Investigating time-independent and time-dependent diffusion phenomena using steady-state diffusion MRI
Abstract Diffusion MRI is a leading method to non-invasively characterise brain tissue microstructure across multiple domains and scales. Diffusion-weighted steady-state free precession (DW-SSFP) is an established imaging sequence for post-mortem MRI, addressing the challenging imaging environment o...
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Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-87377-x |
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| author | Benjamin C. Tendler |
| author_facet | Benjamin C. Tendler |
| author_sort | Benjamin C. Tendler |
| collection | DOAJ |
| description | Abstract Diffusion MRI is a leading method to non-invasively characterise brain tissue microstructure across multiple domains and scales. Diffusion-weighted steady-state free precession (DW-SSFP) is an established imaging sequence for post-mortem MRI, addressing the challenging imaging environment of fixed tissue with short T2 and low diffusivities. However, a current limitation of DW-SSFP is signal interpretation: it is not clear what diffusion ‘regime’ the sequence probes and therefore its potential to characterise tissue microstructure. Building on Extended Phase Graphs (EPG), I establish two alternative representations of the DW-SSFP signal in terms of (1) conventional b-values (time-independent diffusion) and (2) encoding power-spectra (time-dependent diffusion). The proposed representations provide insights into how different parameter regimes and gradient waveforms impact the diffusion sensitivity of DW-SSFP. I subsequently introduce an approach to incorporate existing biophysical models into DW-SSFP without the requirement of extensive derivations, with time dependence estimated via a Gaussian phase approximation representation of the DW-SSFP signal. Investigations incorporating free-diffusion and tissue-relevant microscopic restrictions (cylinder of varying radius) give excellent agreement to complementary analytical models and Monte Carlo simulations. Experimentally, the time-independent representation is used to derive Tensor and proof-of-principle NODDI estimates in a whole human post-mortem brain. A final SNR-efficiency investigation demonstrates the theoretical potential of DW-SSFP for ultra-high field microstructural imaging. |
| format | Article |
| id | doaj-art-1ed6a99fafd4466f997da9e026da61da |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-1ed6a99fafd4466f997da9e026da61da2025-02-02T12:15:48ZengNature PortfolioScientific Reports2045-23222025-01-0115112210.1038/s41598-025-87377-xInvestigating time-independent and time-dependent diffusion phenomena using steady-state diffusion MRIBenjamin C. Tendler0Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordAbstract Diffusion MRI is a leading method to non-invasively characterise brain tissue microstructure across multiple domains and scales. Diffusion-weighted steady-state free precession (DW-SSFP) is an established imaging sequence for post-mortem MRI, addressing the challenging imaging environment of fixed tissue with short T2 and low diffusivities. However, a current limitation of DW-SSFP is signal interpretation: it is not clear what diffusion ‘regime’ the sequence probes and therefore its potential to characterise tissue microstructure. Building on Extended Phase Graphs (EPG), I establish two alternative representations of the DW-SSFP signal in terms of (1) conventional b-values (time-independent diffusion) and (2) encoding power-spectra (time-dependent diffusion). The proposed representations provide insights into how different parameter regimes and gradient waveforms impact the diffusion sensitivity of DW-SSFP. I subsequently introduce an approach to incorporate existing biophysical models into DW-SSFP without the requirement of extensive derivations, with time dependence estimated via a Gaussian phase approximation representation of the DW-SSFP signal. Investigations incorporating free-diffusion and tissue-relevant microscopic restrictions (cylinder of varying radius) give excellent agreement to complementary analytical models and Monte Carlo simulations. Experimentally, the time-independent representation is used to derive Tensor and proof-of-principle NODDI estimates in a whole human post-mortem brain. A final SNR-efficiency investigation demonstrates the theoretical potential of DW-SSFP for ultra-high field microstructural imaging.https://doi.org/10.1038/s41598-025-87377-x |
| spellingShingle | Benjamin C. Tendler Investigating time-independent and time-dependent diffusion phenomena using steady-state diffusion MRI Scientific Reports |
| title | Investigating time-independent and time-dependent diffusion phenomena using steady-state diffusion MRI |
| title_full | Investigating time-independent and time-dependent diffusion phenomena using steady-state diffusion MRI |
| title_fullStr | Investigating time-independent and time-dependent diffusion phenomena using steady-state diffusion MRI |
| title_full_unstemmed | Investigating time-independent and time-dependent diffusion phenomena using steady-state diffusion MRI |
| title_short | Investigating time-independent and time-dependent diffusion phenomena using steady-state diffusion MRI |
| title_sort | investigating time independent and time dependent diffusion phenomena using steady state diffusion mri |
| url | https://doi.org/10.1038/s41598-025-87377-x |
| work_keys_str_mv | AT benjaminctendler investigatingtimeindependentandtimedependentdiffusionphenomenausingsteadystatediffusionmri |