Literature DB >> 27986508

Screening Breast MRI Outcomes in Routine Clinical Practice: Comparison to BI-RADS Benchmarks.

Roberta M Strigel1, Jennifer Rollenhagen2, Elizabeth S Burnside3, Mai Elezaby2, Amy M Fowler4, Frederick Kelcz2, Lonie Salkowski2, Wendy B DeMartini2.   

Abstract

RATIONALE AND
OBJECTIVES: The BI-RADS Atlas 5th Edition includes screening breast magnetic resonance imaging (MRI) outcome benchmarks. However, the metrics are from expert practices and clinical trials of women with hereditary breast cancer predispositions, and it is unknown if they are appropriate for routine practice. We evaluated screening breast MRI audit outcomes in routine practice across a spectrum of elevated risk patients.
MATERIALS AND METHODS: This Institutional Review Board-approved, Health Insurance Portability and Accountability Act-compliant retrospective study included all consecutive screening breast MRI examinations from July 1, 2010 to June 30, 2013. Examination indications were categorized as gene mutation carrier (GMC), personal history (PH) breast cancer, family history (FH) breast cancer, chest radiation, and atypia/lobular carcinoma in situ (LCIS). Outcomes were determined by pathology and/or ≥12 months clinical and/or imaging follow-up. We calculated abnormal interpretation rate (AIR), cancer detection rate (CDR), positive predictive value of recommendation for tissue diagnosis (PPV2) and biopsy performed (PPV3), and median size and percentage of node-negative invasive cancers.
RESULTS: Eight hundred and sixty examinations were performed in 566 patients with a mean age of 47 years. Indications were 367 of 860 (42.7%) FH, 365 of 860 (42.4%) PH, 106 of 860 (12.3%) GMC, 14 of 860 (1.6%) chest radiation, and 8 of 22 (0.9%) atypia/LCIS. The AIR was 134 of 860 (15.6%). Nineteen cancers were identified (13 invasive, 4 DCIS, two lymph nodes), resulting in CDR of 19 of 860 (22.1 per 1000), PPV2 of 19 of 88 (21.6%), and PPV3 of 19 of 80 (23.8%). Of 13 invasive breast cancers, median size was 10 mm, and 8 of 13 were node negative (61.5%).
CONCLUSIONS: Performance outcomes of screening breast MRI in routine clinical practice across a spectrum of elevated risk patients met the American College of Radiology Breast Imaging Reporting and Data System benchmarks, supporting broad application of these metrics. The indication of a personal history of treated breast cancer accounted for a large proportion (42%) of our screening examinations, with breast MRI performance in this population at least comparable to that of other screening indications.
Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Screening breast MRI; benchmarks; outcomes

Mesh:

Year:  2016        PMID: 27986508      PMCID: PMC5339052          DOI: 10.1016/j.acra.2016.10.014

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  27 in total

1.  Mammography, breast ultrasound, and magnetic resonance imaging for surveillance of women at high familial risk for breast cancer.

Authors:  Christiane K Kuhl; Simone Schrading; Claudia C Leutner; Nuschin Morakkabati-Spitz; Eva Wardelmann; Rolf Fimmers; Walther Kuhn; Hans H Schild
Journal:  J Clin Oncol       Date:  2005-11-20       Impact factor: 44.544

2.  Screening magnetic resonance imaging recommendations and outcomes in patients at high risk for breast cancer.

Authors:  Sima Ehsani; Roberta M Strigel; Erica Pettke; Lee Wilke; Amye J Tevaarwerk; Wendy B DeMartini; Kari B Wisinski
Journal:  Breast J       Date:  2015-03-17       Impact factor: 2.431

3.  Screening women at high risk for breast cancer with mammography and magnetic resonance imaging.

Authors:  Constance D Lehman; Jeffrey D Blume; Paul Weatherall; David Thickman; Nola Hylton; Ellen Warner; Etta Pisano; Stuart J Schnitt; Constantine Gatsonis; Mitchell Schnall; Gia A DeAngelis; Paul Stomper; Eric L Rosen; Michael O'Loughlin; Steven Harms; David A Bluemke
Journal:  Cancer       Date:  2005-05-01       Impact factor: 6.860

4.  Auditing a breast MRI practice: performance measures for screening and diagnostic breast MRI.

Authors:  Bethany L Niell; Sara C Gavenonis; Tina Motazedi; Jessica Cott Chubiz; Elkan P Halpern; Elizabeth A Rafferty; Janie M Lee
Journal:  J Am Coll Radiol       Date:  2014-04-29       Impact factor: 5.532

5.  Breast MRI screening of women with a personal history of breast cancer.

Authors:  Sandra Brennan; Laura Liberman; D David Dershaw; Elizabeth Morris
Journal:  AJR Am J Roentgenol       Date:  2010-08       Impact factor: 3.959

6.  Use of breast MRI surveillance in women at high risk for breast cancer: a single-institutional experience.

Authors:  Leisha Elmore; Julie A Margenthaler
Journal:  Ann Surg Oncol       Date:  2010-09-19       Impact factor: 5.344

7.  Screening with magnetic resonance imaging and mammography of a UK population at high familial risk of breast cancer: a prospective multicentre cohort study (MARIBS).

Authors:  M O Leach; C R M Boggis; A K Dixon; D F Easton; R A Eeles; D G R Evans; F J Gilbert; I Griebsch; R J C Hoff; P Kessar; S R Lakhani; S M Moss; A Nerurkar; A R Padhani; L J Pointon; D Thompson; R M L Warren
Journal:  Lancet       Date:  2005 May 21-27       Impact factor: 79.321

8.  Identifying minimally acceptable interpretive performance criteria for screening mammography.

Authors:  Patricia A Carney; Edward A Sickles; Barbara S Monsees; Lawrence W Bassett; R James Brenner; Stephen A Feig; Robert A Smith; Robert D Rosenberg; T Andrew Bogart; Sally Browning; Jane W Barry; Mary M Kelly; Khai A Tran; Diana L Miglioretti
Journal:  Radiology       Date:  2010-05       Impact factor: 11.105

9.  Efficacy of MRI and mammography for breast-cancer screening in women with a familial or genetic predisposition.

Authors:  Mieke Kriege; Cecile T M Brekelmans; Carla Boetes; Peter E Besnard; Harmine M Zonderland; Inge Marie Obdeijn; Radu A Manoliu; Theo Kok; Hans Peterse; Madeleine M A Tilanus-Linthorst; Sara H Muller; Sybren Meijer; Jan C Oosterwijk; Louk V A M Beex; Rob A E M Tollenaar; Harry J de Koning; Emiel J T Rutgers; Jan G M Klijn
Journal:  N Engl J Med       Date:  2004-07-29       Impact factor: 91.245

10.  Surveillance of BRCA1 and BRCA2 mutation carriers with magnetic resonance imaging, ultrasound, mammography, and clinical breast examination.

Authors:  Ellen Warner; Donald B Plewes; Kimberley A Hill; Petrina A Causer; Judit T Zubovits; Roberta A Jong; Margaret R Cutrara; Gerrit DeBoer; Martin J Yaffe; Sandra J Messner; Wendy S Meschino; Cameron A Piron; Steven A Narod
Journal:  JAMA       Date:  2004-09-15       Impact factor: 56.272

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  8 in total

1.  Utility of BI-RADS Assessment Category 4 Subdivisions for Screening Breast MRI.

Authors:  Roberta M Strigel; Elizabeth S Burnside; Mai Elezaby; Amy M Fowler; Frederick Kelcz; Lonie R Salkowski; Wendy B DeMartini
Journal:  AJR Am J Roentgenol       Date:  2017-06       Impact factor: 3.959

Review 2.  Screening MRI in Women at Intermediate Breast Cancer Risk: An Update of the Recent Literature.

Authors:  Manisha Bahl
Journal:  J Breast Imaging       Date:  2022-05-08

3.  Utility of Diffusion-weighted Imaging to Decrease Unnecessary Biopsies Prompted by Breast MRI: A Trial of the ECOG-ACRIN Cancer Research Group (A6702).

Authors:  Habib Rahbar; Zheng Zhang; Thomas L Chenevert; Justin Romanoff; Averi E Kitsch; Lucy G Hanna; Sara M Harvey; Linda Moy; Wendy B DeMartini; Basak Dogan; Wei T Yang; Lilian C Wang; Bonnie N Joe; Karen Y Oh; Colleen H Neal; Elizabeth S McDonald; Mitchell D Schnall; Constance D Lehman; Christopher E Comstock; Savannah C Partridge
Journal:  Clin Cancer Res       Date:  2019-01-15       Impact factor: 12.531

4.  Muscle mass estimation on breast magnetic resonance imaging in breast cancer patients: comparison between psoas muscle area on computer tomography and pectoralis muscle area on MRI.

Authors:  Federica Rossi; Francesca Valdora; Emanuele Barabino; Massimo Calabrese; Alberto Stefano Tagliafico
Journal:  Eur Radiol       Date:  2018-08-07       Impact factor: 5.315

5.  Development and Implementation of an Algorithm to Guide MRI Screening in Patients With a Personal History of Treated Breast Cancer.

Authors:  Roberta M Strigel; Erin Bravo; Amye J Tevaarwerk; Bethany M Anderson; Amy L Stella; Heather B Neuman
Journal:  Clin Breast Cancer       Date:  2020-10-17       Impact factor: 3.225

6.  Diffusion tensor imaging for characterizing tumor microstructure and improving diagnostic performance on breast MRI: a prospective observational study.

Authors:  Jing Luo; Daniel S Hippe; Habib Rahbar; Sana Parsian; Mara H Rendi; Savannah C Partridge
Journal:  Breast Cancer Res       Date:  2019-09-04       Impact factor: 6.466

Review 7.  Contrast-enhanced MRI for breast cancer screening.

Authors:  Ritse M Mann; Christiane K Kuhl; Linda Moy
Journal:  J Magn Reson Imaging       Date:  2019-01-18       Impact factor: 4.813

8.  Availability Versus Utilization of Supplemental Breast Cancer Screening Post Passage of Breast Density Legislation.

Authors:  Mary W Marsh; Thad S Benefield; Sheila Lee; Michael Pritchard; Katie Earnhardt; Robert Agans; Louise M Henderson
Journal:  J Womens Health (Larchmt)       Date:  2020-09-22       Impact factor: 2.681

  8 in total

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