eprintid: 10105470
rev_number: 16
eprint_status: archive
userid: 608
dir: disk0/10/10/54/70
datestamp: 2020-07-20 11:17:40
lastmod: 2021-09-28 22:09:14
status_changed: 2020-07-20 11:17:40
type: article
metadata_visibility: show
creators_name: Visser, M
creators_name: Petr, J
creators_name: Muller, DMJ
creators_name: Eijgelaar, RS
creators_name: Hendriks, EJ
creators_name: Witte, M
creators_name: Barkhof, F
creators_name: van Herk, M
creators_name: Mutsaerts, HJMM
creators_name: Vrenken, H
creators_name: de Munck, JC
creators_name: Hamer, PCDW
title: Accurate MR Image Registration to Anatomical Reference Space for Diffuse Glioma
ispublished: pub
divisions: UCL
divisions: B02
divisions: C07
divisions: D07
divisions: F82
keywords: glioma, magnetic resonance imaging, image processing, computer-assisted, linear registration, nonlinear registration
note: This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
abstract: 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.
date: 2020-06-05
date_type: published
publisher: FRONTIERS MEDIA SA
official_url: https://doi.org/10.3389/fnins.2020.00585
oa_status: green
full_text_type: pub
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1796519
doi: 10.3389/fnins.2020.00585
lyricists_name: Barkhof, Frederik
lyricists_id: FBARK32
actors_name: Flynn, Bernadette
actors_id: BFFLY94
actors_role: owner
full_text_status: public
publication: Frontiers in Neuroscience |
volume: 14
article_number: 585
pages: 12
issn: 1662-453X
citation:        Visser, M;    Petr, J;    Muller, DMJ;    Eijgelaar, RS;    Hendriks, EJ;    Witte, M;    Barkhof, F;                     ... Hamer, PCDW; + view all <#>        Visser, M;  Petr, J;  Muller, DMJ;  Eijgelaar, RS;  Hendriks, EJ;  Witte, M;  Barkhof, F;  van Herk, M;  Mutsaerts, HJMM;  Vrenken, H;  de Munck, JC;  Hamer, PCDW;   - view fewer <#>    (2020)    Accurate MR Image Registration to Anatomical Reference Space for Diffuse Glioma.                   Frontiers in Neuroscience | , 14     , Article 585.  10.3389/fnins.2020.00585 <https://doi.org/10.3389/fnins.2020.00585>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10105470/1/fnins-14-00585.pdf