Literature DB >> 24787571

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

Bethany L Niell1, Sara C Gavenonis2, Tina Motazedi3, Jessica Cott Chubiz4, Elkan P Halpern4, Elizabeth A Rafferty5, Janie M Lee4.   

Abstract

PURPOSE: Breast MRI is increasingly used for both screening and diagnostic purposes. Although performance benchmarks for screening and diagnostic mammography have been published, performance benchmarks for breast MRI have yet to be established. The purpose of this study was to comprehensively evaluate breast MRI performance measures, stratified by screening and diagnostic indications, from a single academic institution.
METHODS: Institutional review board approval was acquired for this HIPAA-compliant study. Informed consent was not required. Retrospective review of the institutional database identified all breast MRI examinations performed from April 1, 2007, to March 31, 2008. After application of exclusion criteria, the following performance measures for screening and diagnostic indications were calculated: cancer detection rate, positive predictive value (PPV), and abnormal interpretation rates.
RESULTS: The study included 2,444 examinations, 1,313 for screening and 1,131 for diagnostic indications. The cancer detection rates were 14 per 1,000 screening breast MRI examinations and 47 per 1,000 diagnostic examinations (P < .00001). The abnormal interpretation rate was 12% (152 of 1,313) for screening and 17% (194 of 1,131) for diagnostic indications (P = .00008). The PPVs of MRI were lower for screening [PPV1 (abnormal findings) = 12%, PPV2 (biopsy recommended) = 24%, PPV3 (biopsy performed) = 27%] compared with diagnostic indications (PPV1 (abnormal findings) = 28%, PPV2 (biopsy recommended) = 36%, PPV3 (biopsy performed) = 38%].
CONCLUSIONS: Breast MRI performance measures differ significantly between screening and diagnostic MRI indications. Medical audits for breast MRI should calculate performance measures for screening and diagnostic breast MRI separately, as recommended for mammography.
Copyright © 2014 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Audit; abnormal interpretation rate; breast MRI; cancer detection rate; positive predictive value

Mesh:

Substances:

Year:  2014        PMID: 24787571      PMCID: PMC4156888          DOI: 10.1016/j.jacr.2014.02.003

Source DB:  PubMed          Journal:  J Am Coll Radiol        ISSN: 1546-1440            Impact factor:   5.532


  26 in total

1.  The positive predictive value of mammography.

Authors:  D B Kopans
Journal:  AJR Am J Roentgenol       Date:  1992-03       Impact factor: 3.959

2.  Quality assurance. How to audit your own mammography practice.

Authors:  E A Sickles
Journal:  Radiol Clin North Am       Date:  1992-01       Impact factor: 2.303

3.  Updates and revisions to the BI-RADS magnetic resonance imaging lexicon.

Authors:  Sonya D Edwards; Jafi A Lipson; Debra M Ikeda; Janie M Lee
Journal:  Magn Reson Imaging Clin N Am       Date:  2013-05-14       Impact factor: 2.266

4.  MR-guided intervention in women with a family history of breast cancer.

Authors:  P Viehweg; T Bernerth; M Kiechle; J Buchmann; A Heinig; H Koelbl; M Laniado; S H Heywang-Köbrunner
Journal:  Eur J Radiol       Date:  2005-12-20       Impact factor: 3.528

5.  Frequency of malignancy in lesions classified as probably benign after dynamic contrast-enhanced breast MRI examination.

Authors:  Elizabeth A Sadowski; Frederick Kelcz
Journal:  J Magn Reson Imaging       Date:  2005-05       Impact factor: 4.813

Review 6.  The mammography audit: a primer for the mammography quality standards act (MQSA).

Authors:  M N Linver; J R Osuch; R J Brenner; R A Smith
Journal:  AJR Am J Roentgenol       Date:  1995-07       Impact factor: 3.959

7.  Does size matter? Positive predictive value of MRI-detected breast lesions as a function of lesion size.

Authors:  Laura Liberman; Gary Mason; Elizabeth A Morris; D David Dershaw
Journal:  AJR Am J Roentgenol       Date:  2006-02       Impact factor: 3.959

8.  Breast MR imaging screening in 192 women proved or suspected to be carriers of a breast cancer susceptibility gene: preliminary results.

Authors:  C K Kuhl; R K Schmutzler; C C Leutner; A Kempe; E Wardelmann; A Hocke; M Maringa; U Pfeifer; D Krebs; H H Schild
Journal:  Radiology       Date:  2000-04       Impact factor: 11.105

9.  Performance benchmarks for diagnostic mammography.

Authors:  Edward A Sickles; Diana L Miglioretti; Rachel Ballard-Barbash; Berta M Geller; Jessica W T Leung; Robert D Rosenberg; Rebecca Smith-Bindman; Bonnie C Yankaskas
Journal:  Radiology       Date:  2005-06       Impact factor: 11.105

10.  Medical audit of a rapid-throughput mammography screening practice: methodology and results of 27,114 examinations.

Authors:  E A Sickles; S H Ominsky; R A Sollitto; H B Galvin; D L Monticciolo
Journal:  Radiology       Date:  1990-05       Impact factor: 11.105

View more
  8 in total

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

Authors:  Roberta M Strigel; Jennifer Rollenhagen; Elizabeth S Burnside; Mai Elezaby; Amy M Fowler; Frederick Kelcz; Lonie Salkowski; Wendy B DeMartini
Journal:  Acad Radiol       Date:  2016-12-13       Impact factor: 3.173

2.  The Impact of Preoperative Breast MRI on Surgical Management of Women with Newly Diagnosed Ductal Carcinoma In Situ.

Authors:  Diana L Lam; Jacob Smith; Savannah C Partridge; Adrienne Kim; Sara H Javid; Daniel S Hippe; Constance D Lehman; Janie M Lee; Habib Rahbar
Journal:  Acad Radiol       Date:  2019-07-05       Impact factor: 3.173

3.  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

4.  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

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.  Predictive performance of BI-RADS magnetic resonance imaging descriptors in the context of suspicious (category 4) findings.

Authors:  João Ricardo Maltez de Almeida; André Boechat Gomes; Thomas Pitangueiras Barros; Paulo Eduardo Fahel; Mário de Seixas Rocha
Journal:  Radiol Bras       Date:  2016 May-Jun

7.  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 8.  Current State of Breast Cancer Diagnosis, Treatment, and Theranostics.

Authors:  Arya Bhushan; Andrea Gonsalves; Jyothi U Menon
Journal:  Pharmaceutics       Date:  2021-05-14       Impact factor: 6.321

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.