In China, no matter in urban or rural areas, breast cancer ranks first in the spectrum of female cancer incidence and top 4 in the spectrum of female cancer death, and is also the most common type of cancer after lung cancer (1). Breast cancer is associated with complex biological behavior, and the classification of molecular subtypes can provide a basis for the formulation of treatment strategies and prognosis assessment for breast cancer patients (2). Perou et al. (3) proposed that expression of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER-2) and antigen identified by monoclonal antibody Ki-67 were the main factors determining the classification of breast cancer, which would guide the strategies for targeted therapy, endocrine therapy, or chemotherapy (4, 5). And efforts to identify molecular subtypes or prognostic factors of breast cancer using preoperative imaging have been ongoing.

Magnetic resonance imaging (MRI) is a non-invasive technique with exceptional soft tissue contrast and can provide anatomical and functional information on both normal and diseased tissues, such as tumors. MRI plays an important role in the diagnosis, treatment and prognosis assessment of breast diseases (6–8). However, traditional MRI can only reflect macroscopic features of a lesion, such as lesion size and morphology (9). Dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI) based imaging biomarkers have been shown to be highly correlated with molecular subtypes and other prognostic and predictive factors in breast cancer (10). For DCE-MRI, due to the enhancement of background parenchyma and partial overlap of the time-intensity curves of benign and malignant lesions, the diagnosis by DCE-MRI is neither specific nor consistent (11). The conventional diffusion-weighted imaging (DWI) along with the derived apparent diffusion coefficient (ADC) has shown important diagnostic value in breast cancer, e.g., for discriminating malignancy. However, there is currently still no uniform standard of using ADC values for predicting the status of different tumor characteristic receptors (12). One of the key reasons may lie in that ADC is a general measurement of restricted diffusion rate that cannot pinpoint the underlying pathology; e.g., the change of cell size, cell density, and intra- or extra-cellular diffusivity (13).

The recently developed microstructural diffusion MRI methods, which captures the restriction of water diffusion at different diffusion length scales by varying diffusion times (td) and b values, have shown unique advantages in delineating cellular microstructures (14–16). In addition to the commonly used pulse gradient spin-echo (PGSE) sequence, which only allows td measurement on the order of tens of milliseconds on most clinical MRI scanners, the oscillating gradient spin-echo (OGSE) technique (15, 17) was usually introduced by microstructural diffusion MRI to achieve shorter td for probing microstructures at smaller scales. By incorporating the microstructural diffusion MRI with specific biophysical models, we can estimate important microstructural properties such as cell size, cell volume fraction, and transcytolemmal water exchange, which are closely related to the pathological changes of tumor (18). Among them, the IMPULSED (imaging microstructural parameters using limited spectrally edited diffusion) method (19) has been comprehensively validated using computer simulations in silico, cells in vitro, and animals in vivo. The MRI data acquisition for the IMPULSED method has also been successfully implemented in patients with breast (20) and prostate cancer (21–23) within clinically feasible scan times (eg, <7 minutes for breast imaging). Changes in cell sizes are typical features for both mitotic arrest (cell swelling) and apoptosis (cell shrinkage), for example, a cell in an early apoptotic stage may have a smaller diameter than a normal cell (22), therefore, measurements of cellular microstructures including cell size may provide a unique means for characterization of breast tumors associated with different kinds of risk factors.

The current study aims to evaluate the efficacy of microstructural mapping by the IMPULSED method in breast tumors, and further to evaluate whether the MRI-derived microstructural properties are associated with and can be used to predict the prognostic factors of breast cancer.

In our study, we used the microstructural diffusion MRI (IMPULSED) to evaluate the microscopic characteristics of breast tumors and found that the microstructural parameters and ADC values showed significant differences between malignant and benign lesions. The microstructural parameters and/or ADC values also showed potential for non-invasive prediction of different prognostic risk factors in breast cancer.

Our results showed that the d _mean , f_in and cellularity index values of malignant lesions were significantly higher than those of benign lesions, and the D_ex and ADCs of malignant lesions were significantly lower than those of benign lesions, which is mostly in agreement with studies by Xu et al. (20) and Wu et al (21). Previous studies have shown that the ADC value is an effective parameter in differentiating benign and malignant breast lesions (27). Malignant tumors usually have lower ADC values than benign lesions due to their high cell density (28, 29), at the same time, the restriction of cell biofilm and the adsorption of macromolecules such as proteins on water molecules are also enhanced. The combined effect of these factors prevents the effective movement of water molecules in malignant tumors, thus reducing the ADC value, consistent with our findings. Lima et al. (30) found that ADC values of breast tumors increased with the shortening of diffusion time (increasing of gradient oscillation frequency) (ADC_PGSE<ADC_OGSE), and all the ADC values (by PGSE and OGSE) of malignant breast tumors were lower than those of benign breast tumors, which is consistent with our study. The combination (AUC = 0.897) of IMPULSED-derived parameters and ADCs by PGSE and OGSE show significant improvement in the diagnostic performance when compared to results by individual parameters (AUC = 0.630-0.753). Compared with benign lesions, the proliferation rate of malignant lesions was faster, the cell density was higher, and the extracellular space was reduced, which explained that d _mean, f _in and cellularity index were higher in malignant lesions than in benign lesions. When distinguishing benign and malignant lesions, our results showed that ADC had the best performance among all the quantitative measurements, followed by the different microstructural features. Wu et al. (21) showed that the cellularity index had an AUC of 0.96 in distinguishing clinically significant from clinically insignificant prostate tumors, which is better than traditional ADC measurements. The lower AUCs of the IMPULSED derived microstructural parameters (compared to ADC) in our study may be related to the complex tissue composition of breast lesions. The advanced and complex model fitting of the IMPULSED method may also suffer from lower image quality and contribute to greater intra-group variation.

In breast cancer, the status of IHC (Immunohistochemistry) tumor receptors determines the subtype of breast cancer and is closely related to the cellular, vascular, and aggressive nature of the tumor (18). HER-2 is a transmembrane tyrosine kinase receptor, and its overexpression in breast cancer is a major factor in tumor progression and metastasis (31, 32). Her2-positive cells have a more malignant phenotype that stimulates excessive cell proliferation, invasion, and metastasis (33). Our research showed that the f_in was significantly lower in the HER-2(+) group compared to its negative counterpart, while the ADC_DWI, ADC_17Hz and ADC_33Hz were significantly higher, which is in line with the previous reports by Catalano et al (34). The positive expression of HER-2 may lead to increased microcirculation perfusion in tumor tissue, and the limited diffusion of water molecules in tissue and increased blood perfusion may jointly affect the ADC value of tumor, resulting in increased ADC value in HER-2 positive tumors. The lower f_in was observed in HER-2(+) than in HER-2(-) tumors, which may be related to the increase of water exchange across the membrane in HER-2-overexpressing breast tumors. Previous studies (35) found that if transmembrane water exchange could not be ignored, the intracellular volume fraction would be essentially underestimated for any biophysical diffusion method that assumes no water exchange (including the IMPLUSE method). Besides, the reduced f _in may also indicate the more presence of necrotic core in HER-2(+) tumors, which is mainly composed of fluid and cell debris with reduced diffusion limitation (36).

ER and PR are hormone receptors that are known to be good prognostic factors, and in the presence of both receptors, treatment is effective for adjuvant or palliative hormone therapy. The cellularity index and f_in were significantly higher in the PR(+) groups compared to their negative counterparts. This is consistent with the results of f _in increase in the PR(+) group in the previous study by BaR et al. (13). The cellularity index is calculated as the quotient of intracellular volume fraction and IMPULSED-derived cell diameter, and thus is proportional to the intracellular volume fraction. Our results also show that the ADC_17Hz value of PR(+) is lower than that of PR(-), which is basically consistent with the previous study by Ba et al. (13), which may be related to the differences in membrane permeability between different PR-expressing tumors. The D_ex was significantly lower in the ER(+) group compared to its negative counterpart. The previous study has reported that ER-positive tumors were highly cellular (37). Animal model studies have also shown that angiogenic markers were inhibited when ER was overexpressed. All of these may result in the reduced D _ex values (38) in ER(+) tumors. The results of this study show that the ADC_17Hz value of ER(+) tumors is lower than that of ER(-) tumors, which may be due to the inhibitory effect of high level of ER expression on the angiogenic pathway of breast cancer (39).

Our study showed no statistical significance in quantitative microstructural diffusion MRI parameters and ADC values between low and high grade histological classification of malignant breast lesions, which is consistent with previous studies demonstrating no direct relationship between cell number and tumor grade (40, 41). Ki-67 index in tumor tissue is currently recognized as a marker of aggressive behavior in breast cancer. The microstructural diffusion MRI parameters and ADC values showed no significant difference between breast tumors with high and low expression of Ki-67. This is consistent with the results in the previous study by BaR, et al (13).

The current study has several limitations. First, although the consistency between IMPULSED-derived parameters and pathological results have been verified in previous studies (13, 20), it is still necessary for the current study to present such verification. However, the original pathological data for patients were unavailable to us, therefore, the related comparison was not presented in this study. Secondly, the number of some pathological type tumors was still relatively small, further investigation in a larger population is needed to verify the results of this study.

In conclusion, we have demonstrated the diagnostic potential of microstructural diffusion MRI based on the IMPULSED method for non-invasive exploration of cellular microstructural features in breast cancer in a clinical setting, and the feasibility of IMPULSED-derived parameters in differentiating breast cancer immunophenotypes. Results showed significant potential of microstructural diffusion MRI in discrimination of breast cancer immunophenotypes including the different expression status of ER, PR and HER-2.