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P025 MPRAGE Pre-Contrast

P025 MPRAGE Pre-Contrast. P025 MPRAGE w/ Z-Score < -4. Notes. This was accomplished by doing an inverse nonlinear warp from MNI to the SPGR FA 18, then to the MPRAGE space with a linear transform (ideally these transforms should be combined)

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P025 MPRAGE Pre-Contrast

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  1. P025 MPRAGE Pre-Contrast

  2. P025 MPRAGE w/ Z-Score < -4

  3. Notes • This was accomplished by doing an inverse nonlinear warp from MNI to the SPGR FA 18, then to the MPRAGE space with a linear transform (ideally these transforms should be combined) • Images are larger than shown, zoom in for more detail • Not all lesions are found by the z-score thresholding but a significant amount are • Large volumes of white matter are found to be significantly demyelinated: perhaps DAWM or actually revealing the “invisible disease”? • This was one the patients with a larger amount of low MWF volume, EDSS 5.0 SPMS

  4. Another Look at Multi-Channel Segmentation with FSL FAST

  5. MPRAGE • Same slices as shown in the z-score slides • Lesions of interest circled

  6. SPGR 3 class-CSF • Generally good CSF segmentation • Does not capture most lesions

  7. SPGR 3 class-GM • Includes some or all of lesions

  8. SPGR 3 class-WM • Matches nicely with the MPRAGE scan • Partially includes lesions

  9. SPGR 4 class-CSF • Generally worse than 3 class CSF

  10. SPGR 4 class-GM • More conservative estimate of GM, much fewer lesions included

  11. SPGR 4 class-More GM • Deep GM • Includes many of the lesions

  12. SPGR 4 class-WM • Does well at excluding most focal lesions but appears to be some partially including some • More conservative

  13. SPGR-FLAIR 3 class-CSF • Grabs most lesions • Unfortunately mis-classifies GM too

  14. SPGR-FLAIR 3 class-GM • Includes many regions previously seen as WM

  15. SPGR-FLAIR 3 class-WM • Good exclusion of lesions identified by z-score • Does poorly at WM and GM segmentation, misses some WM

  16. SPGR-FLAIR 4 class-CSF • Generally worse than 3 class CSF also • Chokes back mask too far

  17. SPGR-FLAIR 4 class-GM • Still misidentifies a lot of WM as GM • Catches edges of our lesions of interest

  18. SPGR-FLAIR 4 class-More GM • Again mis-includes a lot of WM

  19. SPGR-FLAIR 4 class-WM • Avoids lesions but also misses a lot of regular WM since those are misidentified as GM

  20. SPGR-T2-PD 3 class-CSF • Decent at outside brain CSF, though catches some WM • Does not get any CSF inside brain

  21. SPGR-T2-PD 3 class-GM • Captures our lesions of interest • Gets ventricle CSF • Not as good as SPGR 3 class

  22. SPGR-T2-PD 3 class-WM • Overly greedy WM • Misses focal lesions but gets GM

  23. SPGR-T2-PD 4 class-CSF • Same problems as with SPGR-T2-PD CSF segmentation

  24. SPGR-T2-PD 4 class-GM • GM + inner CSF • Catches darker lesions • Pretty poor, also gets WM

  25. SPGR-T2-PD 4 class-More GM • Catches some lesions but overall pretty garbagey • Doesn’t really correspond to a distinct tissue class

  26. SPGR-T2-PD 4 class-WM • A conservative estimate • Circled region shows possible inclusion of GM and missing of brain stem

  27. Best CSF • SPGR 3 class (includes some lesions) • SPGR-FLAIR 3 class (includes all lesions) • SPGR-T2-PD 3 class (useful for out of brain CSF, does not include lesions)

  28. Best WM • SPGR 3 class (best anatomically) • SPGR 4 class (conservative) • SPGR-FLAIR 4 class (more lesion exclusion)

  29. Best GM • SPGR 3 class (GM+lesions) • SPGR 4 class (deep GM+lesions)

  30. Best Lesion • SPGR 3 class (GM+lesions) • SPGR-FLAIR 3 class (CSF missing some lesions)

  31. Coming Soon • Segmentation with a priori maps • Ideas about how to combine maps to produce NAWM, NAGM, and lesion only masks

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