动态增强磁共振定量分析在常见子宫肿瘤中的应用

周微，吕富荣

1 动态增强磁共振定量分析原理

动态增强磁共振(dynamic contrast-enhanced MRI，DCE-MRI)是基于小分子对比剂在灌注程度和渗透性不同的组织中分布不同而引起信号变化的原理进行成像。所得图像可以进行定性、半定量、定量分析，其中定量分析是经过药代动力学模型处理后得到可重复的全定量参数，可以定量反映靶组织或器官的生理病理特性如血流量、血管渗透性等来间接反映肿瘤的微循环特点[1]。其后处理药代动力学模型多样，如Tofts双室模型、Reference region模型、Patlak模型、Exchange模型等。在选择最适模型时，要考虑到在假设理想状态下不同部位的组织具有不同的血流特点及对图像质量、采集时间及时间、空间分辨率等诸多因素的要求[2]，尽可能使参数值可以反映真实情况。如乳腺癌常选水交换模型，脑肿瘤中一般选择双室交换模型。大部分模型需要选取动脉输入函数，部分不需要。当采用一个基于人群的输入函数，可以提高重复性[3]。定量DCE-MRI常得到如下参数[2]：容量转运常数(Ktrans，min-1)，是反映单位时间内从血管内转移到血管外细胞外间隙(extravascular extracellular space，EES)的对比剂的容积，其值于不同状态下代表意义不同，当血流量较大时主要反映血管的渗透性，反之则主要反映组织灌注的特点；速率常数(Kep，min-1)，为对比剂从EES反渗回到血管内的速率常数；血管外细胞外间隙容积比(Ve，ml/100 m1)，为对比剂在EES所占的体积比；血浆容积分数(Vp，ml/100 m1)，为对比剂在血浆所占的体积比。其中Ve= Ktrans/Kep；Ve+Vp≤1。

2 定量DCE-MRI在常见子宫肿瘤中的应用

由于当组织发生病变时其微血管生理特征也会改变，尤其是恶性肿瘤，近年来定量DCE-MRI多用于对病变定位、常见恶性肿瘤性病变的分期、治疗方案的选择、预后的判断及良恶性肿瘤的鉴别[4]。

2.1 宫颈癌

宫颈癌是女性生殖系统中最常见的恶性肿瘤。张庆等[5]发现宫颈癌Ktrans、Kep及Ve值较正常宫颈显著升高。Wang[6]证实宫颈癌组织内血管密度(microvessel density，MVD)较正常宫颈组织明显增高。也有研究显示宫颈癌Ktrans值与表皮生长因子(vascular endothelial growth factor，VEGF)、MVD有良好的相关性[7]。所以可以用定量参数Ktrans值来反映肿瘤微血管密度和生长速度。早期不同类型及级别的宫颈癌其治疗方式不一样，因此对其正确的分型、分级与分期十分重要。有人认为宫颈腺癌的MVD水平、新生血管及微血管通透性高于鳞癌，张庆等[5]发现宫颈腺癌的Ktrans值较宫颈鳞癌高，而周星等[8]发现鳞癌Ktrans值高于腺癌，认为鳞癌的MVD较腺癌高。多数研究均发现宫颈癌分化程度越低，分期越高，其Ktrans值越大。Qu等[9]提出宫颈癌MVD值随着临床分期、分级的增加而升高。张朝赫等[10]认为宫颈鳞癌的Ktrans、Kep、Ve值与肿瘤分期不具有相关性。周延等[11]认为随着肿瘤级别增高，MVD和VEGF也增加。Haldorsen等[12]发现Ki-67和VIII因子可以反映微血管密度的变化，但它们和定量参数值之间有无关系有待研究。

刘伟峰等[13]认为DCE-MRI定量参数可以预测宫颈癌放化疗敏感度。Ellingsen等[14]认为中晚期宫颈癌组织缺氧、放疗效果差及生长转移等可能与低Ktrans值相关。Park等[15]和Mills等[16]提出在治疗前具有较低的Ktrans值和较低的灌注的宫颈癌的放疗效果差。Zahra等[17]提出宫颈癌放化疗消退率与治疗前半定量、定量参数间明显相关。Himoto等[18]用定量DCE评价宫颈癌新辅助化疗的早期疗效发现治疗前宫颈癌组织Ktrans值和Ve值与最初治疗后4 w和结束治疗后1个月肿瘤体积有明显相关性。Kim等[19]发现Ktrans、Ve值在宫颈癌放化疗后先升高后下降及治疗前Ktrans、Ve值和治疗后体积无明显相关。Mills等[16]认为Ve值因受到宫颈癌内部的囊变坏死水肿等影响而不准确。Andersen等[20]认为定量参数可以预测宫颈癌放化疗失败的风险，并且其疗效差可能与肿瘤内缺氧有关。朱志军等[21]发现Ⅱ期宫颈癌患者复发组较无复发组的Ktrans及Kep值显著升高。在判断转移方面，Lollert等[22]发现，较大的Ktrans值意味着较高的淋巴结转移风险，且Kep与肿瘤远处转移和表皮生长因子受体(epithelial growth factor receptor，EGFR)的表达呈正相关。杨晓棠等[23]认为宫颈癌淋巴结转移的定量参数值中Ve值敏感性及特异性较高。

周星等[8]认为宫颈鳞癌病灶的表观扩散系数(apparent diffusion coefficient，ADC)值与Ktrans有相关性，但刘梦秋[24]认为两者间不存在相关性。在人体中，一部分人认为ADC值的大小也会受到组织微循环灌注的影响[25]。何永红等[26]对100例宫颈癌患者和20名健康志愿者行常规MRI，扩散加权成像(diffusion weighted imaging，DWI)和DCEMRI扫描，发现Ktrans、Kep和ADCmean联合应用可以提高宫颈癌的诊断效能。

2.2 子宫内膜癌

子宫内膜癌为一种来源于子宫内膜的腺体且主要攻击绝经后女性的恶性肿瘤[27]。Haldorsen等[28]对55例子宫内膜癌患者行DCE-MRI检查及分析得到相关参数值如血流量(blood flow，FB)、摄取分数(extraction fraction，EF)、Kep、血容量(blood volume，VB)、Ve、Ktrans等值。结果发现子宫内膜癌组织的 FB、EF、VB、Ve、渗透率表面积乘积(permeability surface area product，PS)、Ktrans均较正常子宫肌层相应值低，他认为其中反映肿瘤毛细血管渗透性的EF、PS、Ktrans值低，可能是由于选择了具有较内膜血供丰富的子宫肌层作为参考组织。在分析子宫内膜癌总体预后中，他认为表现为低FB值、高EF值、高毛细血管通过时间值的肿瘤组织因相对缺氧而容易进展、转移及放化疗疗效差从而影响患者生存期。另外，他也发现非子宫内膜样腺癌组织FB值和EF值均较子宫内膜样腺癌低，两者的区分对内膜癌在选择治疗方案时尤为重要。郭永梅等[29]发现Ktrans值、Kep值及Ve值在子宫内膜癌高分化、中分化及低分化组间均有差异。

2.3 子宫肉瘤

子宫肉瘤约占所有子宫恶性肿瘤的3%[30]，其恶性程度高、预后差。有研究者于动态增强上观察到子宫肉瘤多为形态不规则且血流丰富。薛康康等[31]用DWI及DCE-MRI半定量分析鉴别诊断子宫肉瘤与变性子宫肌瘤，发现两者的半定量参数差异有统计学意义。而对于定量分析在子宫肉瘤的研究，国内尚无报道。

2.4 子宫肌瘤的分型、诊断及高强度聚焦超声消融的监测

定量DCE-MRI也可以应用于子宫良性肿瘤。子宫肌瘤是好发于育龄期女性的常见良性肿瘤，40岁以上的女性中其发病率高达40%[32]。在诊断及分型上，赵飞飞等[2]收集78个与患者自身子宫肌层相应值进行比较的子宫肌瘤的定量参数值相对Ktrans、相对Kep、感兴趣组织Kep，发现子宫肌瘤的参数值低于肌层且与肌瘤体积、部位无相关性。同时发现其中T2WI信号为均匀轻度高信号的肌瘤最特殊，作者认为可能和肌瘤亚型有关。郑静等[33]发现定量参数值可以提示肌瘤的病理亚型，其中细胞型肌瘤的Ktrans、Vp、血浆灌流量(plasma perfusion，PP)高于普通型、退变型肌瘤。Tal等[34]发现在子宫肌瘤的生成与生长过程中，血管内皮生长因子(vascular endothelial growth factor，VEGF)起着重要的作用，可以促进其血管的生长。也有王玉玲等[35]提出，肌瘤的新生血管的形成及其渗透性会受到VEGF、雌孕激素等的影响。研究[36]表明子宫间质肿瘤中雌激素受体介导的相关信号传导通路有重要作用。所以对于子宫肌瘤定量参数值与各种生理因子、病理亚型等相关性可以进一步深入研究。

王伟等[37]提出DCE-MRI定量分析可以用于肌瘤高强度聚焦超声(high intensity focused ultrasound，HIFU)疗效的监测。韦超等[38]搜集36例术前测量了DCE-MRI定量参数值[Ktrans、Kep、Ve、Vp、血流量(blood flow，BF)、血容量(blood volume，BV) ]的子宫肌瘤患者信息，以术后70%的首次体积消融率为界分为H组和L组，发现术前Ktrans、BF、BV值越高，首次体积消融率越低，其中BF预测效能最好，Ktrans次之。但临床应用中发现有部分肌瘤的消融效果不好。刘柳恒等[39]收集65例子宫肌瘤患者HIFU术前的肌瘤本身和子宫肌层的动态增强定量参数值，分析得出术前肌瘤Ktrans越高其消融率越低。Kim等[40]认为肌瘤内部的组织灌注状态影响消融效果。Zhao等[41]发现DCEMRI图像上子宫肌瘤呈轻度不均匀强化则容易消融，而呈均匀强化的子宫肌瘤消融率较低。同时部分肌瘤的消融效果欠佳是否和病理亚型相关还需要进一步研究。Kim等[42]通过多因素回归分析发现治疗前高Ktrans值是子宫肌瘤HIFU消融治疗疗效不佳的显著预测因素，其值越高就提示越多的能量被新生血管为主的渗透性部分带走。对此他提出用更高的声能来消融肌瘤内高灌注区域，在设置声能测试位置时要考虑到肌瘤内部血管分布的非均质性。因此Liu等[43]建议结合T2WI和可以展示血管分布的Ktrans图对肌瘤高灌注区定位和定性。

3 鉴别子宫良、恶性肿瘤

赵飞飞等[2]和郭永梅等[44]用DCE-MRI定量分析子宫良、恶性肿瘤的各个参数，发现病变处Ktrans值均较正常子宫肌层低，子宫恶性病变的Ve值较正常子宫肌层和良性病变低，但他们各自选择的参考组织不一样，目前还没有研究选择不同的参考组织是否有差异。孙俊旗等[45]发现Ktrans、Kep值在宫颈癌、子宫肌瘤、正常宫颈间差异均有统计学意义。有人发现在鉴别子宫良恶性肿瘤中Ktrans值的诊断效能最高。目前还没有研究显示不同子宫恶性肿瘤间Ktrans值是否存在差异。

4 DCE-MRI定量分析的局限与前景

对于不同的研究对象即具有不同生理病理特点的组织选择何种药代动力学模型来分析是值得进一步研究的。以此建立一个分析的标准，促进研究间的比较。对于动脉输入函数的稳定性以及在后处理分析中感兴趣区(region of interest，ROI)的选择与画法是否会影响最终的研究结果都具有不确定因素。这就需要大数据实验证明何种方法更加客观准确。对于子宫恶性肿瘤而言，其基因的表达和定量参数值反映的生物因子如MVD和VEGF之间有无相关性也可能成为未来的研究方向。临床医生制订个体化的治疗方案还需要结合其他反映组织结构及功能方面的影像学图像来全面评价肿瘤的生物学特性。所以未来需要动态增强和其他能提供多种病理生理学及分子生物学信息的复合影像。

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