MRI IVIM-DWI参数直方图对预测乳腺癌分子分型的价值
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摘要
目的:探究体素内不相干运动(IVIM)模型定量参数直方图对乳腺癌不同病理分型的评估价值,为临床对不同分子亚型的乳腺癌患者进行精准的个体化治疗、预后评估等提供影像学依据。方法:前瞻性搜集2017年8月至2018年12月深圳市第二人民医院临床怀疑为乳腺癌的患者61例,术前进行MRI检查并扫描IVIM–扩散加权成像(DWI)序列,将IVIM原始数据传送至工作站进行图像后处理和分析,得到IVIM各参数图像,将相应参数图输入ITK–SNAP软件进行肿瘤ROI绘制,获取相应直方图。在每个直方图上记录平均值、方差、中位数、第10百分位数、最左10%区域平均值、第90百分位数、最右10%区域平均值。采用SPSS 22.0统计软件进行数据分析,比较不同分子分型分组间的直方图参数值。结果:不同分子亚型间ADC值整体比较及组间比较,差异无统计学意义(P> 0.05)。人表皮生长因子受体–2(HER–2)过表达型组D、D*、f的直方图参数最大,大于其他各组,差异均具有统计学意义(P <0.05);Luminal A型组D、D*值的各直方图参数值小于Luminal B型组和基底细胞样型组,差异均具有统计学意义(P <0.05);Luminal B型组与基底细胞样型组D、D*值的各直方图参数值差异均无统计学意义。Luminal A型、Luminal B型与基底细胞样型的f值直方图参数组间比较差异均无统计学意义。结论:IVIM–DWI模型对预测乳腺癌的分子分型具有评估价值,特别是D值、D*值、f值与HER–2表达呈正相关关系,具有将HER–2过表达型组与其他分子亚型鉴别的潜在价值。
Objective To explore the value of the quantitative parameter histogram of the incoherent motion model in voxel for different pathological types of breast cancer. To provide imaging evidence for clinically accurate individualized treatment and prognosis evaluation of breast cancer patients with different molecular subtypes. Methods Prospectively collected 61 patients with suspected breast cancer in Shenzhen Second People's Hospital from August 2017 to December 2018. Perform MRI before surgery and scan for in voxel incoherent motion(IVIM)–Diffusion Weighted Imaging(DWI) sequences, The IVIM raw data is transmitted to the workstation for image post-processing and analysis, and the IVIM parameter images are obtained. Enter the corresponding parameter map into the ITK–SNAP software for tumor ROI mapping and obtain the corresponding histogram. The mean, variance, median, 10 th percentile, leftmost 10 % regional average, 90 th percentile, and rightmost 10% regional average were recorded on each histogram.Data analysis was performed using SPSS 22.0 statistical software to compare the histogram parameter values between different molecular typing groups. Results There was no signi? cant difference in the overall comparison of ADC values between different molecular subtypes and between groups(P > 0.05). The histogram parameters of human epidermal growth factor receptor-2(HER-2)overexpression group D, D*, and f were the largest, which were statistically signi? cant(P < 0.05). The values of the histogram values of the D and D* values of the Luminal A group were smaller than those of the Luminal B group and the basal cell type group, and the differences were statistically signi? cant(P < 0.05). There were no signi? cant differences in the values of the histogram parameters between the Luminal B group and the basal cell type group. There were no signi? cant differences between the Luminal A, Luminal B and basal cell-like f-value histogram parameters. Conclusion IVIM–DWI model can be used to predict the molecular typing of breast cancer, especially D value, D * value and f value are positively correlated with the expression of HER–2. It has great potential value to distinguish HER–2 over-expression group from other molecular subtypes.
Objective To explore the value of the quantitative parameter histogram of the incoherent motion model in voxel for different pathological types of breast cancer. To provide imaging evidence for clinically accurate individualized treatment and prognosis evaluation of breast cancer patients with different molecular subtypes. Methods Prospectively collected 61 patients with suspected breast cancer in Shenzhen Second People's Hospital from August 2017 to December 2018. Perform MRI before surgery and scan for in voxel incoherent motion(IVIM)–Diffusion Weighted Imaging(DWI) sequences, The IVIM raw data is transmitted to the workstation for image post-processing and analysis, and the IVIM parameter images are obtained. Enter the corresponding parameter map into the ITK–SNAP software for tumor ROI mapping and obtain the corresponding histogram. The mean, variance, median, 10 th percentile, leftmost 10 % regional average, 90 th percentile, and rightmost 10% regional average were recorded on each histogram.Data analysis was performed using SPSS 22.0 statistical software to compare the histogram parameter values between different molecular typing groups. Results There was no signi? cant difference in the overall comparison of ADC values between different molecular subtypes and between groups(P > 0.05). The histogram parameters of human epidermal growth factor receptor-2(HER-2)overexpression group D, D*, and f were the largest, which were statistically signi? cant(P < 0.05). The values of the histogram values of the D and D* values of the Luminal A group were smaller than those of the Luminal B group and the basal cell type group, and the differences were statistically signi? cant(P < 0.05). There were no signi? cant differences in the values of the histogram parameters between the Luminal B group and the basal cell type group. There were no signi? cant differences between the Luminal A, Luminal B and basal cell-like f-value histogram parameters. Conclusion IVIM–DWI model can be used to predict the molecular typing of breast cancer, especially D value, D * value and f value are positively correlated with the expression of HER–2. It has great potential value to distinguish HER–2 over-expression group from other molecular subtypes.
引文
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[12]Wei Y,Ji-Ping W,Yuebai L,et al.Tamoxifen versus aromatase inhibitors for breast cancer prevention[J].Clinical Cancer Research,2005,11(2):925s-930s.
[13]邹雪雪,秦东京,张虎,等.IVIM-DWI参数与乳腺浸润性导管癌预后因子ER、c-erb-2的相关性[J].实用医学杂志.2016,32(2):199-202.
[14]Linderholm BK,Hellborg H,Johansson U,et al.Signifi cantly higher levels of vascular endothelial growth factor(VEGF)and shoter survival times for patients with primary operable triplenegative breast cancer[J].Ann Oncol.2009,20(10):1639-1946.
[15]Kim JY,Kim SH,Kim YJ,et al.Enhancement parameters on dynamic contrast enhanced breast MRI:do they correlate with prognostic factors and subtypes of breast cancer?[J].Magn Reson Imaging.2015,33(1):72-80.
[16]车树楠,李静,欧阳汉,等.扩散加权成像体素内不相干运动模型参数与乳腺癌预后因素及分子亚型的相关性[J].中国医学影像技术,2016,32(3):367-371.
[2]Cho GY,Moy L,Kim SG,et al.Evaluation of breast cancer using intravoxel incoherent motion(IVIM)histogram analysis:comparison with malignant status,histological subtype,and molecular prognostic factors[J].European Radiology,2016,26(8):2547-2558.
[3]LI H,ZHU Y,BURNSIDE ES,et al.MR imaging radiomics signatures for predicting the risk of breast cancer recurrence as given by research versions of MammaPrint,Oncotype DX,and PAM50 gene assays[J].Radiology,2016,281(2):382-391.
[4]Kurebayashi J.Current clinical trials of endocrine therapy for breast[J].Breast Cancer.2007,14(2):200-214.
[5]TOBIN NP,LINDSTRM LS,CARLSON JW,et al.Multi-level gene expression signatures,but not binary,outperform Ki67 for the long term prognostication of breast cancer patients[J].Mol oncol,2014,8(3):741-752.
[6]Kim Y,Ko K,Kim D,et al.Intravoxel incoherent motion diffusion-weighted MR imaging of breast cancer association with histopathological features and subtypes[J].Br J Radiol,2016,89(1063):20160140.
[7]Jeh SK,Kim SH,Kim HS,et al.Correlation of the apparent diffusion coef cient value and dynamic magnetic resonance imaging ndings with prognostic factors in invasive ductal carcinoma[J].J MagnReson Imaging,2011,33(1):102-109.
[8]Choi SY,Chang YW,Park HJ,et al.Correlation of the apparent diffusion coefficiency values on diffusion-weighted imaging with prognostic factors for breast cancer[J].Br JRadiol,2012,85(1016):474-479.
[9]Sun K,Chen X,Chai W,et al.Breast cancer:diffusion kurtosis MR imaging-diagnostic accuracy and correlation with clinical-pathologic factors[J].Radiology,2015,277(1):46-55.
[10]宋萌萌,张天月,王丽君,等.IVIM多参数预测乳腺癌免疫组化指标表达的可行性研究[J].磁共振成像,2017,8(3):170-175.
[11]Bufi E,Belli P,Costantini M,et al.Role of the Diffusion Coefficient in the Predicticion of Response to Neadjuvant Chemotherapy in Patients With Locally Advanced Breast Cancer[J].Clin Breast Cancer.2015,15(5):370-380.
[12]Wei Y,Ji-Ping W,Yuebai L,et al.Tamoxifen versus aromatase inhibitors for breast cancer prevention[J].Clinical Cancer Research,2005,11(2):925s-930s.
[13]邹雪雪,秦东京,张虎,等.IVIM-DWI参数与乳腺浸润性导管癌预后因子ER、c-erb-2的相关性[J].实用医学杂志.2016,32(2):199-202.
[14]Linderholm BK,Hellborg H,Johansson U,et al.Signifi cantly higher levels of vascular endothelial growth factor(VEGF)and shoter survival times for patients with primary operable triplenegative breast cancer[J].Ann Oncol.2009,20(10):1639-1946.
[15]Kim JY,Kim SH,Kim YJ,et al.Enhancement parameters on dynamic contrast enhanced breast MRI:do they correlate with prognostic factors and subtypes of breast cancer?[J].Magn Reson Imaging.2015,33(1):72-80.
[16]车树楠,李静,欧阳汉,等.扩散加权成像体素内不相干运动模型参数与乳腺癌预后因素及分子亚型的相关性[J].中国医学影像技术,2016,32(3):367-371.