A risk stratification algorithm for lesions of uncertain malignant potential diagnosed by vacuum-assisted breast biopsy (VABB) of mammographic microcalcifications.


Journal

European journal of radiology
ISSN: 1872-7727
Titre abrégé: Eur J Radiol
Pays: Ireland
ID NLM: 8106411

Informations de publication

Date de publication:
Feb 2021
Historique:
received: 18 10 2020
revised: 28 11 2020
accepted: 13 12 2020
pubmed: 29 12 2020
medline: 15 4 2021
entrez: 28 12 2020
Statut: ppublish

Résumé

To investigate a risk stratification strategy for lesions of uncertain malignant potential (B3) diagnosed by vacuum-assisted breast biopsy (VABB) of mammographic microcalcifications. Patients who underwent VABB for microcalcification-only lesions with a diagnosis of B3 and subsequent surgery were included in this retrospective, IRB-approved study. Seventy-six B3-lesions (final histology: 66 benign, 10 malignant) were included (Tr). Data on B3 lesion type and presence of atypia, microcalcification characteristics (BI-RADS), removal at biopsy and concomitant lesions were collected. After univariate analysis (Chi-square test), data were combined into a risk stratification algorithm by using a ten-fold, cross-validated Classification and Regression Tree analysis (CRT). The algorithm was tested on a testing dataset (Te) of 23 B3-lesions (six malignant, 17 benign). Malignancy was more frequent in women with a concomitant cancer (P < 0.001) and highly suspicious microcalcifications (P < 0.001). The CRT algorithm retained three characteristics: morphology; presence of atypia; presence of concomitant cancer. The algorithm identified 25/76 (32.9 %,Tr) and 6/23 (26.1 %,Te) lesions at low risk of malignancy. No malignant cases were identified at surgery (0/31). There were 3/76 (3.9 %,Tr) and 1/23 (4.3 %,Te) lesions assigned as high-risk by the algorithm and confirmed at surgery (4/4). In the remaining lesions (48/76, 63.1 %,Tr; 16/23, 69.6 %,Te), malignancy rates varied between 9% and 88.4 %; thus, surgery could not have been avoided. We constructed and tested a risk stratification algorithm for B3 microcalcifications, including clinical, imaging, and pathological features, to assign probabilities of malignancy, which has the potential to reduce unnecessary surgeries.

Identifiants

pubmed: 33370641
pii: S0720-048X(20)30669-0
doi: 10.1016/j.ejrad.2020.109479
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

109479

Informations de copyright

Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.

Auteurs

Paola Clauser (P)

Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, Vienna, Austria.

Panagiotis Kapetas (P)

Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, Vienna, Austria.

Alexander Stöttinger (A)

Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, Vienna, Austria.

Alexander Bumberger (A)

Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, Vienna, Austria.

Margaretha Rudas (M)

Department of Clinical Pathology, Medical University of Vienna, Waehringer Guertel 18-20, Vienna, Austria.

Pascal A T Baltzer (PAT)

Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, Vienna, Austria. Electronic address: pascal.baltzer@meduniwien.ac.at.

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