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. 2025 May 13;25(1):159.
doi: 10.1186/s12880-025-01698-x.

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

Xiaolei Zhang #  1 , Xiaoyan Chen #  1 , Yao Fu  1 , Han Zhou  1 , Yan Lin  2
Affiliations

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

Xiaolei Zhang et al. BMC Med Imaging. .

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.

Keywords: Breast cancer; HER2 expression; Habitat imaging; Multiparametric MRI; Tumor heterogeneity.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: Institutional Review Board approval was obtained. This study was approved by the Ethics Committee of the Second Affiliated Hospital of Shantou University Medical College (2020-34), which waived the requirement for written informed consent owing to the use of de-identified retrospective data. The authors confirm that all experiments involving humans and/or the use of human tissue samples were performed in accordance with the Declaration of Helsinki. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Flowchart of the study population
Fig. 2
Fig. 2
Image analysis and segmentation. a A 3D-slicer sketch map of the breast cancer focus VOI. b a multi-parameter MRI image registration map
Fig. 3
Fig. 3
Flowchart of FCM based lesions VOIs clustering
Fig. 4
Fig. 4
Three cases of breast cancer lesions. a Invasive ductal breast carcinoma (IHC 2+ with an amplified FISH assay). b Invasive ductal breast carcinoma (IHC 2+ with a non-amplified FISH assay). c Invasive ductal breast carcinoma (IHC 0)
Fig. 5
Fig. 5
An example of three divided spatial habitat sub-regions. a VOI of breast cancer lesions was sketched and aligned with quantitative parameter maps of ADC, ktrans, Ve and Kep. b FCM clustering algorithm was used to identify different habitat sub-regions of breast lesions
See this image and copyright information in PMC

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