On the accuracy of a mutual information algorithm for PET-MR image registration

Abstract

Image registration has been increasingly used in radiation diagnosis and treatment planning as a means of information integration from different imaging modalities (e.g. MRI, PET, CT). Especially for brain lesions, accurate 3D registration and fusion of MR and PET images can provide comprehensive information about the patient under study by relating functional information from PET images to the detailed anatomical information available in MR images. However, direct PET-MR image fusion in soft tissue is complicated mainly due to the lack of conspicuous anatomical features in PET images. This study describes the implementation and validation of a mutual information registration algorithm for this purpose. Ten patients with brain lesions underwent MR and PET/CT scanning. MR-PET registration was performed a) based on the well validated MR-CT registration technique and copying the transformation to the PET images derived from the PET/CT scan (MR/PET/CT registration method) and b) directly from the MR and PET images without taking into account the CT images (MR/PET registration method). In order to check the registration accuracy of the MR/PET method, the lesion (target) was contoured in the PET images and it was transferred to the MR images using both the above methods. The MR/PET/CT method served as the gold standard for target contouring. Target contours derived by the MR/PET method were compared with the gold standard target contours for each patient and the deviation between the two contours was used to estimate the accuracy of the PET-MR registration method. This deviation was less than 3 mm (i.e. comparable to the imaging voxel of the PET/CT scanning) for 9/10 of the cases studied. Results show that the mutual information algorithm used is able to perform the PET-MR registration reliably and accurately.