Physiological noise in human cerebellar fMRI

Denis Butticaz, João Pedro Forjaco Jorge, Rolf Gruetter, Wietske Van der Zwaag
Springer Verlag, 2015
Journal paper

Abstract

Objectives To compare physiological noise contributions in cerebellar and cerebral regions of interest in high-resolution functional magnetic resonance imaging (fMRI) data acquired at 7T, to estimate the need for physiological noise removal in cerebellar fMRI. Materials and methods Signal fluctuations in high resolution (1 mm isotropic) 7T fMRI data were attributed to one of the following categories: task-induced BOLD changes, slow drift, signal changes correlated with the cardiac and respiratory cycles, signal changes related to the cardiac rate and respiratory volume per unit of time or other. R2adj values for all categories were compared across regions of interest. Results In this high-resolution data, signal fluctuations related to the phase of the cardiac cycle and cardiac rate were shown to be significant, but comparable between cerebellar and cerebral regions of interest. However, respiratory related signal fluctuations were increased in the cerebellar regions, with explained variances that were up to 80 % higher than for the primary motor cortex region. Conclusion Even at a millimetre spatial resolution, significant correlations with both cardiac and respiratory RETROICOR components were found in all healthy volunteer data. Therefore, physiological noise correction is highly likely to improve the temporal signal-to-noise ratio (SNR) for cerebellar fMRI at 7T, even at high spatial resolution.

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Denis Butticaz, João Pedro Forjaco Jorge, Rolf Gruetter, Wietske Van der Zwaag
Springer Verlag, 2015
Journal paper

Abstract

Official source

https://infoscience.epfl.ch/record/207514?ln=en

About this result

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Quantitative Susceptibility Mapping in the Human Brain

Diana Khabipova

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EPFL2016

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Yohan Boillat

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EPFL2020

Magnetic resonance resonance (MRI) is a widely used modality to obtain in vivo tissue information. Clinical applications are near countless, and almost all body parts can be examined using an MR scanner. As the method is non invasive, does not use ionizing radiation and provides excellent soft tissue contrast, it also appears as an excellent tool for neuroscience research. The major drawback of MRI remains the relatively long acquisition times, of the order of several minutes. During the measurement, the subject must stay still and avoid moving at all costs, as otherwise image artefacts will appear and potentially render the acquired data (partially) unusable. As higher image resolution imply longer acquisition time, probing finer anatomical details imply ultimately requires dealing with said motion. While some research goes in the way of reducing the acquisition time, it necessarily comes at the price of lower sensitivity and hence inherently diminishes the achievable gain for high- resolution imaging as the signal is weaker to start with. In this work, the focus is to try and compensate for motion during brain imaging using a navigator method. This amounts to measure not only the desired image, but also other MR based information, called navigator, at regular intervals during the scan. A modeling step then establishes a link between the navigators samples and the head position change. Incorporating the motion information into the main image reconstruction framework helps to retrospectively reduce the impact of said motion and the associated incoherences which would appear during the standard reconstruction. Brain imaging is probably the easiest case of motion correction in MRI, as the motion can readily be well approximated as rigid. The navigator methods developed and investigated in this work, called FatNavs, are based on the fat signal, which in head imaging is very sparse in space and therefore can be imaged rapidly. They also present the advantage of reduced impact on the main image water signal. Several implementation strategies were tested as, due to the versatility of MRI, all image contrasts cannot be ideally navigated using a single general implementation. Applications to inversion recovery based sequences (MP2RAGE) used a well separated navigator and image acquisition scheme. This method being routinely acquired, comparison to Moir Ìe Phase Tracking, the current gold standard for motion tracking and correction, was also performed in collaboration with Hendrik Mattern from the Magdeburg University. For gradient-echo imaging sequences (GRE), on which time-of-flight angiography and susceptibil- ity induced contrasts are based, both separate and mixed acquisition schemes were tested. Further- more, for imaging protocols using long echo time, the fluctuation of the magnetic field during the scan can also induce severe artefacts. Therefore, extension of the FatNavs to a dual-echo field-mapping version was also explored. Finally, combination of FatNavs with FID navigators, which lack spatial information but have much higher temporal resolution, was investigated for both motion and field fluctuation retrospective correction.

EPFL2020

Metabolic and hemodynamic changes in the activated human brain and cerebellar organisation measured by MRS/MRl at 7 Tesla

Yohan Boillat

EPFL2020

Quantitative Susceptibility Mapping in the Human Brain

Diana Khabipova

EPFL2016