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. 2017 Jul 28;38(11):5519–5534. doi: 10.1002/hbm.23744

The relationship between subcortical brain volume and striatal dopamine D2/3 receptor availability in healthy humans assessed with [11C]‐raclopride and [11C]‐(+)‐PHNO PET

Fernando Caravaggio 1,2, Jun Ku Chung 1, Eric Plitman 1, Isabelle Boileau 1,2, Philip Gerretsen 1,2, Julia Kim 1, Yusuke Iwata 1,2, Raihaan Patel 3,4, M Mallar Chakravarty 3,4,5, Gary Remington 1,2, Ariel Graff‐Guerrero 1,2,✉
PMCID: PMC6867134  PMID: 28752565

Abstract

Background

Abnormalities in dopamine (DA) and brain morphology are observed in several neuropsychiatric disorders. However, it is not fully understood how these abnormalities may relate to one another. For such in vivo findings to be used as biomarkers for neuropsychiatric disease, it must be understood how variability in DA relates to brain structure under healthy conditions. We explored how the availability of striatal DA D2/3 receptors (D2/3R) is related to the volume of subcortical brain structures in a sample of healthy humans. Differences in D2/3R availability measured with an antagonist radiotracer ([11C]‐raclopride) versus an agonist radiotracer ([11C]‐(+)‐PHNO) were examined.

Methods

Data from 62 subjects scanned with [11C]‐raclopride (mean age = 38.98 ± 14.45; 23 female) and 68 subjects scanned with [11C]‐(+)‐PHNO (mean age = 38.54 ± 14.59; 25 female) were used. Subcortical volumes were extracted from T1‐weighted images using the Multiple Automatically Generated Templates (MAGeT‐Brain) algorithm. Partial correlations were used controlling for age, gender, and total brain volume.

Results

For [11C]‐(+)‐PHNO, ventral caudate volumes were positively correlated with BPND in the dorsal caudate and globus pallidus (GP). Ventral striatum (VS) volumes were positively correlated with BPND in the VS. With [11C]‐raclopride, BPND in the VS was negatively correlated with subiculum volume of the hippocampus. Moreover, BPND in the GP was negatively correlated with the volume of the lateral posterior nucleus of the thalamus.

Conclusion

Findings are purely exploratory and presented corrected and uncorrected for multiple comparisons. We hope they will help inform the interpretation of future PET studies where concurrent changes in D2/3R and brain morphology are observed. Hum Brain Mapp 38:5519–5534, 2017. © 2017 Wiley Periodicals, Inc.

Keywords: dopamine, positron emission tomography, D2/3 receptors, raclopride, PHNO, morphology, volume, striatum

INTRODUCTION

Elucidating neurochemical and structural brain changes associated with mental disorders remains a critical challenge for the development of robust “biomarkers” in psychiatry [Perlis, 2011]. However, it remains poorly understood how in vivo differences in neurochemistry relates to variation in brain structure. For example, while it has been demonstrated that persons with schizophrenia have increased endogenous dopamine (DA) levels in the striatum [Abi‐Dargham et al., 2000; Caravaggio et al., 2015b; Kegeles et al., 2010], this has yet to be associated with any of the morphological brain changes observed in this disorder [Ellison‐Wright et al., 2008; Haijma et al., 2013; Rimol et al., 2010; Song et al., 2015; van Erp et al., 2016; Xiao et al., 2015]. Similarly in obesity, while changes in DA D2/3 receptor (D2/3R) availability [Caravaggio et al., 2015c; Dang et al., 2016; Gaiser et al., 2016; Guo et al., 2014; Karlsson et al., 2016; Mawlawi et al., 2001] and brain morphology [Bond et al., 2011; Taki et al., 2008; Veit et al., 2014; Walther et al., 2010] have been observed, these changes have yet to be directly associated with each other [Karlsson, 2016]. Thus, the use of in vivo DA functioning and brain morphology as biomarkers for disease remains hindered insofar as it is not firmly established how they may relate to one another under normal conditions [Strimbu and Tavel, 2010].

While several animal studies have examined the effect of altering DA levels on brain development [Alvarez et al., 2002; Jones et al., 1996; Kalsbeek et al., 1989; Meredith et al., 1995; Pappas et al., 1992; Reinoso et al., 1996], few human studies have examined how in vivo DA functioning, measured with positron emission tomography (PET), relates to brain morphology [Casey et al., 2013; Morales et al., 2015; Werhahn et al., 2006; Woodward et al., 2009]. Using voxel‐based morphology and the antagonist radioligand [18F]‐fallypride, Woodward et al. were the first to examine how variations in brain morphology relates to D2/3R availability in healthy persons [Woodward et al., 2009]. They observed that D2/3R availability within a given brain region was generally positively correlated with the gray matter (GM) density/volume of that region (e.g., within the caudate, thalamus, amygdala, and substantia nigra). This generally suggests that, (i) D2/3R availability may vary positively with the amount of GM, and/or, (ii) differences in D2/3R availability may alter brain structure during development [Woodward et al., 2009]. However, negative correlations [Woodward et al., 2009], and null correlations [Werhahn et al., 2006], have been observed between hippocampal volume and hippocampal D2/3R availability measured with [18F]‐fallypride. Using [18F]‐fallypride, midbrain D2/3R availability was also found to be positively correlated with GM volume in the striatum, prefrontal cortex, insula, hippocampus, and temporal cortex of methamphetamine users, but not healthy controls [Morales et al., 2015]. Finally, using [11C]‐raclopride, it has been demonstrated that striatal DA release in response to amphetamine is negatively correlated with frontal lobe thickness in healthy controls [Casey et al., 2013].

Previous studies have not systematically examined how striatal D2/3R availability is related to subcortical morphology in healthy persons. Moreover, previous studies have only used antagonist radiotracers for D2/3R, that is, [18F]‐fallypride and [11C]‐raclopride. It is generally believed that D2/3R exist in (at least) two conformational states for agonist binding: an active state (D2High) and an inactive state (D2Low) [Seeman, 2011]. In theory, agonist radiotracers—such as [11C]NPA [Narendran et al., 2004], [11C]MNPA [Finnema et al., 2005], and [11C]‐(+)‐PHNO [Willeit et al., 2006]—should preferably bind to “active” D2/3R. Thus, agonist radiotracers may provide a more sensitive and physiologically meaningful estimate of DA release and D2/3R availability, respectively.

[11C]‐(+)‐PHNO is an agonist radiotracer for D2/3R which also has preferential affinity for D3R over D2R [Narendran et al., 2006; Wilson et al., 2005]. This unique property of [11C]‐(+)‐PHNO, ∼20–40 fold selectivity of D3R over D2R [Freedman et al., 1994; Gallezot et al., 2012; Rabiner et al., 2009; Searle et al., 2010; Seeman et al., 1993], results in a differential contribution of D2R and D3R to the [11C]‐(+)‐PHNO signal across different regions of interest (ROIs). The estimated percent of the [11C]‐(+)‐PHNO signal attributed to D3R across ROIs in humans are: substantia nigra (∼100%), globus pallidus (GP, ∼65%), ventral striatum (VS, ∼26%), and dorsal caudate‐putamen (negligible) [Graff‐Guerrero et al., 2010; Searle et al., 2013b; Tziortzi et al., 2011]. Also, as an agonist, baseline [11C]‐(+)‐PHNO binding to D2/3R is more sensitive to competition with endogenous dopamine in vivo in humans [Caravaggio et al., 2014, 2016a; Shotbolt et al., 2012]. Thus, it remains unknown how D2/3R availability measured with an agonist radiotracer, and how D3R availability specifically, may be related to brain morphology.

In the current investigation, we sought to explore how D2/3R availability measured with the antagonist radiotracer [11C]‐raclopride and the agonist radiotracer [11C]‐(+)‐PHNO is related to subcortical brain volume in healthy persons. We specifically examined the volume of (i) striatal subdivisions, (ii) hippocampal subdivisions, (iii) thalamic subdivisions, and (iv) the amygdala. This investigation marks an important first step in elucidating how in vivo differences in dopaminergic functioning may relate to subcortical brain morphology. A better understanding of these relationships will help inform the use of neurochemical and structural brain changes as potential biomarkers for neuropsychiatric disease.

METHODS

Participants

Healthy control data from a previous study were re‐analyzed for the current investigation [Nakajima et al., 2015]. This sample comprises data collected by our laboratory from various PET studies [Caravaggio et al., 2015b; Graff‐Guerrero et al., 2008, 2009; Payer et al., 2014] that were approved by the Research Ethics Board of the Centre for Addiction and Mental Health (CAMH), Toronto. For the current investigation, subjects were included if they provided a T1 structural MRI (1.5T or 3T), and an [11C]‐raclopride or [11C]‐(+)‐PHNO scan. The participants were right‐handed and free of any major medical or psychiatric disorder as determined by clinical interview, the Mini‐International Neuropsychiatric Interview, and electrocardiography. Current or past alcohol abuse was an exclusion criteria. Participants were required to provide a full urine drug screen, and produced a negative urine screen for drugs of abuse and/or pregnancy at inclusion and before the PET scan. This included ethyl alcohol. Before the scan, the aural temperature and blood pressure of the participants were measured to insure they were within normal limits. All participants provided written informed consent and were non‐smokers.

MRI Imaging

Fifty‐one subjects scanned with [11C]‐raclopride and 58 subjects scanned with [11C]‐(+)‐PHNO provided fast spin echo T1‐weighted imaging (fast spoiled gradient echo, TE = 5.3–15 ms, TR = 8.9–12 ms, FOV = 20 cm 3D, 256 × 256, voxel 1.5 mm isotropic, NEX = 1) acquired on a 1.5‐Tesla Sigma‐GE scanner (General Electric Medical Systems, Milwaukee, WI) at Toronto General Hospital (Toronto, Canada). Eleven subjects scanned with [11C]‐raclopride and 11 subjects scanned with [11C]‐(+)‐PHNO underwent MRI fast spin echo T1‐weighted imaging (TR/TE = 30/8 ms, flip angle 45°, field of view 24 cm, 256 × 256 matrix, 124 coronal slices, and slice thickness = 1.0 mm, NEX = 1) acquired on a 3‐Tesla Signa‐GE scanner (GE Discovery MR750 3T; 8‐Channel Head Coil, GE Standard 8HR Brain) at CAMH (Toronto, Canada).

Subcortical Volume Analyses

The Multiple Automatically Generated Templates (MAGeT‐Brain) algorithm [Chakravarty et al., 2013; Pipitone et al., 2014] was used to provide fully‐automated segmentation of striatal subdivisions [Chakravarty et al., 2006], hippocampal subdivisions [Pipitone et al., 2014; Winterburn et al., 2013], thalamic subdivisions [Chakravarty et al., 2006, 2008, 2009], and the amygdala [Treadway et al., 2015]. Typically, in a multi‐atlas segmentation approach, manually drawn labels from atlases are warped (or propagated) into subject space by applying transformations estimated from non‐linear image registration. Candidate labels from all atlas images are fused (via probabilistic segmentation techniques) to create a final segmentation. The goal of the MAGeT‐Brain algorithm is to mitigate sources of error from such approaches including: (1) spurious non‐linear registration or resampling errors (including partial volume effects [PVE] in label resampling), and (2) irreconcilable differences in neuroanatomy between the atlas and target images. The MAGeT‐Brain algorithm is a modified multi‐atlas segmentation technique, which uses a limited number of high‐quality manually segmented atlases as an input to reduce bias and enhance segmentation accuracy. MAGeT‐Brain propagates atlas segmentations to a template library, formed from a subset of target images, via transformations estimated by nonlinear image registration. The resulting segmentations are then propagated to each target image and fused using a label fusion method. Specifically, for those subjects who provided a 1.5T MRI, subsets of subjects scanned with [11C]‐raclopride (n = 21) and [11C]‐(+)‐PHNO (n = 21) were used as template libraries through which the final segmentation was bootstrapped. All 11 subjects who provided a 3T MRI were used as a separate template. Templates were chosen based on representative subject characteristics [Schuetze et al., 2016]. Each subject in the template library was segmented through non‐linear atlas‐to‐template registration followed by label propagation, yielding a unique definition of the subdivisions for each of the templates. The bootstrapping of the final segmentations through the template library results in candidate labels produced for each subject and labels are then fused using a majority vote to complete the segmentation process. Non‐linear registration was performed using a version of the Automatic Normalization Tools (ANTS) registration technique [Avants et al., 2008] that is compatible with the minc toolkit (https://github.com/vfonov/mincANTS). Volumes (mm3) from ROIs were averaged across hemispheres. It is important to note that regional BPND values and regional volume values are not derived from images warped into the same space. Namely, the BPND values come from images normalized to MNI space, while the regional volume values do not (labels are propagated into individual subject space, based on a voxel‐voting procedure from a large number of candidate labels, using study sample specific templates). Thus, it is highly unlikely that there is overlap in potential variance from differences in “goodness” of normalization to the same image space (MNI). Importantly, compared to other automated techniques such as FreeSurfer and FSL, MAGeT‐Brain demonstrates the highest correlation with gold‐standard manual segmentation techniques—FreeSurfer and FSL significantly overestimate subcortical volumes compared to MAGeT‐Brain [Makowski et al., in press].

Total Brain Volume Analysis

The procedure for total brain volume (TBV) analysis has been published elsewhere [Plitman et al., 2016b]. TBV was obtained using the Brain Extraction based on non‐local Segmentation Technique (BEaST) method [Eskildsen et al., 2012], which is based on non‐local segmentation in a multi‐resolution framework. Each voxel is labeled based on the similarity of its neighborhood of voxels to all the neighborhoods in a library of pre‐defined priors, and a non‐local means estimator is used to estimate the label at the voxel. Inputs are down‐sampled to a lower resolution, segmentation is performed, and results are propagated up to higher resolutions [Eskildsen et al., 2012]. BEaST is designed to include CSF (in the ventricles, cerebellar cistern, deep sulci, along surface of brain, and brainstem), the brainstem, and cerebellar white matter (WM) and GM in the brain mask, while excluding the skull, skin, fat, muscles, dura, eyes, bone, exterior blood vessels, and exterior nerves.

PET Imaging

Subjects were asked to abstain from food for no less than 90 min prior to PET procedures. The radiosynthesis of [11C]‐raclopride [Wilson et al., 2000] and [11C]‐(+)‐PHNO [Wilson et al., 2005], along with the acquisition of PET images [Graff‐Guerrero et al., 2010], has been described in detail elsewhere. Images were acquired on a high–resolution, head‐dedicated PET camera system (CPS‐HRRT; Siemens Molecular Imaging, USA), which measures radioactivity in 207 brain slices with a thickness of 1.2 mm each. The in‐plane resolution was ∼2.8 mm full‐width at half‐maximum (FWHM). Transmission scans were acquired with the use of a 137Cs (T 1/2 = 30.2 years, energy = 662 KeV) single‐photon point source to provide attenuation correction, and the emission data were acquired in list mode. The raw data were reconstructed by filtered back‐projection. For the [11C]‐raclopride scans (n = 62), the mean radioactivity dose was 9.75(±1.0)mCi, with a specific activity of 1,234.58(±569.11)mCi/µmol, and an injected mass of 3.78(±2.19)µg. [11C]‐raclopride data were acquired for 60 min and redefined into 28 frames (1–5 of 1‐min duration, 6–25 of 2‐min duration, and 26–28 of 5‐min duration). For the [11C]‐(+)‐PHNO scans (n = 68), the mean radioactivity dose was 9.13(±1.46)mCi, with a specific activity of 1,100.91(±394.67)mCi/µmol, and an injected mass of 2.15(±.47)µg. None of the participants included in this sample reported nausea given the [11C]‐(+)‐PHNO injection. [11C]‐(+)‐PHNO data were acquired for 90 min after injection and redefined into 30 frames (1–15 of 1–min duration and 16–30 of 5–min duration).

PET Image Analysis

The ROI‐based analysis for [11C]‐(+)‐PHNO has been described in detail elsewhere [Graff‐Guerrero et al., 2008; Tziortzi et al., 2011]. Time activity curves (TACs) from ROIs were obtained from the dynamic PET images in native space with reference to each subject's co‐registered MRI image. The co‐registration of each subjects MRI to PET space was done using the normalized mutual information algorithm [Studholme et al., 1997] as implemented in SPM2 (SPM2, Wellcome Department of Cognitive Neurology, London; http://www.fil.ion.ucl.ac.uk/spm). The TACs were analyzed using the Simplified Reference Tissue Method (SRTM) [Lammertsma and Hume, 1996] which has been validated for use with [11C]‐(+)‐PHNO [Ginovart et al., 2007]. The cerebellum was used as the reference region to derive a quantitative estimate of binding—binding potential relative to the non‐displaceable compartment (BPND)—as defined by the consensus nomenclature for in vivo imaging of reversibly binding radioligands [Innis et al., 2007]. The basis function implementation of the SRTM [Gunn et al., 1997] was applied to the dynamic PET images to generate parametric voxelwise BPND maps using PMOD (v2.7, PMOD Technologies, Zurich, Switzerland). These images were spatially normalized into MNI brain space by Nearest Neighbor Interpolation with a voxel size fixed in 2 × 2 × 2 mm3 using SPM2. Regional BPND estimates were then derived from ROIs defined in MNI space, except for the hypothalamus and ventral pallidum ROIs. The VS and dorsal striatum (dorsal caudate, hereafter caudate, and dorsal putamen, hereafter putamen) were defined according with the criteria of Mawlawi et al [Mawlawi et al., 2001]. The GP ROI was defined according to the criteria of Tziortzi et al [Tziortzi et al., 2011].

Statistical Analysis

Statistical analyses were conducted using IBM SPSS (v.20; Armonk, NY: IBM Corp) and GraphPad Prism (v.7.0; GraphPad Software, La Jolla California). The relationship between D2/3R availability and subcortical volume was explored using partial correlations (two‐tailed), controlling for age, gender, and TBV. Four exploratory partial correlation matrices were conducted separately for [11C]‐raclopride and [11C]‐(+)‐PHNO (i.e., eight in total). These explored the relationship between BPND in each ROI and volumes of, (i) striatal subdivisions, (ii) hippocampal subdivisions, (iii) thalamic subdivisions, and (iv) the amygdalaBonferroni correction for multiple comparisons was applied to each correlation matrix individually, and relationships surviving this threshold (P < 0.05 ÷ n, where n = # of comparisons) were considered noteworthy. We believe this exploratory, data‐driven approach may help guide future studies in developing potential a priori hypotheses, while minimizing potential type‐II errors.

RESULTS

Data from 62 subjects scanned with [11C]‐raclopride (mean age = 38.98 ± 14.45; 23 female) and 68 subjects scanned with [11C]‐(+)‐PHNO (mean age = 38.54 ± 14.59; 25 female) were used in the study (see Supporting Information Figure 1). The relationships between striatal subregion volume and D2/3R availability measured with [11C]‐raclopride are presented in Table 1. While [11C]‐raclopride BPND in the VS was positively correlated with VS volume (see Fig. 1), this relationship did not survive correction for multiple comparisons. Adding MRI fieldstrength (1.5T versus 3T) as an additional covariate did not significantly alter the strength of this finding (r(56) = 0.30, P = 0.02).

Table 1.

Relationship between [11C]‐raclopride BPND and striatal volume in healthy participants (n = 62), controlling for age, sex, and total brain volume

[11C]‐raclopride BPND
Striatal Volume Dorsal caudate Dorsal putamen Ventral striatum Globus pallidus
Pre‐commissural caudate 0.12 0.02 0.003 0.02
(0.36) (0.86) (0.98) (0.87)
Post‐commissural caudate 0.08 −0.07 −0.09 0.02
(0.57) (0.61) (0.52) (0.88)
Pre‐commissural putamen 0.15 0.16 0.08 −0.06
(0.27) (0.23) (0.55) (0.67)
Post‐commissural putamen 0.19 0.16 0.06 −0.004
(0.15) (0.24) (0.68) (0.94)
Ventral striatum 0.23 0.19 0.30 a −0.02
(0.08) (0.16) (0.02) (0.87)
Globus pallidus 0.14 0.06 −0.04 −0.06
(0.29) (0.67) (0.76) (0.65)
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Data are presented as Pearson product moment partial correlations (r) with P‐values in parentheses.

a

Significance at P < 0.05 (two‐tailed), uncorrected for multiple comparisons (adjusted P‐threshold < 0.002).

Figure 1.

Figure 1

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Relationship between [11C]‐raclopride BPND in the ventral striatum (VS) and VS volume. Values represent standardized residuals controlling for age, sex, and total brain volume.

The relationships between striatal subregion volume and D2/3R availability measured with [11C]‐(+)‐PHNO are presented in Table 2 and Figure 2. Several positive correlations emerged and survived correction for multiple comparisons. Notably, (i) BPND in both the dorsal caudate and GP was correlated with ventral caudate volume and (ii) BPND in the VS was correlated with VS volume. Adding MRI tesla strength as an additional covariate did not significantly alter the strength of any of the aforementioned correlations: ventral caudate volume with BPND in the dorsal caudate (r(62) = 0.40, P = 0.001) and GP (r(62) = 0.38, P = 0.002); VS volume with VS BPND (r(62) = 0.39, P = 0.001).

Table 2.

Relationship between [11C]‐(+)‐PHNO BPND and striatal volume in healthy participants (n = 69), controlling for age, sex, and total brain volume

[11C]‐(+)‐PHNO BPND
Striatal volume Substantia nigra Dorsal caudate Dorsal putamen Ventral striatum Globus pallidus
Pre‐commissural caudate −0.05 0.26 a 0.17 0.21 0.11
(0.69) (0.04) (0.17) (0.10) (0.38)
Post‐commissural caudate −0.02 0.40 c 0.32 a 0.01 0.38 c
(0.90) (0.001) (0.01) (0.92) (0.002)
Pre‐commissural putamen 0.14 0.03 0.24 0.26 a 0.11
(0.26) (0.79) (0.05) (0.04) (0.39)
Post‐commissural putamen 0.22 0.05 0.23 0.09 0.30 a
(0.08) (0.72) (0.07) (0.49) (0.02)
Ventral striatum 0.16 −0.02 −0.005 0.39 c −0.01
(0.22) (0.87) (0.97) (0.001) (0.93)
Globus pallidus 0.22 0.26 a 0.24 0.18 0.36 b
(0.09) (0.04) (0.06) (0.15) (0.004)
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Data are presented as Pearson product moment partial correlations (r) with P‐values in parentheses.

a

Significance at P < 0.05 (two‐tailed), uncorrected for multiple comparisons (adjusted P‐threshold < 0.002).

b

Significance at P < 0.01 (two‐tailed), uncorrected for multiple comparisons (adjusted P‐threshold < 0.002).

c

Survives correction for multiple comparisons (adjusted P‐threshold < 0.002).

Figure 2.

Figure 2

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Relationships between [11C]‐(+)‐PHNO BPND in several regions of interest with striatal volumes. Values represent standardized residuals controlling for age, sex, and total brain volume.

The relationships between hippocampal subregion volume and D2/3R availability measured with [11C]‐raclopride and [11C]‐(+)‐PHNO are presented in Table 3 and Table 4, respectively. A negative correlation between [11C]‐raclopride BPND in the VS and subiculum volume was observed (see Fig. 3). However, this did not survive correction for multiple comparisons. Adding MRI tesla strength as an additional covariate did not significantly alter the strength of any of the aforementioned correlations: VS BPND with subiculum volume (r(56) = −0.27, P = 0.04).

Table 3.

Relationship between [11C]‐raclopride BPND and hippocampal volume in healthy participants (n = 62), controlling for age, sex, and total brain volume

[11C]‐raclopride BPND
Hippocampal volume Caudate Putamen Ventral striatum Globus pallidus
CA1 −0.14 −0.17 −0.26 0.004
(0.29) (0.21) (0.05) (0.98)
Subiculum 0.003 −0.15 –0.29 a −0.02
(0.98) (0.25) (0.03) (0.90)
CA4/Dentate gyrus −0.05 −0.02 −0.08 0.13
(0.72) (0.86) (0.56) (0.32)
CA2/CA3 −0.06 0.02 −0.06 0.09
(0.67) (0.88) (0.64) (0.48)
Stratum radiatum −0.08 −0.13 −0.24 0.05
(0.54) (0.33) (0.07) (0.68)
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Data are presented as Pearson product moment partial correlations (r) with P‐values in parentheses.

a

Significance at P < 0.05 (two‐tailed), uncorrected for multiple comparisons (adjusted P‐threshold < 0.003).

Table 4.

Relationship between [11C]‐(+)‐PHNO BPND and hippocampal volume in healthy participants (n = 69), controlling for age, sex, and total brain volume

[11C]‐(+)‐PHNO BPND

Hippocampal

volume

 Substantia nigra Caudate Putamen Ventral striatum Globus pallidus
CA1 0.04 0.03 0.03 −0.11 0.11
(0.76) (0.79) (0.79) (0.37) (0.38)
Subiculum 0.13 0.19 0.10 0.05 0.12
(0.29) (0.13) (0.44) (0.71) (0.35)
CA4/Dentate gyrus 0.13 0.09 0.09 0.11 0.04
(0.30) (0.48) (0.49) (0.38) (0.76)
CA2/CA3 0.13 −0.14 −0.08 0.01 0.10
(0.30) (0.26) (0.55) (0.91) (0.41)
Stratum radiatum 0.04 −0.06 −0.03 −0.11 0.05
(0.74) (0.66) (0.79) (0.38) (0.72)
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Data are presented as Pearson product moment partial correlations (r) with P‐values in parentheses.

Figure 3.

Figure 3

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Relationship between [11C]‐raclopride BPND in the ventral striatum (VS) and subiculum volume. Values represent standardized residuals controlling for age, sex, and total brain volume.

The relationships between thalamic subregion volume and D2/3R availability measured with [11C]‐raclopride and [11C]‐(+)‐PHNO and are presented in Table 5 and Table 6, respectively. While several positive and negative correlations emerged (see Fig. 4), none survived correction for multiple comparisons. Adding MRI tesla strength as an additional covariate did not significantly alter the strength of these correlations (data not shown).

Table 5.

Relationship between [11C]‐raclopride BPND and thalamus volume in healthy participants (n = 62), controlling for age, sex, and total brain volume

[11C]‐raclopride BPND
Thalamus volume Caudate Putamen Ventral striatum Globus pallidus
Lateral geniculate nucleus (LGN) −0.21 –0.30 a −0.26 −0.14
(0.13) (0.02) (0.05) (0.30)
Medial geniculate nucleus (MGN) −0.06 −0.11 −0.12 −0.12
(0.68) (0.40) (0.35) (0.36)
Anterior nuclei −0.14 0.11 0.29 a 0.09
(0.30) (0.41) (0.03) (0.48)
Central nuclei 0.02 −0.18 −0.24 −0.17
(0.89) (0.18) (0.07) (0.19)
Lateral dorsal −0.04 0.10 0.15 −0.06
(0.78) (0.46) (0.27) (0.64)
Lateral posterior −0.15 −0.07 −0.09 –0.36 a
(0.25) (0.58) (0.50) (0.006)
Medial dorsal 0.02 0.01 −0.06 −0.06
(0.86) (0.93) (0.68) (0.67)
Pulvinar −0.09 −0.09 −0.13 −0.08
(0.51) (0.52) (0.31) (0.55)
Ventral anterior nucleus (VAN) −0.06 0.08 0.09 0.04
(0.65) (0.53) (0.49) (0.78)
Ventral lateral nucleus (VLN) −0.03 −0.001 −0.04 −0.14
(0.81) (0.99) (0.79) (0.30)
Ventral posterior nucleus (VPN) −0.03 −0.17 −0.18 −0.25
(0.82) (0.19) (0.18) (0.06)
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Data are presented as Pearson product moment partial correlations (r) with P‐values in parentheses.

a

Significance at P < 0.05 (two‐tailed), uncorrected for multiple comparisons (adjusted P‐threshold < 0.001).

Table 6.

Relationship between [11C]‐(+)‐PHNO BPND and thalamus volume in healthy participants (n = 67), controlling for age, sex, and total brain volume

[11C]‐(+)‐PHNO BPND
Thalamus volume Substantia nigra Caudate Putamen Ventral striatum Globus pallidus
Lateral geniculate nucleus (LGN) 0.07 −0.003 −0.07 −0.09 0.02
(0.57) (0.98) (0.58) (0.49) (0.87)
Medial geniculate nucleus (MGN) 0.11 0.002 −0.09 0.02 −0.11
(0.39) (0.99) (0.48) (0.91) (0.37)
Anterior nuclei −0.02 −0.001 0.03 0.19 −0.12
(0.90) (0.99) (0.83) (0.13) (0.33)
Central nuclei 0.26 a −0.10 −0.01 0.19 −0.08
(0.04) (0.42) (0.93) (0.12) (0.52)
Lateral dorsal −0.08 0.09 0.05 0.14 −0.005
(0.52) (0.48) (0.68) (0.27) (0.97)
Lateral posterior −0.07 −0.03 −0.05 0.05 −0.19
(0.60) (0.85) (0.70) (0.69) (0.14)
Medial dorsal −0.07 −0.20 0.03 0.16 −0.07
(0.56) (0.12) (0.81) (0.20) (0.58)
Pulvinar 0.02 −0.10 0.04 −0.09 0.06
(0.90) (0.45) (0.77) (0.50) (0.62)
Ventral anterior nucleus (VAN) −0.03 −0.02 0.02 0.26 a −0.13
(0.83) (0.86) (0.86) (0.04) (0.30)
Ventral lateral nucleus (VLN) −0.04 −0.03 0.02 0.18 −0.14
(0.73) (0.82) (0.87) (0.14) (0.27)
Ventral posterior nucleus (VPN) 0.06 0.03 0.03 −0.02 −0.05
(0.62) (0.84) (0.79) (0.86) (0.67)
Open in a new tab

Data are presented as Pearson product moment partial correlations (r) with P‐values in parentheses.

a

Significance at P < 0.05 (two‐tailed), uncorrected for multiple comparisons (adjusted P‐threshold < 0.001).

Figure 4.

Figure 4

Open in a new tab

Relationship between [11C]‐raclopride and [11C]‐(+)‐PHNO BPND in several regions of interest with thalamic volumes. Values represent standardized residuals controlling for age, sex, and total brain volume.

For [11C]‐raclopride, amygdala volume was not significantly correlated with BPND in the caudate (r(57) = −0.11, P = 0.45), putamen (r(57) = −0.06, P = 0.65), VS (r(57) = −0.11, P = 0.40), nor the GP (r(57) = 0.11, P = 0.41). Adding MRI tesla strength as an additional covariate did not significantly alter the strength of these correlations: caudate (r(56) = −0.11, P = 0.40), putamen (r(56) = −0.05, P = 0.73), VS (r(56) = −0.09, P = 0.52), and GP (r(56) = 0.14, P = 0.23). For [11C]‐(+)‐PHNO, amygdala volume was not significantly correlated with BPND in the SN (r(63) = 0.15, P = 0.24), caudate (r(63) = 0.14, P = 0.26), putamen (r(63) = 0.13, P = 0.30), VS (r(63) = 0.05, P = 0.72), nor the GP (r(63) = 0.12, P = 0.34). Adding MRI tesla strength as an additional covariate did not significantly alter the strength of these correlations: SN (r(62) = 0.15, P = 0.25), caudate (r(62) = 0.14, P = 0.26), putamen (r(62) = 0.12, P = 0.35), VS (r(62) = 0.05, P = 0.68), and GP (r(62) = 0.12, P = 0.36).

DISCUSSION

This investigation is the first to examine how subcortical brain morphology is related to striatal D2R and D3R availability as measured with both an antagonist and agonist radiotracer. First with the antagonist [11C]‐raclopride, D2/3R availability within striatal subregions was generally not significantly correlated with the volume of those regions. This is in contrast to the findings of Woodward et al., who used the antagonist radiotracer [18F]‐fallypride [Woodward et al., 2009]. One exception was the VS, for which there was a positive correlation that did not survive correction for multiple comparisons. However, with the agonist [11C]‐(+)‐PHNO, BPND within striatal subregions was generally correlated with the volume of those regions, with the exception of the putamen. Notably, this was especially true for the VS, which survived correction for multiple comparisons.

One potential interpretation of this finding is a causal, biological one. Namely, that the availability of functional D2/3R binding sites (i.e., D2High) is positively related to striatal size, while the availability of total binding sites (i.e., D2High + D2Low) is not. As [11C]‐(+)‐PHNO is more sensitive to endogenous DA at baseline [Caravaggio et al., 2016a], an alternative interpretation is that persons with less endogenous DA (and therefore more radiotracer binding) have larger striatal volumes. Another potential interpretation is a methodological one. Namely, that subtle individual variations in striatal size which persist after normalization may influence D2/3R availability measures, that is, a partial volume effect (PVE). The PVE is a phenomenon whereby the apparent concentration of a radiotracer decreases as the size of the ROI approaches the instrument resolution (FWHM) [Hoffman et al., 1979]. We suggest it is unlikely that our findings are due to potential PVE. First, PVEs are most pronounced for ROIs 2–3 times smaller than the FWHM [Rousset et al., 1998]. It is also a concern for studies of aging, where certain ROIs are known to decrease in size with age. However, the PVE is minimized using the resolution of the CPS‐HRRT, and we have not observed significant PVE using other radiotracers in healthy persons with this scanner [Nakajima et al., 2015; Uchida et al., 2011]. Moreover, it is unclear why [11C]‐(+)‐PHNO BPND in the striatum would be more susceptible to PVE than [11C]‐raclopride, acquired on the same scanner.

Unlike Woodward et al. [2009], we controlled for differences in age, gender, and TBV. Thus, our findings suggest that after considering these factors, subtle variations in striatal structure may be related to D2/3R availability measured with [11C]‐(+)‐PHNO, but not [11C]‐raclopride. This finding is generally important for [11C]‐(+)‐PHNO studies using cross‐sectional or between group designs. For example, it will be important to determine whether increased [11C]‐(+)‐PHNO BPND in obese persons corresponds with concordant increases in striatal volumes [Caravaggio et al., 2015c; Gaiser et al., 2016].

Notably, [11C]‐(+)‐PHNO BPND in the dorsal caudate and GP were both correlated with ventral caudate volume. As the dorsal and ventral caudate border each other, it could be argued that this relationship is being driven by spill‐over effects. However, with such an interpretation it would be harder to explain the relationship between GP BPND and ventral caudate volume. Notably, ∼65% of the [11C]‐(+)‐PHNO BPND signal from the GP reflects D3R versus D2R [Tziortzi et al., 2011]. While the dorsal caudate and putamen have negligible D3R expression, the ventral caudate and putamen express D3R (∼1/3rd) [Seeman et al., 2006]. It may be possible that neurons which express D3R in the ventral caudate project to those neurons in the internal segment of the GP (GPi) which express D3R [Gurevich and Joyce, 1999]. This in turn could potentially drive the relationship between [11C]‐(+)‐PHNO BPND in the GP and ventral caudate volume. However, this is speculative and requires substantiation from ex vivo work.

We also explored how D2/3R availability in the striatum was related to the volume of other subcortical structures: the hippocampus, thalamus, and amygdala. While none of these correlations survived correction for multiple comparisons, a few notable relationships emerged. First, with [11C]‐raclopride there was a negative correlation between VS BPND and subiculum volume of the hippocampus. The subiculum, which is the main output structure of the hippocampus, projects densely to the nucleus accumbens of the VS [Chase et al., 2015; Groenewegen et al., 1987; Kelley and Domesick, 1982; Lopes da Silva et al., 1984]. It will be important for future in vivo and ex vivo work to elucidate the relationship between the structure and neurochemistry of this pathway. [11C]‐raclopride BPND in the GP was also negatively correlated with the volume of the lateral posterior nucleus of the thalamus. This large nucleus lies medial to the dorsal lateral geniculate nucleus and receives inputs mainly from the superior colliculus—projecting to primary and secondary visual areas [Puelles et al., 2012]. The superior colliculus plays a large role in integrating sensory motor information and, in particular, the generation of saccadic eye movements [Gandhi and Katnani, 2011]. Interestingly, while the GP is involved in motor generation and inhibition in general, the external segment of the GP (GPe) in particular may play an integral role in the generation and suppression of antisaccadic eye movements [Yoshida and Tanaka, 2016]. As the majority of the [11C]‐raclopride BPND in the GP reflects D2R in the external segment, our exploratory finding may point to a role for these receptors in saccadic eye movements. While highly speculative, we surmise that future PET studies should examine the relationship between the availability of D2R in the GPe and D3R in the GPi and saccadic eye movements—measured with [11C]‐raclopride and [11C]‐(+)‐PHNO, respectively.

There are several limitations to the current investigation. First, it has been noted that the injected mass of [11C]‐(+)‐PHNO is not within ideal radiotracer conditions (i.e., <1.5 ng/kg) [Gallezot et al., 2012]. The specific activity required to obtain tracer conditions is not possible with the available radiosynthesis method. While this limitation is currently unavoidable, we attempt to minimize this technical limitation by aiming to control the injected mass of the radiotracer to ≤2.5 µg (≤0.02 µg/kg), as previously used [Mizrahi et al., 2009; Rabiner and Laruelle, 2010; Searle et al., 2013a]. Importantly, our sample (mean injected mass: 2.15 ± 0.47µg) did not include any incidence of side effects associated with high [11C]‐(+)‐PHNO injected mass, such as nausea/vomiting [Mizrahi et al., 2009; Rabiner and Laruelle, 2010]. Second, it has been suggested that [11C]‐(+)‐PHNO BPND in D3R‐rich regions is underestimated if SRTM quantification is used in conjunction with 90 min of data acquisition [Girgis et al., 2011]. Thus, using arterial plasma‐based kinetic models following 120 min of emission data is more ideal for quantifying [11C]‐(+)‐PHNO BPND in D3R‐rich regions [Girgis et al., 2011]. Moreover, use of arterial plasma‐based kinetic models would circumvent limitations associated with using reference tissue methods, namely concerns about specific binding to D3R in cerebellar reference tissue [Searle et al., 2013b]. Future [11C]‐(+)‐PHNO studies would benefit from examining the relationship between D2/3R availability and brain morphology using plasma‐based modeling and 120 mine emission data. This study was retrospective, reanalyzing previously collected PET data. Thus, other relevant measures such as cognition were not available. Moreover, it would be important to determine how longitudinal changes in D2/3R availability with age may be associated with age‐related changes in brain morphology in healthy persons and persons with neuropsychiatric disorders. Moreover, it will be important to determine how brain morphology changes and striatal D2/3R availability changes relate to each other in addiction. For example, while we did not include heavy drinkers in our study, it would be important to determine how the frequency of alcohol use affects the relationship between in vivo brain morphology measures and DA measures. Finally, it will be important for future studies to examine how brain morphology is related to the in vivo status of other neurochemical systems. For example, increased striatal glutamate levels measured with proton magnetic resonance spectroscopy (1H‐MRS) have also been observed in patients with first‐episode psychosis [Plitman et al., 2016a]. In turn, striatal glutamate levels were found to be negatively correlated with dorsal caudate volumes in these patients [Plitman et al., 2016b]. Given the potential interactions between striatal DA and glutamate [Caravaggio et al., 2016b; Stone et al., 2007], it can be inferred that the dopaminergic changes observed in schizophrenia may also be related changes in brain morphology. However, without direct evidence this remains merely conjuncture.

While our participants were not taking medications for any serious medical condition, we did not record oral contraceptive use in our female participants. While some [11C]‐raclopride PET studies have observed no effect of menstrual cycle on baseline D2/3R availability in humans [Farde et al., 1995; Nordström et al., 1998], it is currently unknown whether this may effect [11C]‐(+)‐PHNO BPND. Future studies are required to examine the potential interacting effects between menstrual cycle, contraceptive use, and the availability of D2/3R using agonist radiotracers in females. Several lines of indirect evidence suggest that striatal DA functioning may differ between men and women. For example, women may be more vulnerable to the reinforcing effects of drugs of abuse [Becker and Hu, 2008; Fattore et al., 2007; Lynch et al., 2002; Nolen‐Hoeksema, 2004]. However, PET studies in humans have provided conflicting results as to whether there are sex differences in amphetamine‐induced striatal dopamine release [Munro et al., 2006; Riccardi et al., 2006, 2011]. Moreover, some studies suggest that DA transporter availability may not differ between gender, nor across the menstrual cycle [Best et al., 2005]. However, other studies suggests that women may have greater DA transporter functioning in the dorsal striatum [Andersen et al., 2012; Kaasinen et al., 2015; Lee et al., 2015; Wong et al., 2012], as well as greater DA synthesis capacity in the caudate [Laakso et al., 2002]. While we used sex as a covariate in our main analyses, there may be important sex differences between D2/3R availability and brain morphology. For the purposes of transparency, in Supporting Information A, we re‐conduct all our exploratory analyses within males and females separately. However, we did not sufficiently sample a large, nor equally matched number of males and females. Thus, interpretation of these data warrants caution and requires replication by sufficiently powered samples in the future.

Elucidating the relationship between metabolic health and striatal D2/3R availability remains an on‐going and exciting field of exploration in PET [Caravaggio et al., 2015a, 2015c; Dang et al., 2016; Gaiser et al., 2016; Horstmann, 2017]. It is beyond the scope of the current manuscript to review all these conflicting PET findings; considering all the different radioligands used for D2/3R, each with their own unique in vivo binding characteristics. Unfortunately, in our current sample, body mass index (BMI) was not collected for all the subjects. Moreover, other relevant markers of metabolic health, such as lipid profiles and insulin resistance, were not collected. In Supporting Information B, we provide the demographics of the subjects who provided BMI. For these subjects, we also re‐ran all the analyses of the current investigation using BMI as an additional covariate. Notably, only four subjects scanned with [11C]‐raclopride and three subjects scanned with [11C]‐(+)‐PHNO had BMI's within the moderately obese range (30–35). This is unsurprising as having a co‐morbid medical condition, such as diabetes or heart disease, was an exclusion criteria for being scanned in this retrospective dataset. Thus, we warrant caution when interpreting these supplementary results. We believe our sample is inadequate to address how obesity modulates D2/3R availability and brain morphology; we present this Supporting Information for the purposes of transparency, and for guiding future studies which are better poised to address this important topic. Related to metabolic syndrome, several lines of evidence suggest that low‐grade systemic inflammation may have an impact on cognition and brain structure [Marsland et al., 2015; Minihane et al., 2015]. While we have tried to screen “healthy” participants, we did not collect peripheral markers of inflammation. Future studies should examine how peripheral inflammatory markers—such as cytokines, leukocytes, and C‐reactive protein levels—relates to concurrent changes in brain morphology and D2/3R availability; in healthy persons, persons with neuropsychiatric disorders, and persons with metabolic diseases.

In our sample, PET scans were collected at various times of day. Moreover, we did not record when was the last meal participants had before their PET scans and were only suggested to abstain from food for no less than 90 min prior to PET. To our knowledge, DA release in response to food intake has only been examined with [11C]‐raclopride, and methylphenidate was required to be co‐administered to see a significant change in BPND [Volkow et al., 2002; Wang et al., 2011]. However, given the increased sensitivity of [11C]‐(+)‐PHNO to DA release, this tracer may be able to quantify DA release in response to food receipt without the co‐administration of methylphenidate. This can be examined by future [11C]‐(+)‐PHNO studies. With regards to the current investigation, it is noteworthy that the time of day of the scan did not correlate with the BPND of [11C]‐(+)‐PHNO (SN: r = 0.09, P = 0.49; Caudate: r = 0.10, P = 0.43; Putamen: r = 0.009, P = 0.95; VS: r = 0.20, P = 0.11; GP: r = −0.15, P = 0.21) nor of [11C]‐raclopride (Caudate: r = 0.11, P = 0.41; Putamen: r = 0.11, P = 0.40; VS: r = 0.12, P = 0.36; GP: r = 0.03, P = 0.85). Moreover, the month of scan acquisition was not correlated with the BPND of [11C]‐ (+)‐PHNO (SN: r = −0.02, P = .86; Caudate: r = −0.07, P = 0.57; Putamen: r = 0.06, P = 0.63; VS: r = 0.04, P = 0.74; GP: r = 0.13, P = 0.29) nor of [11C]‐raclopride (Caudate: r = 0.02, P = 0.90; Putamen: r = −0.04, P = 0.79; VS: r = 0.04, P = 0.78; GP: r = −0.08, P = 0.53). While the time of the last meal is not routinely collected across DA PET scans, this may be an important consideration for the future.

In sum, we examined how striatal D2/3R availability, measured with the antagonist [11C]‐raclopride and the agonist [11C]‐(+)‐PHNO, was related to the volume of several subcortical structures in healthy controls. Such an exploration will, (1) aid the interpretation of future PET findings and (2) help elucidate the relationships between brain chemistry, structure, and function which could be used as potential biomarkers for neuropsychiatric disease. Extension of this work to understand how abnormal in vivo DA functioning relates to brain structure and function in disorders like schizophrenia and food addiction are highly warranted.

Conflict of Interest

The authors have no potential conflicts of interest to declare in relation to the current study.

Supporting information

Supporting Information BMI

Click here for additional data file. (33.8KB, docx)

Supporting Information Gender

Click here for additional data file. (52.6KB, docx)

Supporting Information Figure01

Click here for additional data file. (221.3KB, tif)

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