Sakr, H., Allam, A., Hasan, Z. (2017). Malignant Breast Tumors: Role of MRI in Predicting Histopathological Grading. The Egyptian Journal of Hospital Medicine, 68(2), 1236-1245. doi: 10.12816/0039055
Hossam Moussa Sakr; Allam Elsayed Allam; Zinah Nashee Hasan. "Malignant Breast Tumors: Role of MRI in Predicting Histopathological Grading". The Egyptian Journal of Hospital Medicine, 68, 2, 2017, 1236-1245. doi: 10.12816/0039055
Sakr, H., Allam, A., Hasan, Z. (2017). 'Malignant Breast Tumors: Role of MRI in Predicting Histopathological Grading', The Egyptian Journal of Hospital Medicine, 68(2), pp. 1236-1245. doi: 10.12816/0039055
Sakr, H., Allam, A., Hasan, Z. Malignant Breast Tumors: Role of MRI in Predicting Histopathological Grading. The Egyptian Journal of Hospital Medicine, 2017; 68(2): 1236-1245. doi: 10.12816/0039055
Malignant Breast Tumors: Role of MRI in Predicting Histopathological Grading
Department of Radiodiagnosis, Faculty of Medicine - Ain Shams University, *Thi-Qar University
Abstract
Introduction: Magnetic Resonance Imaging (MRI) is an established supplemental technique to mammography and ultrasonography for evaluation of breast lesions. Diffusion-weighted MR imaging (DWI) has recently been integrated into the standard breast MRI in addition to images obtained from dynamic contrast enhanced MRI. DWI is quantified using the Apparent Diffusion Coefficient (ADC) value which is the measurement of the mean diffusivity of water in tissues along three orthogonal directions. Aim of the Work: The aim of this study was to investigate the relationship between DWI findings (represented by ADC values) and the dynamic contrast enhanced MRI findings (including functional parameters and morphological criteria) with the histopathological grade of malignant breast tumors. Methodology: 25 Patients (age >30 years) were enrolled in this study. All patients were referred either from the screening clinic or the outpatient clinic of Eldemerdash Hospital with clinically suspicious findings and the abnormality was detected by mammography and/or ultrasound. Included masses are those with BI-RADS 5 category on imaging, with no previous biopsy or treatment. There was no knowledge about the histopathological diagnosis at the time of initial evaluation. Exclusion criteria were breast masses with diagnosed or proved benign features. All patients were scheduled for dynamic MRI with diffusion weighted imaging in addition to the conventional MR imaging. Results: Histopathological analysis revealed all 25 lesions to be invasive ductal carcinomas not otherwise specified. Grading of included carcinomas was as follows: 3 lesions (12.0%) were grade I, 14 lesions (56.0%) were grade II and 8 lesions (32.0%) were grade III. Conclusion: That makes DWI the best non-invasive tool available to predict grades of breast carcinoma. However, further larger and more detailed studies are still needed to fully understand the role MR imaging in distinguishing different histological grades of breast cancer.
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