNA甲基转移酶(O6-methylguanine-DNA methyltransferase, MGMT)是一种DNA修复酶,能够修复TMZ对胶质瘤的细胞毒性效应,限制TMZ发挥最大药理作用,导致肿瘤细胞对TMZ等烷基化剂产生耐药性。而MGMT启动子甲基化可以使MGMT基因转录沉默,从而抑制TMZ引起的治疗性DNA损伤的修复,增加胶质瘤对TMZ治疗的敏感性[6]。因此,胶质瘤治疗前预测MGMT启动子状态对胶质瘤的TMZ治疗至关重要。目前,对MGMT启动子状态的判断主要基于对活检或者手术切除得到的组织进行病理学检测,一方面为有创检查,存在出血等风险,在某些重要功能区,如运动性语言中枢(Broca区)等,还可能造成神经功能的损害;另一方面胶质瘤高度的异质性也限制了病理检测的准确性。因此,早期术前无创判读MGMT启动子的状态有助于制订更准确的治疗方案。

       既往的研究已经证实,肿瘤坏死、增强模式及肿瘤位置等可能与MGMT启动子甲基化状态相关[7, 8],然而定性征象的判读受到放射科医生主观和个体差异影响,准确性不高。近年来,酰胺质子转移成像(amide proton transfer, APT)、体素内不相干运动(intravoxel incoherent motion, IVIM)等多模态MRI技术以及影像组学、深度学习等新方法被用于预测胶质瘤MGMT启动子甲基化,然而APT、IVIM在预测MGMT甲基化特异度及敏感度中存在争议,影像组学及深度学习方法则需要建立复杂的模型,临床可推广性较低[7,9, 10, 11, 12, 13, 14, 15]。集成MRI(synthetic MRI, Sy-MRI)是一种新型定量MRI技术,可通过设置不同的回波时间和延迟时间来计算得到多种对比度图像,无创地反映组织的某些固有属性。其中,纵向弛豫时间(T1)、横向弛豫时间(T2)、质子密度(proton density, PD)图像最为常用,可客观定量分析组织的相关物理特性且可重复性高,且与常规MRI相比在保证图像质量的同时明显缩短扫描时间,可清晰显示大脑的解剖和形态学特征,对病灶的检出率更高[16, 17],可用于术前预测肿瘤细胞增殖抗原[18, 19, 20]。扩散加权成像(diffusion weighted imaging, DWI)衍生的表观扩散系数(apparent diffusion coefficient, ADC)可以无创地反映活体组织微观水分子的扩散能力[21],是脑肿瘤诊断、分级及预后预测常用的影像学标志物[22, 23]。因此,本研究拟联合采用Sy-MRI与DWI技术预测胶质瘤MGMT启动子甲基化状态,为胶质瘤的分子诊断、TMZ的决策治疗提供辅助。

1 材料与方法

1.1 一般资料

       前瞻性纳入2020年10月至2021年12月就诊于宁夏医科大学总医院并疑诊为颅内占位性病变且术前均行Sy-MRI及DWI序列扫描的60例患者。纳入标准:(1)患者MRI检查前未进行治疗;(2)所有患者术前经临床或CT等检查疑诊为颅内占位性病变。排除标准:(1)经病理证实为非胶质瘤者;(2)图像因存在伪影而不能定量评估者;(3)MGMT启动子状态不明确或病理结果不完整者。最终共有47例患者被纳入研究,13例被排除。本研究遵守《赫尔辛基宣言》,经宁夏医科大学总医院伦理委员会批准(批准文号:KYLL-2021-466),所有受试者检查前签署知情同意书。

1.2 扫描序列与参数

       本研究采用GE SIGNA Architect 3.0 T超导型磁共振扫描仪(Signa Architect;GE Healthcare,Milwaukee,WI USA)及48通道头颈联合科研线圈。所有患者行横断位DWI及增强前后Sy-MRI(pre-Sy-MRI、post-Sy-MRI)扫描。DWI扫描参数:采用自旋回波-回波平面成像(spin echo-echo planar imaging, SE-EPI)序列,TR 4214 ms,TE 21.6 ms,矩阵160×160(频率×相位),FOV 24.0 cm×24.0 cm,带宽250 kHz,层数20,层厚5 mm,层间距1 mm,激励次数1次,激发次数2次,b值取0和1000 mm2/s, 扫描时长1 min 11 s。增强前后Sy-MRI扫描参数相同,具体扫描参数如下:采用多延迟饱和多回波(multi-dynamic multi-echo, MDME)的快速自旋回波(fast spin echo, FSE)序列,TR 4214 ms,TE 21.6 ms,矩阵320×256(频率×相位),FOV 24.0 cm×24.0 cm,带宽±22.73 kHz,层数20,层厚5 mm,层间距1 mm,激励次数1次,扫描时间3 min 39 s。随后采用GE配套专用高压注射器经肘静脉团注钆双胺对比剂,剂量为0.1 mmol/kg,后注射20 mL生理盐水,注射速率均为4.0 mL/s,1 min 30 s后再进行Sy-MRI序列扫描。

1.3 定量参数的数据处理

       从宁夏医科大学总医院影像存档与通信系统获取所有胶质瘤患者的DWI和Sy-MRI数据,在GE AW 4.7(MAGIC software,v.100.1.1)工作站上分别获取DWI和Sy-MRI后处理图像,包括ADC、弛豫定量图谱(T1 map、T2 map和PD map)和对比度图像[合成T1液体衰减反转恢复(fluid-attenuated inversion-recovery, FLAIR)序列、合成T2WI、合成T2 FLAIR和合成T1 FLAIR+C]。首先利用MATLAB软件中的SPM 12组件,将所有图像配准到合成T2 FLAIR。由两名分别具有3年和5年经验的神经影像诊断医师采用双盲法参考结构像,避开坏死、囊变、钙化及出血区域,在合成T1 FLAIR+C胶质瘤实质最大层面上选择强化最明显处(若强化不明显或无强化,则选择合成T2 FLAIR上肿瘤实质等或高信号区域),选取3个大小形状相同的感兴趣区(region of interest, ROI),ROI的面积范围为20~45 mm2,随后复制到各定量图中,得到ADC、pre-T1、post-T1、pre-T2、post-T2、pre-PD及post-PD值(pre代表增强前,post代表增强后)。

1.4 病理学和免疫组织化学

       术后对肿瘤组织行常规病理学和免疫组织化学检测。根据第四版WHO中枢神经系统肿瘤分类[24]对胶质瘤的病理级别进行确定,免疫组织化学检测指标为MGMT。MGMT阳性染色以10%为临界值,将MGMT启动子状态分为甲基化(≥10%)和非甲基化(<10%)[25, 26]

1.5 统计分析

       采用SPSS 26.0软件进行统计分析,计量资料以均数±标准差(x¯±s)表示,对所测数据进行正态及方差齐性检验,若符合正态分布及方差齐性,则使用两独立样本t检验,不符合正态分布的资料用中位数(四分位数间距)[MQ1,Q3)]表示,组间比较采用Mann-Whitney U检验。采用组内相关系数(intra-class correlation coefficient, ICC)评价两名医师测量参数的一致性,ICC>0.75为一致性良好。对单因素分析差异有统计学意义的结果进行共线性诊断,排除多重共线性后采用多因素logistic回归及受试者工作特征(receiver operating characteristic, ROC)曲线分析各参数及其联合诊断的效能,计算曲线下面积(area under the curve, AUC),确定Sy-MRI参数、ADC值以及联合诊断的最佳临界值、敏感度和特异度,评估不同参数及联合参数对MGMT启动子状态的诊断效能。采用DeLong检验比较各参数AUC值的差异。结果均以双侧P<0.05为差异有统计学意义。

2 结果

2.1 一致性检验

       两位神经放射医师测量参数的一致性较好,ICC均大于0.85。

2.2 临床资料

       本研究最终共纳入具有完整病理及免疫组化结果的胶质瘤患者47例(表1),MGMT启动子甲基化(图1)组26例,MGMT启动子非甲基化(图2)组21例;其中男25例,女22例;年龄43.25±15.67岁。

图1  女,45 岁,右侧枕叶星形细胞瘤(WHO 3 级),MGMT(+),1p/19q无同时缺失。1A~1C分别为增强前T1、T2、PD图;1D为ADC图;1E为Sy-MRI T1增强图像,右侧枕叶病灶明显强化;1F~1H分别为增强后T1、T2、PD图。
图2  男,33岁,右侧额叶胶质母细胞瘤(WHO 4级),MGMT(-),1p有缺失,19q无缺失。2A~2C分别为增强前T1、T2、PD图;2D为ADC图;2E为Sy-MRI T1增强图像,右侧额叶病灶明显不均匀强化;2F~2H分别为增强后T1、T2、PD图。图中黑色圆圈为感兴趣区的示意图。MGMT:O6-甲基鸟嘌呤-DNA-甲基转移酶;1p:1 号染色体短臂;19q:19 号染色体长臂;PD:质子密度;ADC:表观扩散系数图;Sy-MRI:集成MRI。
Fig. 1  Female, 45 years old, astrocytoma of the right occipital lobe (WHO grade 3), MGMT (+), 1p/19q without joint loss. 1A-1C: T1, T2, PD maps before enhancement; 1D: ADC map; 1E: Sy-MRI T1 enhanced image, the right occipital lobe lesion is significantly enhanced; 1F-1H: T1, T2, PD maps after enhancement.
Fig. 2  Male, 33 years old, right frontal lobe glioblastoma (WHO grade 4), MGMT (-), 1p is absent and 19q is not. 2A-2C: T1, T2 and PD maps before enhancement; 2D: ADC map; 2E: Sy-MRI T1 enhanced image, the lesions in the right frontal lobe are enhanced unevenly; 2F-2H: T1, T2, PD maps after enhancement. The black circle in the figure is the schematic diagram of region of interest. MGMT: O6-methylguanine-DNA methyltransferase; 1p: the short arm of chromosome 1; 19q: the long arm of chromosome 19; PD: proton density; ADC: apparent diffusion coefficient; Sy-MRI: synthetic MRI.
表1  患者的临床特征
Tab. 1  Clinical characteristics of the patients

2.3 脑胶质瘤MGMT启动子甲基化组与非甲基化组Sy-MRI各参数值及ADC值的比较

       MGMT启动子甲基化组post-T1、pre-T2、post-T2、post-PD值低于非甲基化组,差异有统计学意义(P<0.05);pre-T1值、pre-PD两组间差异无统计学意义(P>0.05);甲基化组ADC值低于非甲基化组,差异有统计学意义(P<0.05,表2)。

表2  MGMT启动子甲基化组与非甲基化组各参数间的比较
Tab. 2  Comparison between the parameters of MGMT promoter methylation and nonmethylation groups

2.4 脑胶质瘤MGMT启动子甲基化组与非甲基化组Sy-MRI参数值和ADC值诊断效能及联合诊断效能的比较

       共线性诊断结果显示,所有单因素分析差异有统计学意义的结果不存在多重共线性,方差膨胀因子(variance inflation factor, VIF)值均<10(表2)。多因素logistic回归分析显示,pre-T2 [OR=1.031,95%置信区间(confidence interval, CI):1.002~1.062,P=0.038]、post-T1(OR=1.003,95% CI:1.001~1.007,P=0.015)、ADC(OR=1.041,95% CI:1.008~1.072,P=0.047)值是预测胶质瘤MGMT甲基化的独立影响因素(表3)。ROC曲线分析显示,pre-T2、post-T1、ADC值在预测胶质瘤MGMT启动子状态中的AUC值分别为0.722、0.808及0.685,当截断值为982.17 ms时,post-T1的诊断效能最高。采用多因素logistics分析得出的独立影响因素pre-T2、post-T1与ADC构建多参数联合预测模型,其诊断效能最高,AUC为0.815,较单一参数诊断效能提高。DeLong检验结果显示联合参数模型诊断与ADC的AUC值的差异存在统计学意义(P=0.03),联合参数模型与pre-T2、post-T1的AUC值的差异无统计学意义(P>0.05;表4图3)。

图3  ADC值、Sy-MRI(pre-T2、post-T1)定量参数及其联合诊断的ROC曲线。ADC:表观扩散系数;Sy-MRI:集成MRI;pre-T2:增强前T2值;post-T1:增强后T1值;ROC为受试者工作特征。
Fig. 3  The quantitative parameters of ADC value and Sy-MRI (pre-T2, post-T1) and their combined ROC curves. ADC: apparent diffusion coefficient; Sy-MRI: synthetic MRI; pre-T2: T2 value before the enhancement; post-T1: T1 value after the enhancement; ROC: receiver operating characteristic.
表3  ADC值及Sy-MRI(pre-T2、post-T1)定量参数多因素logistics回归分析
Tab. 3  Multivariate logistic regression analysis of ADC value and Sy-MRI (pre-T2, post-T1) quantitative parameters
表4  ADC值及Sy-MRI(pre-T2、post-T1)定量参数及其联合的ROC曲线诊断效能
Tab. 4  The quantitative parameters of ADC value and Sy-MRI (pre-T2, post-T1) and the results of combined ROC curve analysis

3 讨论

       既往Sy-MRI用于胶质瘤的分级、鉴别复发和假性进展、预测IDH1基因突变及定量检测瘤周水肿[27, 28, 29, 30]等领域,但利用其预测MGMT启动子状态的研究目前尚无报道。基于术前无创预测胶质瘤MGMT的病理需求,本研究采用Sy-MRI联合DWI预测胶质瘤MGMT启动子状态,为术前预测MGMT启动子的状态提供影像学依据,为患者制订个性化治疗提供辅助。本研究发现两者联合诊断效能最佳。

3.1 胶质瘤MGMT启动子甲基化与非甲基化组间的Sy-MRI定量参数差异

       Sy-MRI较传统MRI表现出较大优势,在量化组织固有特征属性上,将MRI带入后定量参数时代。本研究探索了Sy-MRI在胶质瘤中预测MGMT启动子甲基化的应用价值,系目前首次基于Sy-MRI来预测MGMT启动子状态的研究。T1、T2及PD值是组织的固有属性,会随着肿瘤生物学行为的不同阶段来反映组织的特征,而顺磁性物质、细胞密度、蛋白质、脂肪含量以及细胞内外水分含量的变化会对其造成影响,这些因素通常伴随肿瘤的病理生理过程,因此,不同的病理生理特征可以在Sy-MRI中被检测。

       T1值是组织的内源性标志之一,T1值的变化受多种因素的综合影响,包括组织内对比剂的浓度、细胞密度,蛋白质等多种因素。本研究表明,与MGMT启动子非甲基化组相比,甲基化组post-T1值更低且差异有统计学意义(P<0.001),而pre-T1与MGMT启动子状态间差异无统计学意义(P>0.05)。综合考虑,增强前后最主要的影响因素为顺磁性对比剂钆双胺,钆剂能够缩短肿瘤组织T1值,与周围组织形成明显的对比。EOLI等[8]研究发现,非甲基化胶质瘤具有更明显的环形强化,在MRI图像上表现高信号,而在定量弛豫时间的表现可能是弛豫时间的延长,对比剂经血流分布于肿瘤实质或瘤周区域,瘤周区域伴有一定的血脑屏障破坏,非甲基化胶质瘤由于其浸润性更强,拥有更丰富的肿瘤增殖血管,意味着在增强早期钆剂快速进入肿瘤内部,之后很快进入组织间隙及小的吻合动静脉中,而甲基化胶质瘤由于血供较非甲基化组低,对比剂缓慢积累,缩短组织T1、T2值的作用更明显,这也督促我们进一步探索两种基因状态的血流调控机制。

       横向弛豫时间T2值(pre-T2和post-T2)在甲基化和非甲基化组之间差异显著(P<0.001),甲基化组较非甲基化组pre-T2、post-T2值明显缩短。不只是浸润性肿瘤细胞、增生的小胶质细胞及其他炎性细胞会使T2弛豫时间发生变化,蛋白含量的变化也会有影响等。我们认为,两种胶质瘤的基因类型不同,甲基化组降低了MGMT蛋白水平,但两者除本身修复蛋白含量存在差异外,甲基化导致染色质结构的变化可能影响其下游相应DNA决定的某些蛋白的转录及翻译,肿瘤内整体蛋白含量的变化与胶质瘤的分级相关,而不是单一MGMT蛋白。此外,甲基化组较非甲基化组更容易发生坏死[31],坏死物质排出后与结合水结合,减少自由水的比例也会缩短T2时间。在功能上,MGMT启动子甲基化和转录沉默不仅降低了TMZ的耐药性,还可能增加遗传不稳定性(可能促进肿瘤的发生)[32]

       Post-PD在两组间差异显著(P<0.05),PD值反映了组织中水分含量的变化。除钆剂外,血管内皮生长因子(vascular endothelial growth factor, VEGF)的表达致使血管增生,促进血液供应,非甲基化较甲基化恶性程度更高,这与MENG等[33]用PD值评估鼻咽癌良恶性的研究结果一致,我们推测,肿瘤恶性程度越高,PD值越高。

3.2 ADC值与MGMT启动子甲基化的相关性分析

       本研究发现,胶质瘤MGMT启动子甲基化组较非甲基化组ADC值更低。这与POPE等[34]的研究一致,甲基化肿瘤的ADC值较非甲基化低,并且低ADC值的甲基化组具有更长的贝伐单抗治疗下的生存期[8],因为它存在化疗药物的相应靶点,MGMT启动子甲基化使得MGMT基因沉默,促进TMZ对胶质瘤的细胞毒性作用。本研究与HAN等[31]报道的非甲基化胶质母细胞瘤ADC值较低存在差异,可能与本研究纳入的病例包括不同级别胶质瘤有关,另外,ROI的选取及不同的研究队列也可能是导致这种差异的原因。此外,ADC值和MGMT启动子状态之间无显著相关性的研究也有报道[35, 36]。研究发现,血管源性水肿和坏死与高VEGF水平和胶质瘤预后不良相关[37],胶质母细胞瘤具有更大面积的水肿和坏死,VEGF表达上调促进新血管生成,细胞核密集且异型性明显,从而降低ADC值。ADC值低的肿瘤区域匹配于细胞密度增高的区域,但血管源性水肿和坏死增加可能会引起ADC值的升高。因此,纳入不同级别的肿瘤对ADC值的测定可能存在差异。EOLI等[8]研究报道,MGMT非甲基化和环形强化之间具有关联,非甲基化的肿瘤伴有更多的囊变坏死和水肿引起肿瘤的不均质性,细胞密度较甲基化低,而甲基化细胞连接更紧密,水分子扩散程度受限,ADC值降低。RUNDLE等[38]采用双混合模型直方图法产生的ADC最低分布的平均值来评估MGMT的状态,甲基化组ADC值低于非甲基化组(P<0.05),以上研究与本研究结果存在一致性。

3.3 单一定量参数及联合参数(pre-T2+post-T1+ADC)诊断MGMT启动子状态的效能

       胶质瘤MGMT启动子状态对TMZ参与的化疗的敏感性有决定性作用,手术或活检的侵入性取材似乎是检验MGMT状态的金标准,但这不可避免地会带来一定的风险,尤其在某些重要功能区,肿瘤的异质性和取材的误差也可能增加基因分析错误的风险。MRI作为一种非侵入性的检查方法,基于先进扫描技术和后处理手段,通过各种模型来预测肿瘤的相关基因分型似乎是另一种替代方式。Sy-MRI各参数的AUC显示使用单一参数诊断胶质瘤MGMT甲基化的效能较低,分析原因为甲基化和非甲基化组在Sy-MRI定量参数中存在一定程度的重叠,单独应用可能存在局限性,多因素logistics回归结果显示pre-T2、post-T1及ADC值是诊断MGMT甲基化的独立影响因素,基于MDME序列的定量Sy-MRI和ADC联合参数预测MGMT启动子甲基化可以更全面地反映肿瘤信息,未来基于定量分析的高级模型将可能为术前无创预测肿瘤的基因类型提供新方法,为患者的个性化监测治疗和决策管理提供辅助。

3.4 局限性

       本研究存在以下局限性:(1)所有样本数据均为单中心且样本量较小,多中心大样本的前瞻性研究将是一种趋势;(2)未对各级胶质瘤MGMT状态与定量参数相匹配,各级胶质瘤MGMT启动子与定量参数是否存在差异需进一步探索;(3)对胶质瘤ROI的勾画是基于2D而不是肿瘤全层信息,可能不能代表肿瘤的整体信息;(4)存在系统误差等。

4 结论

       综上所述,本研究采用Sy-MRI联合DWI预测胶质瘤MGMT启动子状态,为术前无创鉴定MGMT启动子甲基化与否提供了新的方法,对选择TMZ化疗获益的潜在胶质瘤患者具有重要的临床意义,从而有助于规划治疗方案。

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