Literature DB >> 6713115

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

M Le Gal, G Chavanne, D Pellier.   

Abstract

UNLABELLED: Excisions with histological examination were performed in 227 cases of breast microcalcifications without palpable tumor. 99 benign lesions, 27 borderline lesions and 101 carcinomas, 58 of them in situ, were found. Different radiological parameters were studied in relation to histological results: According to the morphology of the calcifications, a classification of 5 types was made. Type 1: annular: 100 per cent were benign lesions. Type 2: regularly punctiform: 22 per cent were malignant lesions. Type 3: too fine for precizing the shape: 40 per cent were malignant lesions. Type 4: irregularly punctiform: 66 per cent were malignant lesions. Type 5: vermicular: 100 per cent of the lesions were malignant. The number of calcifications was higher in carcinomas and 56 per cent of the lesions with more than 30 calcifications were malignant. Close grouping: when there were more than 10 calcifications within a 5 mm diameter area, 57 per cent of malignant lesions were found. Several clusters: 70 per cent were correlated with malignant lesions. Uneven sizes: no signification. LOCATION: the rare retroareolar location correlated with benign lesions in 64 per cent of the cases. Furthermore, the malignant lesions were rare (24%) in women under 40 years of age. For these young women, the authors suggest to directly excise the most suspicious microcalcifications as based on the factors of suspicion and to simply follow the other cases.

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Year:  1984        PMID: 6713115

Source DB:  PubMed          Journal:  Bull Cancer        ISSN: 0007-4551            Impact factor:   1.276


  9 in total

1.  Contrast enhancement in dense breast images to aid clustered microcalcifications detection.

Authors:  Fátima L S Nunes; Homero Schiabel; Claudio E Goes
Journal:  J Digit Imaging       Date:  2007-03       Impact factor: 4.056

2.  An improved method for simulating microcalcifications in digital mammograms.

Authors:  Federica Zanca; Dev Prasad Chakraborty; Chantal Van Ongeval; Jurgen Jacobs; Filip Claus; Guy Marchal; Hilde Bosmans
Journal:  Med Phys       Date:  2008-09       Impact factor: 4.071

3.  Comparison of visual grading and free-response ROC analyses for assessment of image-processing algorithms in digital mammography.

Authors:  F Zanca; C Van Ongeval; F Claus; J Jacobs; R Oyen; H Bosmans
Journal:  Br J Radiol       Date:  2012-07-27       Impact factor: 3.039

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

Authors:  A-S Hamy; S Giacchetti; M Albiter; C de Bazelaire; C Cuvier; F Perret; S Bonfils; P Charvériat; H Hocini; A de Roquancourt; M Espie
Journal:  Eur Radiol       Date:  2011-07-16       Impact factor: 5.315

5.  Different types of microcalcifications observed in breast pathology. Correlations with histopathological diagnosis and radiological examination of operative specimens.

Authors:  L Frappart; I Remy; H C Lin; A Bremond; D Raudrant; B Grousson; J L Vauzelle
Journal:  Virchows Arch A Pathol Anat Histopathol       Date:  1986

6.  "Hippocrates-mst": a prototype for computer-aided microcalcification analysis and risk assessment for breast cancer.

Authors:  George Spyrou; Smaragda Kapsimalakou; Antonis Frigas; Konstantinos Koufopoulos; Stamatios Vassilaros; Panos Ligomenides
Journal:  Med Biol Eng Comput       Date:  2006-10-27       Impact factor: 2.602

Review 7.  A Molecular View of Pathological Microcalcification in Breast Cancer.

Authors:  Tanu Sharma; James A Radosevich; Geeta Pachori; Chandi C Mandal
Journal:  J Mammary Gland Biol Neoplasia       Date:  2016-01-15       Impact factor: 2.673

8.  Radiological, Histological and Chemical Analysis of Breast Microcalcifications: Diagnostic Value and Biological Significance.

Authors:  Rita Bonfiglio; Manuel Scimeca; Nicola Toschi; Chiara Adriana Pistolese; Elena Giannini; Chiara Antonacci; Sara Ciuffa; Virginia Tancredi; Umberto Tarantino; Loredana Albonici; Elena Bonanno
Journal:  J Mammary Gland Biol Neoplasia       Date:  2018-05-09       Impact factor: 2.673

9.  A new approach for clustered MCs classification with sparse features learning and TWSVM.

Authors:  Xin-Sheng Zhang
Journal:  ScientificWorldJournal       Date:  2014-02-09
  9 in total

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