Predicting immunohistochemical expression status and molecular subtypes using synthetic magnetic resonance imaging and multiple multiplexed sensitivity encoding diffusion weighted imaging in breast cancer: a prospective study

To evaluate and compare the performance of synthetic magnetic resonance imaging (SyMRI) and multiple multiplexed sensitivity encoding diffusion weighted imaging (MUSE DWI) in predicting the expression status of immunohistochemistry (IHC) markers and molecular subtypes in patients with breast cancer. This prospective study included patients who underwent breast SyMRI examinations between September 2022 and April 2024, with subsequent pathological confirmation of breast cancer. SyMRI imaging provided pre-contrast and post-contrast T1, T2, and proton density (PD) relaxation times for breast lesions. We subsequently computed the differences and ratios of these relaxation times before and after contrast enhancement, enabling a comparison of the quantitative values. Univariate analysis was then conducted to examine the associations between each parameter and receptor status, proliferation rate, as well as the subtypes of breast cancer, including Luminal, triple-negative breast cancer (TNBC), and human epidermal growth factor receptor 2 (HER2)-enriched categories. We employed multivariate logistic regression analysis for the purposes of feature selection and model development, subsequently constructing a nomogram based on the optimal model. The multivariate analysis revealed that T2-Pre was the sole quantitative parameter associated with TNBC and luminal breast cancer, whereas the apparent diffusion coefficient (ADC) emerged as an independent predictor for the HER2-enriched subtype. When distinguishing molecular subtypes, area under the curve (AUC) of the joint model which combination of quantitative parameter and other parameter showed a relatively higher AUC than any single model. There was a significant difference in AUCs between joint parameters (T2-Pre + histologic grade) and T2-Pre for distinguishing luminal subtype from non-luminal breast cancers, AUC being 0.878 and 0.709, respectively (P = 0.002). No statistically significant difference was observed in AUC between the paired models for distinguishing HER2-enriched subtypes (joint model combining ADC values and histologic grade versus ADC values alone, AUC = 0.824 and AUC = 0.760, respectively; P > 0.05) and TNBC subtypes (joint model combining T2-weighted pre-contrast imaging (T2-Pre) and enhancement versus T2-Pre alone, AUC = 0.854 and AUC = 0.814, respectively; P > 0.05). Quantitative parameters derived from SyMRI and MUSE DWI represent a promising approach for differentiating breast cancer subtypes. However, these findings are preliminary due to sample size limitations and lack of external validation, requiring confirmation in multicenter studies.