Clinical validation of the normalized mutual information method for registration of CT and MR images in radiotherapy of brain tumors

Abstract

Image registration integrates information from different imaging modalities and has the potential to improve determination of target volume in radiotherapy planning. This paper describes the implementation and validation of a 3D fully automated registration procedure in the process of radiotherapy treatment planning of brain tumors. Fifteen patients with various brain tumors received computed tomography (CT) and magnetic resonance (MR) brain imaging before the start of radiotherapy. First, the normalized mutual information (NMI) method was used for image registration. Registration accuracy was estimated by performing statistical analysis of coordinate differences between CT and MR anatomical landmarks along the x-, y-and zaxes. Second, a visual validation protocol was developed to validate the quality of individual registration solutions, and this protocol was tested in a series of 36 CT-MR registration procedures with intentionally applied registration errors. The mean coordinate differences between CT and MR landmarks along the x-and y-axes were in general within 0.5 mm. The mean coordinate differences along the z-axis were within 1.0 mm, which is of the same magnitude as the applied slice thickness in scanning. In addition, the detection of intentionally applied registration errors by employment of a standardized visual validation protocol resulted in low false-negative and low false-positive rates. Application of the NMI method for the brain results in excellent automatic registration accuracy, and the method has been incorporated into the daily routine at our institution. A standardized validation protocol ensures the quality of individual registrations by detecting registration errors with high sensitivity and specificity. This protocol is proposed for the validation of other linear registration methods.

Imaging 18F-fluorodeoxy glucose/11C-methionine uptake decoupling for identification of tumor cell infiltration in peritumoral brain edema

“…Registration of the images was confirmed visually. The reported registration error for NMI is less than 1 mm [13]. After image registration was completed, all image sets, including the standard anatomical MR images and PET data, were converted into 256 9 256 9 256 isotropic, 1 9 1 9 1 mm images enabling further voxel-wise analysis of the images (Fig.…”

11C‐methionine uptake and intraoperative 5‐aminolevulinic acid‐induced fluorescence as separate index markers of cell density in glioma

“…The reported registration error of NMI is <1 mm. 21 After image registration was completed, all For stereotactic measurement, mean signal intensity was computed within the ROI with 3 Â 3 voxels in axial images located at the biopsy site (Fig. 1).…”

The influence of MRI scan position on image registration accuracy, target delineation and calculated dose in prostatic radiotherapy

“…It is also important that patients are positioned the same way in MRI as they are for CT. Changes in patient position in MRI can lead to misalignments when registering with CT. The difference in the shape of the MRI table from the CT table is one reason for the misalignment in registration. There have been a number of studies published investigating rigid registration accuracy [17][18][19][20]. Moore et al [17] assessed the registration accuracy of their treatment planning system by outlining structures on a registered phantom.…”

“…Using the position, area and perimeter of each structure and with a coefficient of agreement analysis, the accuracy of the image registration algorithm was determined. Another group [18] used anatomical landmarks to determine the registration accuracy of CT and MRI data sets.…”