Synopsis

Keywords: Breast, Diffusion/other diffusion imaging techniques

Breast cancer is a heterogeneous tumor, and its treatment is customized determined by the pathologic and tumor molecular features. This study used a continuous-time random-walk (CTRW) diffusion model to characterize prognostic factors status of breast lesions. The parameter β showed significantly differences in ER and PR status and showed significant correlation with ER and PR expression, and the combination of Dm, α, and β produced the best performance in identifying ER and PR status. Our study demonstrated that the CTRW parameters as potential biomarkers were superior to conventional ADC in predicting prognostic factors of breast cancer.

Introduction

Breast cancer is a complex and heterogeneous tumor, and its treatment is extremely customized and frequently determined by the common pathologic characteristics and tumor molecular biomarkers¹.
Previous research had shown that diffusion-weighted imaging (DWI) can improve overall diagnostic accuracy, sensitivity and specificity of breast cancer detection ². However, the diagnostic value of mono-exponential diffusion model was limited by assuming Gaussian diffusion of water molecules and lacking specific parameters to reflect the heterogeneous and complex tumor microenvironment³.
Several studies had proposed that the parameters α and β derived from the continuous-time random-walk (CTRW) diffusion model can reflect the degree of tissue heterogeneity in time and space domains^4-6. Together with parameter Dm, the three parameters can assess different dimensions of complex microstructure and heterogeneity in tumor.
However, the research of the CTRW model in identifying molecular prognostic factors is still rare. Therefore, this study aims to investigate the potential value of CTRW model in determining prognostic factors status of breast lesions and evaluating their relationships.

Methods

MRI acquisition：
Fifty-three breast malignant lesions with different prognostic factors status were enrolled in this study (Table 1). MRI examinations were performed with a 3.0T scanner (uMR 790, United Imaging Healthcare, Shanghai, China) to obtain 16 b-values (0, 10, 20, 30, 50, 70, 100, 150, 200, 400, 800, 1200, 1500, 2000, 2500, 3000 s/mm²) diffusion-weighted imaging (DWI).
Image analysis:
The CTRW model was calculated by the following equation^4,7:
S / S ₀ = E_α [-(bD_m)^β]
where Dm is an anomalous diffusion coefficient, α and β are parameters related to temporal and spatial diffusion heterogeneity, respectively, and Eα is a Mittag-Leffler function.
The apparent diffusion coefficient (ADC) derived from a conventional mono-exponential DWI model was calculated using the following equation:
S / S₀ = e^b*ADC
where S₀ (b-values=0 s/mm²) and S (b-values=400, 800 s/mm²) are the signal intensity in the voxel with different b-values.
Regions of interest (ROIs) were drawn manually on one slice with the largest tumor area (cystic or nec rotic areas were excluded) on diffusion image with b=1200 s/mm². These ROIs were then copied onto the Dm, α, β, and ADC maps.
Stained nuclei indicated positive estrogen receptor (ER) or progesterone receptor (PR) expression in >1% of cancer cells on 10% high-power fields. An immunohistochemical score of 3+ or 2+ with fluorescence in situ hybridization amplification with a ratio ≥2.0 were considered human epidermal growth factor receptor-2 (HER2) positive. High Ki-67 expression was defined tumor with a labeling index >20%.
Statistics:
The CTRW parameters (Dm, α, and β) and ADC were compared among the prognostic factors status by Mann–Whitney U-test. Binary logistic regression and receiver operating characteristic (ROC) curve analysis were used to evaluate the diagnostic performance of the individual ADC or CTRW parameters and their combinations in distinguishing the prognostic factors status. Spearman correlation was used to evaluate the associations between the parameters and various prognostic factors.

Result

The β was significantly higher in ER-negative than ER-positive group (P=0.007) (Table 2, Figure 1). The Dm, ADC were significantly lower and the β was higher in PR-negative than PR-positive group (P=0.011, 0.019, 0.010, respectively) (Figure 1). No significant differences were observed among the parameters in HER2 and Ki67 status (Table 2). For differentiating ER and PR status, the combination of Dm, α, and β produced the highest sensitivity (81.8%, 80.0%, respectively) and the area under the curve (AUC) (0.801 and 0.774, respectively) (Table 3).
Furthermore, the β showed a significantly positive association with Ki67 expression (r=0.275, P=0.046) and a significantly negative correlation with ER and PR expression (r=-0.315, P=0.021 and r=-0.387, P=0.004, respectively), whereas Dm and ADC were negatively correlated with Ki-67 expression (r=-0.299, P=0.030 and r=-0.276, P=0.045) and Dm was positively correlated with PR expression (r=0.295, P=0.032) (Figure 2).

Discussion

This explorative study found that β was significantly lower in the ER-positive and PR-positive group. The β was related to spatial diffusion heterogeneity^4-6, and a higher β indicated that the water molecules diffusion process with more unbalanced steps. Therefore, the lower β meant higher spatiotemporal diffusion heterogeneity in the ER-positive and PR-positive lesions. In addition, the Dm, ADC were higher in the PR-positive group, which is speculated to be related to perfusion contribution and vascularity^6,8.
Furthermore, the combination of Dm, α, and β produced the best performance in identifying ER and PR status. The CTRW parameters represented tissue cellularity and heterogeneity in space and time domains, which indicated that combining CTRW parameters could provide complementary tissue properties in describing complex lesions.
The Ki67 expression was significantly correlated with Dm, ADC, and β. This could be interpreted as the dense cellularity and nuclear enlargement appear in high Ki67 proliferation subgroups, and this active proliferative status leads to restricted diffusion of water molecules.
The parameter β showed the significant correlation with the ER, PR, and Ki67 expression. This may indicate the potential to provide prognostic factors through the parameter β. Therefore, the CTRW model, appeared to provide a more nuanced representation of the microenvironment, with connection to hormonal expression levels⁹.
In conclusion, our findings highlight the CTRW parameters as potential biomarkers are superior to ADC in differentiating and predicting prognostic factors of breast cancer.

Acknowledgements

NO

References

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