3D electron density imaging using single scattered x rays with application to breast CT and mammographic screening

Screening mammography is the current standard in detecting breast cancer. However, its fundamental disadvantage is that it projects a 3D object into a 2D image. Small lesions are difficult to detect when superimposed over layers of normal tissue. Commercial Computed Tomography (CT) produces a true 3D image yet has a limited role in mammography due to relatively low resolution and contrast.;This technique has been validated in simulation using data produced by the EGSnrc Monte Carlo code system. At both mammographic and CT energies, a scanning polychromatic pencil beam was used to image breast tissue phantoms containing lesion-like inhomogeneities. The resulting Monte Carlo data is processed using a Nelder-Mead iterative algorithm (MATLAB) to produce the 3D matrix of electron density values. Resulting images have confirmed the ability of the algorithm to detect various 1x1x2.5 mm3 lesions with calcification content as low as 0.5% (p<0.005) at a dose comparable to mammography.;With the intent of enhancing mammography and breast CT, we have developed an algorithm which can produce 3D electron density images using a single projection. Imaging an object with x rays produces a characteristic scattered photon spectrum at the detector plane. A known incident beam spectrum, beam shape, and arbitrary 3D matrix of electron density values enable a theoretical scattered photon distribution to be calculated. An iterative minimization algorithm is used to make changes to the electron density voxel matrix to reduce regular differences between the theoretical and the experimentally measured distributions. The object is characterized by the converged electron density image.