MPRAGEpre – Image Quality Quality is fairly consistent throughout subjects but there are a couple notable outliers: P003 & P025.

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MPRAGEpre – Image Quality Quality is fairly consistent throughout subjects but there are a couple notable outliers: P003 & P025

Lesion Segmentation

Process Z-score-based (> 4) one-sided thresholding method on FLAIR registered to MNI 1mm 3 – > “raw MNI FLAIR z-score masks” Similar to tissue segmentation, this seemed to contain speckling that was not clearly associated with lesions to me Median filtering – > “filtered MNI FLAIR z-score masks” Used median filtering with a kernel of (3mm) 3 to reduce speckle I presented Hagen with the choice of editing either the raw filtered masks

Process Manual editing Hagen decided to go work from the raw MNI FLAIR z-score masks He found the median filtering to be overly aggressive and saw what I had considered as speckling as legitimate lesions Basic workflow was two passes: remove non-lesion matter such as misclassified skull, add back and correct any lesion boundaries Hagen focused heavily on the first step and after consideration, felt that most of the pre-lesion boundaries were adequate and actually advantageous because they were not generated by subjective human eyes

Post-Process Warping back to patient space, SPGR target Thresholding to recover a binary lesion mask Further editing?

P015 – Low CIS – MNI

P015 – Low CIS – FLAIR Space

P027 – High CIS – MNI

P027 – High CIS – FLAIR Space

P001 – RR – MNI

P001 – RR – FLAIR Space

P016 – SP – MNI

P016 – SP – FLAIR Space

P021 – PP – MNI

P021 – PP – FLAIR Space

Quality of Edits Free of any obvious skull defects Many lesions remain on sulci, suspicious given limits of standard space registration

Thresholding Relapsing case, P001: – Some lesions are very close to 0 in value, hard to tell if they should be thrown out Progressive case, P021: – Thresholds of preserve the sometimes smooth transition into surrounding normal tissue – For conservative lesion boundaries, 0.95 or higher After we settle on a value, compute the volume of “lost” voxels as a measure of how significant the reduction was

Remaining Work Tissue segmentation correction Reiss group multi-spectral segmentation as an alternative to our lesion masks