Distinction of Breast Masses from Benign to Malignant using Magnetic Resonance Imaging and Dynamic Contrast-Enhanced in Tertiary Care Hospitals of Taif, Saudi Arabia: A Retrospective Study

Abstract

Background: Breast cancer is the most frequent cancer among women throughout the world. A range of noninvasive techniques have been employed for early prevention. In health-care practice, however, quality and sensitivity remained critical. Objective: The aim of this study is to see how well Breast Magnetic Resonance Imaging (MRIs) and Dynamic Contrast-Enhanced MRI (DCE-MRI) techniques can detect breast cancer and distinguish between malignant and benign lesions. Methods: A retrospective study was conducted at the Taif Hospitals, Saudi Arabia. The Picture Archiving and Communication System was used to acquire medical records and data from 50 individuals with probable breast cancer, and breast MRI pictures were analyzed. Breast Imaging Reporting and Data System (BI-RADS) radiologist reports and DCE-MRI kinetic curves were evaluated. Excel was also used to test the sensitivity and specificity of breast MRI. Results: According to the BI-RADS results, biopsies, and breast MRI data, 52 percent of 50 patients were categorized as benign, 24 percent as malignant, and 24 percent had no abnormalities. Biopsy revealed that 61.5 percent of the malignant lesions were benign, whereas 38.5 percent were appropriately identified as cancerous. The majority of malignant tumors were discovered in patients over the age of 50. The washout curve correctly identified 60% of the malignant lesions and 40% of the benign lesions. Our data demonstrated the usefulness of MRI in detecting breast cancers by analyzing BI-RADS and utilizing DCE-MRI. False-positive, on the other hand, can lead to unnecessary biopsies. Conclusion: Breast cancer is more common among women of their fifties and beyond. Biopsies, breast MRIs, and kinetic curve analysis can all be utilized to differentiate between benign and malignant breast masses with high sensitivity and specificity.