Literature DB >> 21070437

The necrosis sign in magnetic resonance-mammography: diagnostic accuracy in 1,084 histologically verified breast lesions.

Matthias Dietzel1, Pascal A T Baltzer, Tibor Vag, Aimee Herzog, Mieczyslaw Gajda, Oumar Camara, Werner A Kaiser.   

Abstract

Necrosis sign (NS) is a new descriptor for differential diagnosis of breast lesions in magnetic resonance (MR)-mammography (MRM). This study was designed: (a) to analyze diagnostic accuracy of NS in 1,084 histologically verified breast lesions, (b) to assess performance of NS in subgroups. This study was approved by the local ethical committee. All histologically verified lesions having undergone MR-mammography at our institution over 12 years were evaluated by experienced radiologists (> 500 MRM) according to standard protocols and study design (T1w; 0.1 mmol/kg bw gadolinium diethylenetriamine penta-acetic acid; T2-turbo spin echo (TSE)). Patients with history of breast biopsy (surgically, minimal-invasive), radiation- or chemotherapy ≤ 1 year before MRM were excluded. NS was assessed on T2w-TSE sequences and was rated positive if a hyperintense center in a hypointense lesion could be visualized (chi-squared test). One thousand and eighty-four lesions were available for statistical analysis (648: malignant, 436: benign). NS was significantly associated with malignancy (p < 0.001), providing specificity and positive predictive value (PPV) of 96.1% and 78.8%. Malignant lesions > 20 mm presented significantly more often NS (p < 0.001) than neoplasias ≤ 20 mm. There was no difference regarding prevalence of NS in small versus advanced benign lesions (n.s.), leading to better performance of NS in lesions > 20 mm (PPV: 87.8%). Correlation between NS and Grading of invasive carcinomas was significant. In this study of 1,084 lesions necrosis sign was a specific and highly predictive feature for differential diagnosis in MRM (Specificity: 96.1%; PPV: 78.8%). This particularly counts for advanced lesions (PPV 87.8%). As this new descriptor correlates with Grading, it could be used as an initial estimate of patient's prognosis.
© 2010 Wiley Periodicals, Inc.

Entities:  

Mesh:

Year:  2010        PMID: 21070437     DOI: 10.1111/j.1524-4741.2010.00982.x

Source DB:  PubMed          Journal:  Breast J        ISSN: 1075-122X            Impact factor:   2.431


  5 in total

1.  A simple and robust classification tree for differentiation between benign and malignant lesions in MR-mammography.

Authors:  Pascal A T Baltzer; Matthias Dietzel; Werner A Kaiser
Journal:  Eur Radiol       Date:  2013-04-12       Impact factor: 5.315

Review 2.  Tumor necrosis by pretreatment breast MRI: association with neoadjuvant systemic therapy (NAST) response in triple-negative breast cancer (TNBC).

Authors:  Abeer H Abdelhafez; Benjamin C Musall; Wei T Yang; Gaiane M Rauch; Beatriz E Adrada; KennethR Hess; Jong Bum Son; Ken-Pin Hwang; Rosalind P Candelaria; Lumarie Santiago; Gary J Whitman; Huong T Le-Petross; Tanya W Moseley; Elsa Arribas; Deanna L Lane; Marion E Scoggins; Jessica W T Leung; Hagar S Mahmoud; Jason B White; Elizabeth E Ravenberg; Jennifer K Litton; Vicente Valero; Peng Wei; Alastair M Thompson; Stacy L Moulder; Mark D Pagel; Jingfei Ma
Journal:  Breast Cancer Res Treat       Date:  2020-09-13       Impact factor: 4.872

Review 3.  Clinical Breast MR Using MRS or DWI: Who Is the Winner?

Authors:  Francesco Sardanelli; Luca Alessandro Carbonaro; Stefania Montemezzi; Carlo Cavedon; Rubina Manuela Trimboli
Journal:  Front Oncol       Date:  2016-10-28       Impact factor: 6.244

Review 4.  The potential of predictive and prognostic breast MRI (P2-bMRI).

Authors:  Francesco Sardanelli; Pascal A T Baltzer; Matthias Dietzel; Rubina Manuela Trimboli; Moreno Zanardo; Rüdiger Schultz-Wendtland; Michael Uder; Paola Clauser
Journal:  Eur Radiol Exp       Date:  2022-08-22

5.  Automated volumetric radiomic analysis of breast cancer vascularization improves survival prediction in primary breast cancer.

Authors:  Matthias Dietzel; Rüdiger Schulz-Wendtland; Stephan Ellmann; Ramy Zoubi; Evelyn Wenkel; Matthias Hammon; Paola Clauser; Michael Uder; Ingo B Runnebaum; Pascal A T Baltzer
Journal:  Sci Rep       Date:  2020-02-28       Impact factor: 4.379

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.