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

Roberta Fusco; Vincenza Granata; Mauro Mattace Raso; Paolo Vallone; Alessandro Pasquale De Rosa; Claudio Siani; Maurizio Di Bonito; Antonella Petrillo; Mario Sansone

doi:10.3390/cancers13102421

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

Cancers (Basel). 2021 May 17;13(10):2421. doi: 10.3390/cancers13102421.

Authors

Roberta Fusco¹, Vincenza Granata¹, Mauro Mattace Raso¹, Paolo Vallone¹, Alessandro Pasquale De Rosa², Claudio Siani³, Maurizio Di Bonito⁴, Antonella Petrillo¹, Mario Sansone²

Affiliations

¹ Radiology Division, Istituto Nazionale Tumori—IRCCS—Fondazione G. Pascale, 80131 Naples, Italy
² Department Electrical Engineering and Information Technologies, Universita’ Degli Studi DI Napoli Federico II, 80125 Naples, Italy
³ Senology Surgical Division, Istituto Nazionale Tumori—IRCCS—Fondazione G. Pascale, 80131 Naples, Italy
⁴ Pathology Division, Istituto Nazionale Tumori—IRCCS—Fondazione G. Pascale, 80131 Naples, Italy

Abstract

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 K^trans, k^ep, v_e, and v_p 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 (D_p), perfusion fraction (f_p), and tissue diffusivity (D_t)). 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 K^trans, mean value, standard deviation value and Skewness of k_ep, mean value, Skewness and Kurtosis of v_e were obtained and the best AUC among DCE-MRI extracted parameters was reached by the mean value of k_ep 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.

Keywords: BOLD MRI; DCE-MRI; breast cancer; hypoxia; perfusion.