Literature DB >> 19787181

Breast calcifications: which are malignant?

M Muttarak1, P Kongmebhol, N Sukhamwang.   

Abstract

Most calcifications depicted on mammograms are benign. However, calcifications are important because they can be the first and earliest sign of malignancy. For detection and analysis of microcalcifications, high-quality images and magnification views are required. The American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) classifies calcifications on mammograms into three categories: typical benign, intermediate concern and higher probability of malignancy, according to types and distribution of calcifications. Benign calcifications are typically larger, coarser, round with smooth margins and have a scattered or diffuse distribution. Malignant calcifications are typically grouped or clustered, pleomorphic, fine and with linear branching. It is important for radiologists to detect, evaluate, classify and provide appropriate recommendations for calcifications perceived on mammograms to provide proper management.

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Year:  2009        PMID: 19787181

Source DB:  PubMed          Journal:  Singapore Med J        ISSN: 0037-5675            Impact factor:   1.858


  9 in total

1.  The influence of clinicopathological features on the predictive accuracy of conventional breast imaging in determining the extent of screen-detected high-grade pure ductal carcinoma in situ.

Authors:  L Hayward; R S Oeppen; A V Grima; G T Royle; C M Rubin; R I Cutress
Journal:  Ann R Coll Surg Engl       Date:  2011-07       Impact factor: 1.891

2.  Screening mammogram microcalcification due to basal cell carcinoma of the skin.

Authors:  R S Cooper; E Eade; A P Nisbet; J T Allardice
Journal:  Ann R Coll Surg Engl       Date:  2012-03       Impact factor: 1.891

3.  Detection of breast cancer microcalcification using (99m)Tc-MDP SPECT or Osteosense 750EX FMT imaging.

Authors:  Dayo D Felix; John C Gore; Thomas E Yankeelov; Todd E Peterson; Stephanie Barnes; Jennifer Whisenant; Jared Weis; Sepideh Shoukouhi; John Virostko; Michael Nickels; J Oliver McIntyre; Melinda Sanders; Vandana Abramson; Mohammed N Tantawy
Journal:  Nucl Med Biol       Date:  2014-12-06       Impact factor: 2.408

4.  Discrimination of Breast Cancer with Microcalcifications on Mammography by Deep Learning.

Authors:  Jinhua Wang; Xi Yang; Hongmin Cai; Wanchang Tan; Cangzheng Jin; Li Li
Journal:  Sci Rep       Date:  2016-06-07       Impact factor: 4.379

5.  A Micro CT Study in Patients with Breast Microcalcifications Using a Mathematical Algorithm to Assess 3D Structure.

Authors:  David Kenkel; Zsuzsanna Varga; Heike Heuer; Konstantin J Dedes; Nicole Berger; Lukas Filli; Andreas Boss
Journal:  PLoS One       Date:  2017-01-20       Impact factor: 3.240

Review 6.  Canine mammary tumors as a model for human disease.

Authors:  Somaia M Abdelmegeed; Sulma Mohammed
Journal:  Oncol Lett       Date:  2018-04-02       Impact factor: 2.967

7.  Improved automated early detection of breast cancer based on high resolution 3D micro-CT microcalcification images.

Authors:  Redona Brahimetaj; Inneke Willekens; Annelien Massart; Ramses Forsyth; Jan Cornelis; Johan De Mey; Bart Jansen
Journal:  BMC Cancer       Date:  2022-02-11       Impact factor: 4.430

8.  The predictive value of calcification for the grading of ductal carcinoma in situ in Chinese patients.

Authors:  Jianchun Kong; Xiaomin Liu; Xiaodan Zhang; Yu Zou
Journal:  Medicine (Baltimore)       Date:  2020-07-10       Impact factor: 1.817

9.  Digital zoom of the full-field digital mammogram versus magnification mammography: a systematic review.

Authors:  Mona Øynes; Bergliot Strøm; Bente Tveito; Bjørg Hafslund
Journal:  Eur Radiol       Date:  2020-03-28       Impact factor: 5.315

  9 in total

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