Bias Introduced by Multiple Head Coils in MRI Research: An 8 Channel and 32 Channel Coil Comparison
Neuroimaging MRI data in scientific research is increasingly pooled, but the reliability of such studies may be hampered by the use of different hardware elements. This might introduce bias, for example when cross-sectional studies pool data acquired with different head coils, or when longitudinal c...
Main Authors: | , , , , , , , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2019-07-01
|
Series: | Frontiers in Neuroscience |
Subjects: | |
Online Access: | https://www.frontiersin.org/article/10.3389/fnins.2019.00729/full |
id |
doaj-0d539ca8367b43feb1ba163d233088ea |
---|---|
record_format |
Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jessica L. Panman Jessica L. Panman Yang Yang To Emma L. van der Ende Emma L. van der Ende Jackie M. Poos Jackie M. Poos Lize C. Jiskoot Lize C. Jiskoot Lieke H. H. Meeter Elise G. P. Dopper Elise G. P. Dopper Mark J. R. J. Bouts Mark J. R. J. Bouts Mark J. R. J. Bouts Matthias J. P. van Osch Matthias J. P. van Osch Serge A. R. B. Rombouts Serge A. R. B. Rombouts Serge A. R. B. Rombouts John C. van Swieten Jeroen van der Grond Janne M. Papma Anne Hafkemeijer Anne Hafkemeijer Anne Hafkemeijer |
spellingShingle |
Jessica L. Panman Jessica L. Panman Yang Yang To Emma L. van der Ende Emma L. van der Ende Jackie M. Poos Jackie M. Poos Lize C. Jiskoot Lize C. Jiskoot Lieke H. H. Meeter Elise G. P. Dopper Elise G. P. Dopper Mark J. R. J. Bouts Mark J. R. J. Bouts Mark J. R. J. Bouts Matthias J. P. van Osch Matthias J. P. van Osch Serge A. R. B. Rombouts Serge A. R. B. Rombouts Serge A. R. B. Rombouts John C. van Swieten Jeroen van der Grond Janne M. Papma Anne Hafkemeijer Anne Hafkemeijer Anne Hafkemeijer Bias Introduced by Multiple Head Coils in MRI Research: An 8 Channel and 32 Channel Coil Comparison Frontiers in Neuroscience MRI DTI neuroimaging gray matter white matter multicenter study |
author_facet |
Jessica L. Panman Jessica L. Panman Yang Yang To Emma L. van der Ende Emma L. van der Ende Jackie M. Poos Jackie M. Poos Lize C. Jiskoot Lize C. Jiskoot Lieke H. H. Meeter Elise G. P. Dopper Elise G. P. Dopper Mark J. R. J. Bouts Mark J. R. J. Bouts Mark J. R. J. Bouts Matthias J. P. van Osch Matthias J. P. van Osch Serge A. R. B. Rombouts Serge A. R. B. Rombouts Serge A. R. B. Rombouts John C. van Swieten Jeroen van der Grond Janne M. Papma Anne Hafkemeijer Anne Hafkemeijer Anne Hafkemeijer |
author_sort |
Jessica L. Panman |
title |
Bias Introduced by Multiple Head Coils in MRI Research: An 8 Channel and 32 Channel Coil Comparison |
title_short |
Bias Introduced by Multiple Head Coils in MRI Research: An 8 Channel and 32 Channel Coil Comparison |
title_full |
Bias Introduced by Multiple Head Coils in MRI Research: An 8 Channel and 32 Channel Coil Comparison |
title_fullStr |
Bias Introduced by Multiple Head Coils in MRI Research: An 8 Channel and 32 Channel Coil Comparison |
title_full_unstemmed |
Bias Introduced by Multiple Head Coils in MRI Research: An 8 Channel and 32 Channel Coil Comparison |
title_sort |
bias introduced by multiple head coils in mri research: an 8 channel and 32 channel coil comparison |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Neuroscience |
issn |
1662-453X |
publishDate |
2019-07-01 |
description |
Neuroimaging MRI data in scientific research is increasingly pooled, but the reliability of such studies may be hampered by the use of different hardware elements. This might introduce bias, for example when cross-sectional studies pool data acquired with different head coils, or when longitudinal clinical studies change head coils halfway. In the present study, we aimed to estimate this possible bias introduced by using different head coils to create awareness and to avoid misinterpretation of results. We acquired, with both an 8 channel and 32 channel head coil, T1-weighted, diffusion tensor imaging and resting state fMRI images at 3T MRI (Philips Achieva) with stable acquisition parameters in a large group of cognitively healthy participants (n = 77). Standard analysis methods, i.e., voxel-based morphometry, tract-based spatial statistics and resting state functional network analyses, were used in a within-subject design to compare 8 and 32 channel head coil data. Signal-to-noise ratios (SNR) for both head coils showed similar ranges, although the 32 channel SNR profile was more homogeneous. Our data demonstrates specific patterns of gray and white matter volume differences between head coils (relative volume change of 6 to 9%), related to altered image contrast and therefore, altered tissue segmentation. White matter connectivity (fractional anisotropy and diffusivity measures) showed hemispherical dependent differences between head coils (relative connectivity change of 4 to 6%), and functional connectivity in resting state networks was higher using the 32 channel head coil in posterior cortical areas (relative change up to 27.5%). This study shows that, even when acquisition protocols are harmonized, the results of standardized analysis models can be severely affected by the use of different head coils. Researchers should be aware of this when combining multiple neuroimaging MRI datasets, to prevent coil-related bias and avoid misinterpretation of their findings. |
topic |
MRI DTI neuroimaging gray matter white matter multicenter study |
url |
https://www.frontiersin.org/article/10.3389/fnins.2019.00729/full |
work_keys_str_mv |
AT jessicalpanman biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT jessicalpanman biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT yangyangto biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT emmalvanderende biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT emmalvanderende biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT jackiempoos biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT jackiempoos biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT lizecjiskoot biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT lizecjiskoot biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT liekehhmeeter biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT elisegpdopper biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT elisegpdopper biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT markjrjbouts biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT markjrjbouts biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT markjrjbouts biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT matthiasjpvanosch biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT matthiasjpvanosch biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT sergearbrombouts biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT sergearbrombouts biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT sergearbrombouts biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT johncvanswieten biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT jeroenvandergrond biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT jannempapma biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT annehafkemeijer biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT annehafkemeijer biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison AT annehafkemeijer biasintroducedbymultipleheadcoilsinmriresearchan8channeland32channelcoilcomparison |
_version_ |
1725785543084605440 |
spelling |
doaj-0d539ca8367b43feb1ba163d233088ea2020-11-24T22:17:19ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2019-07-011310.3389/fnins.2019.00729460195Bias Introduced by Multiple Head Coils in MRI Research: An 8 Channel and 32 Channel Coil ComparisonJessica L. Panman0Jessica L. Panman1Yang Yang To2Emma L. van der Ende3Emma L. van der Ende4Jackie M. Poos5Jackie M. Poos6Lize C. Jiskoot7Lize C. Jiskoot8Lieke H. H. Meeter9Elise G. P. Dopper10Elise G. P. Dopper11Mark J. R. J. Bouts12Mark J. R. J. Bouts13Mark J. R. J. Bouts14Matthias J. P. van Osch15Matthias J. P. van Osch16Serge A. R. B. Rombouts17Serge A. R. B. Rombouts18Serge A. R. B. Rombouts19John C. van Swieten20Jeroen van der Grond21Janne M. Papma22Anne Hafkemeijer23Anne Hafkemeijer24Anne Hafkemeijer25Department of Radiology, Leiden University Medical Center, Leiden, NetherlandsDepartment of Neurology, Erasmus University Medical Center Rotterdam, Rotterdam, NetherlandsDepartment of Neurology, Erasmus University Medical Center Rotterdam, Rotterdam, NetherlandsDepartment of Radiology, Leiden University Medical Center, Leiden, NetherlandsDepartment of Neurology, Erasmus University Medical Center Rotterdam, Rotterdam, NetherlandsDepartment of Radiology, Leiden University Medical Center, Leiden, NetherlandsDepartment of Neurology, Erasmus University Medical Center Rotterdam, Rotterdam, NetherlandsDepartment of Radiology, Leiden University Medical Center, Leiden, NetherlandsDepartment of Neurology, Erasmus University Medical Center Rotterdam, Rotterdam, NetherlandsDepartment of Neurology, Erasmus University Medical Center Rotterdam, Rotterdam, NetherlandsDepartment of Radiology, Leiden University Medical Center, Leiden, NetherlandsDepartment of Neurology, Erasmus University Medical Center Rotterdam, Rotterdam, NetherlandsDepartment of Radiology, Leiden University Medical Center, Leiden, NetherlandsDepartment of Methodology and Statistics, Institute of Psychology, Leiden University, Leiden, NetherlandsLeiden Institute for Brain and Cognition, Leiden University, Leiden, NetherlandsDepartment of Radiology, Leiden University Medical Center, Leiden, NetherlandsLeiden Institute for Brain and Cognition, Leiden University, Leiden, NetherlandsDepartment of Radiology, Leiden University Medical Center, Leiden, NetherlandsDepartment of Methodology and Statistics, Institute of Psychology, Leiden University, Leiden, NetherlandsLeiden Institute for Brain and Cognition, Leiden University, Leiden, NetherlandsDepartment of Neurology, Erasmus University Medical Center Rotterdam, Rotterdam, NetherlandsDepartment of Radiology, Leiden University Medical Center, Leiden, NetherlandsDepartment of Neurology, Erasmus University Medical Center Rotterdam, Rotterdam, NetherlandsDepartment of Radiology, Leiden University Medical Center, Leiden, NetherlandsDepartment of Methodology and Statistics, Institute of Psychology, Leiden University, Leiden, NetherlandsLeiden Institute for Brain and Cognition, Leiden University, Leiden, NetherlandsNeuroimaging MRI data in scientific research is increasingly pooled, but the reliability of such studies may be hampered by the use of different hardware elements. This might introduce bias, for example when cross-sectional studies pool data acquired with different head coils, or when longitudinal clinical studies change head coils halfway. In the present study, we aimed to estimate this possible bias introduced by using different head coils to create awareness and to avoid misinterpretation of results. We acquired, with both an 8 channel and 32 channel head coil, T1-weighted, diffusion tensor imaging and resting state fMRI images at 3T MRI (Philips Achieva) with stable acquisition parameters in a large group of cognitively healthy participants (n = 77). Standard analysis methods, i.e., voxel-based morphometry, tract-based spatial statistics and resting state functional network analyses, were used in a within-subject design to compare 8 and 32 channel head coil data. Signal-to-noise ratios (SNR) for both head coils showed similar ranges, although the 32 channel SNR profile was more homogeneous. Our data demonstrates specific patterns of gray and white matter volume differences between head coils (relative volume change of 6 to 9%), related to altered image contrast and therefore, altered tissue segmentation. White matter connectivity (fractional anisotropy and diffusivity measures) showed hemispherical dependent differences between head coils (relative connectivity change of 4 to 6%), and functional connectivity in resting state networks was higher using the 32 channel head coil in posterior cortical areas (relative change up to 27.5%). This study shows that, even when acquisition protocols are harmonized, the results of standardized analysis models can be severely affected by the use of different head coils. Researchers should be aware of this when combining multiple neuroimaging MRI datasets, to prevent coil-related bias and avoid misinterpretation of their findings.https://www.frontiersin.org/article/10.3389/fnins.2019.00729/fullMRIDTIneuroimaginggray matterwhite mattermulticenter study |