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Blood Oxygenation Level Dependent Magnetic Resonance Imaging (MRI), Dynamic Contrast Enhanced MRI, and Diffusion Weighted MRI for Benign and Malignant Breast Cancer Discrimination: A Preliminary Experience.
Fusco, Roberta; Granata, Vincenza; Mattace Raso, Mauro; Vallone, Paolo; De Rosa, Alessandro Pasquale; Siani, Claudio; Di Bonito, Maurizio; Petrillo, Antonella; Sansone, Mario.
Afiliación
  • Fusco R; Radiology Division, Istituto Nazionale Tumori­IRCCS­Fondazione G. Pascale, 80131 Naples, Italy
  • Granata V; Radiology Division, Istituto Nazionale Tumori­IRCCS­Fondazione G. Pascale, 80131 Naples, Italy
  • Mattace Raso M; Radiology Division, Istituto Nazionale Tumori­IRCCS­Fondazione G. Pascale, 80131 Naples, Italy
  • Vallone P; Radiology Division, Istituto Nazionale Tumori­IRCCS­Fondazione G. Pascale, 80131 Naples, Italy
  • De Rosa AP; Department Electrical Engineering and Information Technologies, Universita' Degli Studi DI Napoli Federico II, 80125 Naples, Italy
  • Siani C; Senology Surgical Division, Istituto Nazionale Tumori­IRCCS­Fondazione G. Pascale, 80131 Naples, Italy
  • Di Bonito M; Pathology Division, Istituto Nazionale Tumori­IRCCS­Fondazione G. Pascale, 80131 Naples, Italy
  • Petrillo A; Radiology Division, Istituto Nazionale Tumori­IRCCS­Fondazione G. Pascale, 80131 Naples, Italy
  • Sansone M; Department Electrical Engineering and Information Technologies, Universita' Degli Studi DI Napoli Federico II, 80125 Naples, Italy
Cancers (Basel) ; 13(10)2021 05 17.
Article en En | MEDLINE | ID: mdl-34067721
PURPOSE: To combine blood oxygenation level dependent magnetic resonance imaging (BOLD-MRI), dynamic contrast enhanced MRI (DCE-MRI), and diffusion weighted MRI (DW-MRI) in differentiation of benign and malignant breast lesions. METHODS: Thirty-seven breast lesions (11 benign and 21 malignant lesions) pathologically proven were included in this retrospective preliminary study. Pharmaco-kinetic parameters including Ktrans, kep, ve, and vp were extracted by DCE-MRI; BOLD parameters were estimated by basal signal S0 and the relaxation rate R2*; and diffusion and perfusion parameters were derived by DW-MRI (pseudo-diffusion coefficient (Dp), perfusion fraction (fp), and tissue diffusivity (Dt)). The correlation coefficient, Wilcoxon-Mann-Whitney U-test, and receiver operating characteristic (ROC) analysis were calculated and area under the ROC curve (AUC) was obtained. Moreover, pattern recognition approaches (linear discrimination analysis and decision tree) with balancing technique and leave one out cross validation approach were considered. RESULTS: R2* and D had a significant negative correlation (-0.57). The mean value, standard deviation, Skewness and Kurtosis values of R2* did not show a statistical significance between benign and malignant lesions (p > 0.05) confirmed by the 'poor' diagnostic value of ROC analysis. For DW-MRI derived parameters, the univariate analysis, standard deviation of D, Skewness and Kurtosis values of D* had a significant result to discriminate benign and malignant lesions and the best result at the univariate analysis in the discrimination of benign and malignant lesions was obtained by the Skewness of D* with an AUC of 82.9% (p-value = 0.02). Significant results for the mean value of Ktrans, mean value, standard deviation value and Skewness of kep, mean value, Skewness and Kurtosis of ve were obtained and the best AUC among DCE-MRI extracted parameters was reached by the mean value of kep and was equal to 80.0%. The best diagnostic performance in the discrimination of benign and malignant lesions was obtained at the multivariate analysis considering the DCE-MRI parameters alone with an AUC = 0.91 when the balancing technique was considered. CONCLUSIONS: Our results suggest that the combined use of DCE-MRI, DW-MRI and/or BOLD-MRI does not provide a dramatic improvement compared to the use of DCE-MRI features alone, in the classification of breast lesions. However, an interesting result was the negative correlation between R2* and D.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Cancers (Basel) Año: 2021 Tipo del documento: Article País de afiliación: Italia Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Cancers (Basel) Año: 2021 Tipo del documento: Article País de afiliación: Italia Pais de publicación: Suiza