Non-invasive, in-vivo assessments of human locus coeruleus (LC) integrity are notoriously difficult, given the nucleus’ small size and location deep in the brainstem. However, over the life span neuromelanin accumulates in the LC and acts as a natural contrast agent that opens the door to the non-invasive, in-vivo assessment of LC integrity via MRI.
299 healthy younger and older participants that participated in the Berlin Aging Study II (BASE-II) were scanned with a high resolution neuromelanin-sensitive T1-weighted Turbo Spin Echo sequence (T1-TSE; in-plane resolution 0.5 x 0.5 mm). We developed a semi-automatic procedure to extract individual peak LC intensity values and their coordinates across the rostrocaudal extent of the nucleus. The procedure demonstrated high reproducibility across multiple measurements and was validated using both published LC maps (see Figure) and manual intensity assessments. For a detailed description of the method, please refer to Dahl et al. (2019).
Peak intensity coordinates were converted to a LC probability map that we here make freely available to the neuroscientific community to facilitate the comparability of studies. The map is provided in standard Montreal Neurological Institute coordinate space (0.5 mm iso-voxel MNI 152).
When using the map in a study, please cite:
Dahl, M. J., Mather, M., Düzel, S., Bodammer, N. C., Lindenberger, U., Kühn, S., & Werkle-Bergner, M. (2019). Rostral locus coeruleus integrity is associated with better memory performance in older adults. Nature Human Behaviour, 3, 1203–1214. https://doi.org/10.1038/s41562-019-0715-2
To obtain the map, please send a request with your name and research affiliation to: LC@mpib-berlin.mpg.de
Please note the important copyright information in the box below!
Schematic overview of the semi-automatic analysis procedure used to extract individual locus coeruleus (LC) intensity values across the rostrocaudal extent. (a) Native space neuromelanin-sensitive brainstem scans of three randomly selected subjects (axial slices are shown). Hyperintensities corresponding to the LC are indicated by red arrows. (b) Neuromelanin-sensitive scans were aligned and pooled across subjects in order to increase signal-to-noise ratio and facilitate LC delineation using a template-based approach. On a group level, LC location (red) was semi-automatically determined based on an intensity threshold relative to a pontine reference area (blue; see inlays). (c) Areas surviving the thresholding are grouped into a volume of interest (search space: upper plot; 3D representation) and used to restrict automatized extraction of individual peak intensities and their location. Observed peak LC locations were converted to a LC probability map (lower plot). (d) In standard space, the LC probability map was successfully validated using published maps by Keren and colleagues (2009) and Betts and others (2017). Circle radius indicates map size (i.e., number of voxels).
Martin Dahl
Schematic overview of the semi-automatic analysis procedure used to extract individual locus coeruleus (LC) intensity values across the rostrocaudal extent. (a) Native space neuromelanin-sensitive brainstem scans of three randomly selected subjects (axial slices are shown). Hyperintensities corresponding to the LC are indicated by red arrows. (b) Neuromelanin-sensitive scans were aligned and pooled across subjects in order to increase signal-to-noise ratio and facilitate LC delineation using a template-based approach. On a group level, LC location (red) was semi-automatically determined based on an intensity threshold relative to a pontine reference area (blue; see inlays). (c) Areas surviving the thresholding are grouped into a volume of interest (search space: upper plot; 3D representation) and used to restrict automatized extraction of individual peak intensities and their location. Observed peak LC locations were converted to a LC probability map (lower plot). (d) In standard space, the LC probability map was successfully validated using published maps by Keren and colleagues (2009) and Betts and others (2017). Circle radius indicates map size (i.e., number of voxels).
Martin Dahl
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