Quantifying 3D MR fingerprinting (3D‐MRF) reproducibility across subjects, sessions, and scanners automatically using MNI atlases
Purpose Quantitative MRI techniques such as MR fingerprinting (MRF) promise more objective and comparable measurements of tissue properties at the point‐of‐care than weighted imaging. However, few direct cross‐modal comparisons of MRF's repeatability and reproducibility versus weighted acquisit...
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| Veröffentlicht in: | Magnetic resonance in medicine Jg. 91; H. 5; S. 2074 - 2088 |
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| Sprache: | Englisch |
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01.05.2024
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| ISSN: | 0740-3194, 1522-2594, 1522-2594 |
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| Abstract | Purpose
Quantitative MRI techniques such as MR fingerprinting (MRF) promise more objective and comparable measurements of tissue properties at the point‐of‐care than weighted imaging. However, few direct cross‐modal comparisons of MRF's repeatability and reproducibility versus weighted acquisitions have been performed. This work proposes a novel fully automated pipeline for quantitatively comparing cross‐modal imaging performance in vivo via atlas‐based sampling.
Methods
We acquire whole‐brain 3D‐MRF, turbo spin echo, and MPRAGE sequences three times each on two scanners across 10 subjects, for a total of 60 multimodal datasets. The proposed automated registration and analysis pipeline uses linear and nonlinear registration to align all qualitative and quantitative DICOM stacks to Montreal Neurological Institute (MNI) 152 space, then samples each dataset's native space through transformation inversion to compare performance within atlas regions across subjects, scanners, and repetitions.
Results
Voxel values within MRF‐derived maps were found to be more repeatable (σT1 = 1.90, σT2 = 3.20) across sessions than vendor‐reconstructed MPRAGE (σT1w = 6.04) or turbo spin echo (σT2w = 5.66) images. Additionally, MRF was found to be more reproducible across scanners (σT1 = 2.21, σT2 = 3.89) than either qualitative modality (σT1w = 7.84, σT2w = 7.76). Notably, differences between repeatability and reproducibility of in vivo MRF were insignificant, unlike the weighted images.
Conclusion
MRF data from many sessions and scanners can potentially be treated as a single dataset for harmonized analysis or longitudinal comparisons without the additional regularization steps needed for qualitative modalities. |
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| AbstractList | Quantitative MRI techniques such as MR fingerprinting (MRF) promise more objective and comparable measurements of tissue properties at the point-of-care than weighted imaging. However, few direct cross-modal comparisons of MRF's repeatability and reproducibility versus weighted acquisitions have been performed. This work proposes a novel fully automated pipeline for quantitatively comparing cross-modal imaging performance in vivo via atlas-based sampling.PURPOSEQuantitative MRI techniques such as MR fingerprinting (MRF) promise more objective and comparable measurements of tissue properties at the point-of-care than weighted imaging. However, few direct cross-modal comparisons of MRF's repeatability and reproducibility versus weighted acquisitions have been performed. This work proposes a novel fully automated pipeline for quantitatively comparing cross-modal imaging performance in vivo via atlas-based sampling.We acquire whole-brain 3D-MRF, turbo spin echo, and MPRAGE sequences three times each on two scanners across 10 subjects, for a total of 60 multimodal datasets. The proposed automated registration and analysis pipeline uses linear and nonlinear registration to align all qualitative and quantitative DICOM stacks to Montreal Neurological Institute (MNI) 152 space, then samples each dataset's native space through transformation inversion to compare performance within atlas regions across subjects, scanners, and repetitions.METHODSWe acquire whole-brain 3D-MRF, turbo spin echo, and MPRAGE sequences three times each on two scanners across 10 subjects, for a total of 60 multimodal datasets. The proposed automated registration and analysis pipeline uses linear and nonlinear registration to align all qualitative and quantitative DICOM stacks to Montreal Neurological Institute (MNI) 152 space, then samples each dataset's native space through transformation inversion to compare performance within atlas regions across subjects, scanners, and repetitions.Voxel values within MRF-derived maps were found to be more repeatable (σT1 = 1.90, σT2 = 3.20) across sessions than vendor-reconstructed MPRAGE (σT1w = 6.04) or turbo spin echo (σT2w = 5.66) images. Additionally, MRF was found to be more reproducible across scanners (σT1 = 2.21, σT2 = 3.89) than either qualitative modality (σT1w = 7.84, σT2w = 7.76). Notably, differences between repeatability and reproducibility of in vivo MRF were insignificant, unlike the weighted images.RESULTSVoxel values within MRF-derived maps were found to be more repeatable (σT1 = 1.90, σT2 = 3.20) across sessions than vendor-reconstructed MPRAGE (σT1w = 6.04) or turbo spin echo (σT2w = 5.66) images. Additionally, MRF was found to be more reproducible across scanners (σT1 = 2.21, σT2 = 3.89) than either qualitative modality (σT1w = 7.84, σT2w = 7.76). Notably, differences between repeatability and reproducibility of in vivo MRF were insignificant, unlike the weighted images.MRF data from many sessions and scanners can potentially be treated as a single dataset for harmonized analysis or longitudinal comparisons without the additional regularization steps needed for qualitative modalities.CONCLUSIONMRF data from many sessions and scanners can potentially be treated as a single dataset for harmonized analysis or longitudinal comparisons without the additional regularization steps needed for qualitative modalities. PurposeQuantitative MRI techniques such as MR fingerprinting (MRF) promise more objective and comparable measurements of tissue properties at the point‐of‐care than weighted imaging. However, few direct cross‐modal comparisons of MRF's repeatability and reproducibility versus weighted acquisitions have been performed. This work proposes a novel fully automated pipeline for quantitatively comparing cross‐modal imaging performance in vivo via atlas‐based sampling.MethodsWe acquire whole‐brain 3D‐MRF, turbo spin echo, and MPRAGE sequences three times each on two scanners across 10 subjects, for a total of 60 multimodal datasets. The proposed automated registration and analysis pipeline uses linear and nonlinear registration to align all qualitative and quantitative DICOM stacks to Montreal Neurological Institute (MNI) 152 space, then samples each dataset's native space through transformation inversion to compare performance within atlas regions across subjects, scanners, and repetitions.ResultsVoxel values within MRF‐derived maps were found to be more repeatable (σT1 = 1.90, σT2 = 3.20) across sessions than vendor‐reconstructed MPRAGE (σT1w = 6.04) or turbo spin echo (σT2w = 5.66) images. Additionally, MRF was found to be more reproducible across scanners (σT1 = 2.21, σT2 = 3.89) than either qualitative modality (σT1w = 7.84, σT2w = 7.76). Notably, differences between repeatability and reproducibility of in vivo MRF were insignificant, unlike the weighted images.ConclusionMRF data from many sessions and scanners can potentially be treated as a single dataset for harmonized analysis or longitudinal comparisons without the additional regularization steps needed for qualitative modalities. Quantitative MRI techniques such as MR fingerprinting (MRF) promise more objective and comparable measurements of tissue properties at the point-of-care than weighted imaging. However, few direct cross-modal comparisons of MRF's repeatability and reproducibility versus weighted acquisitions have been performed. This work proposes a novel fully automated pipeline for quantitatively comparing cross-modal imaging performance in vivo via atlas-based sampling. We acquire whole-brain 3D-MRF, turbo spin echo, and MPRAGE sequences three times each on two scanners across 10 subjects, for a total of 60 multimodal datasets. The proposed automated registration and analysis pipeline uses linear and nonlinear registration to align all qualitative and quantitative DICOM stacks to Montreal Neurological Institute (MNI) 152 space, then samples each dataset's native space through transformation inversion to compare performance within atlas regions across subjects, scanners, and repetitions. Voxel values within MRF-derived maps were found to be more repeatable (σ = 1.90, σ = 3.20) across sessions than vendor-reconstructed MPRAGE (σ = 6.04) or turbo spin echo (σ = 5.66) images. Additionally, MRF was found to be more reproducible across scanners (σ = 2.21, σ = 3.89) than either qualitative modality (σ = 7.84, σ = 7.76). Notably, differences between repeatability and reproducibility of in vivo MRF were insignificant, unlike the weighted images. MRF data from many sessions and scanners can potentially be treated as a single dataset for harmonized analysis or longitudinal comparisons without the additional regularization steps needed for qualitative modalities. Purpose Quantitative MRI techniques such as MR fingerprinting (MRF) promise more objective and comparable measurements of tissue properties at the point‐of‐care than weighted imaging. However, few direct cross‐modal comparisons of MRF's repeatability and reproducibility versus weighted acquisitions have been performed. This work proposes a novel fully automated pipeline for quantitatively comparing cross‐modal imaging performance in vivo via atlas‐based sampling. Methods We acquire whole‐brain 3D‐MRF, turbo spin echo, and MPRAGE sequences three times each on two scanners across 10 subjects, for a total of 60 multimodal datasets. The proposed automated registration and analysis pipeline uses linear and nonlinear registration to align all qualitative and quantitative DICOM stacks to Montreal Neurological Institute (MNI) 152 space, then samples each dataset's native space through transformation inversion to compare performance within atlas regions across subjects, scanners, and repetitions. Results Voxel values within MRF‐derived maps were found to be more repeatable (σT1 = 1.90, σT2 = 3.20) across sessions than vendor‐reconstructed MPRAGE (σT1w = 6.04) or turbo spin echo (σT2w = 5.66) images. Additionally, MRF was found to be more reproducible across scanners (σT1 = 2.21, σT2 = 3.89) than either qualitative modality (σT1w = 7.84, σT2w = 7.76). Notably, differences between repeatability and reproducibility of in vivo MRF were insignificant, unlike the weighted images. Conclusion MRF data from many sessions and scanners can potentially be treated as a single dataset for harmonized analysis or longitudinal comparisons without the additional regularization steps needed for qualitative modalities. |
| Author | Griswold, Mark A. Boyacioglu, Rasim Hansen, Michael Badve, Chaitra Ma, Dan Dupuis, Andrew Chen, Yong Chow, Kelvin Sun, Jessie E. P. |
| Author_xml | – sequence: 1 givenname: Andrew orcidid: 0000-0002-3714-4812 surname: Dupuis fullname: Dupuis, Andrew email: andrew.dupuis@case.edu organization: Case Western Reserve University – sequence: 2 givenname: Yong orcidid: 0000-0001-6183-2693 surname: Chen fullname: Chen, Yong organization: University Hospitals – sequence: 3 givenname: Michael orcidid: 0000-0002-8087-8731 surname: Hansen fullname: Hansen, Michael organization: Microsoft Research – sequence: 4 givenname: Kelvin orcidid: 0000-0003-0698-1746 surname: Chow fullname: Chow, Kelvin organization: Siemens Medical Solutions USA, Inc – sequence: 5 givenname: Jessie E. P. orcidid: 0000-0003-4659-9883 surname: Sun fullname: Sun, Jessie E. P. organization: Case Western Reserve University – sequence: 6 givenname: Chaitra orcidid: 0000-0001-8547-8019 surname: Badve fullname: Badve, Chaitra organization: University Hospitals – sequence: 7 givenname: Dan orcidid: 0000-0003-1664-9579 surname: Ma fullname: Ma, Dan organization: Case Western Reserve University – sequence: 8 givenname: Mark A. orcidid: 0000-0002-3011-6747 surname: Griswold fullname: Griswold, Mark A. organization: Case Western Reserve University – sequence: 9 givenname: Rasim orcidid: 0000-0002-3099-2640 surname: Boyacioglu fullname: Boyacioglu, Rasim organization: Case Western Reserve University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/38192239$$D View this record in MEDLINE/PubMed |
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| Keywords | quantitative imaging repeatability MR fingerprinting relaxation mapping Bland Altman precision |
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Quantitative MRI techniques such as MR fingerprinting (MRF) promise more objective and comparable measurements of tissue properties at the... Quantitative MRI techniques such as MR fingerprinting (MRF) promise more objective and comparable measurements of tissue properties at the point-of-care than... PurposeQuantitative MRI techniques such as MR fingerprinting (MRF) promise more objective and comparable measurements of tissue properties at the point‐of‐care... |
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| SubjectTerms | Automation Bland Altman Brain - diagnostic imaging Datasets Fingerprinting Humans Image Processing, Computer-Assisted - methods In vivo methods and tests Magnetic Resonance Imaging - methods Medical imaging MR fingerprinting Neuroimaging Phantoms, Imaging precision Qualitative analysis quantitative imaging Regularization relaxation mapping repeatability Reproducibility Reproducibility of Results Scanners |
| Title | Quantifying 3D MR fingerprinting (3D‐MRF) reproducibility across subjects, sessions, and scanners automatically using MNI atlases |
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