Method and apparatus for ductal tube tracking imaging for breast cancer detection and diagnosis, and product

Apparatus for imaging a human breast to map the breast ductal tree comprising:

• a) means for diffusion tensor imaging of a breast with high spatial resolution;
• b) means for tracking the breast ductal tree using a protocol for breast based on echo-planar imaging (EPI) diffusion designed for optimizing diffusion weightings (b values), number of non-collinear directions for tensor calculations, diffusion, echo and repetition times, spatial resolution, signal to noise, scanning time and a sequence for fat suppression;
• c) means for calculating the diffusion tensor by a non-linear best fit algorithm;
• d) means for diagonalizing with principal component analysis to three eigenvectors and their corresponding eigen values;
• e) means for obtaining a vector field map for tracking of breast ducts of the ductal trees along the direction of the 1st eigenvector v1;
• and
• f) means for displaying the ductal tree on a voxel by voxel basis in parametric images using color coding and vector pointing.

A computer product comprising:

• a computer readable medium stored on non-transitory media and containing programmed instructions for—
• obtaining diffusion tensor imaging of a breast with high spatial resolution to map the breast ductal tree;
• tracking the breast ductal tree using a protocol for breast based on echo-planar imaging (EPI) diffusion designed for optimizing diffusion weightings (b values), number of non-collinear directions for tensor calculations, diffusion, echo and repetition times, spatial resolution, signal to noise, scanning time and a sequence for fat suppression;
• calculating the diffusion tensor by a non-linear best fit algorithm;
• diagonalizing with principal component analysis to three eigenvectors and their corresponding eigen values;
• and
• displaying the ductal tree on a voxel by voxel basis in parametric images using color coding and vector pointing.

A method for imaging the human breast comprising the steps of:

• a) obtaining by high spatial resolution diffusion tensor imaging of a breast or breasts to map breast ductal trees;
• b) tracking breast ductal trees via a first set of algorithms using a protocol for breast based on echo-planar imaging (EPI) diffusion designed for optimizing diffusion weightings (b values), number of non-collinear directions for tensor calculations, diffusion, echo and repetition times, as well as spatial resolution, signal to noise, and scanning time and a sequence for fat suppression;
• c) calculating the diffusion tensor by a non linear best fit algorithm;
• d) diagonalizing with principal component analysis or equivalent algorithm this tensor to three eigenvectors and their corresponding eigen values with a first set of algorithms e) deriving from the eigen values characteristic parameters including, Apparent Diffusion Coefficients and the diffusion anisotropy indices using a dedicated set of algorithms;
• f) using a specific set of algorithm for deriving a vector field map for tracking of breast ducts along the direction of the eigenvector with the largest eigen value representing the largest diffusion;
• and
• g) displaying the ductal tree on a voxel by voxel basis using color coding and vector pointing.

An apparatus for imaging the human breast comprising:

• a) means for obtaining by high spatial resolution diffusion tensor imaging of a breast or breasts to map breast ductal trees;
• b) means for tracking breast ductal trees via a first set of algorithms using a protocol for breast echo-planar imaging (EPI) diffusion designed for optimizing diffusion weightings (b values), number of non-collinear directions for tensor calculations, diffusion, echo and repetition times, as well as spatial resolution, signal to noise, and scanning time and fat suppression sequence;
• c) means for calculating the diffusion tensor using a second set of algorithms;
• d) means for using principal component analysis to diagonalize the diffusion tensor and obtain three eigenvectors and their corresponding eigen values;
• e) means deriving characteristic parameters including, Apparent Diffusion Coefficients and the diffusion anisotropy indices;
• f) means for determining the direction of the principal eigen-vector with largest eigen value presenting the direction of greatest diffusion;
• g) means for deriving a vector field map for tracking of breast ducts along the direction of greatest diffusion;
• and
• h) means for displaying the ductal tree on a voxel by voxel basis using color coding and vector pointing.

A product comprising:

• a computer readable medium stored on non-transitory media and containing programmed instructions for—
• obtaining by high spatial resolution diffusion tensor imaging of breasts to map the breast ductal trees;
• tracking the breast ductal trees via a first set of algorithms using a protocol for breast echo-planar imaging (EPI) diffusion designed for optimizing diffusion weightings (b values), number of non-collinear directions for tensor calculations, diffusion, echo and repetition times, as well as spatial resolution, signal to noise, and scanning time and fat suppression sequence;
• calculating the diffusion tensor using non linear best fit algorithms;
• applying principal component analysis to diagonalize the diffusion tensor and obtain three eigenvectors and their corresponding eigen values to derive characteristic parameters including, Apparent Diffusion Coefficients and the diffusion anisotropy indices;
• deriving a vector field map for tracking of breast ducts along the direction of the principal eigenvector representing greatest diffusion;
• and
• displaying the ductal trees on a voxel by voxel basis using color coding and vector pointing.