Computerized method for nonrigid MR-to-PET breast-image registration

• Published in: Computers in biology and medicine Vol. 40; no. 1; pp. 37 - 53
• Main Authors: Unlu, M.Z, Krol, A, Magri, A, Mandel, J.A, Lee, W, Baum, K.G, Lipson, E.D, Coman, I.L, Feiglin, D.H
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01-01-2010; Elsevier Limited
• Subjects: Algorithms; Breast - diagnostic imaging; Breast - pathology; Breast cancer; Education; FEM-based soft tissue multimodality nonrigid image registration; Female; Finite Element Analysis; Humans; Image Processing, Computer-Assisted; Imaging, Three-Dimensional; Internal Medicine; Magnetic Resonance Imaging - methods; Mammography; Medical research; Methods; Middle Aged; MR-to-PET nonrigid breast-image registration; Other; Positron-Emission Tomography - methods; Radio frequency; United States > US; MR-to-PET nonrigid breast-image registration; FEM-based soft tissue multimodality nonrigid image registration
• ISSN: 0010-4825; 1879-0534
• DOI: 10.1016/j.compbiomed.2009.10.010

Abstract We have developed and tested a new simple computerized finite element method (FEM) approach to MR-to-PET nonrigid breast-image registration. The method requires five–nine fiducial skin markers (FSMs) visible in MRI and PET that need to be located in the same spots on the breast and two on the flanks during both scans. Patients need to be similarly positioned prone during MRI and PET scans. This is accomplished by means of a low gamma-ray attenuation breast coil replica used as the breast support during the PET scan. We demonstrate that, under such conditions, the observed FSM displacement vectors between MR and PET images, distributed piecewise linearly over the breast volume, produce a deformed FEM mesh that reasonably approximates nonrigid deformation of the breast tissue between the MRI and PET scans. This method, which does not require a biomechanical breast tissue model, is robust and fast. Contrary to other approaches utilizing voxel intensity-based similarity measures or surface matching, our method works for matching MR with pure molecular images (i.e. PET or SPECT only). Our method does not require a good initialization and would not be trapped by local minima during registration process. All processing including FSMs detection and matching, and mesh generation can be fully automated. We tested our method on MR and PET breast images acquired for 15 subjects. The procedure yielded good quality images with an average target registration error below 4 mm (i.e. well below PET spatial resolution of 6–7 mm). Based on the results obtained for 15 subjects studied to date, we conclude that this is a very fast and a well-performing method for MR-to-PET breast-image nonrigid registration. Therefore, it is a promising approach in clinical practice. This method can be easily applied to nonrigid registration of MRI or CT of any type of soft-tissue images to their molecular counterparts such as obtained using PET and SPECT.