title: Non-invasive quantification of brain [¹⁸F]-FDG uptake by combining medical health records and dynamic PET imaging data.
abstract: Quantification of regional cerebral metabolic rate of glucose (rCMRglu) via positron emission tomography (PET) imaging requires measuring the arterial input function (AIF) via invasive arterial blood sampling. In this study we describe a non-invasive approach, the non-invasive simultaneous estimation (nSIME), for the estimation of rCMRglu that considers a pharmacokinetic input function model and constraints derived from machine learning applied to a fusion of individual medical health records and dynamic [(18)F]-FDG-PET brain images data. The results obtained with our data indicate potential for future clinical application of nSIME, with correlation measures of 0.87 for rCMRglu compared to quantification with full arterial blood sampling.
authors.forename: Elisa
authors.initials: E
authors.lastname: Roccia
authors.forename: Arthur
authors.initials: A
authors.lastname: Mikhno
authors.forename: Francesca
authors.initials: F
authors.lastname: Zanderigo
authors.forename: Elsa D
authors.initials: ED
authors.lastname: Angelini
authors.forename: R Todd
authors.initials: RT
authors.lastname: Ogden
authors.forename: J John
authors.initials: JJ
authors.lastname: Mann
authors.forename: Andrew F
authors.initials: AF
authors.lastname: Laine
mesh_terms: D001158:Arteries / Q000378:metabolism; D001786:Blood Glucose / Q000032:analysis; D001921:Brain / Q000000981:diagnostic imaging / Q000378:metabolism*; D019788:Fluorodeoxyglucose F18 / Q000737:chemistry / Q000378:metabolism; D005947:Glucose / Q000378:metabolism; D006801:Humans; D000069550:Machine Learning; D049268:Positron-Emission Tomography; D011859:Radiography; D019275:Radiopharmaceuticals / Q000737:chemistry / Q000378:metabolism*
chemical_list: D001786:Blood Glucose; D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18; D005947:Glucose