Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK; Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States.
IBME, Department of Engineering Science, University of Oxford, Oxford, UK.
Neuroimage. 2019 Feb 15;187:128-144. doi: 10.1016/j.neuroimage.2017.12.049. Epub 2017 Dec 19.
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.
校准 fMRI 的最终目标是对氧代谢(CMRO)进行定量成像,这也是许多方法和途径的关注焦点。然而,在追求测量 CMRO 的过程中,人们往往忽略了一个方面,即许多其他感兴趣的生理参数也经常在这个过程中被同时测量到。这可以极大地增加数据集的价值,提供更有临床意义的信息,或有助于区分信号变化的原因。这也可以说是一把双刃剑:校准 fMRI 实验将多个参数组合到一个需要多个步骤的生理模型中,从而为误差传播提供了更多的机会,并增加了最终得出值的噪声和误差。与所有测量一样,在成像时间、空间分辨率、覆盖范围和准确性之间需要进行权衡。在本文中,我们简要概述了通过校准 fMRI 实验提取脑生理多参数测量的优缺点。