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Neuroscience and Biobehavioral Reviews xxx (2015) xxx–xxx
Contents lists available at ScienceDirect
Neuroscience and Biobehavioral Reviews journal homepage: www.elsevier.com/locate/neubiorev
Review
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A systematic review of molecular imaging (PET and SPECT) in autism spectrum disorder: Current state and future research opportunities
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Nicole R. Zürcher a,b , Anisha Bhanot a , Christopher J. McDougle b,c,d , Jacob M. Hooker a,b,∗ a
A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA Harvard Medical School, Harvard, Boston, MA, USA Q2 Lurie Center for Autism, Department of Psychiatry, Massachusetts General Hospital, Lexington, MA, USA d Lurie Center for Autism, Department of Pediatrics, Massachusetts General Hospital, Lexington, MA, USA b c
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a r t i c l e
i n f o
a b s t r a c t
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Article history: Received 22 December 2014 Received in revised form 2 February 2015 Accepted 3 February 2015 Available online xxx
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Keywords: Positron emission tomography (PET) Single-photon emission computed tomography (SPECT) Neuroimaging Molecular imaging Autism spectrum disorder
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Contents
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1. 2. 3.
Non-invasive positron emission tomography (PET) and single-photon emission computed tomography (SPECT) are techniques used to quantify molecular interactions, biological processes and protein concentration and distribution. In the central nervous system, these molecular imaging techniques can provide critical insights into neurotransmitter receptors and their occupancy by neurotransmitters or drugs. In recent years, there has been an increase in the number of studies that have investigated neurotransmitters in autism spectrum disorders (ASDs), while earlier studies mostly focused on cerebral blood flow and glucose metabolism. The underlying and contributing mechanisms of ASD are largely undetermined and ASD diagnosis relies on the behavioral phenotype. Discovery of biochemical endophenotypes would represent a milestone in autism research that could potentially lead to ASD subtype stratification and the development of novel therapeutic drugs. This review characterizes the prior use of molecular imaging by PET and SPECT in ASD, addresses methodological challenges and highlights areas of future opportunity for contributions from molecular imaging to understand ASD pathophysiology. © 2015 Published by Elsevier Ltd.
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Article selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Current state and future research opportunities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. General overview of current state . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Targets and ASD population investigated . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1. Cerebral blood flow (CBF) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.2. Glucose metabolism using 2-deoxy-2-(18 F)fluoro-d-glucose ([18 F]FDG) PET . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.3. Serotonin: 5-hydroxytryptamine (5-HT) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.4. Dopamine (DA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.5. Gamma-aminobutyric acid (GABA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.6. Glutamate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.7. Acetylcholine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.8. Other neurochemical investigations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.9. Neuroinflammation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3. Studies based on neuropsychopharmacology in ASD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4. Longitudinal studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5. Combination of imaging modalities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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∗ Corresponding author at: Athinoula A. Martinos Center for Biomedical Imaging, Building 149, 13th Street, Suite 2301, Charlestown, MA 02129, USA. Tel.: +1 617 726 6596; fax: +1 617 726 7422. E-mail address: [email protected] (J.M. Hooker). http://dx.doi.org/10.1016/j.neubiorev.2015.02.002 0149-7634/© 2015 Published by Elsevier Ltd.
Please cite this article in press as: Zürcher, N.R., et al., A systematic review of molecular imaging (PET and SPECT) in autism spectrum disorder: Current state and future research opportunities. Neurosci. Biobehav. Rev. (2015), http://dx.doi.org/10.1016/j.neubiorev.2015.02.002
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ARTICLE IN PRESS
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conflicts of interest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1. Introduction
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Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders with prevalence as high as 1 in 68 children (CDC, 2014). Although a number of genetic mutations appear to be associated with ASD or with an increased risk or vulnerability for ASD, to date the collection of genetic mutations account for only a small percentage of total ASD cases (Persico and Napolioni, 2013). Epigenetic and environmental factors are increasingly implicated in the disorder. To date, there are no biomarkers that can be used to diagnose subtypes of idiopathic ASD (i.e. without any known genetic or environmental cause). An ASD diagnosis is based on clinical criteria with the hallmarks of the disorder being deficits in social communication and interaction, as well as restricted and repetitive behavior (APA, 2013). As implied by the use of the term ‘spectrum’ to describe autism, different forms of ASD exist. Uncovering the pathophysiological differences among disorders on the autism spectrum could help define biological subtypes of ASD and may improve diagnostic precision and clinical management, potentially leading to the development of more effective treatments. Although providing their own methodological strengths, animal models of ASD cannot reflect the complexity of the human disorder and may not represent atypical biology accurately. Thus, in order to better elucidate the underlying pathophysiology in ASD, it is critical to conduct non-invasive in vivo human neuroimaging studies. Nearly all neuroimaging studies in ASD share the common goal of explaining or stratifying ASD mechanisms by increasing our knowledge about structural, functional or neurochemical differences in the brains of individuals with ASD. In this review, we examine single-photon emission computed tomography (SPECT) and positron emission tomography (PET) studies that have been conducted in individuals with ASD to date. We will consider PET and SPECT together as molecular imaging (MI) although each of these modalities has distinct features. Both PET and SPECT are nuclear imaging techniques in which a radioactive material, referred to as radiotracer, is administered (typically intravenously) into a participant. A radiotracer is often a molecule that binds specifically to a particular target protein, e.g. a receptor, thereby allowing for visualization of distribution and quantification of the protein of interest. However, in other cases the distribution of the tracer is determined by where it accumulates following biochemical modification, e.g. with radiolabelled glucose. A very small mass of the tracer is administered in order to allow specific binding to targets of interest without promoting pharmacological effects or interacting through self-competition. With PET, radiotracer concentration is measured through the detection of high energy (511 keV) anti-colinear gamma photon pairs that result from positron annihilation. SPECT on the other hand, measures radiotracer concentration by detecting single gamma rays within a particular energy range, which depends on the isotope being used. In general, PET has about two to three times higher sensitivity than SPECT and while both methods have only moderate spatial resolution, PET has slightly higher spatial resolution than SPECT (Rahmim and Zaidi, 2008). Typically the isotopes used in SPECT studies have longer half-lives than those used in PET, which is why PET radiotracers are usually produced in an onsite cyclotron, and are thus often less accessible and more expensive. Despite some additional differences, PET and SPECT share key strengths at their core: (1) PET and SPECT can be used to
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noninvasively visualize and quantify differences in density of essential proteins such as receptors, transporters and enzymes; (2) in many cases, these techniques can be used to assess neurotransmitter release and occupancy; (3) PET and SPECT can measure drug-target engagement; and (4) functional measures, such as glucose metabolism and oxygen consumption, can be evaluated (though this is mostly limited to PET). 2. Article selection In the current review, we report all studies that we could identify based on a comprehensive literature search in PubMed. PubMed searches were conducted for PET or SPECT studies examining ASD (autism, Asperger syndrome, and pervasive developmental disorder not otherwise specified) in humans. We only reviewed original articles for which English text was available. We then checked the references of all articles for additional relevant studies. We identified 49 PET and 30 SPECT studies that have been performed in individuals with ASD over the past three decades (1985–2014). See Table 1 (PET studies) and 2 (SPECT studies) for an exhaustive list of papers reviewed, including number of participants (N), age, intelligence quotient (IQ), diagnosis, information about control/comparison group(s) and brief summary of main findings for each study.
102 103 104 105 106 107 108
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110 111 112 113 114 115 116 117 118 119 120 121 122 123
3. Current state and future research opportunities
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3.1. General overview of current state
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We identified and reviewed 79 studies that have used MI techniques to investigate ASD. Given the challenges associated with MI studies in ASD, such as the requirement of an intravenous line for radiotracer injection, the exposure to radiation and potential sedation in the context of surrogate consent (for children and adults with ASD unable to consent for themselves), this represents a considerable number of studies. However, compared to other neuropsychiatric/neurological disorders such as Parkinson’s disease, epilepsy, Alzheimer’s disease and schizophrenia, there is a paucity of PET and SPECT studies in the field of ASD (depicted in Fig. 1). While in this review we draw attention to the fact that there is a real need for future MI studies in the field of ASD, Fig. 1 illustrates that there is also a relative lack of MI in bipolar disorder and major depression, two neuropsychiatric diseases with high prevalence. The disparity between the prevalence of ASD and the number of MI studies conducted to date warrants investments in methods to better address and overcome the practical and technical challenges of nuclear imaging modalities. 3.2. Targets and ASD population investigated The most salient feature of the PET/SPECT literature is that the vast majority of MI studies have investigated cerebral blood flow (CBF) or glucose metabolism. About half of all studies conducted in ASD have investigated CBF and approximately a quarter have investigated glucose metabolism. This means that a minority of studies has investigated neurotransmitters (receptors, transporters or synthesis), other proteins or protein synthesis. See Fig. 2A for an illustration of the percentage breakdown for the different molecular targets.
Please cite this article in press as: Zürcher, N.R., et al., A systematic review of molecular imaging (PET and SPECT) in autism spectrum disorder: Current state and future research opportunities. Neurosci. Biobehav. Rev. (2015), http://dx.doi.org/10.1016/j.neubiorev.2015.02.002
126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143
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145 146 147 148 149 150 151 152 153
ASD age: mean ± SD, range
Number of participants (N)
ASD diagnosis
ASD IQ: mean ± SD, range
ASD sedation
Control (CON)/ comparison group
Major findings in ASD
Rumsey et al. (1985) De Volder et al. (1987)
Glucose
26 years ± 6, 18–36 years 9.8 years ± 4.0
ASD: N = 10, CON: N = 15 ASD: N = 14; (i) N = 15; (ii) N = 3; (iii) N = 3
Autism [DSM-III]
IQ: 48–117
No
Widespread hypermetabolism
Autism [DSM-III]
Low to moderate MR
DHB + etybenzatropine when DHB > 0.2 mg/kg dose
Herold et al. (1988)
OER, CBF and Glucose
21–25 years
ASD: N = 6; CON: N = 8
Infantile autism [Rutter’s 1978 criteria], autism [DSM-III-R]
FISQ: < 45–92
No
Horwitz et al. (1988)
Glucose
27 years ± 6.6, 18–39 years
ASD: N = 14; CON: N = 14
VIQ: 48–117; PIQ: 55–126
No
Heh et al. (1989)
Glucose
IQ: 91 ± 25, 72–131 VIQ: 93, 78–122; PIQ: 90, 75–112
No
Matched by age
Glucose
ASD: N = 7; CON: N = 8 ASD: N = 7; CON: N = 13
Fewer positive correlations of regional glucose utilization b/w frontal and parietal regions No differences b/w groups
Buchsbaum et al. (1992)
23 years ± 6, 19–36 years 25 years, 19–38 years
No
Comparable socioeconomic status
↓ rGMR in right posterior thalamus and right putamen
Siegel et al. (1992)
Glucose
23 years ± 6, 17–38 years
ASD: N = 16; CON: N = 26
Infantile autism during childhood, autism [DSM-III] Autism [ICDS and DSM-III] Autism during childhood [DSM-III, ICDS, K-SADS and DICA] Autism during childhood [ICDS]
Matched by sex and age (i) CON adults; (ii) Nearly normal children; (iii) Hemibrains of children w/unilateral pathology (i) age-matched to test CBF, oxygen and glucose; (ii) not age-matched to test CBF and oxygen Matched by sex and age
IQ: 90 ± 17, 74–135
No
Similar socioeconomic status
Schifter et al. (1994)
Glucose
7.3 years ± 2.2, 4.5–11 years
ASD: N = 13
Some degree of MR
No
No CON/comparison group
Siegel et al. (1995)
Glucose
27 years ± 7, 19–46 years
ASD: N = 14; CON: N = 20
Autism [DSM-III-R], some w/coexisting seizure disorders Autism during childhood [ICDS]
↓ GMR in left posterior putamen ↑ GMR in right posterior calcarine cortex 4/13 individuals w/ASD had an abnormal FDG-PET scan
IQ: 90 ± 17, 74–135
No
Matched by age
Chugani et al. (1996)
Glucose
Infantile spasms w/temporal hypometabolism: N = 18; CON: N = 10
Cryptogenic infantile spasms, autism [DSM-IV]
Nonverbal/severe language impairment
Chloral hydrate when not under natural sleep
Previously obtained data from age-matched children: 3 years 6 months ± 1 yr. 3 months, 8 months - 4 years 7 months
Happe et al. (1996)
CBF
2 years 3 months ± 1 yr. 4 months, 10 months–5 years and 6 years 3 months ± 2 years 6 months, 3 years–12 years 5 months at follow-up 24 years, 20–27 years
ASD: N = 5; CON: N = 6
AS [developmental history and current presentation]
FISQ: 100, 87–112; VIQ: 110, 93–125; PIQ: 92, 83–100
No
Normal volunteers from previous study
Chugani et al. (1997)
5-HT Synthesis
6.6 years, 4.1–11.1 years
ASD: N = 8; CON: N = 5
Autism [DSM-IV, GARS and CARS]
OABC: 19–29 months
Nembutal/midazolam
Siblings
Ernst et al. (1997)
Presynaptic DA activity D2
13 years ± 2
ASD: N = 14; CON: N = 10 ASD: N = 6
Autism [DSM-III-R]
IQ: 74 ± 23.1, 46–123 IQ: 20–70
Propofol
Similar age:14 years ± 2 N/A, w/in group treatment study
3–5 years
Autism [DSM-III-R and CARS]
Propofol
No differences b/w groups
No differences b/w groups
Negative correlation b/w GMR in medial frontal cortex and attentional performance Children w/infantile spasms w/temporal hypometabolism have a poor long-term outcome and majority are autistic at follow-up (10/14)
ToM task-induced activity in left mPFC in CON but not in ASD Activity in more ventral mPFC in ASD Abnormalities and asymmetries in dentatothalamocortical pathway ↓ FDOPA uptake in mPFC
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10% ↓ in D2 binding in caudate and putamen after tetrahydrobiopterin treatment
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Fernell et al. (1997)
Glucose
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N.R. Zürcher et al. / Neuroscience and Biobehavioral Reviews xxx (2015) xxx–xxx
Please cite this article in press as: Zürcher, N.R., et al., A systematic review of molecular imaging (PET and SPECT) in autism spectrum disorder: Current state and future research opportunities. Neurosci. Biobehav. Rev. (2015), http://dx.doi.org/10.1016/j.neubiorev.2015.02.002
Table 1 PET Studies in ASD.
Target
ASD age: mean ± SD, range
Number of participants (N)
ASD diagnosis
ASD IQ: mean ± SD, range
ASD sedation
Control (CON)/ comparison group
Major findings in ASD
Haznedar et al. (1997) Muller et al. (1998)
Glucose
24.3 years ± 10.7, 17–47 years 25.5 years, 18–31 years
ASD: N = 7; CON: N = 7 ASD: N = 4; CON: N = 5
Autism [ADI]
IQ: 60–123, Verbally fluent IQ: 77.3, 71–92
No
Matched by sex and age Matched by sex and similar age: 26.2 years, 23–30 years
↓ Metabolic activity in AC
Chugani et al. (1999)
5-HT Synthesis
6.41 years ± 3.3, 2.3–15.4 years
ASD: N = 30; (i) N = 8; (ii) N = 16
Autism [DSM-IV, ADI-R, GARS and CARS]
Mental age < 24 months
Nembutal/midazolam
Muller et al. (1999)
CBF
26.6 years, 18–31 years
ASD: N = 5; CON: N = 5
Autism [GARS]
FISQ: 75.6, 69–92 PIQ: 74.5, 67–84
No
Haznedar et al. (2000)
Glucose
27.7 years ± 11.3
Autism or AS [DSM-IV]
IQ: 55–125, Verbally fluent
No
Matched by sex and age
Zilbovicius et al. (2000)
CBF
1st autistic group: 8.4 years ± 2.7 2nd autistic group: 7.4 years ± 1.7
Autism: N = 10; AS: N = 7; CON: N = 17 ASD: N = 21; CON: N = 10
Infantile autism [DSM-IV]
Pentobarbital sodium
Nonautistic children w/idiopathic MR, similar age and developmental quotient
Hypoperfusion of bilateral temporal lobes
Buchsbaum et al. (2001)
Glucose
30.5 years ± 8.6
Autism: N = 5; AS: N = 1
Autism or AS [DSM-IV and ADI]
MR in both groups. 1st autistic group: 3.3 ± 1. 2nd autistic group: 3.2 ± 1.5 [BSES] IQ: 95, 53–119
No
N/A, w/in group treatment study
Boddaert et al. (2002)
CBF
8.4 years ± 2.7, 6–13 years
ASD: N = 21; CON: N = 10
Autism [DSM-IV]
MR
Nembutal
Castelli et al. (2002)
CBF
33 years ± 7.6
ASD: N = 10; CON: N = 10
Autism or AS [DSM-IV]
No
Boddaert et al. (2003)
CBF
19.1 years ± 4.5
ASD: N = 5; CON: N = 8
Autism [DSM-IV and ADI]
≥ Average verbal (61 ± 24 [Quick Test]) and nonverbal (73 ± 30 [Raven Matrices]) ability IQ: 64 ± 5
CON group w/idiopathic MR, matched by age and IQ CON group did not differ in verbal or nonverbal ability
Regional metabolic rate ↑ after fluoxetine treatment in AC, orbitofrontal areas and striatum Individuals w/↑ baseline metabolic activity most likely to respond to treatment ↓ Blood flow in STS, STG and bilateral temporal lobe
No
Healthy individuals
Hall et al. (2003)
CBF
20–33 years
ASD: N = 8; CON: N = 8
Autism or AS [DSM-IV]
NVIQ: 105 ± 18, 80–130
No
CON group w/similar nonverbal IQs: 109 ± 16, 90–135
CBF
Infantile autism by ≤ 5 years, autism [DSM-IV and GARS]
No
↓ Activity in right dentate nucleus and left frontal BA 46 during auditory and language tasks ↑ Activity during motor speech tasks Atypical age-related changes in 5-HT synthesis in ASD
↓ Activation in mPFC, STS (at TPJ) and temporal poles in response to mentalizing-triggering animations ↓ Activation in left temporal areas and ↑ activation in right middle frontal gyrus in response to speech-like sounds ↓ rCBF in inferior frontal and fusiform areas ↑ rCBF in right anterior temporal pole, AC and thalamus during emotion-recognition task
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Reversal of left hemispheric dominance during language perception ↓ Activation in cerebellum during nonverbal auditory perception ↓ Metabolism in AC and posterior cingulate
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Matched by sex and age: (i) siblings (w/& w/o DD); (ii) children w/epilepsy Matched by sex
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Please cite this article in press as: Zürcher, N.R., et al., A systematic review of molecular imaging (PET and SPECT) in autism spectrum disorder: Current state and future research opportunities. Neurosci. Biobehav. Rev. (2015), http://dx.doi.org/10.1016/j.neubiorev.2015.02.002
Table 1 (Continued)
Children w/idiopathic MR
No
Healthy volunteers matched by sex and age
No
CON group did not differ in social status, cognitive functions and age: 30.5 years ± 4.9 N/A, case study
↓ Activation in left middle temporal gyrus and precentral frontal gyrus ↓ rGMR in medial/cingulate areas ↑ rGMR in occipital and parietal areas ↑ presynaptic DA activity in striatum and frontal cortex
Boddaert et al. (2004)
CBF
6.6 years ± 1.6
ASD: N = 11; CON: N = 6
Autism [DSM-IV]
Hazlett et al. (2004)
Glucose
27.7 years ± 11.3, 17–55 years
ASD: N = 17; CON: N = 17
Autism or AS [DSM-IV]
Nieminen-von Wendt et al. (2004)
Presynaptic DA activity
29.2 years ± 5.8
ASD: N = 8; CON: N = 5
AS [DSM-IV and ICD-10]
Boddaert et al. (2005)
CBF
20 years
ASD: N = 1
Autism [DSM-IV and ADI-R]
IQ: 66
No
Chandana et al. (2005)
5-HT synthesis
6.5 years ± 2.7
ASD: N = 117; Siblings: N = 8; Epilepsy: N = 16
Autism [DSM-IV, ADI-R, GARS and CARS]
Mental age < 24 months
Nembutal/midazolam
Normal siblings and children w/epilepsy
Gendry Meresse et al. (2005)
CBF
7.9 years ± 2.2, 5–11.9 years
ASD: N = 45
Autism [DSM-IV and ADI]
IQ: 44 ± 22
Pentobarbital
Haznedar et al. (2006)
Glucose
27.7 years ± 11.3, 17–55 years
Autism: N = 10; AS: N = 7; CON: N = 17
Autism or AS [DSM-IV]
IQ: 97.1 ± 25.3, 55–125, Verbally fluent
No
N/A, w/in group correlational disease severity study Matched by sex and age
Chugani et al. (2007)
Glucose
4.9 years ± 1.7, 2.7–7.9 years
ASD: N = 12; Port-wine stain + ASD: N = 4; CON: N = 11
Infantile Autism [ADI-R, AQ, VABS and GARS]
Not specified
Yes, “sedated as necessary”
Port-wine stain + ASD: 2.9–6 years; CON: healthy young adults 25.5 years ± 2.0
Nakamura et al. (2010)
SERT and DAT
21.2 years ± 2.0, 18–26 years
ASD: N = 20; CON: N = 20
Autism [DSM-IV-TR, ADI and ADOS]
IQ: 99.3 ± 18.1
No
Matched by sex and similar age: 21.9 years ± 2, 18–26 years, IQ not significantly different
7.9 years ± 2.2, 5–12 years
ASD: N = 45; CON: N = 13
Girgis et al. (2011)
5-HT2A and SERT
34.3 years ± 11.1, 18–50 years
ASD: N = 17; CON: N = 17
Idiopathic ASD, low-functioning [DSM IV-R and ADI-R] AS [DSM-IV]
IQ: 45 ± 22, DQ: 44 ± 23
Rectal pentobarbital
IQ: > 85
No
Non-ASD group: low-functioning individuals w/MR (8.6 years ± 2.7, 5–15 years) Matched by sex, age and ethnicity
Left hippocampus, left frontal cortex and left middle temporal lobe activated during calendar task Abnormal cortical asymmetry in ASD (64/117) ↓ 5-HT synthesis in ASD (58/64) Children w/ASD w/left hemispheric asymmetry more likely to have language impairments Negative correlation b/w rCBF and ADI-R score in left STG ↓ rGMR bilaterally in ventral caudate, putamen and thalamus in ASD ↓ Metabolic activity in ventral thalamus in autism compared to AS Compared to CON, ASD group had ↓ glucose uptake in the cerebellum, medial temporal, AC, lateral temporal and frontal cortices Compared to Port-wine stain + ASD, ASD had ↑ glucose uptake in medial temporal and AC cortices and ↓ glucose uptake in lateral temporal cortex ↓ SERT binding in AC and posterior cingulate correlated w/ASD symptomatology ↑ DAT binding in orbitofrontal cortex ↓ Blood flow in right STS ↑ blood flow in contralateral post central area No differences in 5-HT2A or DAT binding b/w groups
5
CBF
IQ: 93.2 ± 26.4, 55–135, All verbally fluent IQ: 112.5 ± 12.6, 97–140
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AS [DSM-IV and ICD-10]
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ASD: N = 8; CON: N = 8
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↑ Blood flow in cerebellum
28.1 years ± 6.2, 19.2–38.2 years
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CON group did not differ in social status and age: 31.5 years ± 4.5, 23.8–39.8 years
CBF
Duchesnay et al. (2011)
FIQ:109.0 ± 15.7, 88–140; VIQ: 107.9 ± 15.3, 82–131; PIQ: 111.1 ± 15.7, 95–144 IQ: 43 ± 21
No
Nieminen-von Wendt et al. (2003)
Number of participants (N)
ASD diagnosis
ASD IQ: mean ± SD, range
ASD sedation
Control (CON)/ comparison group
Major findings in ASD
Lee et al. (2011b)
Glucose
6.0 years ± 1.8
No
CON: 9.73 years ± 2.55
Glucose
6.0 years ± 1.8
ASD [Korean ADI-R] Not specified
Not specified
Lee et al. (2011a)
Not specified
Not specified
ADHD: 8.2 years ± 1.6; CON: 9.7 years ± 2.8
Local overconnectivity and long-range underconnectivity Segmented brain connectivity and temporal lobe asymmetry
Shandal et al. (2011)
Leucine/protein synthesis
DD w/PDD: 76.25 months ± 20.59; DD w/o PDD: 77.63 months ± 13.8
DD w/& w/o PDD [GARS and VABS]
Significant global DD [assessed clinically and by VABS]
No
Healthy adults
↑ Protein synthesis rate in left posterior middle temporal area in DD w/PDD, also correlated w/GARS scores
Suzuki et al. (2011)
AChE
25.3years ± 4.3, 18–33 years
ASD: N = 26; CON: N = 11 ASD: N = 26; ADHD:N = 24; CON: N = 11 DD w/PDD: N = 8; DD w/o PDD: N = 8; CON: N = 9 ASD: N = 20; CON: N = 20
IQ: 91.6 ± 19.7, 70–140
No
Matched by sex, age and IQ
Beversdorf et al. (2012) Deriaz et al. (2012)
5-HT2A
31.0 years ± 8.0
IQ: 114.7 ± 14.7
No
20 years
General anesthesia
Lee et al. (2012)
Glucose
6.0 years ± 1.8
Severe intellectual disability Not specified
Matched by age and FISQ N/A, case study
↓ AChE activity in bilateral fusiform gyri negatively correlated w/social disabilities ↓ 5-HT2A binding in thalamus
Glucose
Autism [DSM-IV-TR, ADI-R and ADOS] Autism [DSM-IV and ADI-R] PDD w/SIB [Clinical evaluation]
Pagani et al. (2012)
CBF
Dilber et al. (2013)
ASD: N = 8; CON: N = 12 ASD: N = 1
No
ADHD: 8.2 years ± 1.6; CON: 9.7 years ± 2.8
IQ: 105.3 ± 16.4, 87–135
No
Matched by sex, age and IQ
Infantile spasms during childhood, autism [DSM-IV, ABC, CARS] Autism [ICD-10, ADOS]
Mild to severe MR
Chloral hydrate
9 patients w/infantile spasms but no ASD
IQ: 117–127
No
CON group from past study, matched by sex and age
ASD: N = 8
Autism [DSM-IV-TR]
Not specified
No
N/A, w/in group treatment study
ASD: N = 20; CON: N = 20
ASD [DSM-IV-TR, ADI-R, ADOS]
IQ: 95.9 ± 16.7, 81–140
No
Matched by sex, age and IQ
31.8 years ± 8.6, 20–48 years
ASD: N = 26; ADHD:N = 24; CON: N = 11 ASD: N = 13; CON: N = 10
ASD [Korean ADI-R and ADOS] Autism [DSM-IV GAF, ADOS-G, RAADS-R and AQ]
Glucose
7.8 years ± 4, 3–16 years
ASD: N = 15; CON: N = 9
Mendez et al. (2013)
GABAA
34–43 years
ASD: N = 3; CON: N = 3
Sharma et al. (2013)
Glucose
10.5 years ± 5.6, 3–33 years
Suzuki et al. (2013)
TSPO
23.3 years ± 4.0, 18.6–31.9 years
↓ Metabolism in right temporo-parietal area and right left posterior fossa Atypical connectivity b/w left inferior prefrontal regions and other brain areas in ASD ↑CBF in parahippocampal, posterior cingulate, primary visual and temporal cortex, putamen, caudate, substantia nigra and cerebellum ↓ Metabolic activity in temporal lobe (13/15 ASD), frontal lobe (9/15) and parietal lobe (7/15) ↓ Volumes of distribution in amygdala, subcallosal cortex and nucleus accumbens ↓ GABAA receptors in bilateral amygdala and nucleus accumbens Changes in FDG utilization in frontal, temporal, parietal, cingulate occipital, lobes, cerebellum, amygdala, hippocampus, and basal ganglia ↑ Microglial activation in fusiform gyrus, orbitofrontal cortex, cingulate cortex, midbrain, pons and cerebellum
Abbreviations: 5-HT, Serotonin; 5-HT2A , Serotonin 2A Receptor; AC, Anterior Cingulate; AChE, Acetylcholinesterase; ADI, Autism Diagnostic Interview; ADI–R, ADI- Revised; ADOS, Autism Diagnostic Observation Schedule; ADOS-G, ADOS-Generic; AS, Asperger Syndrome; ASD, Autism Spectrum Disorder; AQ, Autism Spectrum Quotient; BA, Brodmann Area; BSES, Behavior Summarized Evaluation Scale; CARS, Childhood Autism Rating Scale; CBF, Cerebral Blood Flow; D2 , Dopamine D2 Receptor; DA, Dopamine; DAT, Dopamine Transporter; DHB, Droperidol; DD, Developmental Delay; DICA, Diagnostic Interview for Children and Adolescents; DQ, Developmental Quotient; DSM-III, Diagnostic and Statistics Manual of Mental Disorder Third Edition; DSM-III-R, DSM Third Edition Revised; DSM-IV, DSM Fourth Edition; DSM-IV-TR, DSM Fourth Edition Text Revised; FISQ, Full Scale Intelligence Quotient; GABAA, ␥-Aminobutyric Acid Type A Receptor; GAF, Global Assessment of Functioning; GARS, Gilliam Autism Rating Scale; GMR, Glucose Metabolic Rate; HFA, High-Functioning Autism; ICD-10, International Classification of Diseases Tenth Revision; ICDS, Interview for Childhood Disorders and Schizophrenia; IQ, Intelligence Quotient; K-SADS, Kiddie Schizophrenia and Affective Disorder Scales; LFA, Low-Functioning Autism; mPFC, Medial Prefrontal Cortex; MR, Mental Retardation [note: now referred to as intellectual disability]; NVIQ, Nonverbal Intelligence Quotient; OABC, Overall Adaptive Behavior Composite from the Vineland Adaptive Behavior Scale; OER, Oxygen Enhancement Ratio; PDD, Pervasive Developmental Disorder; PIQ, Performance Intelligence Quotient; RAADS-R, Ritvo Autism Asperger Diagnostic Scale – Revised; rCBF, Regional Cerebral Blood Flow; rGMR, Relative Glucose Metabolic Rate; SERT, Serotonin Transporter; SIB, Self-Injurious Behavior; STG, Superior Temporal Gyrus; STS, Superior Temporal Sulcus; TPJ, Temporo-Parietal Junction; TSPO, Translocator Protein; VABS, Vineland Adaptive Behavior Scale; VIQ, Verbal Intelligence Quotient.
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Please cite this article in press as: Zürcher, N.R., et al., A systematic review of molecular imaging (PET and SPECT) in autism spectrum disorder: Current state and future research opportunities. Neurosci. Biobehav. Rev. (2015), http://dx.doi.org/10.1016/j.neubiorev.2015.02.002
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Table 1 (Continued)
Target
ASD age: mean ± SD, range
Number of participants (N)
ASD diagnosis
ASD IQ: mean ± SD, range
ASD sedation
Control (CON)/ comparison group
Major findings in ASD
Ozbayrak et al. (1991)
CBF
22 years
ASD: N = 1
N/A, case study
Left occipital hypoperfusion
CBF
27.7 years, 22–34 years
ASD: N = 4; CON: N = 4
VIQ: 90 PIQ: 61 Degree of MR w/minimal verbal skills
No
George et al. (1992)
AS w/TD/PDDNOS [DSM-III-R] Infantile autism [DSM-III-R]
No
Matched by age
Zilbovicius et al. (1992)
CBF
7.5 years ± 1.7, 5–11 years
ASD: N = 21; CON: N = 14
Infantile autism [DSM-III-R]
NVIQ: 36 ± 18.5, 10–75
Pentobarbital + DHB
Gillberg et al. (1993)
CBF
ASD: N = 16; ASD w/epilepsy: N = 10; ASD-like w/epilepsy: N=5
Autism [DSM-III-R, ABC and CARS]
Above average intelligence to severe MR
General anesthesia
Mountz et al. (1994)
CBF
ASD: 10.6 years, 4.5–22 years ASD w/epilepsy: 8.1 years, 1–19 years ASD-like w/epilepsy: 8.7 years, 4.5–12 years 13 years
Nonautistic children w/slight to moderate language disorders, matched by age Autism w/o epilepsy group compared to autism w/epilepsy group and to autism-like w/o epilepsy group
↓ Total brain perfusion ↓ rCBF in right lateral temporal and right, left and midfrontal lobes No cortical differences b/w groups
ASD: N = 1
Not specified
Not specified
NA, case study
Chiron et al. (1995)
CBF
10.9 years ± 4.2, 4.5–17 years
ASD: N = 18; CON: N = 10
Autism [diagnostic criteria not specified] Autism [DSM-III-R and ICD-10]
Normal intelligence to severe MR Verbal level ranging from no words to near-normal speech
Pentobarbitone + DHB
McKelvey et al. (1995)
CBF
Case 1: 14 years Case 2: 16 years Case 3: 17 years
ASD: N = 3
Autism [DSM-III-R], further diagnosis of AS
No
Mountz et al. (1995)
CBF
13.7 years, 9–21 years
ASD: N = 6; CON: N = 7
Autism [DSM-III-R and ASIEP]
Case 1: “normal intelligence” Case 2 ¨’lowaverage intelligence” Case 3 VIQ: 91, NVIQ: 106, GIQ: 98 PIQ scores: 45, 32, 51, 70, 72, 100
Individuals w/transient events unaccompanied by a cerebral lesion retrospectively considered to be normal, matched by sex N/A, case study
Zilbovicius et al. (1995)
CBF
Stage 1: 41.0 months ± 8.5 Stage 2: 79.2 months ± 7.7
ASD: N = 5; CON: N = 5
Childhood autism [DSM-III-R]
Stage 1 DQ IQ: 20–34 Stage 2 DQ IQ: 20–50
Pentobarbital + DHB
Carratala et al. (1998)
CBF
3 years
ASD: N = 1
Autism [DSM-IV]
Not specified
Jambaque et al. (1998)
CBF
13 years
ASD: N = 1
Autism [ADI-R]
IQ: 56 [Brunet-Lehne non-verbal scale] VIQ: 63
i) Children w/suspected neurological problem found to be due to another cause retrospectively ii) Healthy adults Children w/neurological problems found retrospectively to be transient and unaccompanied by cerebral lesions, matched by age N/A, case study
Not specified
N/A, case study
Ryu et al. (1999)
CBF
54 months, 28–92 months
ASD: N = 23
Autism [DSM-IV and CARS]
Not specified
Chlorpromazine
No CON group
↓ rCBF in temporal lobes
↓ Blood flow in bilateral posterior temporal and occipital cortices ↑ rCBF in left vs. right hemisphere
CBF abnormalities in right hemisphere
↓ CBF in temporal and parietal lobes Greater abnormalities in CBF in left vs. right hemisphere Delayed frontal hypoperfusion in ASD at 3–4 years (happens ∼ 2years earlier in children with typical development) Frontal perfusion normalized in ASD by 6–7 years ↓ Blood flow in left temporoparietal cortex Hypoperfusion in left frontal cortex ↓ Perfusion in areas such as: cerebellum, thalamus, basal ganglia, posterior parietal and temporal regions
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Midazolam + ketamine for severely low-functioning subjects
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Please cite this article in press as: Zürcher, N.R., et al., A systematic review of molecular imaging (PET and SPECT) in autism spectrum disorder: Current state and future research opportunities. Neurosci. Biobehav. Rev. (2015), http://dx.doi.org/10.1016/j.neubiorev.2015.02.002
Table 2 SPECT studies in ASD.
7
Number of participants (N)
ASD diagnosis
ASD IQ: mean ± SD, range
ASD sedation
Control (CON)/ comparison group
Major findings in ASD
Hashimoto et al. (2000)
CBF
67.9 months ± 31.2, 2 years, 3 months13 years 11 months
ASD: N = 22; CON: N = 10
Autism [DSM-IV]
IQ: 52.5 ± 16.2, 24–90
Pentobarbital sodium
Nonautistic group w/either ADHD or MR, matched by age
Ohnishi et al. (2000)
CBF CBF
ASD: N = 23; CON: N = 26 ASD: N = 30; CON: N = 14
Infantile autism [DSM-IV] Autism [DSM-IV, ADI and CARS]
IQ: 48 ± 19.5 [Stanford Binet or DQ] PIQ: 30 ± 18.5
Pentobarbital
Starkstein et al. (2000)
6.5 years ± 2.4, 2.6–13 years 11.1 years ± 7.0
Kaya et al. (2002)
CBF
6.13 years ± 1.99, 3–11 years
ASD: N = 18; CON: N = 11
Autism [DSM-IV]
IQ: 56.11 ± 10.51 [Goodenough IQ Test]
Yes, though drug not specified
Wilcox et al. (2002)
CBF
3–37 years
ASD: N = 14; CON: N = 14
Autism [DSM-IV]
Complete mutism to moderately severe difficulty w/language
General anesthesia for most subjects
Nonautistic children w/MR, matched by age and IQ Nonautistic children w/MR, comparable in chronological age, mental age, height, weight and head circumference Children w/suspected neurological problem, retrospectively attributed to other cause CON data from hospital database, matched by sex and age
↓ rCBF in laterotemporal and dorso-medio-frontal regions in ASD Greater ↑ in right vs. left for temporal and parietal lobes in ASD ↓ rCBF in bilateral insula, STG and left prefrontal cortices ↓ Perfusion in right temporal lobe, occipital lobes, thalami and left basal ganglia
Steiner et al. (2003)
CBF
Autism: 10 years Atypical Autism: 7.4 years AS: 11.8 years
Autism, atypical autism or AS [DSM-IV]
Not specified
General anesthesia
Individuals w/MR w/o Down syndrome
Ito et al. (2005)
CBF
11.7 years ± 1.8, 9–14 years
Autism: N = 60; Atypical autism: N = 13; AS: N = 11; CON: N = not specified ASD: N = 16; CON: N = 5
Autism [DSM-IV], High-functioning Autism [IQ ≥ 70]
IQ: 94.7 ± 14.4, 76–126
No
Comparison group w/cryptogenic epilepsy, matched by age
Xiao-Mian et al. (2005)
DAT
3–10 years
No
5-HT2A
26 years ± 6
Children autism [DSM-IV] AS [DSM-IV, ICD-10 and ADI-R]
Not specified
Murphy et al. (2006)
ASD: N = 10; CON: N = 10 ASD: N = 8; CON: N = 10
FISQ: 80–100
No
Matched by sex, age and nation Matched by sex and age
Burroni et al. (2008)
CBF
11.2 years
ASD: N = 11; CON: N = 8
Child autism [DSM-IV and ABC]
Not specified
Propofol
Degirmenci et al. (2008)
CBF
6.9 years ± 1.7
HFA: N = 7; LFA: N = 3; (i): N = 5; (ii): N = 23; (iii): N = 15
Autism [DSM-III-R]
High- and lowfunctioning individuals, but IQ not specified
Midazolam + ketamine
Inhalatory anesthesia + halothane or sevoflurane (if used)
Nonautistic individuals matched by age. Individuals w/an episode of febrile seizure but regular neurological development/normal brain scan (i) Children w/normal brain perfusion, brain CT or MRI and EEG. Matched by age for autism group; (ii) 1st degree relatives of 8 individuals w/autism in study (e.g. mother, father, siblings); (iii) Sex- and age-matched CON for 1st degree relatives
Hypoperfusion in frontal, frontotemporal and temporal occipital areas Hypoperfusion in PFC Hypoperfusion of speech areas in left temporal lobe and frontal areas more prominent w/↑ age No significant differences b/w groups
Significant hypoperfusion in temporal cortex Abnormal laterality in temporal, thalamic and hippocampal regions ↑ DAT binding ↓ 5-HT2A binding in AC, posterior cingulate, left parietal lobe, bilaterally in frontal and superior temporal lobes in AS ↓ CBF Right > left asymmetry, especially in temporo-parietal areas
Abnormalities in brain perfusion found in caudate nucleus, frontal, temporal and parietal cortex in ASD as well as 1st degree relatives
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Please cite this article in press as: Zürcher, N.R., et al., A systematic review of molecular imaging (PET and SPECT) in autism spectrum disorder: Current state and future research opportunities. Neurosci. Biobehav. Rev. (2015), http://dx.doi.org/10.1016/j.neubiorev.2015.02.002
Table 2 (Continued)
ASD: N = 15; CON: N = 10
Autism [ICD-10], “high-functioning individuals w/autism” [CARS]
IQ: 70–79 [Leiter method]
Midazolam for one scan; Propofol + thiopental for other scan
Gupta and Ratnam (2009)
CBF
6 years ± 1.5, 4–8 years
ASD: N = 10; CON: N = 5
Infantile autism [DSM-IV]
IQ: 49 ± 12
No
Sasaki et al. (2010)
CBF
9.9 years, 4–16 years
ASD: N = 15
IQ: 35–85 DQ: 15–58
No
Compared w/a normal database from the institute
Makkonen et al. (2011)
DAT
5–11 years
ASD: N = 13; CON: N = 10
ASD [DSM-IV] w/frontal lobe epilepsy or temporal lobe epilepsy Autism [ATEC]
Not specified
No
Yang et al. (2011)
CBF
7.2 years ± 3
Autism: N = 14; AS: N = 9; CON: N=8
ASD classified as autism or AS [DSM-IV]
Not specified
Chloral hydrate
CON group w/neurological symptoms warranting SPECT examination, age range: 7–14 years Children w/normal brain perfusion and developmental history (assessed during neurological development examination), matched by age
Mori et al. (2012)
GABAA
7.0 years ± 3.7
Autism: N = 9; AS: N = 15; CON: N = 10
ASD classified as autism or AS [DSM-IV]
IQ < 70 (N = 7); IQ > 70 (N = 17)
Triclofos sodium
Zhao et al. (2014)
CBF
4.52 years ± 2.73
ASD: N = 55
Childhood autism [DSM-IV and ABC]
Not specified
Chloral hydrate “administered to uncooperative patients”
CON group w/symptomatic diagnoses (e.g. tremors, cephalalgia, epilepsy, unexplained odd feeling, motor disturbances, and tiredness), matched by age Matched by age
Non-symptomatic partial epilepsy patients w/o intellectual delay, similar age: 7.8 years ± 3.6 N/A, w/in group treatment study
↓ SERT binding in medial frontal cortex
Hypoperfusion in frontal and prefrontal areas, subcortical areas as well as generalized hypoperfusion Pattern of ↓ blood flow in PFC, medial frontal cortex, AC cortex, medial parietal cortex and anterior temporal lobe DAT binding ↓ w/age in ASD but ↑in CON Patients who responded to fluoxetine treatment had ↓ DAT binding ↓ rCBF in bilateral frontal lobe and bilateral basal ganglia in ASD ↓ rCBF in bilateral frontal, temporal and parietal areas as well as cerebellum in AS Asymmetry of hemispheric hypoperfusion ↓ Binding in superior and medial frontal cortex in ASD
Improved blood flow in prefrontal lobe and visual cortex following acupuncture treatment
Abbreviations: Neuropsychological Tests and Diagnosis: 5-HT, Serotonin; 5-HT2A , Serotonin 2A Receptor; ABC, Autism Behavior Checklist; AC, Anterior Cingulate; AChE, Acetylcholinesterase; ADI, Autism Diagnostic Interview; ADI–R, ADI- Revised; AS, Asperger Syndrome; ASD, Autism Spectrum Disorder; ASIEP, Autism Symptom Inventory Educational Profile; ATEC, Autism Treatment Evaluation Checklist; CARS, Childhood Autism Rating Scale; CBF, Cerebral Blood Flow; D2R; Dopamine D2 Receptor; DA, Dopamine; DAT, Dopamine Transporter; DHB, Droperidol; DQ, Developmental Quotient; DSM-III-R, Diagnostic and Statistics Manual of Mental Disorder Third Edition Revised; DSM-IV, DSM Fourth Edition; FISQ, Full Scale Intelligence Quotient; GABAA , ␥-Aminobutyric Acid Type A Receptor; GIQ, Global IQ; HFA, High-Functioning Autism; ICD-10, International Classification of Diseases Tenth Revision; IQ, Intelligence Quotient; LFA, Low-Functioning Autism; MR, Mental Retardation [note: now referred to as intellectual disability]; NVIQ, Nonverbal Intelligence Quotient; PDDNOS, Pervasive Developmental Disorder Not Otherwise Specified; PFC, Prefrontal Cortex; PIQ, Performance Intelligence Quotient; rCBF, Regional Cerebral Blood Flow; SERT, Serotonin Transporter; STG, Superior Temporal Gyrus; TD, Tardive Dyskinesia; VIQ, Verbal Intelligence Quotient.
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Makkonen et al. (2008)
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Fig. 1. Disparity between disease prevalence and MI investigations conducted to date using PET and SPECT in ASD compared to other neuropsychiatric/neurological disorders. The vertical axis shows the number of MI studies for a specific disorder divided by prevalence of that disorder. Prevalence was estimated based on statistics from the CDC, National Institute of Mental Health (NIMH), Alzheimer’s Association and Parkinson’s disease foundation. To estimate the number of MI studies conducted in each disorder, PubMed searches were performed for PET/SPECT studies listing that particular disorder in the title or abstract.
Individuals across a broad age range, from children (70) and both ends of the spectrum have been investigated, with the majority (all but 13) studies specifying IQ: 26 studies have investigated low-functioning individuals with ASD, 21 studies high- functioning individuals with ASD and 19 studies enrolled participants of both ends of the spectrum. However, when studies are grouped by participant age as well as IQ, it becomes clear that research in children has focused on low-functioning individuals with ASD and most studies in adults have involved high-functioning individuals, while studies including participants across a wide age range (mixed age group) have not focused solely on high- or lowfunctioning individuals with ASD, reflecting the inclusion of both low-functioning children and high-functioning adults in the same study. See Fig. 3 for repartition according to age and level of functioning. Taken together, these numbers show that fewer studies
Fig. 2. (A) Pie chart illustrating the different radiotracers used in MI studies (PET and SPECT combined) investigating ASD. Note that CBF and glucose metabolism account for approximately three quarters of the targets investigated in MI studies conducted in the field of autism research, thus reflecting a lack of studies focusing on neurotransmitters or proteins. (B) Pie chart showing the percentage breakdown of MI studies with children/adolescents with ASD (
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Contents lists available at ScienceDirect
Neuroscience and Biobehavioral Reviews journal homepage: www.elsevier.com/locate/neubiorev
Review
1
A systematic review of molecular imaging (PET and SPECT) in autism spectrum disorder: Current state and future research opportunities
2
3
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Nicole R. Zürcher a,b , Anisha Bhanot a , Christopher J. McDougle b,c,d , Jacob M. Hooker a,b,∗ a
A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA Harvard Medical School, Harvard, Boston, MA, USA Q2 Lurie Center for Autism, Department of Psychiatry, Massachusetts General Hospital, Lexington, MA, USA d Lurie Center for Autism, Department of Pediatrics, Massachusetts General Hospital, Lexington, MA, USA b c
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a r t i c l e
i n f o
a b s t r a c t
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Article history: Received 22 December 2014 Received in revised form 2 February 2015 Accepted 3 February 2015 Available online xxx
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Keywords: Positron emission tomography (PET) Single-photon emission computed tomography (SPECT) Neuroimaging Molecular imaging Autism spectrum disorder
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Contents
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27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43
1. 2. 3.
Non-invasive positron emission tomography (PET) and single-photon emission computed tomography (SPECT) are techniques used to quantify molecular interactions, biological processes and protein concentration and distribution. In the central nervous system, these molecular imaging techniques can provide critical insights into neurotransmitter receptors and their occupancy by neurotransmitters or drugs. In recent years, there has been an increase in the number of studies that have investigated neurotransmitters in autism spectrum disorders (ASDs), while earlier studies mostly focused on cerebral blood flow and glucose metabolism. The underlying and contributing mechanisms of ASD are largely undetermined and ASD diagnosis relies on the behavioral phenotype. Discovery of biochemical endophenotypes would represent a milestone in autism research that could potentially lead to ASD subtype stratification and the development of novel therapeutic drugs. This review characterizes the prior use of molecular imaging by PET and SPECT in ASD, addresses methodological challenges and highlights areas of future opportunity for contributions from molecular imaging to understand ASD pathophysiology. © 2015 Published by Elsevier Ltd.
Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Article selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Current state and future research opportunities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. General overview of current state . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Targets and ASD population investigated . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1. Cerebral blood flow (CBF) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.2. Glucose metabolism using 2-deoxy-2-(18 F)fluoro-d-glucose ([18 F]FDG) PET . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.3. Serotonin: 5-hydroxytryptamine (5-HT) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.4. Dopamine (DA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.5. Gamma-aminobutyric acid (GABA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.6. Glutamate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.7. Acetylcholine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.8. Other neurochemical investigations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.9. Neuroinflammation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3. Studies based on neuropsychopharmacology in ASD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4. Longitudinal studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5. Combination of imaging modalities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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∗ Corresponding author at: Athinoula A. Martinos Center for Biomedical Imaging, Building 149, 13th Street, Suite 2301, Charlestown, MA 02129, USA. Tel.: +1 617 726 6596; fax: +1 617 726 7422. E-mail address: [email protected] (J.M. Hooker). http://dx.doi.org/10.1016/j.neubiorev.2015.02.002 0149-7634/© 2015 Published by Elsevier Ltd.
Please cite this article in press as: Zürcher, N.R., et al., A systematic review of molecular imaging (PET and SPECT) in autism spectrum disorder: Current state and future research opportunities. Neurosci. Biobehav. Rev. (2015), http://dx.doi.org/10.1016/j.neubiorev.2015.02.002
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ARTICLE IN PRESS
Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conflicts of interest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1. Introduction
Q3 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101
Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders with prevalence as high as 1 in 68 children (CDC, 2014). Although a number of genetic mutations appear to be associated with ASD or with an increased risk or vulnerability for ASD, to date the collection of genetic mutations account for only a small percentage of total ASD cases (Persico and Napolioni, 2013). Epigenetic and environmental factors are increasingly implicated in the disorder. To date, there are no biomarkers that can be used to diagnose subtypes of idiopathic ASD (i.e. without any known genetic or environmental cause). An ASD diagnosis is based on clinical criteria with the hallmarks of the disorder being deficits in social communication and interaction, as well as restricted and repetitive behavior (APA, 2013). As implied by the use of the term ‘spectrum’ to describe autism, different forms of ASD exist. Uncovering the pathophysiological differences among disorders on the autism spectrum could help define biological subtypes of ASD and may improve diagnostic precision and clinical management, potentially leading to the development of more effective treatments. Although providing their own methodological strengths, animal models of ASD cannot reflect the complexity of the human disorder and may not represent atypical biology accurately. Thus, in order to better elucidate the underlying pathophysiology in ASD, it is critical to conduct non-invasive in vivo human neuroimaging studies. Nearly all neuroimaging studies in ASD share the common goal of explaining or stratifying ASD mechanisms by increasing our knowledge about structural, functional or neurochemical differences in the brains of individuals with ASD. In this review, we examine single-photon emission computed tomography (SPECT) and positron emission tomography (PET) studies that have been conducted in individuals with ASD to date. We will consider PET and SPECT together as molecular imaging (MI) although each of these modalities has distinct features. Both PET and SPECT are nuclear imaging techniques in which a radioactive material, referred to as radiotracer, is administered (typically intravenously) into a participant. A radiotracer is often a molecule that binds specifically to a particular target protein, e.g. a receptor, thereby allowing for visualization of distribution and quantification of the protein of interest. However, in other cases the distribution of the tracer is determined by where it accumulates following biochemical modification, e.g. with radiolabelled glucose. A very small mass of the tracer is administered in order to allow specific binding to targets of interest without promoting pharmacological effects or interacting through self-competition. With PET, radiotracer concentration is measured through the detection of high energy (511 keV) anti-colinear gamma photon pairs that result from positron annihilation. SPECT on the other hand, measures radiotracer concentration by detecting single gamma rays within a particular energy range, which depends on the isotope being used. In general, PET has about two to three times higher sensitivity than SPECT and while both methods have only moderate spatial resolution, PET has slightly higher spatial resolution than SPECT (Rahmim and Zaidi, 2008). Typically the isotopes used in SPECT studies have longer half-lives than those used in PET, which is why PET radiotracers are usually produced in an onsite cyclotron, and are thus often less accessible and more expensive. Despite some additional differences, PET and SPECT share key strengths at their core: (1) PET and SPECT can be used to
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noninvasively visualize and quantify differences in density of essential proteins such as receptors, transporters and enzymes; (2) in many cases, these techniques can be used to assess neurotransmitter release and occupancy; (3) PET and SPECT can measure drug-target engagement; and (4) functional measures, such as glucose metabolism and oxygen consumption, can be evaluated (though this is mostly limited to PET). 2. Article selection In the current review, we report all studies that we could identify based on a comprehensive literature search in PubMed. PubMed searches were conducted for PET or SPECT studies examining ASD (autism, Asperger syndrome, and pervasive developmental disorder not otherwise specified) in humans. We only reviewed original articles for which English text was available. We then checked the references of all articles for additional relevant studies. We identified 49 PET and 30 SPECT studies that have been performed in individuals with ASD over the past three decades (1985–2014). See Table 1 (PET studies) and 2 (SPECT studies) for an exhaustive list of papers reviewed, including number of participants (N), age, intelligence quotient (IQ), diagnosis, information about control/comparison group(s) and brief summary of main findings for each study.
102 103 104 105 106 107 108
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110 111 112 113 114 115 116 117 118 119 120 121 122 123
3. Current state and future research opportunities
124
3.1. General overview of current state
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We identified and reviewed 79 studies that have used MI techniques to investigate ASD. Given the challenges associated with MI studies in ASD, such as the requirement of an intravenous line for radiotracer injection, the exposure to radiation and potential sedation in the context of surrogate consent (for children and adults with ASD unable to consent for themselves), this represents a considerable number of studies. However, compared to other neuropsychiatric/neurological disorders such as Parkinson’s disease, epilepsy, Alzheimer’s disease and schizophrenia, there is a paucity of PET and SPECT studies in the field of ASD (depicted in Fig. 1). While in this review we draw attention to the fact that there is a real need for future MI studies in the field of ASD, Fig. 1 illustrates that there is also a relative lack of MI in bipolar disorder and major depression, two neuropsychiatric diseases with high prevalence. The disparity between the prevalence of ASD and the number of MI studies conducted to date warrants investments in methods to better address and overcome the practical and technical challenges of nuclear imaging modalities. 3.2. Targets and ASD population investigated The most salient feature of the PET/SPECT literature is that the vast majority of MI studies have investigated cerebral blood flow (CBF) or glucose metabolism. About half of all studies conducted in ASD have investigated CBF and approximately a quarter have investigated glucose metabolism. This means that a minority of studies has investigated neurotransmitters (receptors, transporters or synthesis), other proteins or protein synthesis. See Fig. 2A for an illustration of the percentage breakdown for the different molecular targets.
Please cite this article in press as: Zürcher, N.R., et al., A systematic review of molecular imaging (PET and SPECT) in autism spectrum disorder: Current state and future research opportunities. Neurosci. Biobehav. Rev. (2015), http://dx.doi.org/10.1016/j.neubiorev.2015.02.002
126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143
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145 146 147 148 149 150 151 152 153
ASD age: mean ± SD, range
Number of participants (N)
ASD diagnosis
ASD IQ: mean ± SD, range
ASD sedation
Control (CON)/ comparison group
Major findings in ASD
Rumsey et al. (1985) De Volder et al. (1987)
Glucose
26 years ± 6, 18–36 years 9.8 years ± 4.0
ASD: N = 10, CON: N = 15 ASD: N = 14; (i) N = 15; (ii) N = 3; (iii) N = 3
Autism [DSM-III]
IQ: 48–117
No
Widespread hypermetabolism
Autism [DSM-III]
Low to moderate MR
DHB + etybenzatropine when DHB > 0.2 mg/kg dose
Herold et al. (1988)
OER, CBF and Glucose
21–25 years
ASD: N = 6; CON: N = 8
Infantile autism [Rutter’s 1978 criteria], autism [DSM-III-R]
FISQ: < 45–92
No
Horwitz et al. (1988)
Glucose
27 years ± 6.6, 18–39 years
ASD: N = 14; CON: N = 14
VIQ: 48–117; PIQ: 55–126
No
Heh et al. (1989)
Glucose
IQ: 91 ± 25, 72–131 VIQ: 93, 78–122; PIQ: 90, 75–112
No
Matched by age
Glucose
ASD: N = 7; CON: N = 8 ASD: N = 7; CON: N = 13
Fewer positive correlations of regional glucose utilization b/w frontal and parietal regions No differences b/w groups
Buchsbaum et al. (1992)
23 years ± 6, 19–36 years 25 years, 19–38 years
No
Comparable socioeconomic status
↓ rGMR in right posterior thalamus and right putamen
Siegel et al. (1992)
Glucose
23 years ± 6, 17–38 years
ASD: N = 16; CON: N = 26
Infantile autism during childhood, autism [DSM-III] Autism [ICDS and DSM-III] Autism during childhood [DSM-III, ICDS, K-SADS and DICA] Autism during childhood [ICDS]
Matched by sex and age (i) CON adults; (ii) Nearly normal children; (iii) Hemibrains of children w/unilateral pathology (i) age-matched to test CBF, oxygen and glucose; (ii) not age-matched to test CBF and oxygen Matched by sex and age
IQ: 90 ± 17, 74–135
No
Similar socioeconomic status
Schifter et al. (1994)
Glucose
7.3 years ± 2.2, 4.5–11 years
ASD: N = 13
Some degree of MR
No
No CON/comparison group
Siegel et al. (1995)
Glucose
27 years ± 7, 19–46 years
ASD: N = 14; CON: N = 20
Autism [DSM-III-R], some w/coexisting seizure disorders Autism during childhood [ICDS]
↓ GMR in left posterior putamen ↑ GMR in right posterior calcarine cortex 4/13 individuals w/ASD had an abnormal FDG-PET scan
IQ: 90 ± 17, 74–135
No
Matched by age
Chugani et al. (1996)
Glucose
Infantile spasms w/temporal hypometabolism: N = 18; CON: N = 10
Cryptogenic infantile spasms, autism [DSM-IV]
Nonverbal/severe language impairment
Chloral hydrate when not under natural sleep
Previously obtained data from age-matched children: 3 years 6 months ± 1 yr. 3 months, 8 months - 4 years 7 months
Happe et al. (1996)
CBF
2 years 3 months ± 1 yr. 4 months, 10 months–5 years and 6 years 3 months ± 2 years 6 months, 3 years–12 years 5 months at follow-up 24 years, 20–27 years
ASD: N = 5; CON: N = 6
AS [developmental history and current presentation]
FISQ: 100, 87–112; VIQ: 110, 93–125; PIQ: 92, 83–100
No
Normal volunteers from previous study
Chugani et al. (1997)
5-HT Synthesis
6.6 years, 4.1–11.1 years
ASD: N = 8; CON: N = 5
Autism [DSM-IV, GARS and CARS]
OABC: 19–29 months
Nembutal/midazolam
Siblings
Ernst et al. (1997)
Presynaptic DA activity D2
13 years ± 2
ASD: N = 14; CON: N = 10 ASD: N = 6
Autism [DSM-III-R]
IQ: 74 ± 23.1, 46–123 IQ: 20–70
Propofol
Similar age:14 years ± 2 N/A, w/in group treatment study
3–5 years
Autism [DSM-III-R and CARS]
Propofol
No differences b/w groups
No differences b/w groups
Negative correlation b/w GMR in medial frontal cortex and attentional performance Children w/infantile spasms w/temporal hypometabolism have a poor long-term outcome and majority are autistic at follow-up (10/14)
ToM task-induced activity in left mPFC in CON but not in ASD Activity in more ventral mPFC in ASD Abnormalities and asymmetries in dentatothalamocortical pathway ↓ FDOPA uptake in mPFC
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10% ↓ in D2 binding in caudate and putamen after tetrahydrobiopterin treatment
ARTICLE IN PRESS
Fernell et al. (1997)
Glucose
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N.R. Zürcher et al. / Neuroscience and Biobehavioral Reviews xxx (2015) xxx–xxx
Please cite this article in press as: Zürcher, N.R., et al., A systematic review of molecular imaging (PET and SPECT) in autism spectrum disorder: Current state and future research opportunities. Neurosci. Biobehav. Rev. (2015), http://dx.doi.org/10.1016/j.neubiorev.2015.02.002
Table 1 PET Studies in ASD.
Target
ASD age: mean ± SD, range
Number of participants (N)
ASD diagnosis
ASD IQ: mean ± SD, range
ASD sedation
Control (CON)/ comparison group
Major findings in ASD
Haznedar et al. (1997) Muller et al. (1998)
Glucose
24.3 years ± 10.7, 17–47 years 25.5 years, 18–31 years
ASD: N = 7; CON: N = 7 ASD: N = 4; CON: N = 5
Autism [ADI]
IQ: 60–123, Verbally fluent IQ: 77.3, 71–92
No
Matched by sex and age Matched by sex and similar age: 26.2 years, 23–30 years
↓ Metabolic activity in AC
Chugani et al. (1999)
5-HT Synthesis
6.41 years ± 3.3, 2.3–15.4 years
ASD: N = 30; (i) N = 8; (ii) N = 16
Autism [DSM-IV, ADI-R, GARS and CARS]
Mental age < 24 months
Nembutal/midazolam
Muller et al. (1999)
CBF
26.6 years, 18–31 years
ASD: N = 5; CON: N = 5
Autism [GARS]
FISQ: 75.6, 69–92 PIQ: 74.5, 67–84
No
Haznedar et al. (2000)
Glucose
27.7 years ± 11.3
Autism or AS [DSM-IV]
IQ: 55–125, Verbally fluent
No
Matched by sex and age
Zilbovicius et al. (2000)
CBF
1st autistic group: 8.4 years ± 2.7 2nd autistic group: 7.4 years ± 1.7
Autism: N = 10; AS: N = 7; CON: N = 17 ASD: N = 21; CON: N = 10
Infantile autism [DSM-IV]
Pentobarbital sodium
Nonautistic children w/idiopathic MR, similar age and developmental quotient
Hypoperfusion of bilateral temporal lobes
Buchsbaum et al. (2001)
Glucose
30.5 years ± 8.6
Autism: N = 5; AS: N = 1
Autism or AS [DSM-IV and ADI]
MR in both groups. 1st autistic group: 3.3 ± 1. 2nd autistic group: 3.2 ± 1.5 [BSES] IQ: 95, 53–119
No
N/A, w/in group treatment study
Boddaert et al. (2002)
CBF
8.4 years ± 2.7, 6–13 years
ASD: N = 21; CON: N = 10
Autism [DSM-IV]
MR
Nembutal
Castelli et al. (2002)
CBF
33 years ± 7.6
ASD: N = 10; CON: N = 10
Autism or AS [DSM-IV]
No
Boddaert et al. (2003)
CBF
19.1 years ± 4.5
ASD: N = 5; CON: N = 8
Autism [DSM-IV and ADI]
≥ Average verbal (61 ± 24 [Quick Test]) and nonverbal (73 ± 30 [Raven Matrices]) ability IQ: 64 ± 5
CON group w/idiopathic MR, matched by age and IQ CON group did not differ in verbal or nonverbal ability
Regional metabolic rate ↑ after fluoxetine treatment in AC, orbitofrontal areas and striatum Individuals w/↑ baseline metabolic activity most likely to respond to treatment ↓ Blood flow in STS, STG and bilateral temporal lobe
No
Healthy individuals
Hall et al. (2003)
CBF
20–33 years
ASD: N = 8; CON: N = 8
Autism or AS [DSM-IV]
NVIQ: 105 ± 18, 80–130
No
CON group w/similar nonverbal IQs: 109 ± 16, 90–135
CBF
Infantile autism by ≤ 5 years, autism [DSM-IV and GARS]
No
↓ Activity in right dentate nucleus and left frontal BA 46 during auditory and language tasks ↑ Activity during motor speech tasks Atypical age-related changes in 5-HT synthesis in ASD
↓ Activation in mPFC, STS (at TPJ) and temporal poles in response to mentalizing-triggering animations ↓ Activation in left temporal areas and ↑ activation in right middle frontal gyrus in response to speech-like sounds ↓ rCBF in inferior frontal and fusiform areas ↑ rCBF in right anterior temporal pole, AC and thalamus during emotion-recognition task
ARTICLE IN PRESS
Reversal of left hemispheric dominance during language perception ↓ Activation in cerebellum during nonverbal auditory perception ↓ Metabolism in AC and posterior cingulate
N.R. Zürcher et al. / Neuroscience and Biobehavioral Reviews xxx (2015) xxx–xxx
Matched by sex and age: (i) siblings (w/& w/o DD); (ii) children w/epilepsy Matched by sex
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Please cite this article in press as: Zürcher, N.R., et al., A systematic review of molecular imaging (PET and SPECT) in autism spectrum disorder: Current state and future research opportunities. Neurosci. Biobehav. Rev. (2015), http://dx.doi.org/10.1016/j.neubiorev.2015.02.002
Table 1 (Continued)
Children w/idiopathic MR
No
Healthy volunteers matched by sex and age
No
CON group did not differ in social status, cognitive functions and age: 30.5 years ± 4.9 N/A, case study
↓ Activation in left middle temporal gyrus and precentral frontal gyrus ↓ rGMR in medial/cingulate areas ↑ rGMR in occipital and parietal areas ↑ presynaptic DA activity in striatum and frontal cortex
Boddaert et al. (2004)
CBF
6.6 years ± 1.6
ASD: N = 11; CON: N = 6
Autism [DSM-IV]
Hazlett et al. (2004)
Glucose
27.7 years ± 11.3, 17–55 years
ASD: N = 17; CON: N = 17
Autism or AS [DSM-IV]
Nieminen-von Wendt et al. (2004)
Presynaptic DA activity
29.2 years ± 5.8
ASD: N = 8; CON: N = 5
AS [DSM-IV and ICD-10]
Boddaert et al. (2005)
CBF
20 years
ASD: N = 1
Autism [DSM-IV and ADI-R]
IQ: 66
No
Chandana et al. (2005)
5-HT synthesis
6.5 years ± 2.7
ASD: N = 117; Siblings: N = 8; Epilepsy: N = 16
Autism [DSM-IV, ADI-R, GARS and CARS]
Mental age < 24 months
Nembutal/midazolam
Normal siblings and children w/epilepsy
Gendry Meresse et al. (2005)
CBF
7.9 years ± 2.2, 5–11.9 years
ASD: N = 45
Autism [DSM-IV and ADI]
IQ: 44 ± 22
Pentobarbital
Haznedar et al. (2006)
Glucose
27.7 years ± 11.3, 17–55 years
Autism: N = 10; AS: N = 7; CON: N = 17
Autism or AS [DSM-IV]
IQ: 97.1 ± 25.3, 55–125, Verbally fluent
No
N/A, w/in group correlational disease severity study Matched by sex and age
Chugani et al. (2007)
Glucose
4.9 years ± 1.7, 2.7–7.9 years
ASD: N = 12; Port-wine stain + ASD: N = 4; CON: N = 11
Infantile Autism [ADI-R, AQ, VABS and GARS]
Not specified
Yes, “sedated as necessary”
Port-wine stain + ASD: 2.9–6 years; CON: healthy young adults 25.5 years ± 2.0
Nakamura et al. (2010)
SERT and DAT
21.2 years ± 2.0, 18–26 years
ASD: N = 20; CON: N = 20
Autism [DSM-IV-TR, ADI and ADOS]
IQ: 99.3 ± 18.1
No
Matched by sex and similar age: 21.9 years ± 2, 18–26 years, IQ not significantly different
7.9 years ± 2.2, 5–12 years
ASD: N = 45; CON: N = 13
Girgis et al. (2011)
5-HT2A and SERT
34.3 years ± 11.1, 18–50 years
ASD: N = 17; CON: N = 17
Idiopathic ASD, low-functioning [DSM IV-R and ADI-R] AS [DSM-IV]
IQ: 45 ± 22, DQ: 44 ± 23
Rectal pentobarbital
IQ: > 85
No
Non-ASD group: low-functioning individuals w/MR (8.6 years ± 2.7, 5–15 years) Matched by sex, age and ethnicity
Left hippocampus, left frontal cortex and left middle temporal lobe activated during calendar task Abnormal cortical asymmetry in ASD (64/117) ↓ 5-HT synthesis in ASD (58/64) Children w/ASD w/left hemispheric asymmetry more likely to have language impairments Negative correlation b/w rCBF and ADI-R score in left STG ↓ rGMR bilaterally in ventral caudate, putamen and thalamus in ASD ↓ Metabolic activity in ventral thalamus in autism compared to AS Compared to CON, ASD group had ↓ glucose uptake in the cerebellum, medial temporal, AC, lateral temporal and frontal cortices Compared to Port-wine stain + ASD, ASD had ↑ glucose uptake in medial temporal and AC cortices and ↓ glucose uptake in lateral temporal cortex ↓ SERT binding in AC and posterior cingulate correlated w/ASD symptomatology ↑ DAT binding in orbitofrontal cortex ↓ Blood flow in right STS ↑ blood flow in contralateral post central area No differences in 5-HT2A or DAT binding b/w groups
5
CBF
IQ: 93.2 ± 26.4, 55–135, All verbally fluent IQ: 112.5 ± 12.6, 97–140
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AS [DSM-IV and ICD-10]
G Model
Sodium pentobarbital
ASD: N = 8; CON: N = 8
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↑ Blood flow in cerebellum
28.1 years ± 6.2, 19.2–38.2 years
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Please cite this article in press as: Zürcher, N.R., et al., A systematic review of molecular imaging (PET and SPECT) in autism spectrum disorder: Current state and future research opportunities. Neurosci. Biobehav. Rev. (2015), http://dx.doi.org/10.1016/j.neubiorev.2015.02.002
CON group did not differ in social status and age: 31.5 years ± 4.5, 23.8–39.8 years
CBF
Duchesnay et al. (2011)
FIQ:109.0 ± 15.7, 88–140; VIQ: 107.9 ± 15.3, 82–131; PIQ: 111.1 ± 15.7, 95–144 IQ: 43 ± 21
No
Nieminen-von Wendt et al. (2003)
Number of participants (N)
ASD diagnosis
ASD IQ: mean ± SD, range
ASD sedation
Control (CON)/ comparison group
Major findings in ASD
Lee et al. (2011b)
Glucose
6.0 years ± 1.8
No
CON: 9.73 years ± 2.55
Glucose
6.0 years ± 1.8
ASD [Korean ADI-R] Not specified
Not specified
Lee et al. (2011a)
Not specified
Not specified
ADHD: 8.2 years ± 1.6; CON: 9.7 years ± 2.8
Local overconnectivity and long-range underconnectivity Segmented brain connectivity and temporal lobe asymmetry
Shandal et al. (2011)
Leucine/protein synthesis
DD w/PDD: 76.25 months ± 20.59; DD w/o PDD: 77.63 months ± 13.8
DD w/& w/o PDD [GARS and VABS]
Significant global DD [assessed clinically and by VABS]
No
Healthy adults
↑ Protein synthesis rate in left posterior middle temporal area in DD w/PDD, also correlated w/GARS scores
Suzuki et al. (2011)
AChE
25.3years ± 4.3, 18–33 years
ASD: N = 26; CON: N = 11 ASD: N = 26; ADHD:N = 24; CON: N = 11 DD w/PDD: N = 8; DD w/o PDD: N = 8; CON: N = 9 ASD: N = 20; CON: N = 20
IQ: 91.6 ± 19.7, 70–140
No
Matched by sex, age and IQ
Beversdorf et al. (2012) Deriaz et al. (2012)
5-HT2A
31.0 years ± 8.0
IQ: 114.7 ± 14.7
No
20 years
General anesthesia
Lee et al. (2012)
Glucose
6.0 years ± 1.8
Severe intellectual disability Not specified
Matched by age and FISQ N/A, case study
↓ AChE activity in bilateral fusiform gyri negatively correlated w/social disabilities ↓ 5-HT2A binding in thalamus
Glucose
Autism [DSM-IV-TR, ADI-R and ADOS] Autism [DSM-IV and ADI-R] PDD w/SIB [Clinical evaluation]
Pagani et al. (2012)
CBF
Dilber et al. (2013)
ASD: N = 8; CON: N = 12 ASD: N = 1
No
ADHD: 8.2 years ± 1.6; CON: 9.7 years ± 2.8
IQ: 105.3 ± 16.4, 87–135
No
Matched by sex, age and IQ
Infantile spasms during childhood, autism [DSM-IV, ABC, CARS] Autism [ICD-10, ADOS]
Mild to severe MR
Chloral hydrate
9 patients w/infantile spasms but no ASD
IQ: 117–127
No
CON group from past study, matched by sex and age
ASD: N = 8
Autism [DSM-IV-TR]
Not specified
No
N/A, w/in group treatment study
ASD: N = 20; CON: N = 20
ASD [DSM-IV-TR, ADI-R, ADOS]
IQ: 95.9 ± 16.7, 81–140
No
Matched by sex, age and IQ
31.8 years ± 8.6, 20–48 years
ASD: N = 26; ADHD:N = 24; CON: N = 11 ASD: N = 13; CON: N = 10
ASD [Korean ADI-R and ADOS] Autism [DSM-IV GAF, ADOS-G, RAADS-R and AQ]
Glucose
7.8 years ± 4, 3–16 years
ASD: N = 15; CON: N = 9
Mendez et al. (2013)
GABAA
34–43 years
ASD: N = 3; CON: N = 3
Sharma et al. (2013)
Glucose
10.5 years ± 5.6, 3–33 years
Suzuki et al. (2013)
TSPO
23.3 years ± 4.0, 18.6–31.9 years
↓ Metabolism in right temporo-parietal area and right left posterior fossa Atypical connectivity b/w left inferior prefrontal regions and other brain areas in ASD ↑CBF in parahippocampal, posterior cingulate, primary visual and temporal cortex, putamen, caudate, substantia nigra and cerebellum ↓ Metabolic activity in temporal lobe (13/15 ASD), frontal lobe (9/15) and parietal lobe (7/15) ↓ Volumes of distribution in amygdala, subcallosal cortex and nucleus accumbens ↓ GABAA receptors in bilateral amygdala and nucleus accumbens Changes in FDG utilization in frontal, temporal, parietal, cingulate occipital, lobes, cerebellum, amygdala, hippocampus, and basal ganglia ↑ Microglial activation in fusiform gyrus, orbitofrontal cortex, cingulate cortex, midbrain, pons and cerebellum
Abbreviations: 5-HT, Serotonin; 5-HT2A , Serotonin 2A Receptor; AC, Anterior Cingulate; AChE, Acetylcholinesterase; ADI, Autism Diagnostic Interview; ADI–R, ADI- Revised; ADOS, Autism Diagnostic Observation Schedule; ADOS-G, ADOS-Generic; AS, Asperger Syndrome; ASD, Autism Spectrum Disorder; AQ, Autism Spectrum Quotient; BA, Brodmann Area; BSES, Behavior Summarized Evaluation Scale; CARS, Childhood Autism Rating Scale; CBF, Cerebral Blood Flow; D2 , Dopamine D2 Receptor; DA, Dopamine; DAT, Dopamine Transporter; DHB, Droperidol; DD, Developmental Delay; DICA, Diagnostic Interview for Children and Adolescents; DQ, Developmental Quotient; DSM-III, Diagnostic and Statistics Manual of Mental Disorder Third Edition; DSM-III-R, DSM Third Edition Revised; DSM-IV, DSM Fourth Edition; DSM-IV-TR, DSM Fourth Edition Text Revised; FISQ, Full Scale Intelligence Quotient; GABAA, ␥-Aminobutyric Acid Type A Receptor; GAF, Global Assessment of Functioning; GARS, Gilliam Autism Rating Scale; GMR, Glucose Metabolic Rate; HFA, High-Functioning Autism; ICD-10, International Classification of Diseases Tenth Revision; ICDS, Interview for Childhood Disorders and Schizophrenia; IQ, Intelligence Quotient; K-SADS, Kiddie Schizophrenia and Affective Disorder Scales; LFA, Low-Functioning Autism; mPFC, Medial Prefrontal Cortex; MR, Mental Retardation [note: now referred to as intellectual disability]; NVIQ, Nonverbal Intelligence Quotient; OABC, Overall Adaptive Behavior Composite from the Vineland Adaptive Behavior Scale; OER, Oxygen Enhancement Ratio; PDD, Pervasive Developmental Disorder; PIQ, Performance Intelligence Quotient; RAADS-R, Ritvo Autism Asperger Diagnostic Scale – Revised; rCBF, Regional Cerebral Blood Flow; rGMR, Relative Glucose Metabolic Rate; SERT, Serotonin Transporter; SIB, Self-Injurious Behavior; STG, Superior Temporal Gyrus; STS, Superior Temporal Sulcus; TPJ, Temporo-Parietal Junction; TSPO, Translocator Protein; VABS, Vineland Adaptive Behavior Scale; VIQ, Verbal Intelligence Quotient.
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ASD age: mean ± SD, range
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Please cite this article in press as: Zürcher, N.R., et al., A systematic review of molecular imaging (PET and SPECT) in autism spectrum disorder: Current state and future research opportunities. Neurosci. Biobehav. Rev. (2015), http://dx.doi.org/10.1016/j.neubiorev.2015.02.002
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Table 1 (Continued)
Target
ASD age: mean ± SD, range
Number of participants (N)
ASD diagnosis
ASD IQ: mean ± SD, range
ASD sedation
Control (CON)/ comparison group
Major findings in ASD
Ozbayrak et al. (1991)
CBF
22 years
ASD: N = 1
N/A, case study
Left occipital hypoperfusion
CBF
27.7 years, 22–34 years
ASD: N = 4; CON: N = 4
VIQ: 90 PIQ: 61 Degree of MR w/minimal verbal skills
No
George et al. (1992)
AS w/TD/PDDNOS [DSM-III-R] Infantile autism [DSM-III-R]
No
Matched by age
Zilbovicius et al. (1992)
CBF
7.5 years ± 1.7, 5–11 years
ASD: N = 21; CON: N = 14
Infantile autism [DSM-III-R]
NVIQ: 36 ± 18.5, 10–75
Pentobarbital + DHB
Gillberg et al. (1993)
CBF
ASD: N = 16; ASD w/epilepsy: N = 10; ASD-like w/epilepsy: N=5
Autism [DSM-III-R, ABC and CARS]
Above average intelligence to severe MR
General anesthesia
Mountz et al. (1994)
CBF
ASD: 10.6 years, 4.5–22 years ASD w/epilepsy: 8.1 years, 1–19 years ASD-like w/epilepsy: 8.7 years, 4.5–12 years 13 years
Nonautistic children w/slight to moderate language disorders, matched by age Autism w/o epilepsy group compared to autism w/epilepsy group and to autism-like w/o epilepsy group
↓ Total brain perfusion ↓ rCBF in right lateral temporal and right, left and midfrontal lobes No cortical differences b/w groups
ASD: N = 1
Not specified
Not specified
NA, case study
Chiron et al. (1995)
CBF
10.9 years ± 4.2, 4.5–17 years
ASD: N = 18; CON: N = 10
Autism [diagnostic criteria not specified] Autism [DSM-III-R and ICD-10]
Normal intelligence to severe MR Verbal level ranging from no words to near-normal speech
Pentobarbitone + DHB
McKelvey et al. (1995)
CBF
Case 1: 14 years Case 2: 16 years Case 3: 17 years
ASD: N = 3
Autism [DSM-III-R], further diagnosis of AS
No
Mountz et al. (1995)
CBF
13.7 years, 9–21 years
ASD: N = 6; CON: N = 7
Autism [DSM-III-R and ASIEP]
Case 1: “normal intelligence” Case 2 ¨’lowaverage intelligence” Case 3 VIQ: 91, NVIQ: 106, GIQ: 98 PIQ scores: 45, 32, 51, 70, 72, 100
Individuals w/transient events unaccompanied by a cerebral lesion retrospectively considered to be normal, matched by sex N/A, case study
Zilbovicius et al. (1995)
CBF
Stage 1: 41.0 months ± 8.5 Stage 2: 79.2 months ± 7.7
ASD: N = 5; CON: N = 5
Childhood autism [DSM-III-R]
Stage 1 DQ IQ: 20–34 Stage 2 DQ IQ: 20–50
Pentobarbital + DHB
Carratala et al. (1998)
CBF
3 years
ASD: N = 1
Autism [DSM-IV]
Not specified
Jambaque et al. (1998)
CBF
13 years
ASD: N = 1
Autism [ADI-R]
IQ: 56 [Brunet-Lehne non-verbal scale] VIQ: 63
i) Children w/suspected neurological problem found to be due to another cause retrospectively ii) Healthy adults Children w/neurological problems found retrospectively to be transient and unaccompanied by cerebral lesions, matched by age N/A, case study
Not specified
N/A, case study
Ryu et al. (1999)
CBF
54 months, 28–92 months
ASD: N = 23
Autism [DSM-IV and CARS]
Not specified
Chlorpromazine
No CON group
↓ rCBF in temporal lobes
↓ Blood flow in bilateral posterior temporal and occipital cortices ↑ rCBF in left vs. right hemisphere
CBF abnormalities in right hemisphere
↓ CBF in temporal and parietal lobes Greater abnormalities in CBF in left vs. right hemisphere Delayed frontal hypoperfusion in ASD at 3–4 years (happens ∼ 2years earlier in children with typical development) Frontal perfusion normalized in ASD by 6–7 years ↓ Blood flow in left temporoparietal cortex Hypoperfusion in left frontal cortex ↓ Perfusion in areas such as: cerebellum, thalamus, basal ganglia, posterior parietal and temporal regions
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Midazolam + ketamine for severely low-functioning subjects
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Please cite this article in press as: Zürcher, N.R., et al., A systematic review of molecular imaging (PET and SPECT) in autism spectrum disorder: Current state and future research opportunities. Neurosci. Biobehav. Rev. (2015), http://dx.doi.org/10.1016/j.neubiorev.2015.02.002
Table 2 SPECT studies in ASD.
7
Number of participants (N)
ASD diagnosis
ASD IQ: mean ± SD, range
ASD sedation
Control (CON)/ comparison group
Major findings in ASD
Hashimoto et al. (2000)
CBF
67.9 months ± 31.2, 2 years, 3 months13 years 11 months
ASD: N = 22; CON: N = 10
Autism [DSM-IV]
IQ: 52.5 ± 16.2, 24–90
Pentobarbital sodium
Nonautistic group w/either ADHD or MR, matched by age
Ohnishi et al. (2000)
CBF CBF
ASD: N = 23; CON: N = 26 ASD: N = 30; CON: N = 14
Infantile autism [DSM-IV] Autism [DSM-IV, ADI and CARS]
IQ: 48 ± 19.5 [Stanford Binet or DQ] PIQ: 30 ± 18.5
Pentobarbital
Starkstein et al. (2000)
6.5 years ± 2.4, 2.6–13 years 11.1 years ± 7.0
Kaya et al. (2002)
CBF
6.13 years ± 1.99, 3–11 years
ASD: N = 18; CON: N = 11
Autism [DSM-IV]
IQ: 56.11 ± 10.51 [Goodenough IQ Test]
Yes, though drug not specified
Wilcox et al. (2002)
CBF
3–37 years
ASD: N = 14; CON: N = 14
Autism [DSM-IV]
Complete mutism to moderately severe difficulty w/language
General anesthesia for most subjects
Nonautistic children w/MR, matched by age and IQ Nonautistic children w/MR, comparable in chronological age, mental age, height, weight and head circumference Children w/suspected neurological problem, retrospectively attributed to other cause CON data from hospital database, matched by sex and age
↓ rCBF in laterotemporal and dorso-medio-frontal regions in ASD Greater ↑ in right vs. left for temporal and parietal lobes in ASD ↓ rCBF in bilateral insula, STG and left prefrontal cortices ↓ Perfusion in right temporal lobe, occipital lobes, thalami and left basal ganglia
Steiner et al. (2003)
CBF
Autism: 10 years Atypical Autism: 7.4 years AS: 11.8 years
Autism, atypical autism or AS [DSM-IV]
Not specified
General anesthesia
Individuals w/MR w/o Down syndrome
Ito et al. (2005)
CBF
11.7 years ± 1.8, 9–14 years
Autism: N = 60; Atypical autism: N = 13; AS: N = 11; CON: N = not specified ASD: N = 16; CON: N = 5
Autism [DSM-IV], High-functioning Autism [IQ ≥ 70]
IQ: 94.7 ± 14.4, 76–126
No
Comparison group w/cryptogenic epilepsy, matched by age
Xiao-Mian et al. (2005)
DAT
3–10 years
No
5-HT2A
26 years ± 6
Children autism [DSM-IV] AS [DSM-IV, ICD-10 and ADI-R]
Not specified
Murphy et al. (2006)
ASD: N = 10; CON: N = 10 ASD: N = 8; CON: N = 10
FISQ: 80–100
No
Matched by sex, age and nation Matched by sex and age
Burroni et al. (2008)
CBF
11.2 years
ASD: N = 11; CON: N = 8
Child autism [DSM-IV and ABC]
Not specified
Propofol
Degirmenci et al. (2008)
CBF
6.9 years ± 1.7
HFA: N = 7; LFA: N = 3; (i): N = 5; (ii): N = 23; (iii): N = 15
Autism [DSM-III-R]
High- and lowfunctioning individuals, but IQ not specified
Midazolam + ketamine
Inhalatory anesthesia + halothane or sevoflurane (if used)
Nonautistic individuals matched by age. Individuals w/an episode of febrile seizure but regular neurological development/normal brain scan (i) Children w/normal brain perfusion, brain CT or MRI and EEG. Matched by age for autism group; (ii) 1st degree relatives of 8 individuals w/autism in study (e.g. mother, father, siblings); (iii) Sex- and age-matched CON for 1st degree relatives
Hypoperfusion in frontal, frontotemporal and temporal occipital areas Hypoperfusion in PFC Hypoperfusion of speech areas in left temporal lobe and frontal areas more prominent w/↑ age No significant differences b/w groups
Significant hypoperfusion in temporal cortex Abnormal laterality in temporal, thalamic and hippocampal regions ↑ DAT binding ↓ 5-HT2A binding in AC, posterior cingulate, left parietal lobe, bilaterally in frontal and superior temporal lobes in AS ↓ CBF Right > left asymmetry, especially in temporo-parietal areas
Abnormalities in brain perfusion found in caudate nucleus, frontal, temporal and parietal cortex in ASD as well as 1st degree relatives
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Please cite this article in press as: Zürcher, N.R., et al., A systematic review of molecular imaging (PET and SPECT) in autism spectrum disorder: Current state and future research opportunities. Neurosci. Biobehav. Rev. (2015), http://dx.doi.org/10.1016/j.neubiorev.2015.02.002
Table 2 (Continued)
ASD: N = 15; CON: N = 10
Autism [ICD-10], “high-functioning individuals w/autism” [CARS]
IQ: 70–79 [Leiter method]
Midazolam for one scan; Propofol + thiopental for other scan
Gupta and Ratnam (2009)
CBF
6 years ± 1.5, 4–8 years
ASD: N = 10; CON: N = 5
Infantile autism [DSM-IV]
IQ: 49 ± 12
No
Sasaki et al. (2010)
CBF
9.9 years, 4–16 years
ASD: N = 15
IQ: 35–85 DQ: 15–58
No
Compared w/a normal database from the institute
Makkonen et al. (2011)
DAT
5–11 years
ASD: N = 13; CON: N = 10
ASD [DSM-IV] w/frontal lobe epilepsy or temporal lobe epilepsy Autism [ATEC]
Not specified
No
Yang et al. (2011)
CBF
7.2 years ± 3
Autism: N = 14; AS: N = 9; CON: N=8
ASD classified as autism or AS [DSM-IV]
Not specified
Chloral hydrate
CON group w/neurological symptoms warranting SPECT examination, age range: 7–14 years Children w/normal brain perfusion and developmental history (assessed during neurological development examination), matched by age
Mori et al. (2012)
GABAA
7.0 years ± 3.7
Autism: N = 9; AS: N = 15; CON: N = 10
ASD classified as autism or AS [DSM-IV]
IQ < 70 (N = 7); IQ > 70 (N = 17)
Triclofos sodium
Zhao et al. (2014)
CBF
4.52 years ± 2.73
ASD: N = 55
Childhood autism [DSM-IV and ABC]
Not specified
Chloral hydrate “administered to uncooperative patients”
CON group w/symptomatic diagnoses (e.g. tremors, cephalalgia, epilepsy, unexplained odd feeling, motor disturbances, and tiredness), matched by age Matched by age
Non-symptomatic partial epilepsy patients w/o intellectual delay, similar age: 7.8 years ± 3.6 N/A, w/in group treatment study
↓ SERT binding in medial frontal cortex
Hypoperfusion in frontal and prefrontal areas, subcortical areas as well as generalized hypoperfusion Pattern of ↓ blood flow in PFC, medial frontal cortex, AC cortex, medial parietal cortex and anterior temporal lobe DAT binding ↓ w/age in ASD but ↑in CON Patients who responded to fluoxetine treatment had ↓ DAT binding ↓ rCBF in bilateral frontal lobe and bilateral basal ganglia in ASD ↓ rCBF in bilateral frontal, temporal and parietal areas as well as cerebellum in AS Asymmetry of hemispheric hypoperfusion ↓ Binding in superior and medial frontal cortex in ASD
Improved blood flow in prefrontal lobe and visual cortex following acupuncture treatment
Abbreviations: Neuropsychological Tests and Diagnosis: 5-HT, Serotonin; 5-HT2A , Serotonin 2A Receptor; ABC, Autism Behavior Checklist; AC, Anterior Cingulate; AChE, Acetylcholinesterase; ADI, Autism Diagnostic Interview; ADI–R, ADI- Revised; AS, Asperger Syndrome; ASD, Autism Spectrum Disorder; ASIEP, Autism Symptom Inventory Educational Profile; ATEC, Autism Treatment Evaluation Checklist; CARS, Childhood Autism Rating Scale; CBF, Cerebral Blood Flow; D2R; Dopamine D2 Receptor; DA, Dopamine; DAT, Dopamine Transporter; DHB, Droperidol; DQ, Developmental Quotient; DSM-III-R, Diagnostic and Statistics Manual of Mental Disorder Third Edition Revised; DSM-IV, DSM Fourth Edition; FISQ, Full Scale Intelligence Quotient; GABAA , ␥-Aminobutyric Acid Type A Receptor; GIQ, Global IQ; HFA, High-Functioning Autism; ICD-10, International Classification of Diseases Tenth Revision; IQ, Intelligence Quotient; LFA, Low-Functioning Autism; MR, Mental Retardation [note: now referred to as intellectual disability]; NVIQ, Nonverbal Intelligence Quotient; PDDNOS, Pervasive Developmental Disorder Not Otherwise Specified; PFC, Prefrontal Cortex; PIQ, Performance Intelligence Quotient; rCBF, Regional Cerebral Blood Flow; SERT, Serotonin Transporter; STG, Superior Temporal Gyrus; TD, Tardive Dyskinesia; VIQ, Verbal Intelligence Quotient.
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8 years 8 months, 5–16 years
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Please cite this article in press as: Zürcher, N.R., et al., A systematic review of molecular imaging (PET and SPECT) in autism spectrum disorder: Current state and future research opportunities. Neurosci. Biobehav. Rev. (2015), http://dx.doi.org/10.1016/j.neubiorev.2015.02.002
Makkonen et al. (2008)
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Fig. 1. Disparity between disease prevalence and MI investigations conducted to date using PET and SPECT in ASD compared to other neuropsychiatric/neurological disorders. The vertical axis shows the number of MI studies for a specific disorder divided by prevalence of that disorder. Prevalence was estimated based on statistics from the CDC, National Institute of Mental Health (NIMH), Alzheimer’s Association and Parkinson’s disease foundation. To estimate the number of MI studies conducted in each disorder, PubMed searches were performed for PET/SPECT studies listing that particular disorder in the title or abstract.
Individuals across a broad age range, from children (70) and both ends of the spectrum have been investigated, with the majority (all but 13) studies specifying IQ: 26 studies have investigated low-functioning individuals with ASD, 21 studies high- functioning individuals with ASD and 19 studies enrolled participants of both ends of the spectrum. However, when studies are grouped by participant age as well as IQ, it becomes clear that research in children has focused on low-functioning individuals with ASD and most studies in adults have involved high-functioning individuals, while studies including participants across a wide age range (mixed age group) have not focused solely on high- or lowfunctioning individuals with ASD, reflecting the inclusion of both low-functioning children and high-functioning adults in the same study. See Fig. 3 for repartition according to age and level of functioning. Taken together, these numbers show that fewer studies
Fig. 2. (A) Pie chart illustrating the different radiotracers used in MI studies (PET and SPECT combined) investigating ASD. Note that CBF and glucose metabolism account for approximately three quarters of the targets investigated in MI studies conducted in the field of autism research, thus reflecting a lack of studies focusing on neurotransmitters or proteins. (B) Pie chart showing the percentage breakdown of MI studies with children/adolescents with ASD (
