Long-Term Effects of “Ecstasy” Use on Serotonin Transporters of the

Long-Term Effects of “Ecstasy” Use on

Serotonin Transporters of the Brain Investigated

by PET

Ralph Buchert, PhD

; Rainer Thomasius, MD

; Bruno Nebeling, PhD

; Kay Petersen, PhD

; Jost Obrocki, MD

;

Lars Jenicke, MD

; Florian Wilke

; Lutz Wartberg

; Pavlina Zapletalova, MS

; and Malte Clausen, MD

Department of Nuclear Medicine, University Hospital Hamburg-Eppendorf, Hamburg, Germany; and

Department of Psychiatry

and Psychotherapy, University Hospital Hamburg-Eppendorf, Hamburg, Germany

Alterations of the serotonergic system due to ecstasy consump-

tion have been extensively documented in recent literature.

However, reversibility of these neurotoxic effects still remains

unclear. To address this question, PET was performed using the

serotonin transporter (SERT) ligand

C-(⫹)-McN5652 in a total

of 117 subjects subdivided into 4 groups: actual ecstasy users

(n ⫽ 30), former ecstasy users (n ⫽ 29), drug-naive control

subjects (n ⫽ 29), and subjects with abuse of psychoactive

agents other than ecstasy (n ⫽ 29). Methods: About 500 MBq

C-(⫹)-McN5652 were injected intravenously. Thirty-ﬁve scans

were acquired according to a dynamic scan protocol of 90 min

using a full-ring whole-body PET system. Transaxial slices were

reconstructed using an iterative method. Individual brains were

transformed to a template deﬁned earlier. Distribution volume

ratios (DVRs) were derived by application of a reference tissue

approach for reversible binding. Gray matter of the cerebellum

served as reference. SERT-rich brain regions—mesencephalon,

putamen, caudate, and thalamus—were selected for the eval-

uation of SERT availability using volumes of interest predeﬁned

in the template. Results: Compared with drug-naive control

subjects, the DVR in actual ecstasy users was signiﬁcantly

reduced in the mesencephalon (P ⫽ 0.004) and the thalamus

(P ⫽ 0.044). The DVR in former ecstasy users was very close to

the DVR in drug-naive control subjects in all brain regions. The

DVR in polydrug users was slightly higher than that in the

drug-naive control subjects in all SERT-rich regions (not statis-

tically signiﬁcant). Conclusion: Our ﬁndings further support the

hypothesis of ecstasy-induced protracted alterations of the

SERT. In addition, they might indicate reversibility of the avail-

ability of SERT as measured by PET. However, this does not

imply full reversibility of the neurotoxic effects.

Key Words: ecstasy; long-term effects; serotonin transporter;

PET;

C-(⫹)-McN5652

J Nucl Med 2003; 44:375–384

The synthetic hallucinogen, 3,4-methylenedioxymetham-

phetamine (MDMA) is the main psychoactive constituent of

the popular recreational drug ecstasy. It produces euphoria,

increase in psychomotor drive, and enhanced sociability.

Because of these effects, ecstasy has become popular among

adolescents and young adults.

However, apart from these psychologic effects, there is

increasing evidence for the neurotoxicity of MDMA (1).

Initial ﬁndings in animals (in both rats and nonhuman

primates) indicated that MDMA might cause alterations of

serotonergic neurons in the brain (2–5). Moreover, signiﬁ-

cantly reduced concentrations of 5-hydroxyindoleacetic

acid in the cerebrospinal ﬂuid in human ecstasy users gave

evidence that MDMA also leads to an impairment of sero-

tonin neurons in the human brain (6).

To further explore the effect of MDMA on the seroto-

nergic system, markers of the presynaptic serotonin trans-

porter (SERT) have been developed. Using PET, Szabo et

al. (7) demonstrated high speciﬁc ligand binding of

C-(⫹)-

McN5652 to SERT of the human brain in vivo. Initial

investigations of speciﬁc

C-(⫹)-McN5652 binding in

MDMA users were performed by McCann et al. (8). In 14

previous ecstasy users, a decreased global and local binding

to SERT was observed compared with that of 15 control

subjects who had never used MDMA. Ecstasy users had

abstained from psychoactive drugs for 19 wk (range, 3–147

wk) before the study. Semple et al. (9), using

123

I-2␤-

carbomethoxy-3␤-(4-ﬂuorophenyl)tropane (

123

I-␤-CIT)

SPECT, detected a cortical reduction of cerebral SERTs in

long-term MDMA users compared with MDMA-naive but

other drug-using subjects. In ecstasy users, SPECT was

performed 2.6 ⫾ 1.1 wk (range, 0.9–4.0 wk) after the last

tablet. In a study of cerebral glucose metabolism using PET

with

F-FDG, local uptake of

F-FDG was reduced within

the striatum and the amygdala in 93 ecstasy users compared

with that of 27 control subjects (10,11). The time since the

last ecstasy ingestion on the day of PET was 28 ⫾ 62 wk

(range, 0.4–416 wk).

Received May 2, 2002; revision accepted Sep. 25, 2002.

For correspondence or reprints contact: Ralph Buchert, PhD, Department

of Nuclear Medicine, University Hospital Hamburg-Eppendorf, Martinistrasse

52, D-20246 Hamburg, Germany.

E-mail: [email protected]

LONG-TERM EFFECTS OF “ECSTASY”USE • Buchert et al. 375

However, it is still unclear whether MDMA leads to an

irreversible impairment of serotonergic neurons or whether

neuronal alterations are reversible after withdrawing from

using ecstasy. Moreover, criticism of previous studies con-

cerned the potential concurrent abuse of psychoactive

agents other than ecstasy that might also cause a reduction

of the availability of SERT.

Therefore, the aim of this study was to investigate the

long-term effect of MDMA use on the serotonergic system

C-(⫹)-McN5652 PET in a rather large number of

subjects with special regard for actual or former ecstasy

abuse and abuse of psychoactive substances other than

MDMA.

MATERIALS AND METHODS

Subjects

PET using the SERT ligand

C-(⫹)-McN5652 (12) was per

formed on 120 healthy subjects without psychiatric history divided

into 4 different groups: actual ecstasy users (group A), former

ecstasy users (group F), subjects without any known history of

illicit-drug abuse (drug-naive, group N), and subjects with abuse of

psychoactive agents other than ecstasy (polydrug users, group P).

All subjects were tested for psychopathology with the Structured

Clinical Interview for DSM-IV (SKID) (13). Subjects currently

suffering from any axis I disorder, except substance-related disor-

ders (not alcohol- or opiate-related disorders), were excluded from

the study. Drug history was ascertained by a standardized ques-

tionnaire. Plausibility of the drug users’ self-assessment was ver-

iﬁed by testing of hair samples. Participants abstained from use of

all psychoactive drugs for at least 3 d before the study. To verify

this abstention period, the urine of all subjects was screened for the

presence of amphetamines, barbiturates, benzodiazepines, canna-

binoids, cocaine metabolites, opiates, and alcohol on the day of

PET. Subjects who tested positive for any of these substance

groups, except cannabinoids, were excluded from the study. How-

ever, urine testing results might be false-positive. Therefore, in 3

subjects with authentic self-assessment, PET was performed de-

spite positive urine screening. In these subjects an additional blood

screening for drugs was performed. The positive urine test was

conﬁrmed by blood screening in 2 of these subjects, which led to

the exclusion from the study after PET scanning. Thus, the ab-

stention period was veriﬁed in all subjects included in the study.

Scanning of 1 further subject could not be completed because of

claustrophobia. Demographic data of the remaining 117 subjects

are given in detail in Table 1.

The study was approved by the local ethics committee and

radiation protection authorities. All participants gave their written

informed consent.

Actual Ecstasy Users (Group A). Thirty actual ecstasy users (15

females, 15 males; mean age, 24.5 ⫾ 4.2 y) were investigated.

Inclusion criterion was regular ecstasy use (at least once per week)

of at least 2 tablets within 48 h each time. Drug-history data are

listed in detail in Tables 2 and 3.

Former Ecstasy Users (Group F). Twenty-nine former ecstasy

users (14 females, 15 males; mean age, 24.2 ⫾ 3.6 y) were

investigated. The inclusion criterion was a cumulative ecstasy dose

of at least 250 tablets and 400 tablets in female and male subjects,

respectively. We included those subjects who took ecstasy for at

least 36 mo with the last MDMA ingestion at least 20 wk before

C-(⫹)-McN5652 PET. Drug-history data are listed in detail in

Tables 2 and 3.

Drug-Naive Subjects (Group N). Twenty-nine subjects (15 fe-

males, 14 males; mean age, 23.3 ⫾ 3.7 y) without any known

history of illicit drug abuse served as the control group. Drug-naive

control subjects were not on any psychoactive medication. Use of

alcohol or nicotine that did not fulﬁll the dependence criteria

TABLE 1

Demographics

Parameter

Actual ecstasy users

(group A)

Former ecstasy users

(group F)

Drug-naive controls

(group N)

Polydrug users

(group P)

n 30 29 29 29

Age (y) 24.5 ⫾ 4.2 (19–34) 24.2 ⫾ 3.6 (19–36) 23.3 ⫾ 3.7 (18–33) 24.4 ⫾ 4.6 (18–35)

Sex (F/M) 15/15 14/15 15/14 14/15

Data are given as mean ⫾ 1 SD (range).

TABLE 2

Ecstasy Consumption Data

Parameter

Actual ecstasy users

(group A)

Former ecstasy users

(group F)

Cumulated ecstasy dose (tablets) 827 ⫾ 1,268 (13–6,873) 793 ⫾ 679 (78–3,122)

Duration of use (mo) 54 ⫾ 32 (5–120) 55 ⫾ 27 (18–116)

Time since last ecstasy ingestion at day of PET (d) 24 ⫾ 16 (4–60) 514 ⫾ 472 (90–1,500)

Age at ﬁrst ecstasy ingestion (y) 20.0 ⫾ 3.8 (14–30) 18.3 ⫾ 3.0 (15–28)

Data are given as mean ⫾ 1 SD (range).

376 THE JOURNAL OF NUCLEAR MEDICINE • Vol. 44 • No. 3 • March 2003

according to the Diagnostic and Statistical Manual of Mental

Disorders (DSM) (14) was no exclusion criterion.

Polydrug Users (Group P). Twenty-nine subjects (14 females,

15 males; mean age, 24.4 ⫾ 4.6 y) with abuse of psychoactive

substances other than ecstasy were investigated. Drug abuse in this

group was intended to match drug abuse in the ecstasy consumer

groups, except ecstasy. The last drug ingestion was from at least

3 d to a maximum of 2 wk before

C-(⫹)-McN5652 PET. Data

concerning illicit-drug abuse are listed in detail in Tables 2 and 3.

C-(ⴙ)-McN5652

The parent compound of the radiotracer, McN5652-z (6-[4-

methylthiophenyl]-1,2,3,5,6,10b-hexahydropyrrolo[2,1-a]iso-

quinoline), was synthesized and fully determined by x-ray struc-

tural analysis and nuclear magnetic resonance spectroscopy

(nuclear Overhauser effect measurements). The 2 diastereomers

were unequivocally assigned and compared with an authentic

sample. Because this compound possesses 2 centers of asymmetry,

there are 4 stereoisomers (6S, 10bR), (6R, 10bS), (6S, 10bS), and

(6R, 10bR). Regarding the position of the hydrogen atoms at C-6

and C-10b, the 2 enantiomeric pairs were called cis and trans. The

diastereoisomers were separated by preparative column chroma-

tography, and the previously described (⫹)-enantiomer was sepa-

rated by semipreparative chromatography on a chiral phase (amy-

lose tris[3,5-dimethylphenyl carbamat]) and compared with an

authentic sample of the (⫹)-McN5652-z enantiomer (15).

To generate the precursor for the labeling with

C-methyli

odide, the (⫹)-McN5652-z enantiomer was demethylated and the

corresponding thiolate was isolated with a chemical purity of

98.5% using solid-phase extraction techniques. The precursor was

fractionated in quantities of 200 ␮g and stored at ⫺80°C.

The labeling of the thiolate with

C-CH

I, which was ﬁrst

generated by classical reduction of

C-CO

, resulted in an average

speciﬁc activity of 45 MBq/nmol for

C-(⫹)-McN5652-z at the

end of synthesis. An improvement of the average speciﬁc activity

by a factor of 10 was achieved when generating the

C-CH

Iby

direct iodination of the in-target produced,

C-CH

. The synthesis

time was 22 min. The radiochemical yield was 14% ⫾ 5%.

The purity of the enantiomer, radionuclidic purity, and radio-

chemical purity were more than 99.5%, 99.9%, and 90.0%, respec-

tively. The radiochemical purity was limited because of the de-

composition of the

C-(⫹)-McN5652-z depending on the amount of

activity produced. The speciﬁc activity at the end of synthesis was

⬎30 MBq/nmol (mean ⫾ 1 SD, 177 ⫾ 108 MBq/nmol; range,

30–537 MBq/nmol). Doses dispensed to the participants are summa-

rized in Table 4.

PET

PET was performed on a full-ring, whole-body ECAT EXACT

921/47 system (Siemens/CTI, Knoxville, TN) in 2-dimensional

mode. This system covers an axial ﬁeld of view of 16.2 cm by

collecting 47 transversal slices with 3.4-mm slice separation.

Head movement minimization was achieved by a thermoplastic

mask immobilization system (Tru-Scan Imaging, Annapolis, MD).

A 15-min transmission scan for attenuation correction was ob-

tained before tracer injection using 3 rotating

Ge rod sources,

about 70 MBq each. After obtaining the transmission scan, 466 ⫾

76 MBq

C-(⫹)-McN5652, dissolved in 40 mL 0.9% NaCl, were

injected through a vein of the left hand at a ﬂow rate of 600 mL/h.

Thus, the total infusion time was 4 min. At the beginning of tracer

injection a dynamic scan protocol was initiated, including 35

frames with a total acquisition time of 90 min (9 ⫻ 20 s, 6 ⫻ 30 s,

TABLE 3

Exposure to Drugs Other than Ecstasy

Parameter

Actual ecstasy users

(group A)

Former ecstasy users

(group F)

Drug-naive controls

(group N)

Polydrug users

(group P)

Amphetamine cumulated dose (g) 68 ⫾ 106 77 ⫾ 115 0 4 ⫾ 9

Cannabis cumulated dose (g) 567 ⫾ 1,188 2,133 ⫾ 2,200 0 1,232 ⫾ 1,303

LSD cumulated dose (g) 1.6 ⫾ 5.2 2.4 ⫾ 5.1 0 0.2 ⫾ 0.4

Psilocybine cumulated dose (g) 0.9 ⫾ 3.2 5.1 ⫾ 15.6 0 14.4 ⫾ 32.5

Cocaine cumulated dose (g) 38 ⫾ 75 101 ⫾ 219 0 255 ⫾ 708

Alcohol in past week (g) 94 ⫾ 97 152 ⫾ 198 71 ⫾ 72 197 ⫾ 195

Nicotine in past week (cigarettes) 53 ⫾ 58 101 ⫾ 71 66 ⫾ 65 135 ⫾ 80

LSD ⫽ lysergic acid diethylamide.

Data are given as mean ⫾ 1 SD.

TABLE 4

Injected Tracer Doses

Parameter

Actual ecstasy users

(group A)

Former ecstasy users

(group F)

Drug-naive controls

(group N)

Polydrug users

(group P)

Radioactivity dose (MBq) 465 ⫾ 87 (324–700) 451 ⫾ 71 (251–549) 467 ⫾ 84 (134–582) 480 ⫾ 59 (360–555)

Speciﬁc activity at injection

(MBq/nmol) 56.4 ⫾ 50.0 (14.0–203) 66.5 ⫾ 47.5 (14.6–204) 87.7 ⫾ 44.0 (14.7–175) 120 ⫾ 56.7 (47.4–302)

Mass dose (nmol) 14.9 ⫾ 9.8 (1.6–35.3) 11.2 ⫾ 8.6 (2.3–35.2) 8.0 ⫾ 7.7 (2.2–36.7) 4.7 ⫾ 1.7 (1.3–8.6)

Data are given as mean ⫾ 1 SD (range).

LONG-TERM EFFECTS OF “ECSTASY” USE • Buchert et al. 377

4 ⫻ 60 s, 5 ⫻ 120 s, 8 ⫻ 300 s, and 3 ⫻ 600 s). Subjects were

asked to keep their eyes open during the entire time of acquisition.

Noise in the acquisition room was kept to a minimum.

The sinograms were corrected for random coincidences, radio-

active decay, dead time, and varying detector efﬁciency. Thereaf-

ter, sinograms were 3-dimensionally smoothed by application of a

3 ⫻ 3 ⫻ 3 binomial kernel (smoother software, J. van den Hoff,

Medical University, Hannover, Germany). Forty-seven transaxial

slices with 64 ⫻ 64 voxels were reconstructed using an iterative

method (ira-1.25 software, H. Fricke, Medical University, Han-

nover, Germany) (order-subsets expectation maximization

[OSEM], 24 subsets, 3 iterations). The voxel size was 3.4 ⫻ 3.4 ⫻

3.4 mm

; in-plane spatial resolution was about 9-mm full width at

half maximum (FWHM). No scatter correction was performed.

Data Preprocessing

For further processing, the format of the reconstructed images

was converted from the scanner-speciﬁc ECAT 6.5 format to

ANALYZE format using the commercial PMOD software package

(Version 2.25 for Windows NT; Medical Imaging Software, Zu-

rich, Switzerland) (16). Then the images were ﬂipped top to

bottom and the 4-dimensional dataset was clipped to thirty-ﬁve

3-dimensional datasets, each 3-dimensional dataset containing 1

single frame of the dynamic study (MRIcro 1.30, Chris Rorden,

University of Nottingham, Nottingham, U.K.) (17).

To correct the remaining head movement, frames 12–35 (4–90

min after injection) were coregistered using the Realign-Tool of

the SPM99 software package (Wellcome Department of Cognitive

Neurology, Institute of Neurology, University College London,

London, U.K.) (18) (parameter values: coregister only; always

mask images; registration quality 0.5; don’t allow weighting of

reference image). Frame 27 (30–35 min after injection) served as

the reference frame for coregistration. Because frames 1–11 did

not provide sufﬁcient anatomic information for the convergence of

the realign algorithm, the transformation matrix for frame 12 was

applied to these frames assuming that there was no relevant move-

ment during the ﬁrst 4 min of the acquisition.

To support standardized identiﬁcation of the volumes of interest

(VOIs) in each subject, individual images were stereotactically

normalized using the Normalize-Tool of SPM99 (parameter values

for nonlinear warping: 7 ⫻ 8 ⫻ 7 nonlinear basis functions; 12

nonlinear iterations; medium nonlinear regularization; default

brain mask; don’t mask object). To determine the normalization

parameters, the summed image of frames 27–35 (30–90 min after

injection) was compared with a template deﬁned earlier (mean of

9 summed

C-(⫹)-McN5652 PET scans acquired during a pilot

study). Realignment and normalization were combined to 1 single

transformation. Transformed images were written with a voxel size

of 3 ⫻ 3 ⫻ 3mm

using sinc interpolation.

After motion correction and stereotactic normalization, the thir-

ty-ﬁve 3-dimensional datasets were reconverted to a single 4-di-

mensional dataset using MRIcro. Finally, the quality of the pre-

processing steps was controlled by visual inspection of the

4-dimensional dataset in cine mode and by comparing the normal-

ized individual summed image and the template using correspond-

ing crosshairs.

VOIs

According to the current literature, the following brain struc-

tures were selected for testing the hypothesis of ecstasy-induced

alteration of SERT availability (19–21): mesencephalon, putamen,

caudate, and thalamus. The white matter served as the control

region in which no ecstasy-induced effects were expected because

of the absence of SERT. The gray matter of the cerebellum was

chosen as the reference region for the kinetic modeling.

VOIs for the structures to be examined were predeﬁned in the

template. Each VOI was composed of circles of 4.1 mm in radius,

placed in an appropriate number of transversal slices using the VOI-

Tool of PMOD (Fig. 1) (22). No individual adjustment was performed

to guarantee reproducible results. However, in 3 subjects the cerebel-

lum was partly outside of the ﬁeld of view of the PET scanner, so that

the cerebellum VOI had to be adjusted manually.

Kinetic Modeling

Modeling was performed on the level of voxels. Distribution

volume ratios (DVRs) were derived by application of the graphic

reference tissue method for reversible binding described by Ichise

et al. (23) (Ichise noninvasive plot).

The Ichise noninvasive plot is easily derived from the more

widely known invasive Logan plot for the graphical analysis of

reversible radioligand binding (24). The operational equation of

the Logan plot reads:

兰

C共s兲ds

C共t兲

⬇ DV ⫻

兰

共s兲ds

C共t兲

⫹ b, t ⬎ t*, Eq. 1

where C(t) is the time–activity curve of a tissue voxel or VOI, C

(t)

is the time–activity curve of the free fraction of unmetabolized

tracer in arterial plasma (input function), DV is the total distribu-

tion volume of the tracer in the tissue, and b is a quantity that

becomes constant at late times t ⬎ t*. DV is deﬁned as the

tissue-to-plasma ratio C/C

at equilibrium. Neglecting fractional

blood volume DV is just the sum of the nondisplaceable and the

speciﬁc distribution volume—that is:

DV ⫽ DV

nondispl

⫹ DV

spec

.Eq.2

Now, combining the Logan plot formula (Eq. 1) for 2 different

tissue time–activity curves, C and C

, by solving the C

formula for

the plasma integral and inserting the result in the C formula yields:

兰

C共s兲ds

C共t兲

⬇ DVR ⫻

兰

共s兲ds

C共t兲

⫺ DVR ⫻ b

⫻

共t兲

C共t兲

⫹ b, t ⬎ t*,

Eq. 3

FIGURE 1. Deﬁnition of VOIs for putamen, caudate, thalamus,

and white matter (left), mesencephalon (middle), and cerebellum

(right) in transversal slices of the

C-(⫹)-McN5652-PET template.

VOIs were composed of circles of 4.1-mm radius drawn in appro-

priate number of slices (mesencephalon, no. of slices ⫽ 3/no. of

circles ⫽ 9/no. of voxels ⫽ 50; putamen, 4/24/166; caudate, 6/12/

83; thalamus, 4/16/105; cerebellum, 5/40/273; white matter, 8/16/

108).

378 THE JOURNAL OF NUCLEAR MEDICINE • Vol. 44 • No. 3 • March 2003

where DVR is the distribution volume ratio:

DVR ⬅

.Eq.4

Equation 3 is the operational equation of the Ichise noninvasive

plot. Beyond time t* it is a multilinear equation. Thus, the DVR is

easily obtained by multilinear regression analysis.

Assuming that C

is taken from a reference tissue, which is

devoid of the receptor under consideration and provides approxi-

mately the same nondisplaceable DV as that of receptor-rich

tissue, one obtains from Equations 2 and 4:

DVR ⬇ 1 ⫹

spec

nondispl

.Eq.5

The ratio DV

spec

/DV

nondispl

is commonly denoted as binding

potential BP*. It is related to the density of available receptors, B

and the equilibrium dissociation constant, K

, according to:

BP* ⫽

⫻ DV

nondispl

.Eq.6

Therefore, for the DVR to reﬂect the receptor density, both, K

and

nondispl

must be constant between individuals and diseases.

The time–activity curve of the reference region was generated

using the mean of the cerebellum VOI. The starting time for the

multilinear regression analysis was ﬁxed at t* ⫽ 12 min.

DVRs for the examined structures were taken to be the mean

voxel values within the corresponding VOIs copied to the individ-

ual parametric images.

In addition to DVRs, semiquantitative standardized uptake val-

ues (SUVs) were considered. To this end, images of tracer uptake

were obtained by summing frames 31–35 (50–90 min after injec-

tion). SUVs were then computed as the ratio of tracer uptake to

injected dose per body weight (kBq/mL/[MBq/kg]).

Statistical Analysis

The following a priori predictions were made:

H1. Ecstasy use causes long-lasting reduction of SERT avail-

ability. This leads to a reduction of the DVR of

C-(⫹)-

McN5652 in the SERT-rich regions mesencephalon, pu-

tamen, caudate, and thalamus in both former and actual

ecstasy users compared with the group of drug-naive

control subjects.

H2. There is no group difference in the DVR in the white

matter, which is devoid of SERT.

H3. There is a difference in the DVR between the group of

polydrug users and the group of drug-naive control sub-

jects in the SERT-rich brain regions.

One-way ANOVA and post hoc tests for multiple comparisons

were used to test these hypotheses. The Scheffe´ or Tamhane post

hoc test was applied according to the result of the Levene test of

homogeneity of variances. These post hoc tests are deliberately

conservative to reduce the probability of too many signiﬁcant

differences arising by chance. No additional Bonferroni adjust-

ment for the number of VOIs was performed. All statistic compu-

tations were performed using SPSS 10.0 (SPSS, Inc., Chicago, IL)

for Microsoft Windows (Redmond, WA).

RESULTS

Representative time–activity curves are shown in Figure 2.

The results of the VOI analysis are listed in detail in

Tables 5 and 6. In all SERT-rich regions, the mean DVR

was lowest in the group of actual ecstasy users and highest

in the group of polydrug users. The mean DVRs in the

group of former ecstasy users and in the group of drug-naive

control subjects were very similar and slightly lower than

that in the group of polydrug users.

ANOVA detected differences in the DVR between the 4

groups to be statistically signiﬁcant in the mesencephalon

(2-tailed P ⫽ 0.000), caudate (P ⫽ 0.032), and thalamus

(P ⫽ 0.022). There was no signiﬁcant difference in the

putamen (P ⫽ 0.187) and white matter (P ⫽ 0.732). Ac-

cording to the Levene test, variances were homogeneous in

all structures. Therefore, the Scheffe´ test was applied for

multiple comparisons in the structures with signiﬁcant

ANOVA. In the mesencephalon, the DVR was signiﬁcantly

smaller in the group of actual ecstasy users than in all other

FIGURE 2. Representative time–activity

curves. SUVs for mesencephalon, thala-

mus, white matter, and cerebellum VOIs in

drug-naive control subject are plotted.

LONG-TERM EFFECTS OF “ECSTASY” USE • Buchert et al. 379

groups (1-tailed P[A/F] ⫽ 0.008, P[A/N] ⫽ 0.004, P[A/P] ⫽

0.000). In the caudate, the DVR was signiﬁcantly smaller in

the group of actual ecstasy users than in the group of

polydrug users (P[A/P] ⫽ 0.022). In the thalamus, the DVR

was signiﬁcantly smaller in the group of actual ecstasy users

than in both the group of drug-naive control subjects and the

group of polydrug users (P[A/N] ⫽ 0.044, P[A/P] ⫽ 0.033).

The mean SUVs were highest in the group of drug-naive

control subjects in all regions. The mean SUVs in the group

of actual ecstasy users and the group of polydrug users were

rather similar and were slightly larger than those in the

group of former ecstasy users, who showed the smallest

SUVs in all regions. ANOVA detected differences in the

SUV to be statistically signiﬁcant only in the white matter

VOI. However, the following Scheffe´ test did not yield a

signiﬁcant result for the difference between the SUV in

white matter for any pair of groups.

DISCUSSION

Because the drug ecstasy has become increasingly pop-

ular among adolescents and young adults, neurotoxic long-

term effects of recreational use of MDMA are a focus of

ongoing research. Criticisms of previous studies are related

to the potential overlapping neuronal effects of concurrently

used drugs. Furthermore, it remains unclear whether alter-

ations of the serotonergic system are in principle reversible

or whether neurotoxic alterations may persist even after

stopping MDMA abuse. To address these questions, PET

using the SERT ligand

C-(⫹)-McN5652 was performed

on actual ecstasy users, former ecstasy users, drug-naive

control subjects, and subjects with abuse of psychoactive

agents other than ecstasy.

Compared with drug-naive control subjects, the DVR

in actual ecstasy users was reduced in all SERT-rich

regions. The reduction was statistically signiﬁcant in the

mesencephalon and thalamus. This result further supports

the hypothesis that ecstasy use causes protracted alter-

ations of the brain serotonergic system that last (at least)

several weeks (H1).

In the white matter, there were no signiﬁcant differences

in the DVR between the 4 groups. Because the white matter

is devoid of SERT, this supports the hypothesis that the

TABLE 5

DVRs, 1-Way ANOVA, and Scheffe´ Post Hoc Test

Region

Actual ecstasy

users (group A)

(n ⫽ 30)

Former ecstasy

users (group F)

(n ⫽ 29)

Drug-naive controls

(group N)

(n ⫽ 29)

Polydrug users

(group P)

(n ⫽ 29)

ANOVA

Scheffe´

testdF F P

Mesencephalon 1.163 ⫾ 0.071 1.220 ⫾ 0.074 1.224 ⫾ 0.047 1.234 ⫾ 0.069 116 6.858 0.000 A/F*

A/N*

A/P

†

Putamen 1.356 ⫾ 0.100 1.386 ⫾ 0.097 1.387 ⫾ 0.066 1.407 ⫾ 0.090 116 1.628 0.187

Caudate 1.198 ⫾ 0.085 1.239 ⫾ 0.093 1.239 ⫾ 0.049 1.258 ⫾ 0.082 116 3.034 0.032 A/P

‡

Thalamus 1.349 ⫾ 0.088 1.402 ⫾ 0.090 1.408 ⫾ 0.073 1.411 ⫾ 0.100 116 3.341 0.022 A/N

‡

A/P

‡

White matter 0.561 ⫾ 0.064 0.565 ⫾ 0.047 0.577 ⫾ 0.057 0.566 ⫾ 0.062 116 0.430 0.732

*P ⱕ 0.01 (signiﬁcance level of 1-tailed Scheffe´ test).

†

P ⱕ 0.001 (signiﬁcance level of 1-tailed Scheffe´ test).

‡

P ⱕ 0.05 (signiﬁcance level of 1-tailed Scheffe´ test).

DVRs are given as mean ⫾ 1 SD.

TABLE 6

SUVs, 1-Way ANOVA, and Scheffe´ Post Hoc Test

Region

Actual ecstasy

users (group A)

(n ⫽ 30)

Former ecstasy

users (group F)

(n ⫽ 29)

Drug-naive controls

(group N)

(n ⫽ 29)

Polydrug users

(group P)

(n ⫽ 28)

ANOVA

Scheffe´

testdF F P

Mesencephalon 3.856 ⫾ 0.615 3.784 ⫾ 0.929 4.243 ⫾ 0.645 3.861 ⫾ 0.640 115 2.421 0.070

Putamen 4.173 ⫾ 0.690 4.037 ⫾ 1.030 4.452 ⫾ 0.708 4.144 ⫾ 0.634 115 1.481 0.224

Caudate 3.663 ⫾ 0.593 3.559 ⫾ 0.921 3.946 ⫾ 0.631 3.567 ⫾ 0.577 115 1.957 0.125

Thalamus 4.166 ⫾ 0.669 4.095 ⫾ 1.037 4.556 ⫾ 0.729 4.158 ⫾ 0.703 115 2.017 0.116

White matter 1.914 ⫾ 0.321 1.775 ⫾ 0.374 2.000 ⫾ 0.333 1.789 ⫾ 0.328 115 2.883 0.039 —

Cerebellum 2.797 ⫾ 0.478 2.612 ⫾ 0.600 2.858 ⫾ 0.450 2.612 ⫾ 0.386 115 1.964 0.123

SUVs are given as mean ⫾ 1 SD.

380 THE JOURNAL OF NUCLEAR MEDICINE • Vol. 44 • No. 3 • March 2003

observed effects in SERT-rich regions indeed indicate dif-

ferences in SERT availability (H2).

The DVR in former ecstasy users was very close to the

DVR in drug-naive control subjects. There was no signiﬁ-

cant difference between these groups; there was not even a

tendency (2-sided P[F/N] ⫽ 0.997 in mesencephalon). This

is in agreement with the results of Reneman et al. (25,26).

Using

123

I-␤-CIT SPECT and the cerebellum as the refer

ence region, this group found no difference in the SERT

availability in 16 individuals who stopped using MDMA

29 ⫾ 20 mo earlier compared with 15 control subjects who

had never used MDMA. The potential reversibility of SERT

availability was reported by Scheffel et al. (27) using PET

with

C-(⫹)-McN5652 and, for the estimation of nonspe

ciﬁc binding, its pharmacologically inactive enantiomer

C-(⫺)-McN5652 in baboons. Their study showed that

SERT binding was reduced in all brain regions 40 d after

MDMA ingestion. In contrast, 9- and 13-mo follow-up PET

showed recovery of SERTs, however, with regional differ-

ences. This again is in good agreement with Semple et al.

(9), who reported evidence of recovery from alterations of

brain serotonergic neurons after withdraw of MDMA abuse

using

123

I-␤-CIT SPECT and the cerebellum as the refer

ence region. They described a positive partial correlation of

relative tracer uptake in many brain regions and the interval

since intake of the last tablet in a group of 10 male ecstasy

users. Indication that the neuroendocrine impairment caused

by MDMA may be due to a partially reversible neurotoxic

action was also reported by Gerra et al. (28). In 15 MDMA

users, who did not show other drug dependencies or pro-

longed alcohol abuse, prolactin and cortisol responses to the

serotonergic agonist d-fenﬂuramine were signiﬁcantly re-

duced after 3 wk of ecstasy abstinence compared with those

of control subjects. Twelve months later, the prolactin re-

sponse was still reduced but the cortisol response had nor-

malized.

Histologic examination of the brain 5-hydroxytryptamine

(5-HT) innervation pattern in MDMA-treated squirrel mon-

keys revealed a reduced density of serotonergic axons even

7 y after MDMA treatment, although the deﬁcits were less

severe than those at 18 mo after the treatment (29). These

histologic results are not in conﬂict with the results of in

vivo functional brain imaging cited above. Brain imaging

measures the availability of receptors for the ligand used,

which not only is a function of receptor density but also

depends on the actual afﬁnity of the receptor for the ligand,

the transmitter synaptic concentration, and the transmitter

receptor occupancy. Thus, in the outcome measures of

functional brain imaging, reduced SERT density might be

compensated by other effects. In this context, the results of

Kish et al. (30), who found 50%–80% reduced striatal 5-HT

levels in a postmortem study of a single ecstasy user, may

be relevant. Reneman et al. (31) conducted a SPECT study

with the ligand

123

I-5-I-R91150 for the postsynaptic 5-HT

receptor. In 5 abstinent MDMA users, the binding ratio of

123

I-5-I-R91150 in the occipital cortex was signiﬁcantly

elevated compared with that of 9 healthy control subjects.

This may indicate an upregulation of the postsynaptic

5-HT

receptor following the lesion of serotonergic affer

ents. In a second

123

I-5-I-R91150 SPECT study, Reneman et

al. (32) found that the mean cortical binding ratios were

signiﬁcantly lower in recent MDMA users than in former

MDMA users and control subjects. Finally, axonal regen-

eration may lead to abnormal, dysfunctional circuitry.

Thus, the key question of whether MDMA leads to an

irreversible or (partly) reversible impairment of serotoner-

gic neurons remains controversial. To further examine this

question, follow-up examinations of MDMA users are cur-

rently performed.

Ecstasy users usually take additional psychoactive sub-

stances. Therefore, ﬁndings of

C-(⫹)-McN5652 binding

are not necessarily speciﬁc—that is, secondary to ecstasy

use. In addition, (heavy) users of ecstasy may have different

personalities than those of people who have never used

drugs. Therefore, this study investigated a second control

group of polydrug users who did not use ecstasy but were

intended to be matched with the ecstasy users for the con-

sumption of other drugs. We found the DVR in the polydrug

users to be slightly higher in all SERT-rich regions, includ-

ing the mesencephalon, putamen, caudate, and thalamus,

than that in the drug-naive control subjects (H3). Neverthe-

less, the difference was not statistically signiﬁcant in any

region. However, although the reduction of the DVR in the

caudate of actual ecstasy users was not statistically signif-

icant relative to that of the drug-naive control subjects, it

was signiﬁcant relative to that of the group of polydrug

users, despite the fact that the SD was larger in the group of

polydrug users than that in the group of drug-naive control

subjects in all brain regions. The slightly increased DVR in

the group of polydrug users might be explained by acute

serotonergic dysfunction during acute abstinence from

chronic cocaine use, for example. This effect was described

by Jacobsen et al. (33), who found elevated central SERT

availability using

123

I-␤-CIT SPECT in 15 cocaine-depen

dent subjects who were abstinent from drug use a mean of

3.7 d compared with 37 healthy comparison subjects.

The analysis of SUVs did not reveal any statistically

signiﬁcant results. This might be explained by the rather

large variance of SUVs. The relative SD of SUVs within the

different VOIs and groups was 15%–27%, whereas it was

4%–7% for the DVRs. However, SUVs were lowest in the

group of former ecstasy users in all VOIs. In addition, SUVs

in the polydrug control group were quite similar to those in

the ecstasy user groups. Although these results were not

statistically signiﬁcant and, in contrast to DVRs, SUVs are

strongly affected by alterations of local perfusion, further

clariﬁcation is needed.

Concerning the tracer used in this study,

C-(⫹)-

McN5652 has been shown to be appropriate for the quan-

tiﬁcation of SERT availability in brain regions with high

SERT density, such as the mesencephalon, basal ganglia,

and thalamus (7,20,21,34,35). The limitations of

C-(⫹)-

LONG-TERM EFFECTS OF “ECSTASY” USE • Buchert et al. 381

McN5652 are focused on its relatively high nonspeciﬁc

binding and the slow kinetics.

High nonspeciﬁc binding of

C-(⫹)-McN5652 makes

examination of SERT in regions with relatively low SERT

density—such as the neocortex, for example—difﬁcult.

Therefore, these regions were not evaluated in this study.

In addition, within a reference tissue approach, high

nonspeciﬁc binding of

C-(⫹)-McN5652 makes careful

selection of an appropriate reference region necessary to

estimate speciﬁc binding. In this study, according to Parsey

et al. (20), the gray matter of the cerebellum was used as the

reference region. The suitability of the cerebellum as the

reference region is evident because of its relatively large

size combined with its relatively high perfusion. This makes

reproducible generation of time–activity curves with sufﬁ-

cient counting statistics possible. The disadvantage might

be a small amount of speciﬁc tracer binding in the cerebel-

lum (19). Alternatively, Buck et al. (21) used the white

matter as the reference region. However, this may lead to

increased variance and, therefore, decreased separation

power. A further approach to estimate nonspeciﬁc binding is

the use of the pharmacologically inactive enantiomer

C-

(⫺)-McN5652 (7,36). This approach is controversial in

recent literature. Blocking experiments revealed a signiﬁ-

cant nondisplaceable difference between the total DVs of

both enantiomers (20).

The relatively slow kinetic of

C-(⫹)-McN5652 requires

long acquisition times. In our study the acquisition time of

the dynamic emission scan was limited to 90 min. A longer

acquisition would be hardly acceptable for most subjects

and would lead to an increased probability of motion arti-

facts because motion during a frame cannot be removed in

sinogram mode (compared with list mode). In addition,

using 2-dimensional sampling, the counting statistic is not

acceptable in very late frames. According to the results of

both Parsey et al. (20) and Buck et al. (21), there is no

signiﬁcant systematic bias of kinetic parameters at acquisi-

tion times of ⬎80 min. However, statistical power may be

limited to some extent. Parsey et al. reported a dispersion of

20% at 90-min acquisition time (dispersion ⫽ SD of distri-

bution volume expressed as percentage of the reference

value obtained with 150-min acquisition time). However,

reference tissue methods are generally assumed to be less

sensitive to statistical errors than complete invasive model-

ing (see below).

The problem of counting statistics in 2-dimensional mode

acquisition at late times can be overcome by using the

F-labeled S-ﬂuoromethyl analog of (⫹)-McN5652 (37)

because of the much longer half-life of

F compared with

that of

C (110 min vs. 20 min). On the other hand, the

better counting statistics of the S-ﬂuoromethyl analog is

accompanied by an 8-fold lower binding afﬁnity to the

SERT (37). Therefore, the use of SERT radioligands devel-

oped recently, which provide both fast kinetics and low

nonspeciﬁc binding, might be more appropriate.

Concerning the injected tracer mass, the number of re-

ceptors occupied by the tracer should be kept very low to

fulﬁll the requirements of conventional modeling ap-

proaches (linear, ﬁrst-order kinetics, that is, the tracer con-

centration available for binding should be signiﬁcantly be-

low the K

⫽ 0.4 nmol/L of unlabeled (⫹)-McN5652

needed to displace 5-HT from the SERT (38). Due to

continuous improvements in the tracer synthesis, which

resulted in permanent increase of speciﬁc activities injected,

there were signiﬁcant differences between the different

groups regarding the amount of (⫹)-McN5652 injected

(Table 4). This is explained by the sequence of admission of

the groups to the study. On average, ecstasy users were

investigated before control subjects and polydrug users. To

exclude potential systematic errors due to different amounts

of (⫹)-McN5652, linear regression analysis was performed

between the DVR and the injected mass in the group of

drug-naive control subjects, which did not reveal signiﬁcant

correlation (DVR[mesencephalon] ⫽ 0.0004 ⫻ injected

mass [nmol] ⫹ 1.2207; P[slope] ⫽ 0.72).

Head movement minimization was achieved by a ther-

moplastic mask immobilization system, and the remaining

head movement during the dynamic acquisition was com-

pensated using the Realign-Tool of SPM. The maximum

motion correction required was 3.4 ⫾ 2.0 and 2.6 ⫾ 2.5 mm

in the axial and the transaxial direction, respectively. How-

ever, all correction was limited to the emission scans; sub-

ject motion between the attenuation correction scan and

dynamic emission scans was not compensated. Andersson

et al. (39) demonstrated that a horizontal (x-direction) trans-

mission–emission mismatch of 5 mm causes errors of up to

10% in cortical regions of interest in H

O PET studies of

adult subjects. However, the effects of transmission–emis-

sion mismatch are certainly smaller in the central structures

examined here and, to some extent cancel, when VOIs in

both hemispheres are averaged.

There are several methods to determine the DVR of

C-(⫹)-McN5652 in the human brain. These methods can

be divided into 2 major classes: invasive methods, which

require the arterial input function; and noninvasive refer-

ence tissue methods, in which the time–activity curve of a

receptor-free reference region plays the role of the input

function.

In our study, the Ichise noninvasive plot was applied for

the determination of the DVR of

C-(⫹)-McN5652. This

approach yields estimates that are independent of regional

cerebral blood ﬂow and peripheral clearance of the tracer, as

has been shown by simulation studies (23). In healthy

volunteers, Buck et al. (21) found a high correlation of the

DVR obtained from the Ichise noninvasive plot and the DV

in the receptor compartment computed by application of the

invasive 2-compartment model approach.

The Ichise noninvasive plot has some advantages com-

pared with invasive methods. Acton et al. (40), who recently

quantiﬁed the SERT in baboons using the new SERT

SPECT ligand

123

I-ADAM, found that the test–retest reli

382 THE JOURNAL OF NUCLEAR MEDICINE • Vol. 44 • No. 3 • March 2003

ability was much better for the Ichise plot than for full

kinetic modeling (5.4% vs. 14.5%). Therefore, small

changes in SERT availability might be detected more reli-

ably by the Ichise noninvasive plot than by application of

invasive methods. This is particularly important because of

the limited sensitivity of in vivo imaging approaches for the

detection of changes of SERT. In addition, the Ichise non-

invasive plot can be easily applied on a voxel-by-voxel base

to generate parametric images. This allows quality control

by visual inspection of the images and the application of

voxel-wise statistical analysis using SPM for exploratory

evaluation beyond hypothesis-driven VOI evaluation—that

is, without an a priori selection of regions. Finally, nonin-

vasive methods in general improve compliance of the sub-

jects because arterial blood sampling presents a signiﬁcant

discomfort to most people.

The main disadvantage of the Ichise noninvasive method

is the vulnerability of its DVR estimate with respect to

variations of the nondisplaceable component of the tracer

distribution—that is, free tracer and nonspeciﬁcally bound

tracer. To attribute detected group differences to different

SERT availability, it must be assumed that there is no

intergroup difference of the nondisplaceable tracer distribu-

tion. To some extent this assumption is supported by the fact

that there was no difference in group means of the DVR in

white matter, which is devoid of SERT.

When comparing the DVR obtained in this study with

previous results, it is noted that there is no consistency in the

reported values of normal DVR. For example, using an

invasive 1-compartment, 3-parameter model, Parsey et al.

(20) found the thalamus-to-cerebellum DVR to be 1.9 and

Buck et al. (21) found the ratio to be 1.8, whereas Szabo et

al. (35) found the ratio to be 4.3 (the DVR was computed

using uncorrected DVs from Table 2). In this study, using

the noninvasive Ichise plot, the mean DVR in the thalamus

was 1.4, which is lower than all of the cited values. This

ﬁnding may be explained by several different factors. First,

there could be a systematic underestimation of the DVR

because of the use of a graphic reference tissue approach.

This is supported by the results of Acton et al. (40), who

found that the noninvasive Ichise plot indeed produced

some bias by slightly underestimating the DVR compared

with the invasive full kinetic model. Underestimation of the

DVR and DVs has also been observed for graphic methods

other than the Ichise noninvasive plot. In the case of the

Ichise noninvasive plot, singular value decomposition of the

coefﬁcient matrix of the operational equation yields very

large condition numbers. This indicates that the underesti-

mation of the DVR is related to effects of statistical noise.

Therefore, stable application of the Ichise noninvasive plot

might require some kind of regularization that could be

obtained by positivity constraints, for example.

A second factor causing rather low DVRs might be the

reconstruction algorithm used. Parsey et al. (20) performed

reconstruction by ﬁltered backprojection (FBP), whereas in

our study iterative OSEM reconstruction was used. Be-

langer et al. (41) investigated the effect of FBP versus

OSEM on the binding potential of the 5-HT

receptor

ligand

C-WAY-100635 computed by application of an

invasive 3-compartment model in the dorsal raphe nucleus

in 3 healthy volunteers. Compared with FBP, OSEM recon-

struction produced a binding potential that was 28% ⫾ 9%

lower. However, this decrease in binding potential was

accompanied by 17% ⫾ 19% improvement in goodness of

ﬁt as measured by the residual sum of squares.

In addition, DVRs might be affected by the recovery

effect due to the ﬁnite spatial resolution of PET. Parsey et

al. (20) speciﬁed in-plane resolution of 6.0-mm FWHM at

the center of the ﬁeld of view. In our study, in-plane

resolution was about 9-mm FWHM. Therefore, recovery

effects are expected to be larger in this study and to affect

all regions with at least 1 linear dimension smaller than 27

mm (3 times FWHM).

Finally, DVRs are affected by the deﬁnition of VOIs. In

this study, VOIs were predeﬁned in the template. To guar-

antee reproducible results no manual adjustment was per-

formed in individual images. If VOIs are drawn manually in

PET images, one tends to place the VOIs in regions with

maximum tracer uptake. However, the effects of residual

mispositioning of the predeﬁned VOIs in individual PET

images after stereotactic normalization were estimated by

reprocessing the data with the hottest voxel analysis of large

VOIs (results not shown). Large VOIs were predeﬁned in

the template such that the whole structure of interest, but no

other gray matter structure, was included in the VOI. Large

VOIs were then evaluated by the hottest voxel analysis

(mean value of the hottest voxels), where the number of

hottest voxels was taken to be the number of voxels of the

corresponding small VOI composed of circles (Fig. 1).

Statistical analysis of the hottest voxel data conﬁrmed the

results of the statistical analysis of the circles-VOI-data.

Neglect of the vascular contribution to time–activity

curves within reference tissue methods is expected to cause

only minor systematic errors.

CONCLUSION

Our ﬁndings yield further evidence for ecstasy-induced

protracted alterations of the brain serotonergic system that

last at least several weeks. Subjects who match ecstasy users

with respect to the use of psychoactive drugs other than

ecstasy, but do not use ecstasy, are more appropriate for the

evaluation of ecstasy-induced long-term effects than drug-

naive control subjects. Finally, our results might indicate

reversibility of the availability of SERT as measured by

PET, which, however, does not imply full reversibility of

neurotoxic effects. To further elucidate this question, fol-

low-up examinations of MDMA users might be useful.

ACKNOWLEDGMENTS

We thank Prof. Dr. Jo¨rg van den Hoff for his support in

modeling. The study was supported by the Federal Institute

LONG-TERM EFFECTS OF “ECSTASY” USE • Buchert et al. 383

for Drugs and Medical Devices (FZ: Z12.01–68503–206),

Germany.

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