Abstract:
Quantification of regional cerebral metabolic rate of glucose (rCMRglu) via positron emission tomography (PET) imaging requires measuring the arterial input function (AIF...Show MoreMetadata
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 [18F]-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.
Published in: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Date of Conference: 25-29 August 2015
Date Added to IEEE Xplore: 05 November 2015
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PubMed ID: 26736738