Detailed microarchitecture analysis of breast tumors using diffusion tensor imaging

• DOI: 10.1016/j.ejmp.2016.07.142
• Publication Date: 2016-08-27T20:33:56Z
• Authors: M. Bakosis; M. Vlychou; A. Poultsidi; C. Kappas; K. Theodorou; I. Fezoulidis; K. Vassiou; I. Tsougos
• Keywords: Breast MRI; Univariate analysis; Parenchyma

Introduction Conventional breast MRI has shown high diagnostic sensitivities for the detection of breast cancer, whereas relatively low specificities have been reported, resulting in many unnecessary biopsies of benign lesions. Purpose The main purpose of this study was to investigate whether diffusion measures of anisotropy (DWI & DTI) can improve the discrimination between benign and malignant lesions. Moreover, using detailed DTI microstructure analysis, we sought to investigate the contribution of the architecture of breast fibroglandular tissue in the differential diagnosis of malignancy. Methods and materials The study included 58 women with a total of 86 breast lesions. DTI and DWI were performed complementary to dynamic contrast MRI. Apparent diffusion coefficient (ADC), mean diffusivity (MD) and fractional anisotropy (FA) were measured for lesions and contralateral breast parenchyma of each patient. All values were compared between malignant, benign lesions and the normal parenchyma by univariate and multivariate analyses. Results The FA values showed high variation and hence moderate statistical significance. Nevertheless the analysis of DTI vector maps and parametric maps, revealed significantly lower values of the tumor’s orthogonal diffusion coefficients λ1, λ2, λ3 comparing to normal breast and benign tissue. Despite the significant overlap the FA values of malignant tissue were significantly higher than normal and benign tissue (p = 0.002). ROC curve analysis was also performed for every discrimination factor studied. Conclusion ADC measures have accurate discrimination ability in all cases. Careful microstructural analysis revealed significantly lower values of the tumor’s prime diffusion coefficient λ1, and may be used as a potential indicator.