Abstract: Tracer kinetic models are utilized as temporal constraints for highly under-sampled reconstruction of DCE-MRI data. In one embodiment, a method for improving dynamic contrast enhanced imaging. The method includes steps of administering a magnetic resonance contrast agent to a subject and then collecting magnetic resonance contrast agent from the subject. A tracer kinetic model (i.e. eTofts or Patlak) is selected to be applied to the magnetic resonance imaging data. The tracer kinetic model is applied to the magnetic resonance imaging data. Tracer kinetic maps and dynamic images are simultaneously reconstructed and a consistency constraint is applied. The proposed method allows for easy use of different tracer kinetic models in the formulation and estimation of patient-specific arterial input functions jointly with tracer kinetic maps.

Abstract: For radial sampling in magnetic resonance imaging (MRI), a rescaling factor is determined from k-space data for each coil. The rescale factor is inversely proportional to the streak energy in the k-space data. The k-space data from the coils is rescaled for reconstruction, such as weighting the k-space data by the rescale factor in a data consistency term of iterative reconstruction. The rescale factor is additionally or alternatively used to determine a correction field for correction of intensity bias applied to intensities in the image-object space after reconstruction. These approaches may result in a diagnostically useful bias-corrected image with reduced streak artifact while benefiting from the efficient computation (i.e., computer operates to reconstruct more quickly).

Abstract: Tracer kinetic models are utilized as temporal constraints for highly under-sampled reconstruction of DCE-MRI data. The method is flexible in handling any TK model, does not rely on tuning of regularization parameters, and in comparison to existing compressed sensing approaches, provides robust mapping of TK parameters at high under-sampling rates. In summary, the method greatly improves the robustness and ease-of-use while providing better quality of TK parameter maps than existing methods. In another embodiment, TK parameter maps are directly reconstructed from highly under-sampled DCE-MRI data. This method provides more accurate TK parameter values and higher under-sampling rates. It does not require tuning parameters and there are not additional intermediate steps. The proposed method greatly improves the robustness and ease-of-use while providing better quality of TK parameter maps than conventional indirect methods.

Abstract: For radial sampling in magnetic resonance imaging (MRI), a rescaling factor is determined from k-space data for each coil. The rescale factor is inversely proportional to the streak energy in the k-space data. The k-space data from the coils is rescaled for reconstruction, such as weighting the k-space data by the rescale factor in a data consistency term of iterative reconstruction. The rescale factor is additionally or alternatively used to determine a correction field for correction of intensity bias applied to intensities in the image-object space after reconstruction. These approaches may result in a diagnostically useful bias-corrected image with reduced streak artifact while benefiting from the efficient computation (i.e., computer operates to reconstruct more quickly).

Abstract: Tracer kinetic models are utilized as temporal constraints for highly under-sampled reconstruction of DCE-MRI data. The method is flexible in handling any TK model, does not rely on tuning of regularization parameters, and in comparison to existing compressed sensing approaches, provides robust mapping of TK parameters at high under-sampling rates. In summary, the method greatly improves the robustness and ease-of-use while providing better quality of TK parameter maps than existing methods. In another embodiment, TK parameter maps are directly reconstructed from highly under-sampled DCE-MRI data. This method provides more accurate TK parameter values and higher under-sampling rates. It does not require tuning parameters and there are not additional intermediate steps. The proposed method greatly improves the robustness and ease-of-use while providing better quality of TK parameter maps than conventional indirect methods.

Abstract: Methods and a system to unify reconstruction and motion estimation steps in first pass cardiac perfusion MRI include a global objective function that meets data consistency, spatial smoothness, motion and contrast dynamics constraints. The global objective decomposed into simpler sub-problems which include low pass filtering of a deformed object, TV shrinkage, analytical Fourier replacement and an l2 minimizing problem. A registration tool based on the local cross-correlation similarity measure and enabled to perform both rigid and flexile deformations, is applied. Registration parameters are tuned by rigid, semi rigid and flexible models at different stages of iterations. A system to perform the methods is also disclosed.

Abstract: Methods and a system to unify reconstruction and motion estimation steps in first pass cardiac perfusion MRI include a global objective function that meets data consistency, spatial smoothness, motion and contrast dynamics constraints. The global objective decomposed into simpler sub-problems which include low pass filtering of a deformed object, TV shrinkage, analytical Fourier replacement and an l2 minimizing problem. A registration tool based on the local cross-correlation similarity measure and enabled to perform both rigid and flexile deformations, is applied. Registration parameters are tuned by rigid, semi rigid and flexible models at different stages of iterations. A system to perform the methods is also disclosed.