Literature DB >> 28660430

Mammographic breast density decreases after bariatric surgery.

Austin D Williams1, Alycia So2, Marie Synnestvedt3, Colleen M Tewksbury2, Despina Kontos4, Meng-Kang Hsiehm4, Lauren Pantalone4, Emily F Conant4, Mitchell Schnall4, Kristoffel Dumon2, Noel Williams2, Julia Tchou5.   

Abstract

PURPOSE: Breast density (BD), an important risk factor for breast cancer, can change over time in some women, but the underlying mechanism is unclear. Very little is known about the impact of surgical weight loss on BD. Our hypothesis is that weight loss after bariatric surgery is associated with a significant and favorable change in mammographic BD.
METHODS: We identified 1097 women 40 years of age or older who underwent gastric bypass or sleeve gastrectomy at our institution from 2010 to 2014. Women who did not have either pre- and post-bariatric surgery mammograms performed at our institution were excluded; 110 had both mammograms and comprised the cohort. Breast density was determined both qualitatively, using reported BI-RADS density, and quantitatively, using the Laboratory for Individualized Breast Radiodensity Assessment.
RESULTS: Qualitative BI-RADS density, quantitative breast area, and percent BD significantly decreased in post-bariatric surgery mammograms (p = 0.009, <0.001, and <0.001, respectively).
CONCLUSIONS: Our retrospective study demonstrated that surgical weight loss was associated with a significant decrease in breast density. Additional studies are warranted to validate our findings and elucidate the molecular mechanisms underlying breast density change after weight loss surgery.

Entities:  

Keywords:  Bariatric surgery; Breast cancer risk; Breast density; Gastric bypass; Mammography; Sleeve gastrectomy

Mesh:

Year:  2017        PMID: 28660430     DOI: 10.1007/s10549-017-4361-y

Source DB:  PubMed          Journal:  Breast Cancer Res Treat        ISSN: 0167-6806            Impact factor:   4.872


  7 in total

1.  Assessment of mammographic breast density after sleeve gastrectomy.

Authors:  Rafael Alvarez; Elika Ridelman; Natalie Rizk; Morgan S White; Chuan Zhou; Heang-Ping Chan; Oliver A Varban; Mark A Helvie; Randy J Seeley
Journal:  Surg Obes Relat Dis       Date:  2018-08-01       Impact factor: 4.734

2.  Evaluation of LIBRA Software for Fully Automated Mammographic Density Assessment in Breast Cancer Risk Prediction.

Authors:  Aimilia Gastounioti; Christine Damases Kasi; Christopher G Scott; Kathleen R Brandt; Matthew R Jensen; Carrie B Hruska; Fang F Wu; Aaron D Norman; Emily F Conant; Stacey J Winham; Karla Kerlikowske; Despina Kontos; Celine M Vachon
Journal:  Radiology       Date:  2020-05-12       Impact factor: 11.105

3.  Breast Cancer Population Attributable Risk Proportions Associated with Body Mass Index and Breast Density by Race/Ethnicity and Menopausal Status.

Authors:  Michael C S Bissell; Karla Kerlikowske; Brian L Sprague; Jeffery A Tice; Charlotte C Gard; Katherine Y Tossas; Garth H Rauscher; Amy Trentham-Dietz; Louise M Henderson; Tracy Onega; Theresa H M Keegan; Diana L Miglioretti
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2020-07-29       Impact factor: 4.254

4.  Deep-LIBRA: An artificial-intelligence method for robust quantification of breast density with independent validation in breast cancer risk assessment.

Authors:  Omid Haji Maghsoudi; Aimilia Gastounioti; Christopher Scott; Lauren Pantalone; Fang-Fang Wu; Eric A Cohen; Stacey Winham; Emily F Conant; Celine Vachon; Despina Kontos
Journal:  Med Image Anal       Date:  2021-07-02       Impact factor: 13.828

Review 5.  Breast Cancer Risk with Progestin Subdermal Implants: A Challenge in Patients Counseling.

Authors:  Ghada Mohammed; Noha A Mousa; Iman M Talaat; Haya Ibrahim; Maha Saber-Ayad
Journal:  Front Endocrinol (Lausanne)       Date:  2021-12-17       Impact factor: 5.555

6.  Factors associated with mammographic breast density among women in Karachi Pakistan.

Authors:  Uzma Shamsi; Shaista Afzal; Azra Shamsi; Iqbal Azam; David Callen
Journal:  BMC Womens Health       Date:  2021-12-31       Impact factor: 2.809

7.  Breast Dense Tissue Segmentation with Noisy Labels: A Hybrid Threshold-Based and Mask-Based Approach.

Authors:  Andrés Larroza; Francisco Javier Pérez-Benito; Juan-Carlos Perez-Cortes; Marta Román; Marina Pollán; Beatriz Pérez-Gómez; Dolores Salas-Trejo; María Casals; Rafael Llobet
Journal:  Diagnostics (Basel)       Date:  2022-07-28
  7 in total

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