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The Use of Random Forests to Identify Brain Regions on Amyloid and FDG PET Associated With MoCA Score

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dc.contributor.authorZukotynski, Katherine
dc.contributor.authorGaudet, Vincent C.
dc.contributor.authorKuo, Phillip H.
dc.contributor.authorAdamo, Sabrina
dc.contributor.authorGoubran, Maged
dc.contributor.authorScott, Christopher J.M.
dc.contributor.authorBocti, Christian
dc.contributor.authorBorrie, Michael
dc.contributor.authorChertkow, Howard
dc.contributor.authorFrayne, Richard
dc.contributor.authorHsiung, Robin
dc.contributor.authorLaforce, Robert Jr
dc.contributor.authorNoseworthy, Michael D.
dc.contributor.authorPrato, Frank S.
dc.contributor.authorSahlas, Demetrios J.
dc.contributor.authorSmith, Eric E.
dc.contributor.authorSossi, Vesna
dc.contributor.authorThiel, Alexander
dc.contributor.authorSoucy, Jean-Paul
dc.contributor.authorTardif, Jean-Claude
dc.contributor.authorBlack, Sandra E.
dc.date.accessioned2023-11-03T17:38:37Z
dc.date.available2023-11-03T17:38:37Z
dc.date.issued2020-06
dc.descriptionCopyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.en
dc.description.abstractPurpose: The aim of this study was to evaluate random forests (RFs) to identify ROIs on 18F-florbetapir and 18F-FDG PET associated with Montreal Cognitive Assessment (MoCA) score. Materials and Methods: Fifty-seven subjects with significant white matter disease presenting with either transient ischemic attack/lacunar stroke or mild cognitive impairment from early Alzheimer disease, enrolled in a mul- ticenter prospective observational trial, had MoCA and 18F-florbetapir PET; 55 had 18F-FDG PET. Scans were processed using the MINC toolkit to gen- erate SUV ratios, normalized to cerebellar gray matter (18F-florbetapir PET), or pons (18F-FDG PET). SUV ratio data and MoCA score were used for su- pervised training of RFs programmed in MATLAB. Results: 18F-Florbetapir PETs were randomly divided into 40 training and 17 testing scans; 100 RFs of 1000 trees, constructed from a random subset of 16 training scans and 20 ROIs, identified ROIs associated with MoCA score: right posterior cingulate gyrus, right anterior cingulate gyrus, left precuneus, left posterior cingulate gyrus, and right precuneus. Amyloid in- creased with decreasing MoCA score. 18F-FDG PETs were randomly di- vided into 40 training and 15 testing scans; 100 RFs of 1000 trees, each tree constructed from a random subset of 16 training scans and 20 ROIs, identified ROIs associated with MoCA score: left fusiform gyrus, left precuneus, left posterior cingulate gyrus, right precuneus, and left middle orbitofrontal gyrus. 18F-FDG decreased with decreasing MoCA score. Conclusions: Random forests help pinpoint clinically relevant ROIs associ- ated with MoCA score; amyloid increased and 18F-FDG decreased with de- creasing MoCA score, most significantly in the posterior cingulate gyrus.en
dc.description.sponsorshipCIHR MITNEC C6 || Linda C Campbell Foundation || Lilly-Avid Radiopharmaceuticals.en
dc.identifier.urihttps://doi.org/10.1097/rlu.0000000000003043
dc.identifier.urihttp://hdl.handle.net/10012/20084
dc.language.isoenen
dc.publisherWolters Kluwer Healthen
dc.relation.ispartofseriesClinical Nuclear Medicine;45(6)
dc.subjectamyloiden
dc.subjectF-FDGen
dc.subjectPETen
dc.subjectrandom foresten
dc.subjectMontreal Cognitive Assessment scoreen
dc.titleThe Use of Random Forests to Identify Brain Regions on Amyloid and FDG PET Associated With MoCA Scoreen
dc.typeArticleen
dcterms.bibliographicCitationZukotynski, K., Gaudet, V., Kuo, P. H., Adamo, S., Goubran, M., Scott, C. J. M., Bocti, C., Borrie, M., Chertkow, H., Frayne, R., Hsiung, R., Laforce, R., Noseworthy, M. D., Prato, F. S., Sahlas, D. J., Smith, E. E., Sossi, V., Thiel, A., Soucy, J.-P., Tardif, J.-C. & Black, S. E. (2020). The use of random forests to identify brain regions on amyloid and FDG PET associated with MOCA score. Clinical Nuclear Medicine, 45(6), 427–433. https://doi.org/10.1097/rlu.0000000000003043en
uws.contributor.affiliation1Faculty of Engineeringen
uws.contributor.affiliation2Electrical and Computer Engineeringen
uws.peerReviewStatusRevieweden
uws.scholarLevelFacultyen
uws.typeOfResourceTexten

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