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临床研究
治疗前IVIM-DWI参数图纹理特征对直肠癌新辅助放化疗病理反应的预测价值
刘思野 文露 侯静 聂少麟 周菊梅 曹芳 卢强 覃玉卉 于小平

刘思野,文露,侯静,等.治疗前IVIM-DWI参数图纹理特征对直肠癌新辅助放化疗病理反应的预测价值.磁共振成像, 2018, 9(7): 518-524. DOI:10.12015/issn.1674-8034.2018.07.007.


[摘要] 目的 探讨基于体素内不相干运动扩散加权成像(intravoxel incoherent motion diffusion-weighted imaging,IVIM-DWI)参数图的纹理特征对直肠癌原发灶新辅助放化疗病理反应的预测价值。材料与方法 搜集38例直肠癌患者的影像及病理资料,比较其中原发灶病理完全反应(pathological complete response,pCR)组与非pCR组在治疗前IVIM-DWI参数(ADC、D、D*及f)图纹理特征上的差别。结果 与非pCR组相比,pCR组的AngScMomD、AngScMomD*、AngScMomf、DifVarncADC、DifVarncD、ContrastADC及ContrastD*值更低,而Perc10%ADC、Perc10%D、Perc99%D*、CorrelatD*、Correlatf、DifEntrpADC、InvDfMomADC、SumAvergD、SumVarncD*及SumOfSqsD*值更高。在预测pCR方面,单个纹理特征的ROC曲线下面积(area under curve,AUC)值为0.662~0.829。采用多变量(一级+二级纹理特征) Logistic回归模型预测pCR时,DifVarncD (P=0.003)和SumVarncD* (P=0.002)为独立预测因子,AUC值为0.929。结论 基于IVIM-DWI参数图的纹理特征可能有助于预测直肠癌原发灶新辅助放化疗病理反应。
[Abstract] Objective: To investigate the performance of texture features based on intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) on identifying pathological complete response (pCR) to neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC).Materials and Methods: Pretreatment IVIM-DWI was performed on 38 LARC patients receiving nCRT. Nine first-order texture features (TFs) and eleven gray level co-occurrence matrix (GLCM) TFs were derived from four IVIM-DWI parameter maps (ADC, D, D* and f) respectively. The first-order TFs included Mean, Kurtosis, Skewness, Variance, Perc01%, Perc10%, Perc50%, Perc90% and Perc99%, and the GLCM features included Angular Second Moment (AngScMom), Contrast, Correlat, Difference Entropy (DifEntrp), Difference Variance (DifVarnc), Entropy, Inverse Difference Moment (InvDfMom), Sum Average (SumAverg), Sum Entropy (SumEntrp), Sum of Squares (SumOfSqs) and Sum Variance (SumVarnc). The values of first-order and GLCM TFs were compared between the pCR (n=8) and non-pathological responder (non-pCR, n=30) groups, which was classified according to tumor regression grade system. Receiver operating characteristic (ROC) curve in univariate and multivariate Logistic regression analysis was generated to determine the efficiency for identifying pCR.Results: The pCR group had lower AngScMomD, AngScMomD*, AngScMomf, DifVarncADC, DifVarncD, ContrastADC and ContrastD* values. Higher Perc10%ADC, Perc10%D, Perc99%D*, CorrelatD*, Correlatf, DifEntrpADC, InvDfMomADC, SumAvergD, SumVarncD* and SumOfSqsD* values were observed in the pCR group. The area under the ROC curve (AUC) values for the predictors in univariate analysis ranged from 0.662 to 0.829, with sensitivities from 33.33% to 100.00% and specificities from 37.50% to 100.00%. In multivariate Logistic regression analysis based on the first-order TFs, Perc10%ADC (P=0.032) and Perc10%D (P=0.028) were the independent predictors to pCR, with an AUC value of 0.754 (95% confidence interval, 0.588—0.879), a sensitivity of 50% and a specificity of 100.00%. DifVarncD (P=0.003) and SumVarncD* (P=0.002) were the independent predictors to pCR in the multivariate models that were based on either the GLCM TFs or the combination of the first-order and GLCM TFs, with an AUC of 0.929 (95% confidence interval, 0.797-0.987), a sensitivity of 83.33% and a specificity of 100.00%.Conclusions: GLCM analysis based on IVIM-DWI may be a potential approach to identify the pathological response of LARC before starting chemoradiotherapy.
[关键词] 直肠肿瘤;新辅助放化疗;病理反应;扩散磁共振成像;纹理分析
[Keywords] Rectal neoplasms;Chemoradiotherapy;Pathological response;Intravoxel incoherent motion;Diffusion magnetic resonance imaging;texture analysis

刘思野 中南大学湘雅医学院附属肿瘤医院湖南省肿瘤医院放射诊断科,长沙 410006

文露 中南大学湘雅医学院附属肿瘤医院湖南省肿瘤医院放射诊断科,长沙 410006

侯静 中南大学湘雅医学院附属肿瘤医院湖南省肿瘤医院放射诊断科,长沙 410006

聂少麟 中南大学湘雅医学院附属肿瘤医院湖南省肿瘤医院结直肠外科,长沙 410006

周菊梅 中南大学湘雅医学院附属肿瘤医院湖南省肿瘤医院放疗科,长沙 410006

曹芳 中南大学湘雅医学院附属肿瘤医院湖南省肿瘤医院病理科,长沙 410006

卢强 中南大学湘雅医学院附属肿瘤医院湖南省肿瘤医院放射诊断科,长沙 410006

覃玉卉 中南大学湘雅医学院附属肿瘤医院湖南省肿瘤医院放射诊断科,长沙 410006

于小平* 中南大学湘雅医学院附属肿瘤医院湖南省肿瘤医院放射诊断科,长沙 410006

通讯作者:于小平,E-mail:yuxiaoping@hnszlyy.com


基金项目: 湖南省省级临床重点专科(医学影像)建设项目 编号:2015/43 湖南省卫计委科研基金项目 编号:B2017099 国家癌症中心肿瘤科研专项基金 编号:NCC2017A19
收稿日期:2018-03-19
接受日期:2018-05-20
中图分类号:R445.2; R735.37 
文献标识码:A
DOI: 10.12015/issn.1674-8034.2018.07.007
刘思野,文露,侯静,等.治疗前IVIM-DWI参数图纹理特征对直肠癌新辅助放化疗病理反应的预测价值.磁共振成像, 2018, 9(7): 518-524. DOI:10.12015/issn.1674-8034.2018.07.007.

       新辅助放化疗联合全系膜切除术是局部进展期直肠癌的标准疗法[1,2]。病理检查是评估其新辅助放化疗疗效的金标准。早期判别直肠癌新辅助放化疗后的病理反应,有助于制订个性化治疗方案。新兴的影像学方法,例如体素内不相干运动扩散加权成像(intravoxel incoherent motion diffusion-weighted imaging,IVIM-DWI)的平均参数值分析,可用于预测直肠癌新辅助放化疗的病理反应状态[3,4,5]。而新兴的医学图像分析方法-纹理分析,可量化肿瘤内部的异质性[6,7,8]。研究发现,基于磁共振T2WI[9,10]和表观扩散系数(apparent diffusion coefficient,ADC)像[11]的纹理特征有助于预测直肠癌疗效。国外曾有研究发现,基于IVIM-DWI参数图的一级纹理特征能够预测直肠癌新辅助放化疗后是否达到原发灶病理完全反应(pathological complete response,pCR),但尚未见IVIM-DWI参数图二级纹理特征预测直肠癌疗效的研究报道。因此,笔者旨在探讨基于IVIM-DWI参数图的纹理特征在评估直肠癌原发灶放化疗反应方面的潜能,重点是比较一级与二级纹理特征的预测效能之间是否存在差异。

1 材料与方法

1.1 一般资料

       搜集38例临床及影像资料齐全的局部进展期(cT3-4N0-2M0)直肠癌病例。患者年龄22~73岁,平均51岁,男性27例,女性11例。所有研究对象均在放化疗前经结肠镜下病理活检证实为直肠非黏液型腺癌。此研究由我院医学伦理委员会批准。

1.2 设备及扫描方法

       所有患者于新辅助放化疗1~3 d前,依次行盆腔常规平扫及IVIM-DWI扫描。采用GE MR360 1.5 T超导型MRI仪及相控体线圈,患者取仰卧位。IVIM-DWI采用单次激发自旋回波扩散加权平面回波成像(ssSE-DW-EPI)序列行直肠横断面,取12个b值(0、10、20、30、50、80、100、150、200、400、600及800 s/mm2),TR 4694 ms,TE 102 ms,层厚5 mm,层间距1 mm,视野(FOV) 380 mm,NEX为4。

1.3 图像采集及纹理分析

       MRI原始资料先传至AW 4.6工作站,采用MADC软件进行后处理,由软件自动生成IVIM-DWI参数图,包括ADC(表观扩散系数)、D(真实扩散系数)、D* (伪扩散系数)及f(灌注分数)。由1名放诊科医师结合T2WI,在直肠癌原发灶轴位ADC图上沿病灶外缘手动勾画感兴趣区域(region of interest,ROI),这一ROI被自动复制到其他D、D*及f图上。完成病灶所有层面的ROI勾画后,软件自动生成感兴趣体积(volume of interest,VOI),并提供相应的IVIM-DWI参数值。再将这些参数图以BMP格式保存,导入纹理分析软件MaZda (http://www.eletel.p.lodz.pl/programy/mazda/index.php?action=mazda)进行。MaZda自动从每个VOI中提取9个一级纹理特征(Mean、Variance、Skewness、Kurtosis、Perc1%、Perc10%、Perc50%、Perc90%及Perc99%)值及11个共生矩阵特征(AngScMom、Contrast、Correlat、DifEntrp、Difvarnc、Entropy、InvDfMom、SumAverg、SumEntrp、SumOfSqs及SumVarnc)值。肿瘤体积由每一层ROI的面积乘以层厚并累加而得。

1.4 病理反应评估

       患者在完成MRI后行新辅助放化疗,放疗总剂量为50 Gy,分25次完成,同期口服卡培他滨1650 mg/(m2•d)。放化疗结束后8周行全系膜切除术。由1名经验丰富的病理科医师采用Dworak肿瘤消退等级(tumor regression grade,TRG)标准来评估肿瘤原发灶的病理反应状态[12] :TRG 4,完全反应(无残留的存活肿瘤细胞);TRG 3,较少的肿瘤细胞散在分布于纤维组织之中;TRG 2,肿瘤细胞残余较多,但仍少于纤维组织;TRG 1,肿瘤细胞残余多于纤维组织;TRG 0,无反应。本研究中,将原发灶病理反应为TRG 4的患者归为pCR组,其余患者归为非pCR组。

1.5 统计学分析

       应用SPSS 22.0及Medcalc 15.0行统计分析。计量资料用±s表示,计数资料以频数表示。采用卡方检验比较pCR组与非pCR组在性别构成、病理分化程度及治疗前临床分期上的差异。采用Mann-Whitney U检验比较pCR组与非pCR组在治疗前肿瘤体积、IVIM-DWI参数值及纹理特征值上的差异(单变量分析)。采用多变量Logistic回归分析(前进法,LR;进入概率:0.05;剔除概率:0.1)寻找pCR的独立预测因子,共构建3个模型,即模型1(基于一级纹理特征)、模型2(基于二级纹理特征)及模型3(基于一级及二级纹理特征)。采用受试者工作特性(ROC)曲线评价单个纹理特征及多变量回归模型对pCR的预测能力。P<0.05视为有统计学差异。

2 结果

       pCR组(8例)与非pCR组(30例)在患者年龄、性别构成、治疗前肿瘤体积(表1)以及ADC、D、D*、f参数值(表2)上没有显著性差异。

       在基于IVIM-DWI四种参数图的80个纹理特征中,17个在pCR组与非pCR组之间存在显著性差异。与非pCR组相比,pCR组的AngScMomD、AngScMomD*、AngScMomf、DifVarncADC、DifVarncD、ContrastADC及ContrastD*值更低,而Perc10%ADC、Perc10%D、Perc99%D*、CorrelatD*、Correlatf、DifEntrpADC、InvDfMomADC、SumAvergD、SumVarncD*及SumOfSqsD*值更高(表3)。图1图2分别为1例pCR及1例非pCR患者的MRI。

       在pCR的预测方面,单个纹理特征的ROC曲线下面积(area under curve,AUC)值在0.662~0.829之间,敏感度为33.33%~100.00%,特异度为37.50%~100.00%(表3)。就多变量分析而言,模型1中Perc10%ADC (P=0.032)和Perc10%D (P=0.028)为pCR的独立预测因子,该模型的AUC值为0.754 (95%置信区间:0.588~0.879),敏感度为50%,特异度为100%;模型2中pCR的独立预测因子为DifVarncD (P=0.003)和SumVarncD*(P=0.002),该模型的AUC值为0.929 (95%置信区间:0.797~0.987),敏感度为83.33%,特异度为100.00%;模型3的独立预测因子构成、AUC值、敏感度及特异度均与模型2完全一致。

图1  病理完全反应(pCR)组直肠癌患者。A:放化疗前的T2WI;B:放化疗后的T2WI,与放化疗前的T2WI相比,示病灶有缩小;C:感兴趣体积(VOI);D:治疗后的病理图像(HE ×40),示瘤区无残留的存活肿瘤细胞(完全反应,TRG 4);E~H:四张体素内不相干运动扩散加权成像(IVIM-DWI)参数图,分别为ADC、D、D*和f
图2  直肠癌患者(非pCR组)。A:放化疗前的T2WI;B:放化疗后的T2WI,与放化疗前的T2WI相比,示病灶有缩小;C:VOI;D:治疗后的病理图像(HE ×40),示瘤区残留较多的存活肿瘤细胞(非完全反应,TRG 2);E~H:四张IVIM-DWI参数图,分别为ADC、D、D*和f
Fig. 1  A Patient with LARC from the pCR group. A: Pre-therapy T2WI. B: Post-therapy T2WI, showing a relatively good response to nCRT. C: VOI. D: Pathological image (HE ×40) after nCRT, implying the absence of residual cancer (TRG 4). E—H: Four IVIM-DWI parametric maps named ADC, D, D* and f respectively. LARC: locally advanced rectal cancer. pCR: pathological complete response. nCRT: neoadjuvant chemoradiotherapy. VOI: volume of interest. TRG: tumour regression grade. nCRT: neoadjuvant chemoradiotherapy. IVIM-DWI: intravoxel incoherent motion diffusion-weighted imaging.
Fig. 2  A Patient with LARC from the non-pCR group. A: Pre-therapy T2WI. B: Post-therapy T2WI, showing a relatively good response to nCRT. C: VOI. D: Pathological image (HE ×40) after nCRT, impling more residual tumor cells, but still less than fibrosis (TRG 2). E—H: Four IVIM-DWI parametric maps named ADC, D, D* and f respectively.
表1  pCR和非pCR组的治疗前临床及病理特征比较
Tab. 1  Differences in pre-treatment clinical and pathological characteristics between the pCR and non-pCR groups
表2  pCR和非pCR组的治疗前IVIM-DWI参数值比较
Tab. 2  Differences in parameters of IVIM-DWI between the pCR and non-pCR groups
表3  直肠癌pCR组与非pCR组纹理特征的单变量分析结果
Tab. 3  Differences in texture features between the pCR and non-pCR groups

3 讨论

       纹理分析可通过计算图像中像素或体素的灰度变化来量化肿瘤异质性[13]。纹理分析方法众多,最常用的是基于统计学的分析方法,它可提供一级、二级及三级纹理特征。其中,一级纹理特征可通过直方图分析来评估给定区域内像素或体素的灰度频率分布情况,而二级纹理特征是评估图像中像素或体素的位置与空间关系[14]。灰度共生矩阵是目前最常用的二级纹理特征提取方法[15],且已被证实对多种肿瘤的治疗反应有预测价值[5,16,17,18]

3.1 一级纹理特征的预测能力

       本研究结果显示,36个一级纹理特征中,有3个在直肠癌原发灶pCR与非pCR两组之间存在显著性差异,分别是Perc10%ADC、Perc10%D及Perc99%D*。就ADC及D而言,低序百分位数(如Perc10%)主要受细胞致密程度的影响,其值越低代表细胞越密集[19,20]。非pCR组的Perc10%ADC及Perc10%D值明显低于pCR组,提示治疗反应较差的直肠癌其治疗前瘤灶内部细胞更密集,可能反映肿瘤细胞增殖更旺盛。D*值反映肿瘤的微循环灌注状态,与肿瘤内的微循环血流速度成正比[3]。本研究中原发灶pCR组的Perc99%D*值明显高于非pCR组,说明治疗反应好的直肠癌其内部血供较丰富,因而乏氧程度更轻,从而对放化疗的反应更好。不过,Nougaret等[5]却发现直肠癌治疗前IVIM-DWI四个参数(ADC、D、D*及f)图的百分位数均无法预测其放化疗后的pCR状态。本研究中IVIM-DWI所有参数图的Kurtosis无法预测直肠癌原发灶pCR,而De Cecco等[9]却发现基线T2WI像的Kurtosis有助于预测直肠癌pCR状态。另有研究发现,在接受新辅助放化疗的直肠癌中,反应组(影像上T降期或病理上N降期)与无反应组之间在基线ADC图的一级纹理特征值上没有显著性差异[11]。以上不同的研究结果可能是因为各研究之间在样本构成、MRI扫描方法、纹理特征的源影像与提取方法、疗效评价标准等方面存在差异所致。

3.2 二级纹理特征的预测能力

       在二级纹理特征中,Contrast、DifVarnc和InvDfMom是反映肿瘤异质性的指标[21],即Contrast或DifVarnc值越高、异质性越强,而InvDfMom则相反[15,17,21,22]。Correlat和SumAverg与组织异质性无直接关系[21]。本研究中,Contrast、Correlat、DifVarnc、InvDfMom及SumAverg值在原发灶pCR与非pCR两组之间存在显著性差异。与非pCR组相比,pCR组的Contrast和DifVarnc值均更低,而InvDfMom值则更高,这提示治疗前IVIM-DWI参数图上异质性越高的直肠癌对放化疗的反应越差。在以往关于直肠癌、乳腺癌及宫颈癌等恶性肿瘤纹理分析的研究中,也有类似现象[11,15,21,23,24]。比如,新辅助放化疗后影像上T降期或病理上N降期的直肠癌[11],其基线ADC图的InvDfMom值明显高于非降者,而治疗后病理反应为TRG 3~4级的直肠癌,其基线CT增强像的Entropy值明显低于TRG 0~2级的直肠癌[24] (InvDfMom值越高或Entropy值越低都代表肿瘤越均质)。对化疗反应好(肿瘤长径缩小超过50%)的乳腺癌,其治疗前增强T1WI的Contrast值低于无反应(肿瘤长径缩小不足50%)者[15]。对于宫颈癌,如果其动态对比增强MRI参数(增强幅度和对比剂廓清率)图的Contrast值越高,则治疗后复发的可能性越大[23]

3.3 一级纹理特征与二级纹理特征的比较

       本研究中,基于二级纹理特征构建的多变量模型对直肠癌原发灶pCR状态的预测效能高于基于一级纹理特征构建的模型(AUC值:0.929和0.754 ,P=0.056)。此外,本研究中以一级与二级特征混合建模用于预测直肠癌原发灶pCR时,所有的独立预测因子均为二级纹理特征而不是一级纹理特征。曾有研究发现,尽管直肠癌原发灶治疗后ADC及D参数图的一级纹理特征有助于预测pCR,但是其预测效能与IVIM-DWI参数平均值分析无异[5]。以上提示,在预测直肠癌原发灶对新辅助放化疗病理反应方面,二级纹理特征可能要优于一级纹理特征。这可能是因为二级纹理特征能够反映像素及体素之间的空间与位置关系,而一级纹理特征却不能,因此在充分反映肿瘤的异质性方面一级纹理不及二级纹理特征。

       本研究存在以下不足之处。(1)纳入的样本量较小,可能导致一定的统计学偏倚;(2)未探讨治疗后的原发灶IVIM-DWI纹理特征与病理反应之间的关系。因此,今后采用更大样本量以及不同时间点的IVIM-DWI参数图纹理特征来探讨纹理特征与直肠癌原发灶治疗反应之间的关系,可能更有价值。

       总之,本研究发现,基于IVIM-DWI参数图的纹理特征,特别是二级纹理特征,在预测局部进展期直肠癌原发灶新辅助放化疗的病理反应方面可能具有潜在价值。

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