4.7 Article

Inconsistencies in atlas-based volumetric measures of the human nucleus basalis of Meynert: A need for high-resolution alternatives

Journal

NEUROIMAGE
Volume 259, Issue -, Pages -

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2022.119421

Keywords

Nucleus basalis of Meynert; Volumetry; (f)MRI; Quantitative MRI

Funding

  1. Maastricht University, Maastricht Brain Imaging center (MBIC) [F8000H04]
  2. Chinese Scholarship Council (CSC) [201704910927]

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This study examines the feasibility of using MRI to locate the nucleus basalis of Meynert (nbM) in humans, and finds that current methods of mapping nbM may have limitations, especially when dealing with high resolution MRI data. By developing a new nbM mask and utilizing high spatial resolution data, more accurate and stable volume estimates can be obtained. Direct imaging of nbM appears to be feasible, but further development is necessary for standard (f)MRI scanning to allow such imaging.
The nucleus basalis of Meynert (nbM) is the major source of cortical acetylcholine (ACh) and has been related to cognitive processes and to neurological disorders. However, spatially delineating the human nbM in MRI studies remains challenging. Due to the absence of a functional localiser for the human nbM, studies to date have localised it using nearby neuroanatomical landmarks or using probabilistic atlases. To understand the feasibility of MRI of the nbM we set our four goals; our first goal was to review current human nbM region-of-interest (ROI) selection protocols used in MRI studies, which we found have reported highly variable nbM volume estimates. Our next goal was to quantify and discuss the limitations of existing atlas-based volumetry of nbM. We found that the identified ROI volume depends heavily on the atlas used and on the probabilistic threshold set. In addition, we found large disparities even for data/studies using the same atlas and threshold. To test whether spatial resolution contributes to volume variability, as our third goal, we developed a novel nbM mask based on the normalized BigBrain dataset. We found that as long as the spatial resolution of the target data was 1.3 mm isotropic or above, our novel nbM mask offered realistic and stable volume estimates. Finally, as our last goal we tried to discern nbM using publicly available and novel high resolution structural MRI ex vivo MRI datasets. We find that, using an optimised 9.4T quantitative T-2* ex vivo dataset, the nbM can be visualised using MRI. We conclude caution is needed when applying the current methods of mapping nbM, especially for high resolution MRI data. Direct imaging of the nbM appears feasible and would eliminate the problems we identify, although further development is required to allow such imaging using standard (f)MRI scanning.

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