Rebound of background parenchymal enhancement post cessation of tamoxifen therapy

2021 ◽  
Author(s):  
Nicole Marie Sakla ◽  
Tej Phatak ◽  
Luke Partyka
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Na Hu ◽  
Jinghao Zhao ◽  
Yong Li ◽  
Quanshui Fu ◽  
Linwei Zhao ◽  
...  

Abstract Background The background parenchymal enhancement at breast magnetic resonance imaging use to predict breast cancer attracts many searchers to draw a possible relationship. However, the results of their relationships were conflicting. This meta-analysis was performed to assess breast cancer frequency associations with background parenchymal enhancement. Methods A systematic literature search up to January 2020 was performed to detect studies recording associations between breast cancer frequency and background parenchymal enhancement. We found thirteen studies including 13,788 women at the start with 4046 breast cancer. We calculated the odds ratio (OR) and the 95% confidence intervals (CIs) between breast cancer frequency and background parenchymal enhancement by the dichotomous technique with a random or fixed-effect model. Results Women with minimal or mild background parenchymal enhancement at breast magnetic resonance imaging did not have any risk of breast cancer compared to control women (OR, 1.20; 95% CI 0.54–2.67). However, high background parenchymal enhancement at breast magnetic resonance imaging (OR, 2.66; 95% CI 1.36–5.19) and moderate (OR, 2.51; 95% CI 1.49–4.21) was associated with a significantly higher rate of breast cancer frequency compared to control women. Conclusions Our meta-analysis showed that the women with high and moderate background parenchymal enhancement at breast magnetic resonance imaging have higher risks, up to 2.66 fold, of breast cancer. We suggest that women with high or moderate background parenchymal enhancement at breast magnetic resonance imaging to be scheduled for more frequent follow-up and screening for breast cancer to avoid any complications.


2012 ◽  
Vol 22 (12) ◽  
pp. 2641-2647 ◽  
Author(s):  
Valencia King ◽  
Yajia Gu ◽  
Jennifer B. Kaplan ◽  
Jennifer D. Brooks ◽  
Malcolm C. Pike ◽  
...  

2020 ◽  
Vol 61 (12) ◽  
pp. 1600-1607
Author(s):  
Roxanna Hellgren ◽  
Ariel Saracco ◽  
Fredrik Strand ◽  
Mikael Eriksson ◽  
Ann Sundbom ◽  
...  

Background Background parenchymal enhancement (BPE) of normal tissue at breast magnetic resonance imaging is suggested to be an independent risk factor for breast cancer. Its association with established risk factors for breast cancer is not fully investigated. Purpose To study the association between BPE and risk factors for breast cancer in a healthy, non-high-risk screening population. Material and Methods We measured BPE and mammographic density and used data from self-reported questionnaires in 214 healthy women aged 43–74 years. We estimated odds ratios for the univariable association between BPE and risk factors. We then fitted an adjusted model using logistic regression to evaluate associations between BPE (high vs. low) and risk factors, including mammographic breast density. Results The majority of women had low BPE (84%). In a multivariable model, we found statistically significant associations between BPE and age ( P = 0.002) and BMI ( P = 0.03). We did find a significant association between systemic progesterone medication and BPE, but due to small numbers, the results should be interpreted with caution. The adjusted odds ratio for high BPE was 3.1 among women with density D (compared to B) and 2.1 for density C (compared to B). However, the association between high BPE and density was not statistically significant. We did not find statistically significant associations with any other risk factors. Conclusion Our study confirmed the known association of BPE with age and BMI. Although our results show a higher likelihood for high BPE with increasing levels of mammographic density, the association was not statistically significant.


Radiology ◽  
2019 ◽  
Vol 292 (3) ◽  
pp. 552-561 ◽  
Author(s):  
Christopher M. Thompson ◽  
Indika Mallawaarachchi ◽  
Durgesh K. Dwivedi ◽  
Anoop P. Ayyappan ◽  
Navkiran K. Shokar ◽  
...  

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