Accurate MR Image Registration to Anatomical Reference Space for Diffuse Glioma.
computer-assisted
glioma
image processing
linear registration
magnetic resonance imaging
non-linear registration
Journal
Frontiers in neuroscience
ISSN: 1662-4548
Titre abrégé: Front Neurosci
Pays: Switzerland
ID NLM: 101478481
Informations de publication
Date de publication:
2020
2020
Historique:
received:
02
12
2019
accepted:
12
05
2020
entrez:
26
6
2020
pubmed:
26
6
2020
medline:
26
6
2020
Statut:
epublish
Résumé
To summarize the distribution of glioma location within a patient population, registration of individual MR images to anatomical reference space is required. In this study, we quantified the accuracy of MR image registration to anatomical reference space with linear and non-linear transformations using estimated tumor targets of glioblastoma and lower-grade glioma, and anatomical landmarks at pre- and post-operative time-points using six commonly used registration packages (FSL, SPM5, DARTEL, ANTs, Elastix, and NiftyReg). Routine clinical pre- and post-operative, post-contrast T1-weighted images of 20 patients with glioblastoma and 20 with lower-grade glioma were collected. The 2009a Montreal Neurological Institute brain template was used as anatomical reference space. Tumors were manually segmented in the patient space and corresponding healthy tissue was delineated as a target volume in the anatomical reference space. Accuracy of the tumor alignment was quantified using the Dice score and the Hausdorff distance. To measure the accuracy of general brain alignment, anatomical landmarks were placed in patient and in anatomical reference space, and the landmark distance after registration was quantified. Lower-grade gliomas were registered more accurately than glioblastoma. Registration accuracy for pre- and post-operative MR images did not differ. SPM5 and DARTEL registered tumors most accurate, and FSL least accurate. Non-linear transformations resulted in more accurate general brain alignment than linear transformations, but tumor alignment was similar between linear and non-linear transformation. We conclude that linear transformation suffices to summarize glioma locations in anatomical reference space.
Identifiants
pubmed: 32581699
doi: 10.3389/fnins.2020.00585
pmc: PMC7290158
doi:
Types de publication
Journal Article
Langues
eng
Pagination
585Informations de copyright
Copyright © 2020 Visser, Petr, Müller, Eijgelaar, Hendriks, Witte, Barkhof, van Herk, Mutsaerts, Vrenken, de Munck and De Witt Hamer.
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