Dariya I Malyarenko1, David Newitt2, Lisa J Wilmes2, Alina Tudorica3, Karl G Helmer4, Lori R Arlinghaus5, Michael A Jacobs6, Guido Jajamovich7, Bachir Taouli7, Thomas E Yankeelov5,8, Wei Huang9, Thomas L Chenevert1. 1. Radiology, University of Michigan, Ann Arbor, Michigan, USA. 2. Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA. 3. Diagnostic Radiology, Oregon Health and Science University, Portland, Oregon, USA. 4. Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA. 5. Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee, USA. 6. John Hopkins University School of Medicine, Baltimore, Maryland, USA. 7. Translational and Molecular Imaging Institute Icahn School of Medicine at Mount Sinai, New York, USA. 8. Departments of Radiology, Physics and Cancer Biology, Vanderbilt University, Nashville, Tennessee, USA. 9. Advanced Imaging Research Center, Oregon Health and Science University, Portland, Oregon, USA.
Abstract
PURPOSE: Characterize system-specific bias across common magnetic resonance imaging (MRI) platforms for quantitative diffusion measurements in multicenter trials. METHODS: Diffusion weighted imaging (DWI) was performed on an ice-water phantom along the superior-inferior (SI) and right-left (RL) orientations spanning ± 150 mm. The same scanning protocol was implemented on 14 MRI systems at seven imaging centers. The bias was estimated as a deviation of measured from known apparent diffusion coefficient (ADC) along individual DWI directions. The relative contributions of gradient nonlinearity, shim errors, imaging gradients, and eddy currents were assessed independently. The observed bias errors were compared with numerical models. RESULTS: The measured systematic ADC errors scaled quadratically with offset from isocenter, and ranged between -55% (SI) and 25% (RL). Nonlinearity bias was dependent on system design and diffusion gradient direction. Consistent with numerical models, minor ADC errors (± 5%) due to shim, imaging and eddy currents were mitigated by double echo DWI and image coregistration of individual gradient directions. CONCLUSION: The analysis confirms gradient nonlinearity as a major source of spatial DW bias and variability in off-center ADC measurements across MRI platforms, with minor contributions from shim, imaging gradients and eddy currents. The developed protocol enables empiric description of systematic bias in multicenter quantitative DWI studies.
PURPOSE: Characterize system-specific bias across common magnetic resonance imaging (MRI) platforms for quantitative diffusion measurements in multicenter trials. METHODS: Diffusion weighted imaging (DWI) was performed on an ice-water phantom along the superior-inferior (SI) and right-left (RL) orientations spanning ± 150 mm. The same scanning protocol was implemented on 14 MRI systems at seven imaging centers. The bias was estimated as a deviation of measured from known apparent diffusion coefficient (ADC) along individual DWI directions. The relative contributions of gradient nonlinearity, shim errors, imaging gradients, and eddy currents were assessed independently. The observed bias errors were compared with numerical models. RESULTS: The measured systematic ADC errors scaled quadratically with offset from isocenter, and ranged between -55% (SI) and 25% (RL). Nonlinearity bias was dependent on system design and diffusion gradient direction. Consistent with numerical models, minor ADC errors (± 5%) due to shim, imaging and eddy currents were mitigated by double echo DWI and image coregistration of individual gradient directions. CONCLUSION: The analysis confirms gradient nonlinearity as a major source of spatial DW bias and variability in off-center ADC measurements across MRI platforms, with minor contributions from shim, imaging gradients and eddy currents. The developed protocol enables empiric description of systematic bias in multicenter quantitative DWI studies.
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