Study on heterogeneity of vascularity and cellularity via multiparametric MRI habitat imaging in breast cancer.

IF 2.9 3区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Xiaolei Zhang, Xiaoyan Chen, Yao Fu, Han Zhou, Yan Lin
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Abstract

Background: This study aimed to visually analyze the heterogeneity of vascularity and cellularity across different sub-regions of breast cancer using habitat imaging (HI) to predict human epidermal growth factor receptor 2 (HER2) expression and evaluate the effectiveness of neoadjuvant therapy (NAT) in breast cancer patients.

Methods: A retrospective analysis was conducted on 76 patients diagnosed with breast cancer. Diffusion-weighted imaging (DWI) and dynamic contrast-enhanced MRI (DCE-MRI) sequences were utilized to acquire MR images. Apparent diffusion coefficient (ADC), Ktrans, Kep, and Ve values were measured for each sub-region, and the percentage of each sub-region relative to the total lesion was calculated. Statistical analyses, including t-tests, rank-sum tests, chi-square tests, and Spearman correlation, were performed.

Results: Three distinct sub-regions within breast cancer lesions were identified through HI, characterized physiologically as: low vascularity-high cellularity (LV-HC), low vascularity-low cellularity (LV-LC), and high vascularity-low cellularity (HV-LC). Significant differences were observed in the proportions of these tumor sub-regions between HER2-positive and HER2-negative breast cancers. Additionally, HER2-low and HER2-zero breast cancers demonstrated statistical differences in the second sub-region (LV-LC). Furthermore, the proportion of the first sub-region (LV-HC) was negatively correlated with the efficacy of NAT in breast cancer patients.

Conclusions: Habitat imaging can identify distinct sub-regions within breast cancer lesions, providing a noninvasive imaging biomarker for predicting HER2 expression levels and assessing the efficacy of NAT in breast cancer patients.

通过多参数MRI栖息地成像研究乳腺癌血管和细胞的异质性。
背景:本研究旨在利用生境成像(HI)预测人表皮生长因子受体2 (HER2)表达,直观分析乳腺癌不同亚区血管和细胞结构的异质性,并评估乳腺癌患者新辅助治疗(NAT)的有效性。方法:对76例乳腺癌患者进行回顾性分析。采用扩散加权成像(DWI)和动态对比增强MRI (DCE-MRI)序列获取MR图像。测量每个子区域的表观扩散系数(ADC)、Ktrans、Kep和Ve值,并计算每个子区域相对于总病变的百分比。进行统计分析,包括t检验、秩和检验、卡方检验和Spearman相关性。结果:通过HI确定了乳腺癌病变内的三个不同的亚区,其生理学特征为:低血管-高细胞性(LV-HC),低血管-低细胞性(LV-LC)和高血管-低细胞性(HV-LC)。在her2阳性和her2阴性乳腺癌中观察到这些肿瘤亚区比例的显著差异。此外,her2 -低和her2 -零乳腺癌在第二次区域(LV-LC)表现出统计学差异。第一亚区(LV-HC)的比例与NAT在乳腺癌患者中的疗效呈负相关。结论:Habitat成像可以识别乳腺癌病变内不同的亚区域,为预测HER2表达水平和评估NAT在乳腺癌患者中的疗效提供了一种无创成像生物标志物。
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来源期刊
BMC Medical Imaging
BMC Medical Imaging RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
4.60
自引率
3.70%
发文量
198
审稿时长
27 weeks
期刊介绍: BMC Medical Imaging is an open access journal publishing original peer-reviewed research articles in the development, evaluation, and use of imaging techniques and image processing tools to diagnose and manage disease.
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