2 research outputs found

    Contrast Enhancement on Cone-Beam Breast-CT for Discrimination of Breast Cancer Immunohistochemical Subtypes

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    PURPOSE: To evaluate whether contrast enhancement on cone-beam breast-CT (CBBCT) could aid in discrimination of breast cancer subtypes and receptor status. METHODS: This study included female patients age >40 years with malignant breast lesions identified on contrast-enhanced CBBCT. Contrast enhancement of malignant breast lesions was standardized to breast fat tissue contrast enhancement. All breast lesions were approved via image-guided biopsy or surgery. Immunohistochemical staining was conducted for expression of estrogen (ER), progesterone (PR), human epidermal growth factor receptor-2 (HER2) and Ki-67 index. Contrast enhancement of breast lesions was correlated with immunohistochemical breast cancer subtypes (Luminal A, Luminal B, HER2 positive, triple negative), receptor status and Ki-67 expression. RESULTS: Highest contrast enhancement was seen for Luminal A lesions (93.6 HU) compared to Luminal B lesions (47.6 HU, P = .002), HER2 positive lesions (83.5 HU, P = .359) and triple negative lesions (45.3 HU, P = .005). Contrast enhancement of HER2 positive lesions was higher than Luminal B lesions (P = .044) and triple negative lesions (P = .039). No significant difference was evident between Luminal B and triple negative lesions (P = .439). Lesions with high Ki-67 index showed lower contrast enhancement than those with low Ki-67 index (P = .0043). ER, PR and HER2 positive lesions demonstrated higher contrast enhancement than their receptor negative counterparts, although differences did not reach statistical significance (P = .1714; P = .3603; P = .2166). CONCLUSIONS: Contrast enhancement of malignant breast lesions on CBBCT correlates with immunohistochemical subtype and proliferative potential. Thereby, CBBCT might aid in selecting individualized treatment strategies for breast cancer patients based on pre-operative imaging

    Acknowledgement to reviewers of social sciences in 2019

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