Abstract
To determine the factors influencing the degree of detectability of lesions and diffusion background signals on magnetic resonance diffusion-weighted imaging (DWI) in invasive breast cancer. Institutional review board approval was obtained and patient consent was waived. Patients with newly diagnosed invasive ductal carcinoma, who underwent preoperative breast magnetic resonance imaging with DWI were included in this study (n = 167). Lesion detectability on DWI and contrast-enhanced subtracted T1-weighted images, the degree of background parenchymal enhancement (BPE), and diffusion background signal were qualitatively rated. Detectability of lesions on DWI was compared with clinicopathological findings including menopausal status, mammographic density, and molecular subtype of breast cancer. Multivariate linear regression analysis was performed to determine variables independently associated with detectability of lesions on DWI and diffusion background signals. Univariate analysis showed that the detectability of lesions on DWI was significantly associated with lesion size (P = 0.001), diffuse background signal (P < 0.0001), and higher detectability scores for contrast-enhanced T1-weighted subtraction images (P = 0.000). The degree of diffusion background signal was significantly affected by age (P < 0.0001), BPE (P < 0.0001), mammographic density (P = 0.002), and menopausal status (P < 0.0001). On multivariate analysis, the diffusion background signal (P < 0.0001) and histologic grade (P < 0.0001) were correlated with the detectability on DWI of invasive breast cancer. Only BPE was correlated with the amount of diffusion background signal on DWI (P < 0.0001). For invasive breast cancers, detectability on DWI was significantly affected by the diffusion background signal. BPE, menopausal status, menstrual cycle, or mammographic density did not show statistically significant correlation with the diffusion detectability of lesions on DWI.
| Original language | English |
|---|---|
| Article number | e4086 |
| Journal | Medicine (United States) |
| Volume | 95 |
| Issue number | 27 |
| DOIs | |
| State | Published - 1 Jul 2016 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- breast cancer
- diffusion background signal
- diffusion-weighted imaging
- lesion detectability
- magnetic resonance imaging
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