Literature DB >> 21769528

BI-RADS categorisation of 2,708 consecutive nonpalpable breast lesions in patients referred to a dedicated breast care unit.

A-S Hamy1, S Giacchetti, M Albiter, C de Bazelaire, C Cuvier, F Perret, S Bonfils, P Charvériat, H Hocini, A de Roquancourt, M Espie.   

Abstract

OBJECTIVES: To determine the malignancy rate of nonpalpable breast lesions, categorised according to the Breast Imaging Reporting and Data System (BI-RADS) classification in the setting of a Breast Care Unit.
METHODS: All nonpalpable breast lesions from consecutive patients referred to a dedicated Breast Care Unit were prospectively reviewed and classified into 5 BI-RADS assessment categories (0, 2, 3, 4, and 5).
RESULTS: A total of 2708 lesions were diagnosed by mammography (71.6%), ultrasound (8.7%), mammography and ultrasound (19.5%), or MRI (0.2%). The distribution of the lesions by BI-RADS category was: 152 in category 0 (5.6%), 56 in category 2 (2.1%), 742 in category 3 (27.4%), 1523 in category 4 (56.2%) and 235 in category 5 (8.7%). Histology revealed 570 malignant lesions (32.9%), 152 high-risk lesions (8.8%), and 1010 benign lesions (58.3%). Malignancy was detected in 17 (2.3%) category 3 lesions, 364 (23.9%) category 4 lesions and 185 (78.7%) category 5 lesions. Median follow-up was 36.9 months.
CONCLUSION: This pragmatic study reflects the assessment and management of breast impalpable abnormalities referred for care to a specialized Breast Unit. Multidisciplinary evaluation with BI-RADS classification accurately predicts malignancy, and reflects the quality of management. This assessment should be encouraged in community practice appraisal.

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Year:  2011        PMID: 21769528     DOI: 10.1007/s00330-011-2201-8

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  41 in total

1.  Breast Imaging Reporting and Data System: inter- and intraobserver variability in feature analysis and final assessment.

Authors:  W A Berg; C Campassi; P Langenberg; M J Sexton
Journal:  AJR Am J Roentgenol       Date:  2000-06       Impact factor: 3.959

2.  The positive predictive value of the breast imaging reporting and data system (BI-RADS) as a method of quality assessment in breast imaging in a hospital population.

Authors:  Harmine M Zonderland; Thomas L Pope; Arend J Nieborg
Journal:  Eur Radiol       Date:  2004-07-09       Impact factor: 5.315

Review 3.  US of breast masses categorized as BI-RADS 3, 4, and 5: pictorial review of factors influencing clinical management.

Authors:  Sughra Raza; Allison L Goldkamp; Sona A Chikarmane; Robyn L Birdwell
Journal:  Radiographics       Date:  2010-09       Impact factor: 5.333

Review 4.  Applications and literature review of the BI-RADS classification.

Authors:  S Obenauer; K P Hermann; E Grabbe
Journal:  Eur Radiol       Date:  2005-01-26       Impact factor: 5.315

5.  BI-RADS lexicon for US and mammography: interobserver variability and positive predictive value.

Authors:  Elizabeth Lazarus; Martha B Mainiero; Barbara Schepps; Susan L Koelliker; Linda S Livingston
Journal:  Radiology       Date:  2006-03-28       Impact factor: 11.105

6.  Diagnostic performance of stereotactic large core needle biopsy for nonpalpable breast lesions in routine clinical practice.

Authors:  Nicky Peters; Lidewij Hoorntje; Willem Mali; Inne Borel Rinkes; Petra Peeters
Journal:  Int J Cancer       Date:  2008-01-15       Impact factor: 7.396

7.  BI-RADS categorization as a predictor of malignancy.

Authors:  S G Orel; N Kay; C Reynolds; D C Sullivan
Journal:  Radiology       Date:  1999-06       Impact factor: 11.105

8.  [Diagnostic value of clustered microcalcifications discovered by mammography (apropos of 227 cases with histological verification and without a palpable breast tumor)].

Authors:  M Le Gal; G Chavanne; D Pellier
Journal:  Bull Cancer       Date:  1984       Impact factor: 1.276

9.  A nomogram to predict for malignant diagnosis of BI-RADS Category 4 breast lesions.

Authors:  Chafika Mazouni; Nour Sneige; Roman Rouzier; Corinne Balleyguier; Therese Bevers; Fabrice André; Philippe Vielh; Suzette Delaloge
Journal:  J Surg Oncol       Date:  2010-09-01       Impact factor: 3.454

10.  The breast imaging reporting and data system: positive predictive value of mammographic features and final assessment categories.

Authors:  L Liberman; A F Abramson; F B Squires; J R Glassman; E A Morris; D D Dershaw
Journal:  AJR Am J Roentgenol       Date:  1998-07       Impact factor: 3.959

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Journal:  Open Access Maced J Med Sci       Date:  2015-05-19

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Authors:  Lucas Delmonico; Vivian Rabello Areias; Rodrigo César Pinto; Cintia Da Silva Matos; Marco Felipe Franco Rosa; Carolina Maria De Azevedo; Gilda Alves
Journal:  Mol Med Rep       Date:  2015-03-05       Impact factor: 2.952

3.  Clinical applications of multiparametric MRI within the prostate cancer diagnostic pathway.

Authors:  Louise Dickinson; Hashim U Ahmed; Clare Allen; Jelle O Barentsz; Brendan Carey; Jurgen J Futterer; Stijn W Heijmink; Peter Hoskin; Alex P Kirkham; Anwar R Padhani; Ch M Raj Persad; Jan van der Meulen; Arnauld Villers; Mark Emberton
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