PLoS ONENeurosciencePeer-reviewed journal article
3 versus 7 Tesla Magnetic Resonance Imaging for parcellations of subcortical brain structures
Bethany Rose IsaacsiD, Martijn MulderiD, Josephine Maria GrootiD, Nikita van BerendonkiD, Nicky LuteiD, Pierre‐Louis BaziniD, Birte U. ForstmanniD, Anneke AlkemadeiD
Abstract
7 Tesla (7T) magnetic resonance imaging holds great promise for improved visualization of the human brain for clinical purposes. To assess whether 7T is superior regarding localization procedures of small brain structures, we compared manual parcellations of the red nucleus, subthalamic nucleus, substantia nigra, globus pallidus interna and externa, created on a commonly used clinical anisotropic clinical 3T with an optimized isotropic (o)3T and standard 7T scan. While the clinical 3T MRI scan did not allow delineation of an anatomical plausible structure due to its limited spatial resolution, optimized 3T and 7T parcellations could be directly compared. We found that 7T outperformed the o3T MRI as reflected by higher Dice scores, which were used as a measurement of interrater agreement for manual parcellations on quantitative susceptibility maps. This increase in agreement was associated with higher contrast to noise ratios for smaller structures, but not for the larger globus pallidus segments. Additionally, control-analyses were performed to account for potential biases in manual parcellations by assessing semi-automatic parcellations. These results did not confirm increased Dice scores for 7T, although they revealed a higher consistency for structure volumes for 7T compared to optimized 3T, potentially indicative of more agreement with increased field strength. Together these results indicate the importance of the use of isotropic voxels with both 3T and 7T, and the potential for clinical applications.
- organism: human
- assay: imaging
- research focus: cell type annotation
- research focus: clustering
- research focus: dimensionality reduction
- research focus: benchmarking
- approach: statistical model
- Citations
- 41
- FWCI
- 2.19
- Field percentile
- top 10%
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