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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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Abstract

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: (ADCmax−ADCmin)/ADCmean. 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.

Key Points

• Higher kinetic heterogeneity was associated with HER2-enriched and triple-negative breast cancer.

• Higher ADC heterogeneity was associated with triple-negative breast cancer.

• Aggressive breast cancer subtypes exhibited higher intratumoral heterogeneity based on MRI.

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Abbreviations

ADC:

Apparent diffusion coefficient

AUC:

Area under the curve

CAD:

Computer-aided diagnosis

CI:

Confidence interval

DCE:

Dynamic contrast-enhanced

DWI:

Diffusion-weighted imaging

ER:

Estrogen receptor

HER2:

Human epidermal growth factor receptor 2

MRI:

Magnetic resonance imaging

PR:

Progesterone receptor

ROI:

Region of interest

TNBC:

Triple-negative breast cancer

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Funding

This study was supported by Biomedical Research Institute Grant (20200268), Pusan National University Hospital.

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Authors and Affiliations

  1. Department of Radiology, Medical Research Institute, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, 1-10, Ami-Dong, Seo-gu, Busan, 602-739, Republic of Korea

    ** Joo Kim, ** You Kim, Hie Bum Suh, Lee Hwangbo, Nam Kyung Lee, Suk Kim & Ji Won Lee

  2. Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea

    Ki Seok Choo & Kyung ** Nam

  3. Busan Cancer Center, Pusan National University Hospital, Busan, Republic of Korea

    Taewoo Kang & Heeseung Park

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  1. ** Joo Kim
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Correspondence to ** You Kim.

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The scientific guarantor of this publication is ** You Kim.

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The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

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Kim, J.J., Kim, J.Y., Suh, H.B. et al. Characterization of breast cancer subtypes based on quantitative assessment of intratumoral heterogeneity using dynamic contrast-enhanced and diffusion-weighted magnetic resonance imaging. Eur Radiol 32, 822–833 (2022). https://doi.org/10.1007/s00330-021-08166-4

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