Resting state fMRI scanner instabilities revealed by longitudinal phantom scans in a multi-center study
Quality assurance (QA) is crucial in longitudinal and/or multi-site studies, which involve the collection of data from a group of subjects over time and/or at different locations. It is important to regularly monitor the performance of the scanners over time and at different locations to detect and...
| Main Authors: | , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2021-08-01
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| Series: | NeuroImage |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811921004742 |
| _version_ | 1818623161243009024 |
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| author | Aras Kayvanrad Stephen R. Arnott Nathan Churchill Stefanie Hassel Aditi Chemparathy Fan Dong Mojdeh Zamyadi Tom Gee Robert Bartha Sandra E. Black Jane M. Lawrence-Dewar Christopher J.M. Scott Sean Symons Andrew D. Davis Geoffrey B. Hall Jacqueline Harris Nancy J. Lobaugh Glenda MacQueen Cindy Woo Stephen Strother |
| author_facet | Aras Kayvanrad Stephen R. Arnott Nathan Churchill Stefanie Hassel Aditi Chemparathy Fan Dong Mojdeh Zamyadi Tom Gee Robert Bartha Sandra E. Black Jane M. Lawrence-Dewar Christopher J.M. Scott Sean Symons Andrew D. Davis Geoffrey B. Hall Jacqueline Harris Nancy J. Lobaugh Glenda MacQueen Cindy Woo Stephen Strother |
| author_sort | Aras Kayvanrad |
| collection | DOAJ |
| description | Quality assurance (QA) is crucial in longitudinal and/or multi-site studies, which involve the collection of data from a group of subjects over time and/or at different locations. It is important to regularly monitor the performance of the scanners over time and at different locations to detect and control for intrinsic differences (e.g., due to manufacturers) and changes in scanner performance (e.g., due to gradual component aging, software and/or hardware upgrades, etc.). As part of the Ontario Neurodegenerative Disease Research Initiative (ONDRI) and the Canadian Biomarker Integration Network in Depression (CAN-BIND), QA phantom scans were conducted approximately monthly for three to four years at 13 sites across Canada with 3T research MRI scanners. QA parameters were calculated for each scan using the functional Biomarker Imaging Research Network's (fBIRN) QA phantom and pipeline to capture between- and within-scanner variability. We also describe a QA protocol to measure the full-width-at-half-maximum (FWHM) of slice-wise point spread functions (PSF), used in conjunction with the fBIRN QA parameters. Variations in image resolution measured by the FWHM are a primary source of variance over time for many sites, as well as between sites and between manufacturers. We also identify an unexpected range of instabilities affecting individual slices in a number of scanners, which may amount to a substantial contribution of unexplained signal variance to their data. Finally, we identify a preliminary preprocessing approach to reduce this variance and/or alleviate the slice anomalies, and in a small human data set show that this change in preprocessing can have a significant impact on seed-based connectivity measurements for some individual subjects. We expect that other fMRI centres will find this approach to identifying and controlling scanner instabilities useful in similar studies. |
| first_indexed | 2024-12-16T18:36:40Z |
| format | Article |
| id | doaj.art-7f079387e9e94e2281f5b7253a5bb97f |
| institution | Directory Open Access Journal |
| issn | 1095-9572 |
| language | English |
| last_indexed | 2024-12-16T18:36:40Z |
| publishDate | 2021-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj.art-7f079387e9e94e2281f5b7253a5bb97f2022-12-21T22:21:09ZengElsevierNeuroImage1095-95722021-08-01237118197Resting state fMRI scanner instabilities revealed by longitudinal phantom scans in a multi-center studyAras Kayvanrad0Stephen R. Arnott1Nathan Churchill2Stefanie Hassel3Aditi Chemparathy4Fan Dong5Mojdeh Zamyadi6Tom Gee7Robert Bartha8Sandra E. Black9Jane M. Lawrence-Dewar10Christopher J.M. Scott11Sean Symons12Andrew D. Davis13Geoffrey B. Hall14Jacqueline Harris15Nancy J. Lobaugh16Glenda MacQueen17Cindy Woo18Stephen Strother19Rotman Research Institute, University of Toronto, Toronto, ON, Canada; Corresponding author.Rotman Research Institute, University of Toronto, Toronto, ON, CanadaNeuroscience Research Program, St. Michael's Hospital, Toronto, ON, CanadaThe Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary, AB, Canada; Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, CanadaRotman Research Institute, University of Toronto, Toronto, ON, CanadaIndoc Research, Toronto, ON, CanadaRotman Research Institute, University of Toronto, Toronto, ON, CanadaIndoc Research, Toronto, ON, CanadaRobarts Research Institute, Western University, London, ON, Canada; Medical Biophysics, Western University, London, ON, CanadaSunnybrook Research Institute, Toronto, ON, CanadaThunder Bay Regional Health Research Institute, Thunder Bay, ON, CanadaSunnybrook Research Institute, Toronto, ON, CanadaSunnybrook Research Institute, Toronto, ON, CanadaRotman Research Institute, University of Toronto, Toronto, ON, Canada; Department of Psychology, Neuroscience & Behaviour, McMaster University, Hamilton, ON, CanadaDepartment of Psychology, Neuroscience & Behaviour, McMaster University, Hamilton, ON, CanadaDepatment of Computing Science, University of Alberta, Edmonton, AB, CanadaCenter for Addiction and Mental Health, Toronto, ON, CanadaThe Mathison Centre for Mental Health Research and Education, University of Calgary, Calgary, AB, CanadaDepartment of Psychiatry, University of British Columbia, Vancouver, BC, CanadaRotman Research Institute, University of Toronto, Toronto, ON, Canada; Medical Biophysics, University of Toronto, Toronto, ON, CanadaQuality assurance (QA) is crucial in longitudinal and/or multi-site studies, which involve the collection of data from a group of subjects over time and/or at different locations. It is important to regularly monitor the performance of the scanners over time and at different locations to detect and control for intrinsic differences (e.g., due to manufacturers) and changes in scanner performance (e.g., due to gradual component aging, software and/or hardware upgrades, etc.). As part of the Ontario Neurodegenerative Disease Research Initiative (ONDRI) and the Canadian Biomarker Integration Network in Depression (CAN-BIND), QA phantom scans were conducted approximately monthly for three to four years at 13 sites across Canada with 3T research MRI scanners. QA parameters were calculated for each scan using the functional Biomarker Imaging Research Network's (fBIRN) QA phantom and pipeline to capture between- and within-scanner variability. We also describe a QA protocol to measure the full-width-at-half-maximum (FWHM) of slice-wise point spread functions (PSF), used in conjunction with the fBIRN QA parameters. Variations in image resolution measured by the FWHM are a primary source of variance over time for many sites, as well as between sites and between manufacturers. We also identify an unexpected range of instabilities affecting individual slices in a number of scanners, which may amount to a substantial contribution of unexplained signal variance to their data. Finally, we identify a preliminary preprocessing approach to reduce this variance and/or alleviate the slice anomalies, and in a small human data set show that this change in preprocessing can have a significant impact on seed-based connectivity measurements for some individual subjects. We expect that other fMRI centres will find this approach to identifying and controlling scanner instabilities useful in similar studies.http://www.sciencedirect.com/science/article/pii/S1053811921004742Resting state fMRIfMRI quality assuranceMRI scanner instabilitiesMulti-center/Longitudinal fMRI studies |
| spellingShingle | Aras Kayvanrad Stephen R. Arnott Nathan Churchill Stefanie Hassel Aditi Chemparathy Fan Dong Mojdeh Zamyadi Tom Gee Robert Bartha Sandra E. Black Jane M. Lawrence-Dewar Christopher J.M. Scott Sean Symons Andrew D. Davis Geoffrey B. Hall Jacqueline Harris Nancy J. Lobaugh Glenda MacQueen Cindy Woo Stephen Strother Resting state fMRI scanner instabilities revealed by longitudinal phantom scans in a multi-center study NeuroImage Resting state fMRI fMRI quality assurance MRI scanner instabilities Multi-center/Longitudinal fMRI studies |
| title | Resting state fMRI scanner instabilities revealed by longitudinal phantom scans in a multi-center study |
| title_full | Resting state fMRI scanner instabilities revealed by longitudinal phantom scans in a multi-center study |
| title_fullStr | Resting state fMRI scanner instabilities revealed by longitudinal phantom scans in a multi-center study |
| title_full_unstemmed | Resting state fMRI scanner instabilities revealed by longitudinal phantom scans in a multi-center study |
| title_short | Resting state fMRI scanner instabilities revealed by longitudinal phantom scans in a multi-center study |
| title_sort | resting state fmri scanner instabilities revealed by longitudinal phantom scans in a multi center study |
| topic | Resting state fMRI fMRI quality assurance MRI scanner instabilities Multi-center/Longitudinal fMRI studies |
| url | http://www.sciencedirect.com/science/article/pii/S1053811921004742 |
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