journal article·2024-07Open access

High Spatiotemporal Resolution Radial Encoding Single‐Vessel fMRI

Yuanyuan Jiang, Patricia Pais‐Roldán, Rolf Pohmann, Xin Yu

Advanced Science· Volume 11· Issue 26

Abstract

Abstract High‐field preclinical functional MRI (fMRI) is enabled the high spatial resolution mapping of vessel‐specific hemodynamic responses, that is single‐vessel fMRI. In contrast to investigating the neuronal sources of the fMRI signal, single‐vessel fMRI focuses on elucidating its vascular origin, which can be readily implemented to identify vascular changes relevant to vascular dementia or cognitive impairment. However, the limited spatial and temporal resolution of fMRI is hindered hemodynamic mapping of intracortical microvessels. Here, the radial encoding MRI scheme is implemented to measure BOLD signals of individual vessels penetrating the rat somatosensory cortex. Radial encoding MRI is employed to map cortical activation with a focal field of view (FOV), allowing vessel‐specific functional mapping with 50 × 50 µm 2 in‐plane resolution at a 1 to 2 Hz sampling rate. Besides detecting refined hemodynamic responses of intracortical micro‐venules, the radial encoding‐based single‐vessel fMRI enables the distinction of fMRI signals from vessel and peri‐vessel voxels due to the different contribution of intravascular and extravascular effects.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Advanced MRI Techniques and Applications · Functional Brain Connectivity Studies · Advanced Neuroimaging Techniques and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital and Harvard Medical School Charlestown MA 02129 USA

Institute of Neuroscience and Medicine 4 Medical Imaging Physics Forschungszentrum Jülich 52425 Jülich Germany

High‐Field Magnetic Resonance Max Planck Institute for Biological Cybernetics 72076 Tübingen Germany

Funding

National Institutes of Health · National Science Foundation

References (54)

Show source-provided references
1. 10.1073/pnas.89.12.567510.1073/pnas.89.12.5675 ↗
2. 10.1002/mrm.191025022010.1002/mrm.1910250220 ↗
3. 10.1073/pnas.89.13.595110.1073/pnas.89.13.5951 ↗
4. 10.1126/science.194805110.1126/science.1948051 ↗
5. 10.1038/jcbfm.2012.2310.1038/jcbfm.2012.23 ↗
6. 10.1093/cercor/bhm25910.1093/cercor/bhm259 ↗
7. 10.1016/j.neuron.2021.02.00610.1016/j.neuron.2021.02.006 ↗
8. 10.1038/nature0910810.1038/nature09108 ↗
9. 10.1038/nmeth.376510.1038/nmeth.3765 ↗
10. 10.1177/0271678X1561942810.1177/0271678X15619428 ↗
11. 10.1016/j.neuroimage.2017.02.02010.1016/j.neuroimage.2017.02.020 ↗
12. 10.1016/j.neuroimage.2017.01.02810.1016/j.neuroimage.2017.01.028 ↗
13. 10.1016/j.neuroimage.2018.06.02510.1016/j.neuroimage.2018.06.025 ↗
14. 10.1016/j.cobme.2021.10028810.1016/j.cobme.2021.100288 ↗
15. 10.1002/mrm.2589010.1002/mrm.25890 ↗
16. 10.1016/j.neuron.2018.01.02510.1016/j.neuron.2018.01.025 ↗
17. 10.1177/0271678X1988624010.1177/0271678X19886240 ↗
18. 10.1016/j.neuroimage.2006.03.02710.1016/j.neuroimage.2006.03.027 ↗
19. 10.1016/j.neuroimage.2022.11967510.1016/j.neuroimage.2022.119675 ↗
20. 10.1371/journal.pbio.300092310.1371/journal.pbio.3000923 ↗
21. 10.1007/s00330-003-1957-x10.1007/s00330-003-1957-x ↗
22. 10.1016/j.neuroimage.2011.10.04010.1016/j.neuroimage.2011.10.040 ↗
23. 10.1016/j.neuroimage.2011.08.00110.1016/j.neuroimage.2011.08.001 ↗
24. 10.1073/pnas.110042810810.1073/pnas.1100428108 ↗
25. 10.1002/mrm.2124610.1002/mrm.21246 ↗
26. 10.1523/JNEUROSCI.3986-10.201110.1523/JNEUROSCI.3986-10.2011 ↗
27. 10.1016/j.neuroimage.2009.05.05110.1016/j.neuroimage.2009.05.051 ↗
28. 10.1038/s41592-019-0572-y10.1038/s41592-019-0572-y ↗
29. 10.1002/advs.20210558810.1002/advs.202105588 ↗
30. 10.1016/j.pacs.2019.10015310.1016/j.pacs.2019.100153 ↗
31. 10.1002/mrm.1025210.1002/mrm.10252 ↗
32. 10.1109/TMI.2007.90279910.1109/TMI.2007.902799 ↗
33. 10.1002/jmri.2818710.1002/jmri.28187 ↗
34. 10.1002/(SICI)1522-2594(200001)43:1<91::AID-MRM11>3.0.CO;2-410.1002/(SICI)1522-2594(200001)43:1<91::AID-MRM11>3.0.CO;2-4 ↗
35. 10.1002/mrm.2003610.1002/mrm.20036 ↗
36. 10.1109/TMI.2006.88533710.1109/TMI.2006.885337 ↗
37. 10.1002/mrm.2498010.1002/mrm.24980 ↗
38. 10.1002/mrm.2427610.1002/mrm.24276 ↗
39. 10.1002/mrm.2123610.1002/mrm.21236 ↗
40. 10.1126/science.abh434010.1126/science.abh4340 ↗
41. 10.1038/nmeth.273010.1038/nmeth.2730 ↗
42. 10.1073/pnas.22256189910.1073/pnas.222561899 ↗
43. 10.1016/j.neuron.2020.07.02010.1016/j.neuron.2020.07.020 ↗
44. 10.3389/fnins.2018.0078810.3389/fnins.2018.00788 ↗
45. 10.1016/j.neuroimage.2021.11863010.1016/j.neuroimage.2021.118630 ↗
46. 10.1006/nimg.2002.108210.1006/nimg.2002.1082 ↗
47. 10.1002/mrm.1043310.1002/mrm.10433 ↗
48. 10.1016/j.neuron.2012.09.01910.1016/j.neuron.2012.09.019 ↗
49. 10.1038/jcbfm.2010.16410.1038/jcbfm.2010.164 ↗
50. 10.1038/s41592-020-0941-610.1038/s41592-020-0941-6 ↗
51. 10.1016/j.neuroimage.2016.12.01810.1016/j.neuroimage.2016.12.018 ↗
52. 10.1016/j.pneurobio.2021.10217410.1016/j.pneurobio.2021.102174 ↗
53. 10.1073/pnas.100673510710.1073/pnas.1006735107 ↗
54. 10.1002/mrm.2566510.1002/mrm.25665 ↗