结合DCE-MRI、DWI和MR谱预测乳腺癌的MRI遗传谱:一项前瞻性观察研究

Payal Sharma, Ishan Kumar, Ritu Ojha, Seema Khanna, Ashish Verma
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引用次数: 0

摘要

基于基因表达的乳腺癌分类已成为其管理的标准方法,因为在不同亚型中观察到不同的预后和治疗反应。本研究的目的是利用多参数磁共振成像(mMRI),结合动态对比增强磁共振成像(DCE-MRI)、扩散加权成像(DWI)和磁共振波谱(MRS),对乳腺癌分子亚型的影像学特征进行前瞻性评估。方法:这是一项前瞻性观察性单中心队列研究,纳入了在乳房x线摄影/超声(US)上有BI-RADS 4 - 5病变的女性,她们随后接受了1.5 T MRI(包括DCE-MRI、DWI和MRS)。评估乳腺癌的组织学亚型。通过免疫组织化学(IHC)评估雌激素受体(ER)、孕激素受体(PR)、Ki-67状态和人表皮生长受体-2 (HER2)表达,确定了四种分子亚型:luminal A、luminal B、HER2富集(Her2en)和三阴性乳腺癌(TNBC)。研究了四种分子亚型与MRI特征之间的统计学关联。结果共纳入50例患者。外切缘与三阴性肿瘤显著相关(78%对6%,p < 0.001)。非三阴性肿瘤边缘可见毛刺状。与所有其他亚型相比,Rim增强与三阴性肿瘤显著相关(71.4%对25%,p = 0.035)。与非腔内亚型相比,腔内亚型的平均表观扩散系数(ADC)值显著降低(p < 0.001)。三阴性肿瘤总胆碱(tCho)信噪比(SNR)较高。DCE-MRI、DWI和MRS联合预测TNBC和Her2en的特异性分别为86.6%和100%,敏感性分别为100%和85.37%。结论mMRI联合DCE-MRI、DWI、MRS能准确鉴别乳腺癌的分子亚型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Prediction of genetic profile of breast carcinoma on MRI using a combination of DCE-MRI, DWI, and MR spectroscopy: A prospective observational study

Prediction of genetic profile of breast carcinoma on MRI using a combination of DCE-MRI, DWI, and MR spectroscopy: A prospective observational study

Background

Classification of breast cancer based on gene expression has emerged as the standard approach in its management, owing to the distinct prognoses and treatment responses observed among different subtypes. The aim of this study was to prospectively assess the imaging features of the molecular subtypes of breast cancer using multiparametric magnetic resonance imaging (mMRI) with the combined assessment of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), diffusion-weighted imaging (DWI), and MR spectroscopy (MRS).

Methods

This was a prospective observational single-center cohort study, which included women with BI-RADS 4−5 lesions on mammography/ultrasound (US) who subsequently underwent 1.5 T MRI (encompassing DCE-MRI, DWI, and MRS). The histological subtypes of breast cancer were assessed. Estrogen receptor (ER), progesterone receptor (PR), Ki-67 status, and human epidermal growth receptor-2 (HER2) expression, assessed by immunohistochemistry (IHC), defined four molecular subtypes: luminal A, luminal B, HER2-enriched (Her2en), and triple-negative breast carcinoma (TNBC). Statistical associations between the four molecular subtypes and MRI features were investigated.

Results

Fifty patients were included in the study. Circumscribed margins were significantly correlated with triple-negative tumors compared to others (78% versus 6%, p < 0.001). Spiculated margins were observed in non-triple negative tumors. Rim enhancement was significantly correlated to triple-negative tumors compared to all other subtypes (71.4% versus 25%, p = 0.035). Mean apparent diffusion coefficient (ADC) values were significantly lower for luminal subtypes compared to non-luminal subtypes (p < 0.001). The total choline (tCho) signal-to-noise ratio (SNR) was higher in triple-negative tumors. A combined algorithm using DCE-MRI, DWI, and MRS can predict TNBC and Her2en with specificity of 86.6% and 100%, respectively, and sensitivity of 100% and 85.37%, respectively.

Conclusion

The combination of mMRI with DCE-MRI, DWI, and MRS can accurately differentiate the molecular subtypes of breast carcinoma.

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