Retrospective distortion correction of diffusion tensor imaging data by semi-elastic image fusion – Evaluation by means of anatomical landmarks

Objective: Diffusion tensor imaging (DTI) based on echo-planar imaging (EPI) can suffer from geometric image distortions in comparison to conventional anatomical magnetic resonance imaging (MRI). Therefore, DTI-derived information, such as fiber tractography (FT) used for treatment planning of brain tumors, might be associated with spatial inaccuracies when linearly projected on anatomical MRI. Hence, a non-linear, semi-elastic image fusion shall be evaluated in this study that aims at correcting for image distortions in DTI. Patients and methods: In a sample of 27 patient datasets, 614 anatomical landmark pairs were retrospectively defined in DTI and T1- or T2-weighted three-dimensional (3D) MRI data. The datasets were processed by a commercial software package (Elements Image Fusion .0; Brainlab AG, Munich, Germany) providing rigid and semi-elastic fusion functionalities, such as DTI distortion correction. To quantify the displacement prior to and after semi-elastic fusion, the Euclidian distances of rigidly and elastically fused landmarks were evaluated by means of descriptive statistics and Bland-Altman plot. Results: For rigid and semi-elastic fusion mean target registration errors of 3.03 ± 2.29 mm and 2.04 ± 1.95 mm were found, respectively, with 91% of the evaluated landmarks moving closer to their position determined in T1- or T2-weighted 3D MRI data after distortion correction. Most efficient correction was achieved for non-superficial landmarks showing distortions up to 1 cm. Conclusion: This study indicates that semi-elastic image fusion can be used for retrospective distortion correction of DTI data acquired for image guidance, such as DTI FT as used for a broad range of clinical indications.