Literature DB >> 10352614

BI-RADS categorization as a predictor of malignancy.

S G Orel1, N Kay, C Reynolds, D C Sullivan.   

Abstract

PURPOSE: To determine the positive predictive value (PPV) of the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) categories 0, 2, 3, 4, and 5 by using BI-RADS terminology and by auditing data on needle localizations.
MATERIALS AND METHODS: Between April 1991 and December 1996, 1,400 mammographically guided needle localizations were performed in 1,109 patients. Information entered into the mammographic database included where the initial mammography was performed (inside vs outside the institution), BI-RADS category, mammographic finding, and histopathologic findings. A recorded recommendation was available for 1,312 localizations in 1,097 patients, who composed the study population.
RESULTS: The 1,312 localizations yielded 449 (34%) cancers (139 [31%] were ductal carcinoma in situ [DCIS]; 310 [69%] were invasive cancers) and 863 (66%) benign lesions. There were 15 (1%) category 0 lesions; the PPV was 13% (two of 15 lesions). There were 50 (4%) category 2 lesions; the PPV was 0% (0 of 40 lesions). There were 141 (11%) category 3 lesions; the PPV was 2% (three of 141 lesions). The three cancers in this group were all non-comedotype DCIS. There were 936 (71%) category 4 lesions; the PPV was 30% (279 of 936 lesions). There were 170 (13%) category 5 lesions; the PPV was 97% (165 of 170 lesions).
CONCLUSION: Placing mammographic lesions into BI-RADS categories is useful for predicting the presence of malignancy. Perhaps, most important, a lesion placed into BI-RADS category 3 is highly predictive of benignity, and short-term interval follow-up as an alternative to biopsy would decrease the number of biopsies performed in benign lesions.

Entities:  

Mesh:

Year:  1999        PMID: 10352614     DOI: 10.1148/radiology.211.3.r99jn31845

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  63 in total

1.  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

2.  External validation of a publicly available computer assisted diagnostic tool for mammographic mass lesions with two high prevalence research datasets.

Authors:  Matthias Benndorf; Elizabeth S Burnside; Christoph Herda; Mathias Langer; Elmar Kotter
Journal:  Med Phys       Date:  2015-08       Impact factor: 4.071

Review 3.  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

4.  [Evaluation of the results after using of the BI-RADS categories in 1,777 clinical mammograms].

Authors:  E A Hauth; K Khan; B Wolfgarten; A Betzler; R Kimmig; M Forsting
Journal:  Radiologe       Date:  2008-03       Impact factor: 0.635

5.  [Diagnostics of microcalcifications from minimally invasive biopsies in mammography screening: results from the prevalence phase].

Authors:  D Hungermann; S Weigel; E Korsching; W Heindel; W Böcker; T Decker
Journal:  Pathologe       Date:  2009-02       Impact factor: 1.011

6.  Automated annotation and classification of BI-RADS assessment from radiology reports.

Authors:  Sergio M Castro; Eugene Tseytlin; Olga Medvedeva; Kevin Mitchell; Shyam Visweswaran; Tanja Bekhuis; Rebecca S Jacobson
Journal:  J Biomed Inform       Date:  2017-04-18       Impact factor: 6.317

7.  Breast cancer risk prediction and mammography biopsy decisions: a model-based study.

Authors:  Katrina Armstrong; Elizabeth A Handorf; Jinbo Chen; Mirar N Bristol Demeter
Journal:  Am J Prev Med       Date:  2013-01       Impact factor: 5.043

8.  Clinical utility of dual-energy contrast-enhanced spectral mammography for breast microcalcifications without associated mass: a preliminary analysis.

Authors:  Yun-Chung Cheung; Hsiu-Pei Tsai; Yung-Feng Lo; Shir-Hwa Ueng; Pei-Chin Huang; Shin-Chih Chen
Journal:  Eur Radiol       Date:  2015-07-10       Impact factor: 5.315

9.  Incidence, detection, and tumour stage of breast cancer in a cohort of Italian women with negative screening mammography report recommending early (short-interval) rescreen.

Authors:  Alessandra Ravaioli; Flavia Foca; Americo Colamartini; Fabio Falcini; Carlo Naldoni; Alba C Finarelli; Priscilla Sassoli de Bianchi; Lauro Bucchi
Journal:  BMC Med       Date:  2010-02-01       Impact factor: 8.775

10.  How to improve your breast cancer program: Standardized reporting using the new American College of Radiology Breast Imaging-Reporting and Data System.

Authors:  Haydee Ojeda-Fournier; Judy Q Nguyen
Journal:  Indian J Radiol Imaging       Date:  2009 Oct-Dec
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.