1. J OURNAL C LUB : Deoni et al. One Component? Two Components? Three? The Effect of Including a Nonexchanging ‘‘Free’’ Water Component in mcDESPOT. Jan 14, 2013 Jason Su

2. Motivation mcDESPOT provides fast, whole-brain estimation of myelin water fraction – However, its accuracy near CSF may be questionable due to partial voluming – A third non-exchanging component in the tissue model may allow this to be accounted for Lankford has recently criticized the precision of mcDESPOT with an unbiased fitting algorithm – Is this observed in practice with constrained SRC?

3. Theory The mcDESPOT signal equations are expanded to include a 3 rd component or free water pool – This is a straightforward extension of the block diagonal matrices with some key assumptions, 10 total parameters – Adds 3 new parameters: T1, T2, and volume fraction of the free pool 1500 < T1 free <7500ms; 150ms < T2 free < 1000ms; 0 < F free < 0.75 – The free pool is nonexchanging, avoids adding 2 possible new exchange rate parameters Assumes that it models CSF separated by the blood-brain barrier The IE pool is at least 5% of the volume of the voxel

4. Concerns Is degeneracy possible? Can myelin and IE pools be confused with each other? – In 2-pool model, this can occur if MWF is allowed to be ≥0.5 – What if here free pool is 0.2, the remaining 0.8 could be split between MWF and IE interchangeably, is this taken care of? SRC algorithm – Ignoring some fundamental issues I’ve encountered, i.e. mean normalization and off-resonance as a cyclic dimension – Not stated whether it usually converges or ends due to hitting the iteration limit In my simulations, it’s usually the latter

5. Methods Simulation – Simulated a 3-component model 50,000x each over a range of tissue parameters and fitted with 2- or 3- component models In-vivo at 3T – protocol is the same as with 2- component, 8 SPGR and 8 SSFP, and low-res IR-SPGR for DESPOT-HIFI B1 maps – Intra-subject repeatability 24yo male, 5 times over 5 weeks – Inter-subject variability 10 1yo infants Why infants? To accentuate variability?

6. Results – Simulation

7. Notes Seems to be a fair amount of bias in F free estimate, almost 8% Histograms in general are fairly large with a width of about 0.08-0.11 – My own simulations show similar or worse performance in two-pool models with SNR of 20- 30 – Not sure how much noise was added in theirs

8. Product mcDESPOT

9. Modified mcDESPOT – w/o Noise

10. Modified mcDESPOT

12. Notes The 2-pool model tends to underestimate the MWF in regions near CSF compared to 3-pool – Makes sense, uses more of longer IE component as a surrogate Would’ve liked to see this in MS brain with variety of lesions – Especially because there is the question of whether edema would allow exchange with 3 rd pool

13. Results – Curves

14. Notes BIC is a criterion that’s often used to compare fitting models – Penalizes for number of parameters, promotes a simpler model to avoid overfitting – Closely related to Mallow’s Cp for linear models – Is a heuristic, cross validation is better for evaluating predictive value of a model but may not work here SSFP fits are kind of iffy, particularly phase 0

15. Results – Reproducibility and Variability

16. Notes Shows the characteristic behavior of low MWF CoV in white matter, high CoV in gray What registration was used for the inter-subject data? Hard to interpret the intra-subject vs inter-subject results – Are 1yo infants supposed to have about the same amount of myelination, how variable is it in development? – Intra-subject variation is half of inter-subject, either MWF doesn’t vary much between infants or high variability in subject? Is 5 samples enough for CoV? Algorithm reproducibility is bad near edges/CSF? – Wonder what this looks like for 2-pool

17. MWF Variation in Infants Deoni et al. Investigating white matter development in infancy and early childhood using myelin water faction and relaxation time mapping. Neuroimage. 2012 Nov 15;63(3):1038-53.

18. Discussion 3% deviation in homogeneous WM and GM compared to 2-pool – Is it worth changing model depending on location in brain? Is it possible in histology to examine if such a free pool in tissue is real? – The need for a 3 rd pool arises out of need to account for partial voluming, so phantoms should study that not necessarily 3-component mixture – Examine the effects on 3 rd pool as introduce more partial voluming, we could be able to precisely change the F free depending on voxel size?

19. Discussion Concerned about even more reduced precision compared to 2-pool – Variability of MWF near edges may indicate 3-pool model is hard to estimate where it counts. – CoV of F free map? – Surprising that there is nothing added to the acquisition Can we really get a 3-pool fit for free from what we have already? CRLB would say otherwise.