Consistency of parametric registration in serial MRI studies of brain tumor progression

  • Object The consistency of parametric registration in multi-temporal magnetic resonance (MR) imaging studies was evaluated. Materials and methods Serial MRI scans of adult patients with a brain tumor (glioma) were aligned by parametric registration. The performance of low-order spatial alignment (6/9/12 degrees of freedom) of different 3D serial MR-weighted images is evaluated. A registration protocol for the alignment of all images to one reference coordinate system at baseline is presented. Registration results were evaluated for both, multimodal intra-timepoint and mono-modal multi-temporal registration. The latter case might present a challenge to automatic intensity-based registration algorithms due to ill-defined correspondences. The performance of our algorithm was assessed by testing the inverse registration consistency. Four different similarity measures were evaluated to assess consistency. Results Careful visual inspection suggests that images are well aligned, but their consistency may be imperfect. Sub-voxel inconsistency within the brain was found for allsimilarity measures used for parametric multi-temporal registration. T1-weighted images were most reliable for establishing spatial correspondence between different timepoints. Conclusions The parametric registration algorithm is feasible for use in this application. The sub-voxel resolution mean displacement error of registration transformations demonstrates that the algorithm converges to an almost identical solution for forward and reverse registration.

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Author:Andreas Mang, Julia A. Schnabel, William R. Crum, Marc Modat, Oscar Camara-Rey, Christoph PalmORCiDGND, Gisele Brasil Caseiras, H. Rolf Jäger, Sébastien Ourselin, Thorsten M. BuzugORCiD, David J. Hawkes
Parent Title (English):International Journal of Computer Assisted Radiology and Surgery
Document Type:Article
Year of first Publication:2008
Release Date:2020/01/22
Tag:Parametric serial MR image registration
Inverse registration consistency; Tumor disease progression
GND Keyword:Kernspintomografie; Registrierung <Bildverarbeitung>; Hirntumor
First Page:201
Last Page:211
Institutes:Fakultät Informatik und Mathematik
Fakultät Informatik und Mathematik / Regensburg Medical Image Computing (ReMIC)
Publication:Externe Publikationen
research focus:Lebenswissenschaften und Ethik