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Comparison of multicenter MRI protocols for visualizing the spinal cord gray matter.
Cohen-Adad, Julien; Alonso-Ortiz, Eva; Alley, Stephanie; Lagana, Maria Marcella; Baglio, Francesca; Vannesjo, Signe Johanna; Karbasforoushan, Haleh; Seif, Maryam; Seifert, Alan C; Xu, Junqian; Kim, Joo-Won; Labounek, René; Vojtísek, Lubomír; Dostál, Marek; Valosek, Jan; Samson, Rebecca S; Grussu, Francesco; Battiston, Marco; Gandini Wheeler-Kingshott, Claudia A M; Yiannakas, Marios C; Gilbert, Guillaume; Schneider, Torben; Johnson, Brian; Prados, Ferran.
  • Cohen-Adad J; NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Canada.
  • Alonso-Ortiz E; Functional Neuroimaging Unit, CRIUGM, University of Montreal, Montreal, Canada.
  • Alley S; Mila - Quebec AI Institute, Montreal, Canada.
  • Lagana MM; NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Canada.
  • Baglio F; NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Canada.
  • Vannesjo SJ; IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy.
  • Karbasforoushan H; IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy.
  • Seif M; Wellcome Center for Integrative Neuroimaging, FMRIB, University of Oxford, John Radcliffe Hospital, Oxford, UK.
  • Seifert AC; Department of Physics, Norwegian University of Science and Technology, Trondheim, Norway.
  • Xu J; Interdepartmental Neuroscience Program, Northwestern University School of Medicine, Chicago, IL, USA.
  • Kim JW; Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University, Stanford, CA, USA.
  • Labounek R; Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland.
  • Vojtísek L; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
  • Dostál M; Biomedical Engineering and Imaging Institute, Department of Radiology, Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Valosek J; Biomedical Engineering and Imaging Institute, Department of Radiology, Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Samson RS; Biomedical Engineering and Imaging Institute, Department of Radiology, Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Grussu F; Departments of Neurology and Biomedical Engineering, University Hospital Olomouc, Olomouc, Czech Republic.
  • Battiston M; Division of Clinical Behavioral Neuroscience, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA.
  • Gandini Wheeler-Kingshott CAM; Central European Institute of Technology, Masaryk University, Brno, Czech Republic.
  • Yiannakas MC; Department of Radiology and Nuclear Medicine, University Hospital Brno, Brno, Czech Republic.
  • Gilbert G; Departments of Neurology and Biomedical Engineering, University Hospital Olomouc, Olomouc, Czech Republic.
  • Schneider T; Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK.
  • Johnson B; Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK.
  • Prados F; Radiomics Group, Vall d'Hebron Institute of Oncology, Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain.
Magn Reson Med ; 88(2): 849-859, 2022 08.
Article en En | MEDLINE | ID: mdl-35476875
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.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Sustancia Blanca / Médula Cervical Tipo de estudio: Clinical_trials / Qualitative_research Límite: Humans Idioma: En Año: 2022 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Sustancia Blanca / Médula Cervical Tipo de estudio: Clinical_trials / Qualitative_research Límite: Humans Idioma: En Año: 2022 Tipo del documento: Article