dc.creator | Vassiou K., Fanariotis M., Tsougos I., Fezoulidis I. | en |
dc.date.accessioned | 2023-01-31T10:29:21Z | |
dc.date.available | 2023-01-31T10:29:21Z | |
dc.date.issued | 2022 | |
dc.identifier | 10.1177/02841851211041822 | |
dc.identifier.issn | 02841851 | |
dc.identifier.uri | http://hdl.handle.net/11615/80500 | |
dc.description.abstract | Background: Apparent diffusion coefficient (ADC) measurements are not incorporated in BI-RADS classification. Purpose: To assess the probability of malignancy of breast lesions at magnetic resonance mammography (MRM) at 3 T, by combining ADC measurements with the BI-RADS score, in order to improve the specificity of MRM. Material and Methods: A total of 296 biopsy-proven breast lesions were included in this prospective study. MRM was performed at 3 T, using a standard protocol with dynamic sequence (DCE-MRI) and an extra echo-planar diffusion-weighted sequence. A freehand region of interest was drawn inside the lesion, and ADC values were calculated. Each lesion was categorized according to the BI-RADS classification. Logistic regression analysis was employed to predict the probability of malignancy of a lesion. The model combined the BI-RADS classification and the ADC value. Sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy were calculated. Results: In total, 153 malignant and 143 benign lesions were analyzed; 257 lesions were masses and 39 lesions were non-mass-like enhancements. The sensitivity and specificity of the combined method were 96% and 86%, respectively, in contrast to 95% and 81% with BI-RADS classification alone. Conclusion: We propose a method of assessing the probability of malignancy in breast lesions by combining BI-RADS score and ADC values into a single formula, increasing sensitivity and specificity compared to BI-RADS classification alone. © The Foundation Acta Radiologica 2021. | en |
dc.language.iso | en | en |
dc.source | Acta Radiologica | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85116342183&doi=10.1177%2f02841851211041822&partnerID=40&md5=6b329279fa22e0fb2499e93a79edbd43 | |
dc.subject | Image segmentation | en |
dc.subject | Magnetic resonance imaging | en |
dc.subject | Mammography | en |
dc.subject | Probability | en |
dc.subject | Regression analysis | en |
dc.subject | Apparent diffusion coefficient | en |
dc.subject | BI-RADS | en |
dc.subject | Breast lesion | en |
dc.subject | Breast neoplasm | en |
dc.subject | Coefficient measurement | en |
dc.subject | Coefficient values | en |
dc.subject | Diagnostic algorithms | en |
dc.subject | Diffusion weighted imaging | en |
dc.subject | MR mammography | en |
dc.subject | Sensitivity and specificity | en |
dc.subject | Surface diffusion | en |
dc.subject | contrast medium | en |
dc.subject | algorithm | en |
dc.subject | breast | en |
dc.subject | breast tumor | en |
dc.subject | diagnostic imaging | en |
dc.subject | diffusion weighted imaging | en |
dc.subject | female | en |
dc.subject | human | en |
dc.subject | mammography | en |
dc.subject | nuclear magnetic resonance imaging | en |
dc.subject | pathology | en |
dc.subject | procedures | en |
dc.subject | prospective study | en |
dc.subject | sensitivity and specificity | en |
dc.subject | Algorithms | en |
dc.subject | Breast | en |
dc.subject | Breast Neoplasms | en |
dc.subject | Contrast Media | en |
dc.subject | Diffusion Magnetic Resonance Imaging | en |
dc.subject | Female | en |
dc.subject | Humans | en |
dc.subject | Magnetic Resonance Imaging | en |
dc.subject | Mammography | en |
dc.subject | Prospective Studies | en |
dc.subject | Sensitivity and Specificity | en |
dc.subject | SAGE Publications Inc. | en |
dc.title | Incorporating diffusion-weighted imaging in a diagnostic algorithm for multiparametric MR mammography | en |
dc.type | journalArticle | en |