Giving you five: An atlas of the nigrosomes in the substantia nigra based on 3D histology
Poster No:
1798
Submission Type:
Abstract Submission
Authors:
Malte Brammerloh1, Anneke Alkemade2, Pierre-Louis Bazin3, Caroline Jantzen4, Sara Schaumberg1, Carsten Jäger1, Andreas Herrler5, Kerrin Pine1, Markus Cremer6, Katrin Amunts6, Markus Morawski7, Birte Forstmann8, Nikolaus Weiskopf1, Evgeniya Kirilina1
Institutions:
1Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 2Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, Amsterdam, 3Full brain picture Analytics, Leiden, Leiden, 4Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Saxony, 5Department of Anatomy and Embryology, Maastricht, Netherlands, 6Forschungszentrum Juelich GmbH, Juelich, Germany, 7Paul Flechsig Institute - Center of Neuropathology and Brain Research, Medical Faculty University o, Leipzig, Germany, 8University of Amsterdam, Amsterdam, North Holland
First Author:
Malte Brammerloh
Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Co-Author(s):
Anneke Alkemade
Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam
Amsterdam, Amsterdam
Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam
Amsterdam, Amsterdam
Caroline Jantzen
Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Saxony
Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Saxony
Sara Schaumberg
Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Carsten Jäger
Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Kerrin Pine
Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Markus Morawski
Paul Flechsig Institute - Center of Neuropathology and Brain Research, Medical Faculty University o
Leipzig, Germany
Paul Flechsig Institute - Center of Neuropathology and Brain Research, Medical Faculty University o
Leipzig, Germany
Nikolaus Weiskopf
Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Evgeniya Kirilina
Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig, Germany
Introduction:
The five nigrosomes in the substantia nigra (SN) are sub-millimeter-sized clusters of neuromelanin-containing dopaminergic neurons (Fig. 1A) (Damier et al., 1999). Their degeneration, earliest and most pronounced in the largest nigrosome N1, is a hallmark of Parkinson's disease (PD) and contributes to the devastating motor symptoms (Fig. 1B). While nigrosomes have been originally defined in post mortem studies, using calbindin (Calb) histochemistry, in vivo nigrosome imaging promises to diagnose PD earlier.
Nigrosome imaging has come into reach of ultra-high-field MRI. However, direct nigrosome MRI is impeded by conflicting paradigms of contrast (Fig. 1D-E) and unknown 3D anatomy of the nigrosomes: nigrosomes have been described as areas of decreased R2* in vivo (Schwarz et al., 2018) but N1 appeared as a stripe of elevated R2* in post mortem MRI (Brammerloh et al., 2022). A sequence presumably sensitive to the pigment neuromelanin in the dopaminergic neurons has not been able to provide sufficient contrast for nigrosome identification (Rua et al., 2021). Validation of these new imaging approaches using atlases is currently impossible, as the nigrosomes are not included.
Here, we introduce a 3D nigrosome atlas in MNI space, based on 3D block-face images (BFI) and Calb histochemistry on post mortem brains. We describe a dedicated strategy to align the atlas to 7 T quantitative MRI (qMRI) in vivo data and validate the accuracy of the atlas using an independent multi-modal post mortem dataset.
Nigrosome imaging has come into reach of ultra-high-field MRI. However, direct nigrosome MRI is impeded by conflicting paradigms of contrast (Fig. 1D-E) and unknown 3D anatomy of the nigrosomes: nigrosomes have been described as areas of decreased R2* in vivo (Schwarz et al., 2018) but N1 appeared as a stripe of elevated R2* in post mortem MRI (Brammerloh et al., 2022). A sequence presumably sensitive to the pigment neuromelanin in the dopaminergic neurons has not been able to provide sufficient contrast for nigrosome identification (Rua et al., 2021). Validation of these new imaging approaches using atlases is currently impossible, as the nigrosomes are not included.
Here, we introduce a 3D nigrosome atlas in MNI space, based on 3D block-face images (BFI) and Calb histochemistry on post mortem brains. We describe a dedicated strategy to align the atlas to 7 T quantitative MRI (qMRI) in vivo data and validate the accuracy of the atlas using an independent multi-modal post mortem dataset.
Methods:
We identified the nigrosomes in 3D and registered the delineations using the SN as a reference volume (Fig. 2). We delineated the dark-pigmented nigrosomes in open data 3D ultra-high-resolution BFI of four post mortem brain specimens (Alkemade et al., 2022). For two brains, we validated the nigrosome segmentations against the gold-standard nigrosome definition, 2D Calb histochemistry.
We obtained 3D SN segmentations based on the same data, leveraging the contrast between the myelin-poor SN and the surrounding white matter. We validated this segmentation quantitatively against a gold standard 2D Calb SN definition (Halliday et al., 2012).
We non-linearly registered the SN segmentations using the SyN algorithm (Tustison et al., 2021) in the Nighres software (Huntenburg et al., 2018). The resulting transformations aligned the nigrosomes, forming the atlas.
Next, we used the focused_antspy function in Nighres focuse SN as a focus to align the atlas to the AHEAD template (Alkemade et al., 2020). We propose this procedure as a means to most precisely align the nigrosome atlas to 7 T qMRI data.
We validated the registration approach by comparing the N1 atlas to maps of the effective transverse relaxation rate R2* in an ultra-high-resolution qMRI dataset of a fifth post mortem brain, a BigBrain specimen (Kirilina et al., 2021). We illustrate the usage of the nigrosome atlas on in vivo 7 T qMRI multi-parametric mapping (Pine et al., 2024; Vaculčiaková et al., 2022).
We obtained 3D SN segmentations based on the same data, leveraging the contrast between the myelin-poor SN and the surrounding white matter. We validated this segmentation quantitatively against a gold standard 2D Calb SN definition (Halliday et al., 2012).
We non-linearly registered the SN segmentations using the SyN algorithm (Tustison et al., 2021) in the Nighres software (Huntenburg et al., 2018). The resulting transformations aligned the nigrosomes, forming the atlas.
Next, we used the focused_antspy function in Nighres focuse SN as a focus to align the atlas to the AHEAD template (Alkemade et al., 2020). We propose this procedure as a means to most precisely align the nigrosome atlas to 7 T qMRI data.
We validated the registration approach by comparing the N1 atlas to maps of the effective transverse relaxation rate R2* in an ultra-high-resolution qMRI dataset of a fifth post mortem brain, a BigBrain specimen (Kirilina et al., 2021). We illustrate the usage of the nigrosome atlas on in vivo 7 T qMRI multi-parametric mapping (Pine et al., 2024; Vaculčiaková et al., 2022).
Results:
Nigrosomes segmented in 3D BFI showed similar shapes, extents, and arrangement as in Calb histochemistry (Fig. 2, left). The SN segmentations of two raters showed a Dice coefficient of 83±4% (std dev over datasets), indicating good agreement.
After transforming the N1 atlas to the R2* map of the BigBrain qMRI dataset, we observed that the N1 atlas aligned well with a bright stripe known to correspond to N1 in R2* maps (Brammerloh et al., 2022; Fig. 2, top right).
After registering the nigrosome atlas to the use case in vivo dataset, the nigrosomes were found in areas of increased R2* relaxation rates as observed in the post mortem dataset, indicating accurate alignment (Fig. 2, bottom right).
After transforming the N1 atlas to the R2* map of the BigBrain qMRI dataset, we observed that the N1 atlas aligned well with a bright stripe known to correspond to N1 in R2* maps (Brammerloh et al., 2022; Fig. 2, top right).
After registering the nigrosome atlas to the use case in vivo dataset, the nigrosomes were found in areas of increased R2* relaxation rates as observed in the post mortem dataset, indicating accurate alignment (Fig. 2, bottom right).
Conclusions:
We establish a histological nigrosome atlas in standard MRI space and demonstrate its accuracy, making neuroimaging of substantia nigra's substructure possible with unprecedented specificity. This will allow in vivo studies of the differential involvement of the nigrosomes in PD.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 2
Neuroinformatics and Data Sharing:
Brain Atlases 1
Keywords:
Atlasing
Brainstem
Dopamine
HIGH FIELD MR
Movement Disorder
MRI
Open Data
STRUCTURAL MRI
Sub-Cortical
1|2Indicates the priority used for review
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