Spatial Registration Evaluation of [18F]-MK6240 PET

Zou, James Shiyang; Johnson, Aubrey S.; France, Jeanelle K.; Bharadwaj, Srinidhi; Tomljanovic, Zeljko; Stern, Yaakov; Brickman, Adam M.; Devanand, Devangere P.; Luchsinger, Jose A.; Kreisl, William Charles; Provenzano, Frank A.

Image registration is an important preprocessing step in neuroimaging which allows for the matching of anatomical and functional information between modalities and subjects. This can be challenging if there are gross differences in image geometry or in signal intensity, such as in the case of some molecular PET radioligands, where control subjects display relative lack of signal relative to noise within intracranial regions, and may have off target binding that may be confused as other regions, and may vary depending on subject. The use of intermediary images or volumes have been shown to aide registration in such cases.
To account for this phenomena within our own longitudinal aging cohort, we generated a population specific MRI and PET template from a broad distribution of 30 amyloid negative subjects. We then registered the PET image of each of these subjects, as well as a holdout set of thirty 'template-naive' subjects to their corresponding MRI images using the template image as an intermediate using three different sets of registration parameters and procedures. To evaluate the performance of both conventional registration and our method, we compared these to the registration of the attenuation CT (acquired at time of PET acquisition) to MRI as the reference. We then used our template to directly derive SUVR values without the use of MRI.
We found that conventional registration was comparable to an existing CT based standard, and there was no significant difference in errors collectively amongst all methods tested. In addition, there were no significant differences between existing and MR-less tau PET quantification methods. We conclude that a template-based method is a feasible alternative to, or salvage for, direct registration and MR-less quantification; and, may be preferred in cases where there is doubt about the similarity between two image modalities.


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May 4, 2021