FreeSurfer Serotonin Atlas

NRU Serotonin Atlas and Clustering

Overview

Serotonin (5-HT) is a key neurotransmitter involved in a broad range of brain functions and behaviors and is implicated in the pathophysiology of neuropsychiatric illnesses. Here, we present for the first time a PET and MR-based high resolution atlas of some main 5-HT receptors (5-HT1AR, 5-HT1BR, 5-HT2AR and 5-HT4R) and the 5-HT transporter, generated from 210 healthy individuals scanned with different selective PET-radioligands. We related our molecular imaging atlas to seminal autoradiography data and found an unprecedented agreement, supporting the validity of the methodology and results presented here, and allowing us to translate PET binding estimates into densities. As such, this conversion facilitates the interpretability of the atlas and allows for a direct comparison across the five 5-HT targets, in vivo in the human brain. Furthermore, we compare for the first time in vivo in humans the regional target densities to mRNA levels. Our results highlight intrinsic properties of the various 5-HT receptors, furthering the understanding of their individual contribution to the 5-HT system. Taken together, these findings provide novel insights into fundamental properties of the 5-HT system.

Data

All participants included in this study were healthy controls from the Cimbi database (Knudsen et al., 2015); the data analysis was restricted to include individuals aged between 18 and 45 years. Participants were recruited by advertisement for different research protocols approved by the Ethics Committee of Copenhagen and Frederiksberg, Denmark. A total of 232 PET scans and corresponding structural MRI were acquired for 210 individual participants; 189 subjects had only 1 scan, 20 subjects had 2 scans and a single had 3 scans.

Methods


PET data was acquired in list-mode on a Siemens HRRT scanner operating in 3D-acquisition mode, with an approximate in-plane resolution of 2 mm (1.4 mm in the center of the field of view and 2.4 mm in cortex) (Olesen et al., 2009). PET frames were reconstructed using a 3D-OSEM-PSF algorithm (Comtat et al., 2008; Sureau et al., 2008). Scan time and frame length were designed according to the radiotracer characteristics. Dynamic PET frames were realigned using AIR 5.2.5 (Woods et al., 1992).
T1 and T2-weighted structural MRI were acquired on four different Siemens scanners with standard parameters. All structural MRIs (T1 and T2) were unwarped offline using FreeSurfer's gradient_nonlin_unwarp v0.8 or online on the scanner (Jovicich et al., 2006). For further details on structural MRI acquisition parameters, see Knudsen et al. (2015).

Atlas maps

Brain regional BPND values were compared to the corresponding receptor density measurements from post-mortem autoradiography data from Varnäs et al. (2004) and Bonaventure et al. (2000) (for 5-HT4R). For all five targets, we found good to excellent associations between BPND and Bmax. The slope estimates of the regression were used to transform the BPND atlases into Bmax atlases (Figure 1 and 2), allowing for a direct comparison across targets. The regional densities are presented in Figure 3. No global or regional significant effect of age, gender or age x gender was found.
Figure 1
Figure 1. Average density (Bmax) maps for five 5-HT targets on the common FreeSurfer surface (left hemisphere; lateral view, upper and medial view, lower). Color scaling was individually adjusted in order to highlight features of the distributions.
Figure 2
Figure 2.Average density (Bmax) maps for the five 5-HT targets in the common MNI152 space (coronal, upper, z=8mm and sagittal, lower, x=-3mm). Color scaling was individually adjusted to highlight features of the distributions.
Figure 3
Figure 3. Density values (Bmax) of the five 5-HT targets in FreeSurfer defined brain regions. Median raphe is not reported for 5-HTT due the irreversible kinetic of the TACs, see also the Material and Methods section. A table with Bmax values for all regions can be donwloaded here.

Clustering of atlas maps

The abovementioned human brain atlas of the serotonin (5-HT) system does not conform with commonly used parcellations of neocortex, since the spatial distribution of homogeneous 5-HT receptors and transporter is not aligned with such brain regions. This discrepancy indicates that a neocortical parcellation specific to the 5-HT system is needed. Hence we present parcellations of the 5-HT system created using a clustering approach focused on identifying stable and homogeneous clusters and derived from brain MR- and high-resolution PET images of five different 5-HT targets from 210 healthy controls. This is the same data that was used in the derivation of the atlas above. The resulting parcellations show strong lateralization and do not indicate the presence of any network across the combined 5-HT targets, with the exception of two segregated regions that share the same target profile. Furthermore, we reassess the known regional associations between the density of 5-HT targets and mRNA levels and explore how well the parcellations can explain mRNA levels of 5-HT related genes. The parcellations derived here represent a stable characterization of the 5-HT system which may be more sensitive than traditional atlases to capture region-specific changes modulated by 5-HT.
Figure 4
Figure 4. Final clustering for K2 values of 2 (upper left), 7 (upper right), 18 (lower left) and 34 (lower right) for both the left and right hemispheres of the fsaverage5 in ated surface. Rows 1 and 3 lateral views and rows 2 and 4 are medial views. Columns 1 and 3 are the left hemisphere and columns 2 and 4 are the right hemispheres. Colors between the left and right hemispheres have been partially matched, however, each hemisphere should be considered independently from the other.

Publications

The following publications should be referenced when using this atlas:

A high-resolution in vivo atlas of the human brain's serotonin system
Vincent Beliveau, Melanie Ganz, Ling Feng, Brice Ozenne, Liselotte Højgaard, Patrick M. Fisher, Claus Svarer, Douglas N. Greve, Gitte M. Knudsen
J Neurosci. 2017 Jan 4; 37(1): 120 - 128.

The Structure of the Serotonin System: a PET Imaging Study
Vincent Beliveau, Brice Ozenne,Stephen Strother, Douglas N. Greve, Claus Svarer, Gitte M. Knudsen, Melanie Ganz
In submission

Downloads


Average density maps presented in Figures 1 and 2 and table for the data presented in Figure 3 (17 Mb)
Clustering maps presented in Figure 4

Bibliography


Bonaventure P, Hall H, Gommeren W, Cras P, Langlois X, Jurzak M, Leysen JE (2000) Mapping of serotonin 5-HT(4) receptor mRNA and ligand binding sites in the post-mortem human brain. Synapse 36:35-46.
Comtat C, Sureau FC, Sibomana M, Hong IK, Sjoholm N, Trebossen R (2008) Image based resolution modeling for the HRRT OSEM reconstructions software. In: 2008 IEEE Nuclear Science Symposium Conference Record, pp 4120-4123. IEEE.
Jovicich J, Czanner S, Greve D, Haley E, van der Kouwe A, Gollub R, Kennedy D, Schmitt F, Brown G, Macfall J, Fischl B, Dale A (2006) Reliability in multi-site structural MRI studies: effects of gradient non-linearity correction on phantom and human data. Neuroimage 30:436-443.
Knudsen GM et al. (2015) The Center for Integrated Molecular Brain Imaging (Cimbi) Database. Neuroimage:1-7.
Olesen OV, Sibomana M, Keller SH, Andersen F, Jensen J, Holm S, Svarer C, Højgaard L (2009) Spatial resolution of the HRRT PET scanner using 3D-OSEM PSF reconstruction. IEEE Nucl Sci Symp Conf Rec:3789-3790.
Sureau FC, Reader AJ, Comtat C, Leroy C, Ribeiro M-J, Buvat I, Trébossen R (2008) Impact of image-space resolution modeling for studies with the high-resolution research tomograph. J Nucl Med 49:1000-1008.
Varnäs K, Halldin C, Hall H (2004) Autoradiographic distribution of serotonin transporters and receptor subtypes in human brain. Hum Brain Mapp 22:246-260.
Woods RP, Cherry SR, Mazziotta JC (1992) Rapid automated algorithm for aligning and reslicing PET images. J Comput Assist Tomogr 16:620-633.

Contacts

For questions related to the NRU serotonin atlas, contact Vincent Beliveau (vbeliveau-AT-nru.dk) or Melanie Ganz (mganz-AT-nru.dk).

Copyright

Copyright (c) 2016, Neurobiology Research Unit, Rigshospital. All rights reserved according to CC 4.0 BY-NC-SA (https://creativecommons.org/licenses/by-nc-sa/4.0). Redistribution and use in source forms, with or without modification, are permitted provided that the following conditions are met: * You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. * You may not use the material for commercial purposes. Neither the name of the Neurobiology Research Unit, Rigshospital nor the names of its contributors may be used to endorse or promote products derived from this image set without specific prior written permission. * If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.