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Intracranial volume estimated with commonly used methods could introduce bias in studies including brain volume measurements
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Radiology, Oncology and Radiation Science, Radiology.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Radiology, Oncology and Radiation Science, Radiology.
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2013 (English)In: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 83, 355-360 p.Article in journal (Refereed) Published
Abstract [en]

In brain volumetric studies, intracranial volume (ICV) is often used as an estimate of pre-morbid brain size as well as to compensate for inter-subject variations in head size. However, if the estimated ICV is biased by for example gender or atrophy, it could introduce errors in study results. To evaluate how two commonly used methods for ICV estimation perform, computer assisted reference segmentations were created and evaluated. Segmentations were created for 399 MRI volumes from 75-year-old subjects, with 53 of these subjects having an additional scan and segmentation created at age 80. ICV estimates from Statistical Parametric Mapping (SPM, version 8) and Freesurfer (FS, version 5.1.0) were compared to the reference segmentations, and bias related to skull size (approximated with the segmentation measure), gender or atrophy were tested for. The possible ICV related effect on associations between normalized hippocampal volume and factors gender, education and cognition was evaluated by normalizing hippocampal volume with different ICV measures. Excellent agreement was seen for inter- (r=0.999) and intra- (r=0.999) operator reference segmentations. Both SPM and FS overestimated ICV. SPM showed bias associated with gender and atrophy while FS showed bias dependent on skull size. All methods showed good correlation between time points in the longitudinal data (reference: 0.998, SPM: 0.962, FS: 0.995). Hippocampal volume showed different associations with cognition and gender depending on which ICV measure was used for hippocampal volume normalization. These results show that the choice of method used for ICV estimation can bias results in studies including brain volume measurements.

Place, publisher, year, edition, pages
2013. Vol. 83, 355-360 p.
National Category
Radiology, Nuclear Medicine and Medical Imaging Medical Image Processing
Identifiers
URN: urn:nbn:se:uu:diva-207611DOI: 10.1016/j.neuroimage.2013.06.068ISI: 000326953700032PubMedID: 23827332OAI: oai:DiVA.org:uu-207611DiVA: diva2:648874
Available from: 2013-09-17 Created: 2013-09-17 Last updated: 2017-12-06Bibliographically approved
In thesis
1. Analysis of Human Brain MRI: Contributions to Regional Volume Studies
Open this publication in new window or tab >>Analysis of Human Brain MRI: Contributions to Regional Volume Studies
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Many disorders are associated with regional brain volumes. The analysis of these volumes from MR images often requires sequential processing steps such as localization and delineation. It is common to perform volumetric normalization using intracranial volume (ICV, the total volume inside the cranial cavity) when comparing regional brain volumes, since head size varies considerably between individuals. Multiple methods for estimating ICV and procedures for volume normalization exist.

A method for interhemispheric surface localization and extraction, using both intensity and symmetry information and without time consuming pre-processing, was developed. Evaluations of hemisphere division accuracy as well as suitability as a pre-processing step for interhemispheric structure localization were made. The performance of the method was comparable to that of methods focusing on either of these tasks, making it suited for use in many different studies.

Automated ICV estimations from Freesurfer and SPM were evaluated using 399 reference segmentations. Both methods overestimated ICV and estimations using Freesurfer contained errors associated with skull-size. Estimations from SPM contained errors associated with gender and atrophy. An experiment showed that the choice of method can affect study results.

Manual ICV estimation is very time consuming, but can be performed using only a subset of voxels in an image to increase speed and decrease manual labor. Segmenting every nth slice and stereology were evaluated in terms of required manual labor and estimation error, using the previously created ICV references. An illustration showing how much manual labor is required for a given estimation error using different combinations of n and stereology grid spacing was presented.

Finally, different procedures for ICV normalization of regional brain volumes when investigating gender related volume differences were theoretically explained and evaluated using both simulated and real data. Resulting volume differences were seen to depend on the procedure used. A suggested workflow for procedure selection was presented.

Methodological contributions that can aid the analysis of the human brain have been presented. The performed studies also contribute to the understanding of important methodological considerations for regional brain volume analysis.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2014. 73 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1000
Keyword
MRI, Brain, Volume, Hemisphere, Intracranial volume, Image analysis
National Category
Medical Image Processing
Research subject
Computerized Image Analysis
Identifiers
urn:nbn:se:uu:diva-222376 (URN)978-91-554-8957-1 (ISBN)
Public defence
2014-06-10, Gunnesalen, Entrance 10, Uppsala University Hospital, Uppsala, 09:15 (Swedish)
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Supervisors
Available from: 2014-05-20 Created: 2014-04-10 Last updated: 2014-06-30

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Nordenskjöld, RichardMalmberg, FilipLarsson, Elna-MarieBrooks, Samantha J.Lind, LarsAhlström, HåkanJohansson, LarsKullberg, Joel

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