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Whole brain MRI-free tau and amyloid PET quantification

dc.contributor.authorWard, Tyler J.
dc.contributor.authorHarrison, Theresa M.
dc.contributor.authorMurphy, Alice
dc.contributor.authorBaker, Suzanne L.
dc.contributor.authorMormino, Elizabeth C.
dc.contributor.authorKoeppe, Robert A.
dc.contributor.authorJagust, William J.
dc.contributor.authorLandau, Susan M.
dc.date.accessioned2023-01-11T16:22:59Z
dc.date.available2024-01-11 11:22:58en
dc.date.available2023-01-11T16:22:59Z
dc.date.issued2022-12
dc.identifier.citationWard, Tyler J.; Harrison, Theresa M.; Murphy, Alice; Baker, Suzanne L.; Mormino, Elizabeth C.; Koeppe, Robert A.; Jagust, William J.; Landau, Susan M. (2022). "Whole brain MRI-free tau and amyloid PET quantification." Alzheimer’s & Dementia 18: n/a-n/a.
dc.identifier.issn1552-5260
dc.identifier.issn1552-5279
dc.identifier.urihttps://hdl.handle.net/2027.42/175428
dc.description.abstractBackgroundThe growing use of PET imaging in Alzheimer’s research and clinical practice has resulted in the need for PET quantification when an MRI is unavailable or contraindicated. The Desikan-Killiany (DK) atlas in Freesurfer (FS) is often used in conjunction with a native space MRI to define regions of interest for tau and amyloid PET quantification. Here we developed a template-space DK atlas for use in MRI-free amyloid & tau quantification, and validated the performance of the template using MRI-free florbetapir and flortaucipir SUVrs in relation to our gold standard native space SUVrs.MethodTo develop a template-space atlas made up of 112 DK regions identical to those used in our native-space, MRI-dependent pipeline, we segmented T1 MRIs from a subset of 200 cognitively normal ADNI participants using Freesurfer 7.1. Each binary region was nonlinearly warped to template space, smoothed, and averaged across the 200 MRIs to create 112 ROI probability maps (Fig 1A). Each region probability map was normalized between 0 and 1 then merged together into a single template-space atlas by ranking each voxel in relation to each ROI (Fig 1B). To calculate MRI-free SUVrs, ADNI baseline flortaucipir (n=768) and florbetapir (n=1290) images were spatially normalized to PET-only, tracer-specific templates developed in subsets of ADNI scans. We examined several key amyloid and tau target SUVrs based on the MRI-free atlas in relation to corresponding MRI-dependent SUVrs calculated using our gold standard pipeline.ResultMRI-free region-wise cortical SUVRs were highly correlated with their MRI-dependent counterparts for both florbetapir (average R2 across cortical ROIs = 0.80, cortical summary R2 = 0.84; Fig 2A) and flortaucipir (average R2 across cortical ROIs = 0.87, entorhinal R2 = 0.88, temporal metaROI R2 = 0.97; Fig 2B). Positive/negative status agreement between MRI-free and MRI-dependent approaches using previously-validated MRI-dependent thresholds was 91% (Aβ) and 92% (temporal metaROI tau).ConclusionAmyloid and tau SUVRs and +/− status calculated using a template-space DK atlas are comparable to those calculated using our gold standard MRI-dependent approach. This MRI-free approach will be useful for region-wise PET quantification when structural scans are unavailable.
dc.publisherWiley Periodicals, Inc.
dc.titleWhole brain MRI-free tau and amyloid PET quantification
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelNeurology and Neurosciences
dc.subject.hlbtoplevelHealth Sciences
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/175428/1/alz063456.pdf
dc.identifier.doi10.1002/alz.063456
dc.identifier.sourceAlzheimer’s & Dementia
dc.working.doiNOen
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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