Characterization of breast cancer subtypes based on quantitative assessment of intratumoral heterogeneity using dynamic contrast-enhanced and diffusion-weighted magnetic resonance imaging
Characterization of breast cancer subtypes based on quantitative assessment of intratumoral heterogeneity using dynamic contrast-enhanced and diffusion-weighted magnetic resonance imaging
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DOI：
10.1007/s00330-021-08166-4
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发表时间：
2021-08-04
影响因子：
5.9
通讯作者：
Park, Heeseung
中科院分区：
文献类型：
--
作者：
Kim, Jin Joo;Kim, Jin You;Park, Heeseung
目的探讨动态增强磁共振成像（DCE-MRI）和扩散加权成像（DWI）评估的肿瘤内异质性是否反映了浸润性乳腺癌的分子亚型。材料和方法我们回顾性评估了2019年至2020年期间接受术前DCE-MRI和DWI的248名连续女性（平均年龄+/-标准差，54.6 +/- 12.2岁）浸润性乳腺癌患者的数据。为了评价肿瘤内异质性，使用市售计算机辅助诊断系统，通过DCE-MRI评估动力学异质性（肿瘤内具有延迟洗脱、平台期和持续组分的肿瘤像素比例的异质性测量）。使用感兴趣区域技术获得表观扩散系数（ADC），并使用以下公式计算ADC异质性：（ADC（最大值）-ADC（最小值））/ADC（平均值）。分析了基于成像的异质性值与乳腺癌亚型之间的可能关联。结果248例浸润性乳腺癌中，管腔A型61例（24.6%），管腔B型130例（52.4%），HER 2富集型25例（10.1%），三阴性乳腺癌（TNBC）32例（12.9%）。肿瘤亚型之间的动力学和ADC异质性值存在显著差异（分别为p < 0.001和p = 0.023）。TNBC显示出更高的动力学和ADC异质性值，而与管腔亚型相比，HER 2富集亚型显示出更高的动力学异质性值。多变量线性分析显示，HER 2富集（p < 0.001）和TNBC亚型（p < 0.001）与较高的动力学异质性值显著相关。TNBC亚型（p = 0.042）也与较高的ADC异质性值显著相关。结论定量评估增强动力学和ADC值的异质性可能为乳腺癌的分子亚型提供生物学线索。
Objective To investigate whether intratumoral heterogeneity, assessed via dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI), reflects the molecular subtypes of invasive breast cancers. Material and methods We retrospectively evaluated data from 248 consecutive women (mean age +/- standard deviation, 54.6 +/- 12.2 years) with invasive breast cancer who underwent preoperative DCE-MRI and DWI between 2019 and 2020. To evaluate intratumoral heterogeneity, kinetic heterogeneity (a measure of heterogeneity in the proportions of tumor pixels with delayed washout, plateau, and persistent components within a tumor) was assessed with DCE-MRI using a commercially available computer-aided diagnosis system. Apparent diffusion coefficients (ADCs) were obtained using a region-of-interest technique, and ADC heterogeneity was calculated using the following formula: (ADC(max)-ADC(min))/ADC(mean). Possible associations between imaging-based heterogeneity values and breast cancer subtypes were analyzed. Results Of the 248 invasive breast cancers, 61 (24.6%) were classified as luminal A, 130 (52.4%) as luminal B, 25 (10.1%) as HER2-enriched, and 32 (12.9%) as triple-negative breast cancer (TNBC). There were significant differences in the kinetic and ADC heterogeneity values among tumor subtypes (p < 0.001 and p = 0.023, respectively). The TNBC showed higher kinetic and ADC heterogeneity values, whereas the HER2-enriched subtype showed higher kinetic heterogeneity values compared to the luminal subtypes. Multivariate linear analysis showed that the HER2-enriched (p < 0.001) and TNBC subtypes (p < 0.001) were significantly associated with higher kinetic heterogeneity values. The TNBC subtype (p = 0.042) was also significantly associated with higher ADC heterogeneity values. Conclusions Quantitative assessments of heterogeneity in enhancement kinetics and ADC values may provide biological clues regarding the molecular subtypes of breast cancer.