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Prediction of the Malignancy of a Breast Lesion Detected on Breast Ultrasound: Radiomics Applied to Clinical Practice.
Nicosia, Luca; Pesapane, Filippo; Bozzini, Anna Carla; Latronico, Antuono; Rotili, Anna; Ferrari, Federica; Signorelli, Giulia; Raimondi, Sara; Vignati, Silvano; Gaeta, Aurora; Bellerba, Federica; Origgi, Daniela; De Marco, Paolo; Castiglione Minischetti, Giuseppe; Sangalli, Claudia; Montesano, Marta; Palma, Simone; Cassano, Enrico.
Afiliación
  • Nicosia L; 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.
  • Bozzini AC; Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.
  • Latronico A; 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.
  • Ferrari F; Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.
  • Signorelli G; Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.
  • Raimondi S; Molecular and Pharmaco-Epidemiology Unit, Department of Experimental Oncology, IEO IRCCS, 20141 Milan, Italy.
  • Vignati S; Molecular and Pharmaco-Epidemiology Unit, Department of Experimental Oncology, IEO IRCCS, 20141 Milan, Italy.
  • Gaeta A; Molecular and Pharmaco-Epidemiology Unit, Department of Experimental Oncology, IEO IRCCS, 20141 Milan, Italy.
  • Bellerba F; Molecular and Pharmaco-Epidemiology Unit, Department of Experimental Oncology, IEO IRCCS, 20141 Milan, Italy.
  • Origgi D; Medical Physics Unit, IEO European Institute of Oncology IRCCS, via Ripamonti 435, 20141 Milan, Italy.
  • De Marco P; Medical Physics Unit, IEO European Institute of Oncology IRCCS, via Ripamonti 435, 20141 Milan, Italy.
  • Castiglione Minischetti G; Medical Physics Unit, IEO European Institute of Oncology IRCCS, via Ripamonti 435, 20141 Milan, Italy.
  • Sangalli C; School of Medical Physics, University of Milan, via Celoria 16, 20133 Milan, Italy.
  • Montesano M; Data Management, European Institute of Oncology IRCCS, 20141 Milan, Italy.
  • Palma S; Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.
  • Cassano E; Department of Radiological and Hematological Sciences, Catholic University of the Sacred Heart, Largo Francesco Vito 1, 00168 Rome, Italy.
Cancers (Basel) ; 15(3)2023 Feb 02.
Article en En | MEDLINE | ID: mdl-36765921
ABSTRACT
The study aimed to evaluate the performance of radiomics features and one ultrasound CAD (computer-aided diagnosis) in the prediction of the malignancy of a breast lesion detected with ultrasound and to develop a nomogram incorporating radiomic score and available information on CAD performance, conventional Breast Imaging Reporting and Data System evaluation (BI-RADS), and clinical information. Data on 365 breast lesions referred for breast US with subsequent histologic analysis between January 2020 and March 2022 were retrospectively collected. Patients were randomly divided into a training group (n = 255) and a validation test group (n = 110). A radiomics score was generated from the US image. The CAD was performed in a subgroup of 209 cases. The radiomics score included seven radiomics features selected with the LASSO logistic regression model. The multivariable logistic model incorporating CAD performance, BI-RADS evaluation, clinical information, and radiomic score as covariates showed promising results in the prediction of the malignancy of breast lesions Area under the receiver operating characteristic curve, [AUC] 0.914; 95% Confidence Interval, [CI] 0.876-0.951. A nomogram was developed based on these results for possible future applications in clinical practice.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Cancers (Basel) Año: 2023 Tipo del documento: Article País de afiliación: Italia

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Cancers (Basel) Año: 2023 Tipo del documento: Article País de afiliación: Italia
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