A Score to Predict the Malignancy of a Breast Lesion Based on Different Contrast Enhancement Patterns in Contrast-Enhanced Spectral Mammography.

biopsy breast breast carcinoma contrast-enhanced spectral mammography (CESM) score

Journal

Cancers
ISSN: 2072-6694
Titre abrégé: Cancers (Basel)
Pays: Switzerland
ID NLM: 101526829

Informations de publication

Date de publication:
05 Sep 2022
Historique:
received: 27 07 2022
revised: 29 08 2022
accepted: 02 09 2022
entrez: 9 9 2022
pubmed: 10 9 2022
medline: 10 9 2022
Statut: epublish

Résumé

Background: To create a predictive score of malignancy of a breast lesion based on the main contrast enhancement features ascertained by contrast-enhanced spectral mammography (CESM). Methods: In this single-centre prospective study, patients with suspicious breast lesions (BIRADS > 3) were enrolled between January 2013 and February 2022. All participants underwent CESM prior to breast biopsy, and eventually surgery. A radiologist with 20 years’ experience in breast imaging evaluated the presence or absence of enhancement and the following enhancement descriptors: intensity, pattern, margin, and ground glass. A score of 0 or 1 was given for each descriptor, depending on whether the enhancement characteristic was predictive of benignity or malignancy (both in situ and invasive). Then, an overall enhancement score ranging from 0 to 4 was obtained. The histological results were considered the gold standard in the evaluation of the relationship between enhancement patterns and malignancy. Results: A total of 321 women (median age: 51 years; range: 22−83) with 377 suspicious breast lesions were evaluated. Two hundred forty-nine lesions (66%) have malignant histological results (217 invasive and 32 in situ). Considering an overall enhancement score ≥ 2 as predictive of malignancy, we obtain an overall sensitivity of 92.4%; specificity of 89.8%; positive predictive value of 94.7%; and negative predictive value of 85.8%. Conclusions: Our proposed predictive score on the enhancement descriptors of CESM to predict the malignancy of a breast lesion shows excellent results and can help in early breast cancer diagnosis and in avoiding unnecessary biopsies.

Identifiants

pubmed: 36077871
pii: cancers14174337
doi: 10.3390/cancers14174337
pmc: PMC9455061
pii:
doi:

Types de publication

Journal Article

Langues

eng

Références

Breast Cancer Res Treat. 2013 Feb;138(1):137-47
pubmed: 23354364
Radiologia. 2017 Sep - Oct;59(5):368-379
pubmed: 28712528
Radiology. 2004 Aug;232(2):585-91
pubmed: 15205478
J Natl Cancer Inst. 2010 Aug 18;102(16):1224-37
pubmed: 20616353
Diagnostics (Basel). 2021 Sep 08;11(9):
pubmed: 34573983
J Am Coll Radiol. 2010 Jan;7(1):18-27
pubmed: 20129267
Cancers (Basel). 2021 Aug 30;13(17):
pubmed: 34503181
AJR Am J Roentgenol. 2018 Nov;211(5):W267-W274
pubmed: 30240292
Eur Radiol. 2014 Oct;24(10):2394-403
pubmed: 24928280
Br J Radiol. 2017 Jan;90(1069):20160715
pubmed: 27805423
Breast. 2020 Oct;53:8-17
pubmed: 32540554
Radiol Med. 2019 Oct;124(10):1006-1017
pubmed: 31250270
Radiology. 2020 Apr;295(1):52-53
pubmed: 32073379
Eur Radiol. 2015 Oct;25(10):2813-20
pubmed: 25813015
AJR Am J Roentgenol. 2012 Oct;199(4):921-8
pubmed: 22997388
Clin Breast Cancer. 2022 Apr;22(3):e374-e386
pubmed: 34776365
CA Cancer J Clin. 2021 May;71(3):209-249
pubmed: 33538338
Case Rep Oncol. 2019 Sep 25;12(3):728-736
pubmed: 31616281
Eur J Radiol. 2003 Dec;48(3):285-92
pubmed: 14652148
Diagn Interv Imaging. 2017 Feb;98(2):113-123
pubmed: 27687829
JAMA. 2008 May 14;299(18):2151-63
pubmed: 18477782
Cancer. 2020 Jul 1;126(13):2971-2979
pubmed: 32390151
Eur Radiol. 2017 Jul;27(7):2752-2764
pubmed: 27896471
Acta Radiol. 2021 Dec 2;:2841851211060021
pubmed: 34854742
Cancers (Basel). 2022 Jan 12;14(2):
pubmed: 35053533
Medicine (Baltimore). 2020 Sep 11;99(37):e22097
pubmed: 32925753
Med Clin North Am. 2017 Jul;101(4):725-741
pubmed: 28577623
Radiology. 2017 Nov;285(2):389-400
pubmed: 28654337
Sci Rep. 2020 Jun 17;10(1):9807
pubmed: 32555338
Radiologe. 2021 Feb;61(2):177-182
pubmed: 33459811
AJR Am J Roentgenol. 2017 May;208(5):1163-1170
pubmed: 28225643
Eur Radiol. 2011 Mar;21(3):565-74
pubmed: 20839001
Radiology. 2008 Jan;246(1):116-24
pubmed: 18024435
Radiology. 2015 Nov;277(2):527-37
pubmed: 26110667
Br J Radiol. 2018 Jun;91(1086):20170605
pubmed: 29451413
Radiol Clin North Am. 1995 Nov;33(6):1109-21
pubmed: 7480659
Yonago Acta Med. 2015 Jun;58(2):89-93
pubmed: 26306060
Histopathology. 2020 Aug;77(2):181-185
pubmed: 32056259
Breast Cancer Res Treat. 2020 Dec;184(3):723-731
pubmed: 32860166
Eur Radiol. 2019 Apr;29(4):1762-1777
pubmed: 30255244
Radiology. 2006 Nov;241(2):355-65
pubmed: 17057064
Radiology. 2005 Jun;235(3):791-7
pubmed: 15845796
Thorac Cancer. 2020 Jun;11(6):1423-1432
pubmed: 32233072
Eur Radiol. 2015 Dec;25(12):3669-78
pubmed: 26002130
Ann Surg. 2013 Feb;257(2):249-55
pubmed: 23187751
Eur J Cancer. 2010 May;46(8):1296-316
pubmed: 20304629
Radiology. 2013 Mar;266(3):743-51
pubmed: 23220903
Breast Cancer. 2017 Jan;24(1):104-110
pubmed: 26942415

Auteurs

Luca Nicosia (L)

Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.

Anna Carla Bozzini (AC)

Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.

Simone Palma (S)

University Department of Radiological and Hematological Sciences, Catholic University of the Sacred Heart, Largo Francesco Vito 1, 00168 Rome, Italy.

Marta Montesano (M)

Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.

Filippo Pesapane (F)

Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.

Federica Ferrari (F)

Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.

Valeria Dominelli (V)

Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.

Anna Rotili (A)

Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.

Lorenza Meneghetti (L)

Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.

Samuele Frassoni (S)

Department of Statistics and Quantitative Methods, University of Milan-Bicocca, 20126 Milan, Italy.

Vincenzo Bagnardi (V)

Department of Statistics and Quantitative Methods, University of Milan-Bicocca, 20126 Milan, Italy.

Claudia Sangalli (C)

Data Management, European Institute of Oncology IRCCS, 20141 Milan, Italy.

Enrico Cassano (E)

Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.

Classifications MeSH