This study was undertaken to correct for motion artifacts in dynamic breast F-18-FDG PET/CT images, to improve
differential-image quality, and to increase accuracy of time-activity curves. Dynamic PET studies, with subjects prone,
and breast suspended freely employed a protocol with 50 frames, each 1-minute long. A 30 s long CT scan was acquired
immediately before the first PET frame. F-18-FDG was administered during the first PET time frame. Fiducial skin
markers (FSMs) each containing ~0.5 &mgr;Ci of Ge-68 were taped to each breast. In our PET/PET registration method we
utilized CT data. For corresponding FSMs visible on the 1st and nth frames, the geometrical centroids of FSMs were
found and their displacement vectors were estimated and used to deform the finite element method (FEM) mesh of the
CT image (registered with 1st PET frame) to match the consecutive dynamic PET time frames. Each mesh was then
deformed to match the 1st PET frame using known FSM displacement vectors as FEM loads, and the warped PET timeframe
volume was created. All PET time frames were thus nonrigidly registered with the first frame. An analogy
between orthogonal components of the displacement field and the temperature distribution in steady-state heat transfer in
solids is used, via standard heat-conduction FEM software with "conductivity" of surface elements set arbitrarily
significantly higher than that of volume elements. Consequently, the surface reaches steady state before the volume. This
prevents creation of concentrated FEM loads at the locations of FSMs and reaching incorrect FEM solution. We observe
improved similarity between the 1st and nth frames. The contrast and the spatial definition of metabolically hyperactive
regions are superior in the registered 3D images compared to unregistered 3D images. Additional work is needed to
eliminate small image artifacts due to FSMs.
We implemented an iterative nonrigid registration algorithm to accurately combine functional (PET) and anatomical (MRI) images in 3D. Our method relies on a Finite Element Method (FEM) and a set of fiducial skin markers (FSM) placed on breast surface. The method is applicable if the stress conditions in the imaged breast are virtually the same in PET and MRI. In the first phase, the displacement vectors of the corresponding FSM observed in MRI and PET are determined, then FEM is used to distribute FSM displacements linearly over the entire breast volume. Our FEM model relies on the analogy between each of the orthogonal components of displacement field, and the temperature distribution field in a steady state heat transfer (SSHT) in solids. The problem can thus be solved via standard heat-conduction FEM software, with arbitrary conductivity of surface elements set much higher than that of volume elements. After determining the displacements at all mesh nodes, moving (MRI) breast volume is registered to target (PET) breast volume using an image-warping algorithm. In the second iteration, to correct for any residual surface and volume misregistration, a refinement process is applied to the moving image, which was already grossly aligned with the target image in 3D using FSM. To perform this process we determine a number of corresponding points on each moving and target image surfaces using a nearest-point approach. Then, after estimating the displacement vectors between the corresponding points on the surfaces we apply our SSHT model again. We tested our model on twelve patients with suspicious breast lesions. By using lesions visible in both PET and MRI, we established that the target registration error is below two PET voxels. The surface registration error is comparable to the spatial resolution of PET.
The objectives of this investigation are to improve quality of subtraction MR breast images and improve accuracy of time-signal intensity curves (TSIC) related to local contrast-agent concentration in dynamic MR mammography. The patients, with up to nine fiducial skin markers (FSMs) taped to each breast, were prone with both breasts suspended into a single well that housed the receiver coil. After a preliminary scan, paramagnetic contrast agent gadopentate digmeglumine (Gd) was delivered intravenously, followed by physiological saline. The field of view was centered over the breasts. We used a gradient recalled echo (GRE) technique for pre-Gd baseline, and five more measurements at 60s intervals. Centroids were determined for corresponding FSMs visible on pre-Gd and any post-Gd images. This was followed by segmentation of breast surfaces in all dynamic-series images, and meshing of all post-Gd breast images. Tetrahedral volume and triangular surface elements were used to construct a finite element method (FEM) model. We used ANSYSTM software and an analogy between orthogonal components of the displacement field and the temperature differences in steady-state heat transfer (SSHT) in solids. The floating images were warped to a fixed image using an appropriate shape function for interpolation from mesh nodes to voxels. To reduce any residual misregistration, we performed surface matching between the previously warped floating image and the target image. Our method of motion correction via nonrigid coregistration yielded excellent differential-image series that clearly revealed lesions not visible in unregistered differential-image series. Further, it produced clinically useful maximum intensity projection (MIP) 3D images.
We implemented a new approach to intramodal non-rigid 3D breast image registration. Our method uses fiducial skin markers (FSM) placed on the breast surface. After determining the displacements of FSM, finite element method (FEM) is used to distribute the markers’ displacements linearly over the entire breast volume using the analogy between the orthogonal components of the displacement field and a steady state heat transfer (SSHT). It is valid because the displacement field in x, y and z direction and a SSHT problem can both be modeled using LaPlace’s equation and the displacements are analogous to temperature differences in SSHT. It can be solved via standard heat conduction FEM software with arbitrary conductivity of surface elements significantly higher than that of volume elements. After determining the displacements of the mesh nodes over the entire breast volume, moving breast volume is registered to target breast volume using an image warping algorithm. Very good quality of the registration was obtained. Following similarity measurements were estimated: Normalized Mutual Information (NMI), Normalized Correlation Coefficient (NCC) and Sum of Absolute Valued Differences (SAVD). We also compared our method with rigid registration technique.