Literature DB >> 30625040

Population-Based Assessment of the Association Between Magnetic Resonance Imaging Background Parenchymal Enhancement and Future Primary Breast Cancer Risk.

Vignesh A Arasu1,2, Diana L Miglioretti3,4, Brian L Sprague5, Nila H Alsheik6, Diana S M Buist4, Louise M Henderson7, Sally D Herschorn5, Janie M Lee8, Tracy Onega9, Garth H Rauscher10, Karen J Wernli4, Constance D Lehman11, Karla Kerlikowske2.   

Abstract

PURPOSE: To evaluate comparative associations of breast magnetic resonance imaging (MRI) background parenchymal enhancement (BPE) and mammographic breast density with subsequent breast cancer risk. PATIENTS AND METHODS: We examined women undergoing breast MRI in the Breast Cancer Surveillance Consortium from 2005 to 2015 (with one exam in 2000) using qualitative BPE assessments of minimal, mild, moderate, or marked. Breast density was assessed on mammography performed within 5 years of MRI. Among women diagnosed with breast cancer, the first BPE assessment was included if it was more than 3 months before their first diagnosis. Breast cancer risk associated with BPE was estimated using Cox proportional hazards regression.
RESULTS: Among 4,247 women, 176 developed breast cancer (invasive, n = 129; ductal carcinoma in situ,n = 47) over a median follow-up time of 2.8 years. More women with cancer had mild, moderate, or marked BPE than women without cancer (80% v 66%, respectively). Compared with minimal BPE, increasing BPE levels were associated with significantly increased cancer risk (mild: hazard ratio [HR], 1.80; 95% CI, 1.12 to 2.87; moderate: HR, 2.42; 95% CI, 1.51 to 3.86; and marked: HR, 3.41; 95% CI, 2.05 to 5.66). Compared with women with minimal BPE and almost entirely fatty or scattered fibroglandular breast density, women with mild, moderate, or marked BPE demonstrated elevated cancer risk if they had almost entirely fatty or scattered fibroglandular breast density (HR, 2.30; 95% CI, 1.19 to 4.46) or heterogeneous or extremely dense breasts (HR, 2.61; 95% CI, 1.44 to 4.72), with no significant interaction (P = .82). Combined mild, moderate, and marked BPE demonstrated significantly increased risk of invasive cancer (HR, 2.73; 95% CI, 1.66 to 4.49) but not ductal carcinoma in situ (HR, 1.48; 95% CI, 0.72 to 3.05).
CONCLUSION: BPE is associated with future invasive breast cancer risk independent of breast density. BPE should be considered for risk prediction models for women undergoing breast MRI.

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Year:  2019        PMID: 30625040      PMCID: PMC6494266          DOI: 10.1200/JCO.18.00378

Source DB:  PubMed          Journal:  J Clin Oncol        ISSN: 0732-183X            Impact factor:   50.717


  41 in total

1.  Metrology Standards for Quantitative Imaging Biomarkers.

Authors:  Daniel C Sullivan; Nancy A Obuchowski; Larry G Kessler; David L Raunig; Constantine Gatsonis; Erich P Huang; Marina Kondratovich; Lisa M McShane; Anthony P Reeves; Daniel P Barboriak; Alexander R Guimaraes; Richard L Wahl
Journal:  Radiology       Date:  2015-08-12       Impact factor: 11.105

2.  Biologic significance of false-positive magnetic resonance imaging enhancement in the setting of ductal carcinoma in situ.

Authors:  Anjali S Kumar; Daniel F Chen; Alfred Au; Yunn-Yi Chen; Jessica Leung; Elisabeth R Garwood; Jessica Gibbs; Nola Hylton; Laura J Esserman
Journal:  Am J Surg       Date:  2006-10       Impact factor: 2.565

Review 3.  The current status of breast MR imaging. Part I. Choice of technique, image interpretation, diagnostic accuracy, and transfer to clinical practice.

Authors:  Christiane Kuhl
Journal:  Radiology       Date:  2007-08       Impact factor: 11.105

4.  Atypical hyperplastic lesions of the female breast. A long-term follow-up study.

Authors:  D L Page; W D Dupont; L W Rogers; M S Rados
Journal:  Cancer       Date:  1985-06-01       Impact factor: 6.860

5.  Breast Density and Benign Breast Disease: Risk Assessment to Identify Women at High Risk of Breast Cancer.

Authors:  Jeffrey A Tice; Diana L Miglioretti; Chin-Shang Li; Celine M Vachon; Charlotte C Gard; Karla Kerlikowske
Journal:  J Clin Oncol       Date:  2015-08-17       Impact factor: 44.544

6.  Breast Cancer Screening in Women at Higher-Than-Average Risk: Recommendations From the ACR.

Authors:  Debra L Monticciolo; Mary S Newell; Linda Moy; Bethany Niell; Barbara Monsees; Edward A Sickles
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7.  Breast stromal enhancement on MRI is associated with response to neoadjuvant chemotherapy.

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8.  Using clinical factors and mammographic breast density to estimate breast cancer risk: development and validation of a new predictive model.

Authors:  Jeffrey A Tice; Steven R Cummings; Rebecca Smith-Bindman; Laura Ichikawa; William E Barlow; Karla Kerlikowske
Journal:  Ann Intern Med       Date:  2008-03-04       Impact factor: 25.391

9.  Patterns of breast magnetic resonance imaging use in community practice.

Authors:  Karen J Wernli; Wendy B DeMartini; Laura Ichikawa; Constance D Lehman; Tracy Onega; Karla Kerlikowske; Louise M Henderson; Berta M Geller; Mike Hofmann; Bonnie C Yankaskas
Journal:  JAMA Intern Med       Date:  2014-01       Impact factor: 21.873

10.  MRI enhancement in stromal tissue surrounding breast tumors: association with recurrence free survival following neoadjuvant chemotherapy.

Authors:  Ella F Jones; Sumedha P Sinha; David C Newitt; Catherine Klifa; John Kornak; Catherine C Park; Nola M Hylton
Journal:  PLoS One       Date:  2013-05-07       Impact factor: 3.240

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  17 in total

Review 1.  Background parenchymal enhancement on breast MRI: A comprehensive review.

Authors:  Geraldine J Liao; Leah C Henze Bancroft; Roberta M Strigel; Rhea D Chitalia; Despina Kontos; Linda Moy; Savannah C Partridge; Habib Rahbar
Journal:  J Magn Reson Imaging       Date:  2019-04-19       Impact factor: 4.813

Review 2.  Clinical Artificial Intelligence Applications: Breast Imaging.

Authors:  Qiyuan Hu; Maryellen L Giger
Journal:  Radiol Clin North Am       Date:  2021-11       Impact factor: 1.947

3.  Impact of short-term low-dose tamoxifen on molecular breast imaging background parenchymal uptake: a pilot study.

Authors:  Carrie B Hruska; Katie N Hunt; Amy Lynn Conners; Jennifer R Geske; Kathleen R Brandt; Amy C Degnim; Celine M Vachon; Michael K O'Connor; Deborah J Rhodes
Journal:  Breast Cancer Res       Date:  2019-03-08       Impact factor: 6.466

4.  Harmonization of Quantitative Parenchymal Enhancement in T1 -Weighted Breast MRI.

Authors:  Bas H M van der Velden; Michael J van Rijssel; Beatrice Lena; Marielle E P Philippens; Claudette E Loo; Max A A Ragusi; Sjoerd G Elias; Elizabeth J Sutton; Elizabeth A Morris; Lambertus W Bartels; Kenneth G A Gilhuijs
Journal:  J Magn Reson Imaging       Date:  2020-06-03       Impact factor: 4.813

5.  3,3-Diindolylmethane (DIM): a nutritional intervention and its impact on breast density in healthy BRCA carriers. A prospective clinical trial.

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Journal:  Carcinogenesis       Date:  2020-10-15       Impact factor: 4.944

6.  Early prediction of neoadjuvant chemotherapy response by exploiting a transfer learning approach on breast DCE-MRIs.

Authors:  Maria Colomba Comes; Annarita Fanizzi; Samantha Bove; Vittorio Didonna; Sergio Diotaiuti; Daniele La Forgia; Agnese Latorre; Eugenio Martinelli; Arianna Mencattini; Annalisa Nardone; Angelo Virgilio Paradiso; Cosmo Maurizio Ressa; Pasquale Tamborra; Vito Lorusso; Raffaella Massafra
Journal:  Sci Rep       Date:  2021-07-08       Impact factor: 4.379

7.  Predictive Value of Breast MRI Background Parenchymal Enhancement for Neoadjuvant Treatment Response among HER2- Patients.

Authors:  Vignesh A Arasu; Paul Kim; Wen Li; Fredrik Strand; Cody McHargue; Roy Harnish; David C Newitt; Ella F Jones; M Maria Glymour; John Kornak; Laura J Esserman; Nola M Hylton
Journal:  J Breast Imaging       Date:  2020-07-22

8.  The association between breast cancer risk factors and background parenchymal enhancement at dynamic contrast-enhanced breast MRI.

Authors:  Roxanna Hellgren; Ariel Saracco; Fredrik Strand; Mikael Eriksson; Ann Sundbom; Per Hall; Paul W Dickman
Journal:  Acta Radiol       Date:  2020-03-26       Impact factor: 1.990

9.  Predicting breast cancer response to neoadjuvant treatment using multi-feature MRI: results from the I-SPY 2 TRIAL.

Authors:  Wen Li; David C Newitt; Jessica Gibbs; Lisa J Wilmes; Ella F Jones; Vignesh A Arasu; Fredrik Strand; Natsuko Onishi; Alex Anh-Tu Nguyen; John Kornak; Bonnie N Joe; Elissa R Price; Haydee Ojeda-Fournier; Mohammad Eghtedari; Kathryn W Zamora; Stefanie A Woodard; Heidi Umphrey; Wanda Bernreuter; Michael Nelson; An Ly Church; Patrick Bolan; Theresa Kuritza; Kathleen Ward; Kevin Morley; Dulcy Wolverton; Kelly Fountain; Dan Lopez-Paniagua; Lara Hardesty; Kathy Brandt; Elizabeth S McDonald; Mark Rosen; Despina Kontos; Hiroyuki Abe; Deepa Sheth; Erin P Crane; Charlotte Dillis; Pulin Sheth; Linda Hovanessian-Larsen; Dae Hee Bang; Bruce Porter; Karen Y Oh; Neda Jafarian; Alina Tudorica; Bethany L Niell; Jennifer Drukteinis; Mary S Newell; Michael A Cohen; Marina Giurescu; Elise Berman; Constance Lehman; Savannah C Partridge; Kimberly A Fitzpatrick; Marisa H Borders; Wei T Yang; Basak Dogan; Sally Goudreau; Thomas Chenevert; Christina Yau; Angela DeMichele; Don Berry; Laura J Esserman; Nola M Hylton
Journal:  NPJ Breast Cancer       Date:  2020-11-27

10.  Comparison of Segmentation Methods in Assessing Background Parenchymal Enhancement as a Biomarker for Response to Neoadjuvant Therapy.

Authors:  Alex Anh-Tu Nguyen; Vignesh A Arasu; Fredrik Strand; Wen Li; Natsuko Onishi; Jessica Gibbs; Ella F Jones; Bonnie N Joe; Laura J Esserman; David C Newitt; Nola M Hylton
Journal:  Tomography       Date:  2020-06
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