1. Journal Club: mcDESPOT with B0 & B1 Inhomogeneity

2. Papers Deoni et al. Gleaning multicomponent T1 and T2 information from steady-state imaging data. Magn. Reson. Med. (2008) vol. 60 (6) pp. 1372-1387 Deoni. Correction of main and transmit magnetic field (B0 and B1) inhomogeneity effects in multicomponent-driven equilibrium single-pulse observation of T1 and T2. Magn. Reson. Med. (2010)

3. mcDESPOT A whole-brain quantitative mapping technique Idea: collect SPGR and SSFP scans at several flip angles – These have a known theoretical steady-state signal equation – Fit the equation as it varies with flip angle to the collected data at each voxel – Gives us: T1, T2, and more Uses a two-compartment model for the signal equation: a fast and slow relaxing species in exchange

4. scDESPOT Theory DESPOT1: SPGR equation – Find M0 and T1, minimize (S SPGR -Ŝ SPGR ) 2 DESPOT2: SSFP equation – Given T1, find M0 and T2, minimize (S SSFP -Ŝ SSFP ) 2

5. mcDESPOT Theory 2 component SPGR equation – Find f F, f S, T 1,F, T 1,S, k FS =1/τ F, k SF =1/τ S

6. mcDESPOT Theory 2 component SSFP equation – Find M0 and T1, minimize (S SPGR -Ŝ SPGR ) 2

7. mcDESPOT Theory

8. Simplifying Assumptions 2 component model – Only need to find f F (the fast volume fraction) Chemical equilibrium – Allows us to eliminate finding k SF =1/τ S Both components are on the same resonance

9. Fitting Method Genetic Algorithm – Previous method, proved to be too slow Stochastic Region of Contraction – Current method, processing time is still substantial (about 24 hrs. for a 2mm isotropic brain) – Supposedly good for avoiding local minima – Not much literature on it (Berger and Silverman. Microphone Array Optimization by Stochastic Region Contraction.)

10. Stochastic Region of Contraction Has been offered as an alternative to simulated annealing, which can be slow but is very general SRC is good for objective functions with these characteristics: – Few large valleys, many small local minima is fine – The neighborhood around the global minimum is still lower than any other local minima – Depends on <100 variables

11. Stochastic Region of Contraction Given an initial N-dimensional, rectangular, search volume containing the global optimum – Explore the objective function with random points in the space – Systematically contract the volume until it reaches a satisfactorily small region that traps the global optimum

12. Stochastic Region of Contraction Algorithm – Define initial search space for: T 1,F&S, T 2,F&S, f F, τ F, Δω s – Treat this rectangular box as a uniform distribution and sample N times – Compute the objective function for each sample – Keep M of the best samples and define the new box based on the ranges of the variables in these samples – Rinse and repeat until convergence

13. Stochastic Region of Contraction

14. When Things Go Wrong Simulation of artifacts – B0 effects – B1 and slab profile effects The key assumption of mcDESPOT is that the prescribed flip angle is achieved everywhere in the volume Need to account for this if not the case In vivo at 1.5T (and some proof of concept 3T) – 4 normal volunteers

15. B0 Solutions B0 mapping DESPOT2-FM with phase-cycled SSFP – Requires collection of another set of 9 SSFP images – Modified signal equation and objective function as presented earlier

16. When Things Go Wrong: B0 Artifacts

18. B1 Solutions B1 mapping – AFI, niDALL, Bloch-Siegert DESPOT1-HIFI with IR-SPGR (1 component) – Requires addition of 1 IR-prepped scan – Details of signal equation to derive B1 map not covered here – Gives κ(r):

19. When Things Go Wrong: B1 Artifacts

23. In Vivo

25. B0 and B1 effects are not enough to account for the difference in MWF between mcDESPOT and T2-MCRI (usu. in range of 8-9%)

26. Conclusions DESPOT1-HIFI does well even thought slab profile changes with angle and assumes single component – Alternatives should be considered though since anatomical structures are visible on the maps: not the best B1 map – Bloch-Siegert seems compelling but need a way to incorporate slab profile as well DESPOT2-FM and phase-cycled SSFP has been a part of the protocol at 1.5T and should also stay when we move to 3T+ – Alternative B0 mapping methods should be considered if they offer a significant benefit in acquisition time

27. Other Avenues to Explore 3 component model, is another pool skewing the MWF? Are the 2 components actually on the same resonance?