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A Score to Predict the Malignancy of a Breast Lesion Based on Different Contrast Enhancement Patterns in Contrast-Enhanced Spectral Mammography.
Nicosia, Luca; Bozzini, Anna Carla; Palma, Simone; Montesano, Marta; Pesapane, Filippo; Ferrari, Federica; Dominelli, Valeria; Rotili, Anna; Meneghetti, Lorenza; Frassoni, Samuele; Bagnardi, Vincenzo; Sangalli, Claudia; Cassano, Enrico.
Afiliação
  • Nicosia L; Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.
  • Bozzini AC; Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.
  • Palma S; University Department of Radiological and Hematological Sciences, Catholic University of the Sacred Heart, Largo Francesco Vito 1, 00168 Rome, Italy.
  • Montesano M; Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.
  • Pesapane F; Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.
  • Ferrari F; Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.
  • Dominelli V; Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.
  • Rotili A; Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.
  • Meneghetti L; Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.
  • Frassoni S; Department of Statistics and Quantitative Methods, University of Milan-Bicocca, 20126 Milan, Italy.
  • Bagnardi V; Department of Statistics and Quantitative Methods, University of Milan-Bicocca, 20126 Milan, Italy.
  • Sangalli C; Data Management, European Institute of Oncology IRCCS, 20141 Milan, Italy.
  • Cassano E; Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.
Cancers (Basel) ; 14(17)2022 Sep 05.
Article em En | MEDLINE | ID: mdl-36077871
ABSTRACT

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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Cancers (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Itália

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Cancers (Basel) Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Itália
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