Comparison of multicenter MRI protocols for visualizing the spinal cord gray matter

Julien Cohen-Adad; Eva Alonso-Ortiz; Stephanie Alley; Maria Marcella Lagana; Francesca Baglio; Signe Johanna Vannesjo; Haleh Karbasforoushan; Maryam Seif; Alan C Seifert; Junqian Xu; Joo-Won Kim; René Labounek; Lubomír Vojtíšek; Marek Dostál; Jan Valošek; Rebecca S Samson; Francesco Grussu; Marco Battiston; Claudia A M Gandini Wheeler-Kingshott; Marios C Yiannakas; Guillaume Gilbert; Torben Schneider; Brian Johnson; Ferran Prados

doi:10.1002/mrm.29249

Comparison of multicenter MRI protocols for visualizing the spinal cord gray matter

Julien Cohen-Adad, Eva Alonso-Ortiz, Stephanie Alley, Maria Marcella Lagana, Francesca Baglio, Signe Johanna Vannesjo, Haleh Karbasforoushan, Maryam Seif, Alan C Seifert, Junqian Xu, Joo-Won Kim, René Labounek, Lubomír Vojtíšek, Marek Dostál, Jan Valošek, Rebecca S Samson, Francesco Grussu, Marco Battiston, Claudia A M Gandini Wheeler-Kingshott, Marios C YiannakasGuillaume Gilbert, Torben Schneider, Brian Johnson, Ferran Prados

Clinical Behavioral Neuroscience (Pediatrics)

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

PURPOSE: Spinal cord gray-matter imaging is valuable for a number of applications, but remains challenging. The purpose of this work was to compare various MRI protocols at 1.5 T, 3 T, and 7 T for visualizing the gray matter.

METHODS: In vivo data of the cervical spinal cord were collected from nine different imaging centers. Data processing consisted of automatically segmenting the spinal cord and its gray matter and co-registering back-to-back scans. We computed the SNR using two methods (SNR_single using a single scan and SNR_diff using the difference between back-to-back scans) and the white/gray matter contrast-to-noise ratio per unit time. Synthetic phantom data were generated to evaluate the metrics performance. Experienced radiologists qualitatively scored the images. We ran the same processing on an open-access multicenter data set of the spinal cord MRI (N = 267 participants).

RESULTS: Qualitative assessments indicated comparable image quality for 3T and 7T scans. Spatial resolution was higher at higher field strength, and image quality at 1.5 T was found to be moderate to low. The proposed quantitative metrics were found to be robust to underlying changes to the SNR and contrast; however, the SNR_single method lacked accuracy when there were excessive partial-volume effects.

CONCLUSION: We propose quality assessment criteria and metrics for gray-matter visualization and apply them to different protocols. The proposed criteria and metrics, the analyzed protocols, and our open-source code can serve as a benchmark for future optimization of spinal cord gray-matter imaging protocols.

Original language	English (US)
Pages (from-to)	849-859
Number of pages	11
Journal	Magnetic resonance in medicine
Volume	88
Issue number	2
DOIs	https://doi.org/10.1002/mrm.29249
State	Published - Aug 2022

Bibliographical note

Funding Information:
information The Canada Research Chair in Quantitative Magnetic Resonance Imaging (950-230815), the Canadian Institute of Health Research (CIHR FDN-143263), the Canada Foundation for Innovation (32454, 34824), the Fonds de Recherche du Québec - Santé (28826), the Natural Sciences and Engineering Research Council of Canada (RGPIN-2019-07244), the Canada First Research Excellence Fund (IVADO and TransMedTech), the Courtois NeuroMod project, the Quebec BioImaging Network (5886, 35450), the Czech Health Research Council (NV18-04-00159), the Ministry of Education Youth and Sport of the Czech Republic (LM2015062, Czech-BioImaging project) and the Ministry of Health of the Czech Republic (65269705, project for conceptual development in research organizations), EU Horizon 2020 (CDS-QuaMRI 634541), Engineering and Physical Sciences Research Council (EPSRC EP/R006032/1 and EP/I027084/1), INSPIRED (Spinal Research, UK; Wings for Life, Austria; Craig H. Neilsen Foundation, USA), UK Multiple Sclerosis Society (892/08 and 77/2017), Department of Health's NIHR BRC (R&D 03/10/RAG0449), Guarantors of Brain post-doctoral nonclinical fellowships, the US National Institute of Neurological Disorders and Stroke (NIH/NINDS K01-NS105160), and Beatriu de Pinós postdoctoral fellowships (2020 BP 00117, Secretary of Universities and Research, Government of Catalonia). The National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre.The authors thank Alexandru Foias and Nicolas Pinon for helping with the generation of figures, and Pavla Hanzlíková (from the Department of Radiology, University of Ostrava, Czechia) for helping with the qualitative assessment.

Funding Information:
The Canada Research Chair in Quantitative Magnetic Resonance Imaging (950‐230815), the Canadian Institute of Health Research (CIHR FDN‐143263), the Canada Foundation for Innovation (32454, 34824), the Fonds de Recherche du Québec ‐ Santé (28826), the Natural Sciences and Engineering Research Council of Canada (RGPIN‐2019‐07244), the Canada First Research Excellence Fund (IVADO and TransMedTech), the Courtois NeuroMod project, the Quebec BioImaging Network (5886, 35450), the Czech Health Research Council (NV18‐04‐00159), the Ministry of Education Youth and Sport of the Czech Republic (LM2015062, Czech‐BioImaging project) and the Ministry of Health of the Czech Republic (65269705, project for conceptual development in research organizations), EU Horizon 2020 (CDS‐QuaMRI 634541), Engineering and Physical Sciences Research Council (EPSRC EP/R006032/1 and EP/I027084/1), INSPIRED (Spinal Research, UK; Wings for Life, Austria; Craig H. Neilsen Foundation, USA), UK Multiple Sclerosis Society (892/08 and 77/2017), Department of Health's NIHR BRC (R&D 03/10/RAG0449), Guarantors of Brain post‐doctoral nonclinical fellowships, the US National Institute of Neurological Disorders and Stroke (NIH/NINDS K01‐NS105160), and Beatriu de Pinós postdoctoral fellowships (2020 BP 00117, Secretary of Universities and Research, Government of Catalonia). The National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre. Funding information

Publisher Copyright:
© 2022 International Society for Magnetic Resonance in Medicine.

Keywords

Cervical Cord
Gray Matter/diagnostic imaging
Humans
Image Processing, Computer-Assisted/methods
Magnetic Resonance Imaging/methods
Multicenter Studies as Topic
Spinal Cord/diagnostic imaging
White Matter/diagnostic imaging

PubMed: MeSH publication types

Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

Publisher link

10.1002/mrm.29249

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Cohen-Adad, J., Alonso-Ortiz, E., Alley, S., Lagana, M. M., Baglio, F., Vannesjo, S. J., Karbasforoushan, H., Seif, M., Seifert, A. C., Xu, J., Kim, J.-W., Labounek, R., Vojtíšek, L., Dostál, M., Valošek, J., Samson, R. S., Grussu, F., Battiston, M., Gandini Wheeler-Kingshott, C. A. M., ... Prados, F. (2022). Comparison of multicenter MRI protocols for visualizing the spinal cord gray matter. Magnetic resonance in medicine, 88(2), 849-859. https://doi.org/10.1002/mrm.29249

Cohen-Adad, J, Alonso-Ortiz, E, Alley, S, Lagana, MM, Baglio, F, Vannesjo, SJ, Karbasforoushan, H, Seif, M, Seifert, AC, Xu, J, Kim, J-W, Labounek, R, Vojtíšek, L, Dostál, M, Valošek, J, Samson, RS, Grussu, F, Battiston, M, Gandini Wheeler-Kingshott, CAM, Yiannakas, MC, Gilbert, G, Schneider, T, Johnson, B & Prados, F 2022, 'Comparison of multicenter MRI protocols for visualizing the spinal cord gray matter', Magnetic resonance in medicine, vol. 88, no. 2, pp. 849-859. https://doi.org/10.1002/mrm.29249

@article{3e9d8cb5aa684443bc7c2aa086963113,

title = "Comparison of multicenter MRI protocols for visualizing the spinal cord gray matter",

abstract = "PURPOSE: Spinal cord gray-matter imaging is valuable for a number of applications, but remains challenging. The purpose of this work was to compare various MRI protocols at 1.5 T, 3 T, and 7 T for visualizing the gray matter.METHODS: In vivo data of the cervical spinal cord were collected from nine different imaging centers. Data processing consisted of automatically segmenting the spinal cord and its gray matter and co-registering back-to-back scans. We computed the SNR using two methods (SNR_single using a single scan and SNR_diff using the difference between back-to-back scans) and the white/gray matter contrast-to-noise ratio per unit time. Synthetic phantom data were generated to evaluate the metrics performance. Experienced radiologists qualitatively scored the images. We ran the same processing on an open-access multicenter data set of the spinal cord MRI (N = 267 participants).RESULTS: Qualitative assessments indicated comparable image quality for 3T and 7T scans. Spatial resolution was higher at higher field strength, and image quality at 1.5 T was found to be moderate to low. The proposed quantitative metrics were found to be robust to underlying changes to the SNR and contrast; however, the SNR_single method lacked accuracy when there were excessive partial-volume effects.CONCLUSION: We propose quality assessment criteria and metrics for gray-matter visualization and apply them to different protocols. The proposed criteria and metrics, the analyzed protocols, and our open-source code can serve as a benchmark for future optimization of spinal cord gray-matter imaging protocols.",

keywords = "Cervical Cord, Gray Matter/diagnostic imaging, Humans, Image Processing, Computer-Assisted/methods, Magnetic Resonance Imaging/methods, Multicenter Studies as Topic, Spinal Cord/diagnostic imaging, White Matter/diagnostic imaging",

author = "Julien Cohen-Adad and Eva Alonso-Ortiz and Stephanie Alley and Lagana, {Maria Marcella} and Francesca Baglio and Vannesjo, {Signe Johanna} and Haleh Karbasforoushan and Maryam Seif and Seifert, {Alan C} and Junqian Xu and Joo-Won Kim and Ren{\'e} Labounek and Lubom{\'i}r Vojt{\'i}{\v s}ek and Marek Dost{\'a}l and Jan Valo{\v s}ek and Samson, {Rebecca S} and Francesco Grussu and Marco Battiston and {Gandini Wheeler-Kingshott}, {Claudia A M} and Yiannakas, {Marios C} and Guillaume Gilbert and Torben Schneider and Brian Johnson and Ferran Prados",

note = "Funding Information: information The Canada Research Chair in Quantitative Magnetic Resonance Imaging (950-230815), the Canadian Institute of Health Research (CIHR FDN-143263), the Canada Foundation for Innovation (32454, 34824), the Fonds de Recherche du Qu{\'e}bec - Sant{\'e} (28826), the Natural Sciences and Engineering Research Council of Canada (RGPIN-2019-07244), the Canada First Research Excellence Fund (IVADO and TransMedTech), the Courtois NeuroMod project, the Quebec BioImaging Network (5886, 35450), the Czech Health Research Council (NV18-04-00159), the Ministry of Education Youth and Sport of the Czech Republic (LM2015062, Czech-BioImaging project) and the Ministry of Health of the Czech Republic (65269705, project for conceptual development in research organizations), EU Horizon 2020 (CDS-QuaMRI 634541), Engineering and Physical Sciences Research Council (EPSRC EP/R006032/1 and EP/I027084/1), INSPIRED (Spinal Research, UK; Wings for Life, Austria; Craig H. Neilsen Foundation, USA), UK Multiple Sclerosis Society (892/08 and 77/2017), Department of Health's NIHR BRC (R&D 03/10/RAG0449), Guarantors of Brain post-doctoral nonclinical fellowships, the US National Institute of Neurological Disorders and Stroke (NIH/NINDS K01-NS105160), and Beatriu de Pin{\'o}s postdoctoral fellowships (2020 BP 00117, Secretary of Universities and Research, Government of Catalonia). The National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre.The authors thank Alexandru Foias and Nicolas Pinon for helping with the generation of figures, and Pavla Hanzl{\'i}kov{\'a} (from the Department of Radiology, University of Ostrava, Czechia) for helping with the qualitative assessment. Funding Information: The Canada Research Chair in Quantitative Magnetic Resonance Imaging (950‐230815), the Canadian Institute of Health Research (CIHR FDN‐143263), the Canada Foundation for Innovation (32454, 34824), the Fonds de Recherche du Qu{\'e}bec ‐ Sant{\'e} (28826), the Natural Sciences and Engineering Research Council of Canada (RGPIN‐2019‐07244), the Canada First Research Excellence Fund (IVADO and TransMedTech), the Courtois NeuroMod project, the Quebec BioImaging Network (5886, 35450), the Czech Health Research Council (NV18‐04‐00159), the Ministry of Education Youth and Sport of the Czech Republic (LM2015062, Czech‐BioImaging project) and the Ministry of Health of the Czech Republic (65269705, project for conceptual development in research organizations), EU Horizon 2020 (CDS‐QuaMRI 634541), Engineering and Physical Sciences Research Council (EPSRC EP/R006032/1 and EP/I027084/1), INSPIRED (Spinal Research, UK; Wings for Life, Austria; Craig H. Neilsen Foundation, USA), UK Multiple Sclerosis Society (892/08 and 77/2017), Department of Health's NIHR BRC (R&D 03/10/RAG0449), Guarantors of Brain post‐doctoral nonclinical fellowships, the US National Institute of Neurological Disorders and Stroke (NIH/NINDS K01‐NS105160), and Beatriu de Pin{\'o}s postdoctoral fellowships (2020 BP 00117, Secretary of Universities and Research, Government of Catalonia). The National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre. Funding information Publisher Copyright: {\textcopyright} 2022 International Society for Magnetic Resonance in Medicine.",

year = "2022",

month = aug,

doi = "10.1002/mrm.29249",

language = "English (US)",

volume = "88",

pages = "849--859",

journal = "Magnetic resonance in medicine",

issn = "0740-3194",

publisher = "John Wiley and Sons Inc.",

number = "2",

}

TY - JOUR

T1 - Comparison of multicenter MRI protocols for visualizing the spinal cord gray matter

AU - Cohen-Adad, Julien

AU - Alonso-Ortiz, Eva

AU - Alley, Stephanie

AU - Lagana, Maria Marcella

AU - Baglio, Francesca

AU - Vannesjo, Signe Johanna

AU - Karbasforoushan, Haleh

AU - Seif, Maryam

AU - Seifert, Alan C

AU - Xu, Junqian

AU - Kim, Joo-Won

AU - Labounek, René

AU - Vojtíšek, Lubomír

AU - Dostál, Marek

AU - Valošek, Jan

AU - Samson, Rebecca S

AU - Grussu, Francesco

AU - Battiston, Marco

AU - Gandini Wheeler-Kingshott, Claudia A M

AU - Yiannakas, Marios C

AU - Gilbert, Guillaume

AU - Schneider, Torben

AU - Johnson, Brian

AU - Prados, Ferran

N1 - Funding Information: information The Canada Research Chair in Quantitative Magnetic Resonance Imaging (950-230815), the Canadian Institute of Health Research (CIHR FDN-143263), the Canada Foundation for Innovation (32454, 34824), the Fonds de Recherche du Québec - Santé (28826), the Natural Sciences and Engineering Research Council of Canada (RGPIN-2019-07244), the Canada First Research Excellence Fund (IVADO and TransMedTech), the Courtois NeuroMod project, the Quebec BioImaging Network (5886, 35450), the Czech Health Research Council (NV18-04-00159), the Ministry of Education Youth and Sport of the Czech Republic (LM2015062, Czech-BioImaging project) and the Ministry of Health of the Czech Republic (65269705, project for conceptual development in research organizations), EU Horizon 2020 (CDS-QuaMRI 634541), Engineering and Physical Sciences Research Council (EPSRC EP/R006032/1 and EP/I027084/1), INSPIRED (Spinal Research, UK; Wings for Life, Austria; Craig H. Neilsen Foundation, USA), UK Multiple Sclerosis Society (892/08 and 77/2017), Department of Health's NIHR BRC (R&D 03/10/RAG0449), Guarantors of Brain post-doctoral nonclinical fellowships, the US National Institute of Neurological Disorders and Stroke (NIH/NINDS K01-NS105160), and Beatriu de Pinós postdoctoral fellowships (2020 BP 00117, Secretary of Universities and Research, Government of Catalonia). The National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre.The authors thank Alexandru Foias and Nicolas Pinon for helping with the generation of figures, and Pavla Hanzlíková (from the Department of Radiology, University of Ostrava, Czechia) for helping with the qualitative assessment. Funding Information: The Canada Research Chair in Quantitative Magnetic Resonance Imaging (950‐230815), the Canadian Institute of Health Research (CIHR FDN‐143263), the Canada Foundation for Innovation (32454, 34824), the Fonds de Recherche du Québec ‐ Santé (28826), the Natural Sciences and Engineering Research Council of Canada (RGPIN‐2019‐07244), the Canada First Research Excellence Fund (IVADO and TransMedTech), the Courtois NeuroMod project, the Quebec BioImaging Network (5886, 35450), the Czech Health Research Council (NV18‐04‐00159), the Ministry of Education Youth and Sport of the Czech Republic (LM2015062, Czech‐BioImaging project) and the Ministry of Health of the Czech Republic (65269705, project for conceptual development in research organizations), EU Horizon 2020 (CDS‐QuaMRI 634541), Engineering and Physical Sciences Research Council (EPSRC EP/R006032/1 and EP/I027084/1), INSPIRED (Spinal Research, UK; Wings for Life, Austria; Craig H. Neilsen Foundation, USA), UK Multiple Sclerosis Society (892/08 and 77/2017), Department of Health's NIHR BRC (R&D 03/10/RAG0449), Guarantors of Brain post‐doctoral nonclinical fellowships, the US National Institute of Neurological Disorders and Stroke (NIH/NINDS K01‐NS105160), and Beatriu de Pinós postdoctoral fellowships (2020 BP 00117, Secretary of Universities and Research, Government of Catalonia). The National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre. Funding information Publisher Copyright: © 2022 International Society for Magnetic Resonance in Medicine.

PY - 2022/8

Y1 - 2022/8

N2 - PURPOSE: Spinal cord gray-matter imaging is valuable for a number of applications, but remains challenging. The purpose of this work was to compare various MRI protocols at 1.5 T, 3 T, and 7 T for visualizing the gray matter.METHODS: In vivo data of the cervical spinal cord were collected from nine different imaging centers. Data processing consisted of automatically segmenting the spinal cord and its gray matter and co-registering back-to-back scans. We computed the SNR using two methods (SNR_single using a single scan and SNR_diff using the difference between back-to-back scans) and the white/gray matter contrast-to-noise ratio per unit time. Synthetic phantom data were generated to evaluate the metrics performance. Experienced radiologists qualitatively scored the images. We ran the same processing on an open-access multicenter data set of the spinal cord MRI (N = 267 participants).RESULTS: Qualitative assessments indicated comparable image quality for 3T and 7T scans. Spatial resolution was higher at higher field strength, and image quality at 1.5 T was found to be moderate to low. The proposed quantitative metrics were found to be robust to underlying changes to the SNR and contrast; however, the SNR_single method lacked accuracy when there were excessive partial-volume effects.CONCLUSION: We propose quality assessment criteria and metrics for gray-matter visualization and apply them to different protocols. The proposed criteria and metrics, the analyzed protocols, and our open-source code can serve as a benchmark for future optimization of spinal cord gray-matter imaging protocols.

AB - PURPOSE: Spinal cord gray-matter imaging is valuable for a number of applications, but remains challenging. The purpose of this work was to compare various MRI protocols at 1.5 T, 3 T, and 7 T for visualizing the gray matter.METHODS: In vivo data of the cervical spinal cord were collected from nine different imaging centers. Data processing consisted of automatically segmenting the spinal cord and its gray matter and co-registering back-to-back scans. We computed the SNR using two methods (SNR_single using a single scan and SNR_diff using the difference between back-to-back scans) and the white/gray matter contrast-to-noise ratio per unit time. Synthetic phantom data were generated to evaluate the metrics performance. Experienced radiologists qualitatively scored the images. We ran the same processing on an open-access multicenter data set of the spinal cord MRI (N = 267 participants).RESULTS: Qualitative assessments indicated comparable image quality for 3T and 7T scans. Spatial resolution was higher at higher field strength, and image quality at 1.5 T was found to be moderate to low. The proposed quantitative metrics were found to be robust to underlying changes to the SNR and contrast; however, the SNR_single method lacked accuracy when there were excessive partial-volume effects.CONCLUSION: We propose quality assessment criteria and metrics for gray-matter visualization and apply them to different protocols. The proposed criteria and metrics, the analyzed protocols, and our open-source code can serve as a benchmark for future optimization of spinal cord gray-matter imaging protocols.

KW - Cervical Cord

KW - Gray Matter/diagnostic imaging

KW - Humans

KW - Image Processing, Computer-Assisted/methods

KW - Magnetic Resonance Imaging/methods

KW - Multicenter Studies as Topic

KW - Spinal Cord/diagnostic imaging

KW - White Matter/diagnostic imaging

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DO - 10.1002/mrm.29249

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SN - 0740-3194

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JO - Magnetic resonance in medicine

JF - Magnetic resonance in medicine

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Comparison of multicenter MRI protocols for visualizing the spinal cord gray matter

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