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Multiparametric measurement of cerebral physiology using calibrated fMRI. | LitMetric

Multiparametric measurement of cerebral physiology using calibrated fMRI.

Neuroimage

IBME, Department of Engineering Science, University of Oxford, Oxford, UK; FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK. Electronic address:

Published: February 2019

AI Article Synopsis

  • The main aim of calibrated fMRI is to quantitatively measure oxygen metabolism (CMRO), which involves various methods and techniques.
  • While pursuing this goal, other important physiological parameters are also collected, enhancing the value and clinical relevance of the data.
  • However, combining multiple parameters into one model can lead to increased errors and noise in the final results, highlighting the trade-offs between imaging time, resolution, coverage, and accuracy in these experiments.

Article Abstract

The ultimate goal of calibrated fMRI is the quantitative imaging of oxygen metabolism (CMRO), and this has been the focus of numerous methods and approaches. However, one underappreciated aspect of this quest is that in the drive to measure CMRO, many other physiological parameters of interest are often acquired along the way. This can significantly increase the value of the dataset, providing greater information that is clinically relevant, or detail that can disambiguate the cause of signal variations. This can also be somewhat of a double-edged sword: calibrated fMRI experiments combine multiple parameters into a physiological model that requires multiple steps, thereby providing more opportunity for error propagation and increasing the noise and error of the final derived values. As with all measurements, there is a trade-off between imaging time, spatial resolution, coverage, and accuracy. In this review, we provide a brief overview of the benefits and pitfalls of extracting multiparametric measurements of cerebral physiology through calibrated fMRI experiments.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.neuroimage.2017.12.049DOI Listing

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