Registration Of Magnetic Resonance Imaging Images Research Articles

Computed Tomography–Magnetic Resonance Image Registration in Radiotherapy Treatment Planning

Magnetic resonance imaging (MRI) is being increasingly used in radiotherapy treatment planning (RTP). MRI has the potential to provide improved localisation of target volumes, leading to better tumour control rates and reduced normal tissue complications, due to capabilities including excellent soft-tissue discrimination and the ability to provide scans in which the image contrast is weighted according to different tissue properties. When computed tomography (CT)–MRI image registration is deployed, MR’s advantages are combined with CT’s geometrical security and its ability to provide electron density information. The quality of CT–MRI image registration can be favourably influenced by aspects of scan acquisition, including patient positioning/immobilisation and scan protocols. Appropriate protocols can ameliorate the possible presence of MR spatial distortions and other artefacts, but quality assurance of scanning remains essential. Here, the methods and quality assurance of CT–MR image registration are discussed. Developments in MRI scanner technology are progressively offering advantages for RTP, in terms of the possibility of better matching of patient positioning versus CT in a greater range of anatomical regions, while allowing thinner slices for better image quality in reformatted orthogonal planes.

SU-GG-I-138: Registration and Fusion of MRI and Interventional X-Ray Images Based On External Markers in a XMR Suite

Purpose: To report a method for registration and fusion of 3D magnetic resonance(MR) volume and 2D X‐ray images obtained from a C‐arm mounted flat panel detector. This XMR (X‐ray/MR) technique has been designed as a support for X‐ray guided embolization of venous malformations using pre‐interventional magnetic resonance imaging(MRI).Method and Materials: Registration and fusion are performed through a custom‐made graphical user interface and are based on multimodality external markers. A high resolution MR sequence has been optimized to obtain a precise pre‐interventional localization of the markers. After the localization, a rigid body registration method is implemented, based on one or two X‐ray acquisitions, which can be apply to subsequent images with different C‐arm angulations. The precision of the registration, with respect to the number of markers used, has been evaluated on a phantom and tested off‐line with patients. Results: The computation of registration parameters from one MR volume, two X‐ray images and four external markers on a phantom, is a good example of realistic clinical conditions. For this computation, an excellent registration accuracy is obtained for any subsequent image taken at different C‐arm orientations (0.9±0.6mm). Furthermore, we find that only one X‐ray view is sufficient to reach equivalent accuracy when the registration is performed on images taken at similar C‐arm orientation (0.8±0.6mm). Conclusion: As far as we know, this level of accuracy has never been reported in the literature using a similar registration method. Starting with only two X‐ray acquisitions, this work shows that excellent registration accuracy with an MRI acquisition is possible for any subsequent image taken at different C‐arm angulations. Moreover, we show that when the registration is performed on images taken at about the same C‐arm orientation, one view is definitely enough for an accuracy of approximately 1 mm.

SU-FF-J-122: Deformable Image Registration Using FDG-PET/MRI for Metastatic Breast Cancer Detection

Introduction: Diagnostic imaging techniques using fluoro-deoxy-glucose (FDG) — positron emission tomography (PET) and magnetic resonance imaging (MRI) offer tumor-specific imaging capabilities for breast cancer imaging. Combining PET-MRI systems may provide synergistic information on abnormal soft tissue processes useful for discriminating tumor from other soft tissue abnormalities that may mimic tumor. We propose a deformable image registration method able to align MRI series over an FDG-PET dataset which may improve metastatic for breast cancer imaging. Method: To more precisely replicate presentation of FDG-PET when analyzing FDG-PET/MRI, a deformable registration method was devised to correct locally defined posture changes. To mathematically represent the deformations, we use a BSpline model whose coefficients are iteratively calculated in small steps using a gradient-based optimization algorithm under the guidance of a mutual information metric. The deformable BSpline approach technique was evaluated using checkerboard views and compared to a rigid body registration. Results: Comparison of rigid versus deformable registration of checkerboard FDG-PET and MRI images revealed superior results for deformable registration. The deformable registration was feasible and showed exact anatomical correlation between FDG-PET and MR images in a checkerboard. Increased activity from the FDG-PET scan clearly corresponded to anatomical structures on the MR images. Clinically, the deformable registration of FDG-PET and MRI revealed the complimentary information. Regions of increased FDG activity on PET-CT, which was initially rated as possible tumor disease, were evaluated based on the additional soft tissue information available from the MRI. In one patient case, MRI revealed a benign uterine fibroid which was not definitive on PET-CT. Conclusion: Deformable image registration of PET-CT and MRI using a BSpline algorithm is feasible for metastatic breast cancer detection.

Deformable and rigid registration of MRI and microPET images for photodynamic therapy of cancer in mice

We are investigating imaging techniques to study the tumor response to photodynamic therapy (PDT). Positron emission tomography (PET) can provide physiological and functional information. High-resolution magnetic resonance imaging (MRI) can provide anatomical and morphological changes. Image registration can combine MRI and PET images for improved tumor monitoring. In this study, we acquired high-resolution MRI and microPET 18F-fluorodeoxyglucose (FDG) images from C3H mice with RIF-1 tumors that were treated with Pc 4-based PDT. We developed two registration methods for this application. For registration of the whole mouse body, we used an automatic three-dimensional, normalized mutual information algorithm. For tumor registration, we developed a finite element model (FEM)-based deformable registration scheme. To assess the quality of whole body registration, we performed slice-by-slice review of both image volumes; manually segmented feature organs, such as the left and right kidneys and the bladder, in each slice; and computed the distance between corresponding centroids. Over 40 volume registration experiments were performed with MRI and microPET images. The distance between corresponding centroids of organs was 1.5 +/- 0.4 mm which is about 2 pixels of microPET images. The mean volume overlap ratios for tumors were 94.7% and 86.3% for the deformable and rigid registration methods, respectively. Registration of high-resolution MRI and microPET images combines anatomical and functional information of the tumors and provides a useful tool for evaluating photodynamic therapy.

Measurement of radiotracer concentration in brain gray matter using positron emission tomography: MRI-based correction for partial volume effects.

Accuracy in in vivo quantitation of brain function with positron emission tomography (PET) has often been limited by partial volume effects. This limitation becomes prominent in studies of aging and degenerative brain diseases where partial volume effects vary with different degrees of atrophy. The present study describes how the actual gray matter (GM) tracer concentration can be estimated using an algorithm that relates the regional fraction of GM to partial volume effects. The regional fraction of GM was determined by magnetic resonance imaging (MRI). The procedure is designated as GM PET. In computer simulations and phantom studies, the GM PET algorithm permitted a 100% recovery of the actual tracer concentration in neocortical GM and hippocampus, irrespective of the GM volume. GM PET was applied in a test case of temporal lobe epilepsy revealing an increase in radiotracer activity in GM that was undetected in the PET image before correction for partial volume effects. In computer simulations, errors in the segmentation of GM and errors in registration of PET and MRI images resulted in less than 15% inaccuracy in the GM PET image. In conclusion, GM PET permits accurate determination of the actual radiotracer concentration in human brain GM in vivo. The method differentiates whether a change in the apparent radiotracer concentration reflects solely an alteration in GM volume or rather a change in radiotracer concentration per unit volume of GM.