| Literature DB >> 26736738 |
Elisa Roccia, Arthur Mikhno, Francesca Zanderigo, Elsa D Angelini, R Todd Ogden, J John Mann, Andrew F Laine.
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.Entities:
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Year: 2015 PMID： 26736738 DOI： 10.1109/EMBC.2015.7318838
Source DB: PubMed Journal: Conf Proc IEEE Eng Med Biol Soc ISSN： 1557-170X