Abstract

To develop and demonstrate the efficacy of a novel head-and-neck multimodality image registration technique using generative adversarial networks, and show its improvement over traditional direct multimodal registration. 25 head-and-neck patients received MR and CT (CTaligned) scans on the same day with the same immobilization. 19 of the MR-CT pairs were used to train a neural network to generate synthetic CTs from MR images while the registration testing was performed on the remaining 6 patients, who also had a separate CT without immobilization (CTnon-aligned). The CTnon-aligned images exhibited large neck motion. CTnon-aligned’s were deformed to the synthetic CT using b-splines and mutual information, thus effectively becoming a monomodal registration. These results were compared to CTnon-aligned directly registered to MR (multimodal). The same registrations were performed in the opposite direction. Results were evaluated using the mean distance to agreement (MDA) among spinal cord contours, landmark error, and Jacobian determinant of the estimated deformation fields. The cord contours are better matched when a synthetic CT replaces the MR, compared to a direct deformable registration with the MR. At larger initial misalignment (2-15mm MDA), the synthetic CT decreases the MDA by 1 - 10mm and 0.4 - 3mm for MR→CT and CT→MR directions, respectively. The average landmark error decreased from 10.95mm to 6.22mm when going from an MR→CTnon-aligned to a CTsynth→CTnon-aligned deformable registration. In the CT to MR direction, the average landmark error decreased from 8.19mm to 6.71mm when going from a CTnon-aligned→MR to a CTnon-aligned→CTsynth deformable registration. The proposed method demonstrated inverse consistency for both the contour and landmark analysis, while the direct method does not. Additionally, the Jacobian determinant showed feasible expansion and shrinking, with no infeasible space folding (negative values). We showed that using a synthetic CT in lieu of an MR for MR→CT and CT→MR deformable registration offers superior results to direct registration.

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