Parametric Diffusion Tensor Imaging of the Breast

Abstract

Mapping the diffusion tensor parameters at high spatial resolution provides a potential novel means for dissecting breast architecture. Parametric maps of λ1 and λ1-λ3 facilitate the detection and diagnosis of breast cancer.

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

“…The changes in λ 1 were found to provide the highest contrast to noise ratio 19 . This study included 68 patients with confirmed pathology including 33 patients diagnosed with invasive ductal carcinoma (IDC), 19 with ductal carcinoma in situ (DCIS), 13 with invasive lobular carcinoma (ILC) and 3 with other malignancies.…”

“…More recently, diffusion weighted MRI and the resulting maps of apparent diffusion coefficient (ADC) have been evaluated as a complement method to DCE-MRI and it was shown that ADC values can help distinguish between cancers, benign lesions and normal breast tissue 9,10 . In addition, studies of breast diffusion tensor imaging (DTI) were initiated in healthy volunteers and patients with breast lesions at field strength of 1.5 T [11][12][13][14][15] and of 3 T [16][17][18][19][20][21][22][23][24] . Most of these studies reported ADC and fractional anisotropy (FA) values 11,12,14,15,[20][21][22][23] and found these two parameters to be reproducible with ADC values more reproducible than FA 13,20 .…”

“…The results of these studies indicated that malignant lesions exhibit low ADC values as compared to normal tissue and benign lesions, however, conflicting results were reported on the values and diagnostic capability of FA 11,12,14,[20][21][22][23] . In a set of 3 T-DTI studies the values of the three tensor eigenvalues and eigenvectors in the breast tissue frame were reported as well, and the results were presented in vector maps of the main eigenvector and parametric maps of the eigenvalues, ADC, FA and a maximal anisotropy index [16][17][18][19]24 . In these studies the main diffusion eigenvalue and the maximal anisotropy were shown to serve as the most sensitive independent parameters for the detection and diagnosis of cancer lesions…”

“…1. Here, perform the steps described below using the homebuilt software package written in C++ that was verified by using the programing environment of MATLAB 19 . In general, commercial scanners provide image processing tools for brain DTI experiments that can be adapted for the breast but may not have all the processing functions applied by our homebuilt software package 2.…”

Diffusion tensor imaging of breast lesions: evaluation of apparent diffusion coefficient and fractional anisotropy and tissue cellularity

“…Second, ROI is another influencing factor because of the heterogeneity of the breast tissue. 23,26,27 As for cellularity, tumour cells are not homogeneously distributed in the whole tumour. As is always the case, the ROIs in ADC and FA maps cannot be precisely corresponded to the FOVs for calculating the cellularity in the specimens; it will influence the evaluation of the correlation between ADC, FA and cellularity.…”