Arterial spin tagging techniques originally used the one-compartment Kety model to describe the dynamics of tagged water in the brain. The work presented here develops a more realistic model that includes the contribution of tagged water in the capillary bed and accounts for the finite time required
Effect of magnetization transfer on the measurement of cerebral blood flow using steady-state arterial spin tagging approaches: A theoretical investigation
✍ Scribed by Alan C. McLaughlin; Frank Q. Ye; James J. Pekar; Attanagoda K. S. Santha; Joseph A. Frank
- Publisher
- John Wiley and Sons
- Year
- 1997
- Tongue
- English
- Weight
- 902 KB
- Volume
- 37
- Category
- Article
- ISSN
- 0740-3194
No coin nor oath required. For personal study only.
✦ Synopsis
Abstract
A simple four‐compartment model for magnetization transfer was used to obtain theoretical expressions for the relationship between regional cerebral blood flow and Δ__M__, the change in longitudinal magnetization of brain water spins when arterial water spins are perturbed. The theoretical relationship can be written in two forms, depending on the approach used to normalize Δ__M.__ Using the first approach, the calculation of cerebral blood flow requires a knowledge of R~1~ (ω~1~, Δω), the longitudinal relaxation rate observed in the presence of continuous off‐resonance RF irradiation. Using the second approach, the calculation of cerebral blood flow requires a knowledge of ℛ~1~(ω~1~, Δω), where ℛ~1~(ω~1~, Δω) is given by the product of R~1~(ω~1~, Δω) and the fractional steady‐state longitudinal water magnetization in the presence of off‐resonance RF irradiation. If the off‐resonance RF irradiation used for arterial tagging does not produce appreciable magnetization transfer effects, ℛ~1~, (ω~1~, Δω) can be approximated by the longitudinal relaxation rate measured in the absence of offresonance RF irradiation, R~1obs.~ Theoretical expressions obtained by using the four‐component model for magnetization transfer are compared with equivalent expressions obtained by using two‐compartment models.
📜 SIMILAR VOLUMES