FDG-PET in never-previously medicated psychotic adolescents treated with olanzapine or haloperidol

94 (2007) 293–305www.elsevier.com/locate/schres

Schizophrenia Research

FDG-PET in never-previously medicated psychotic adolescentstreated with olanzapine or haloperidol

Monte S. Buchsbaum ⁎, M. Mehmet Haznedar, Jonathan Aronowitz, Adam M. Brickman,Randall E. Newmark, Rachel Bloom, Jesse Brand, Kim E Goldstein,

Desmond Heath, Meghan Starson, Erin A. Hazlett

Department of Psychiatry, Mount Sinai School of Medicine, New York, NY 10029, USA

Received 17 December 2006; received in revised form 6 April 2007; accepted 12 April 2007Available online 15 June 2007

Abstract

We acquired Positron emission tomography with 18-F-deoxyglucose (FDG-PET) and anatomical MRI in 30 never-previouslymedicated psychotic adolescents (ages 13–20). (FDG-PET) was obtained at baseline and after 8–9 weeks of a randomized double-blind trial of either olanzapine or haloperidol. Neuropsychological tests of executive function were also obtained. Patients carriedout the serial verbal learning task, a modification of the California Verbal Learning Test, during the uptake of the FDG. PET scanswere coregistered with spoiled gradient MRI (TR=24, TE=5, flip angle 40°, slice thickness 1.2 mm, field of view 230 mm) foraccurate anatomical identification of regions of interest traced on the MRI. Twenty-two of the thirty patients completed the secondPET and clinical evaluation. Individuals treated with olanzapine increased relative metabolic rates in the frontal lobe more than theoccipital lobe while patients treated with haloperidol failed to increase frontal metabolic rates and did not show an anteroposteriorgradient in medication response. Haloperidol increased striatal metabolic rate more than olanzapine. Both drugs increased thalamicmetabolic rates and this increase was significantly larger in younger (age 13–15) than older (16–21) patients.© 2007 Published by Elsevier B.V.

Keywords: Schizophrenia; Neuroleptic; Early onset; Hypofrontality; Thalamus; Striatum

1. Introduction

Only a few typical and atypical neuroleptics havebeen characterized with FDG-PET. These studies havewell demonstrated the sensitivity of the FDG method toneuroleptic effects and differential effects of thiothix-ene, haloperidol and clozapine (Bartlett et al., 1991;Buchsbaum et al., 1992a; Buchsbaum et al., 1992b;

⁎ Corresponding author. Mount Sinai School of Medicine, 1 GustaveLevy Place, Box 1505, New York, NY 10029, USA.

E-mail address: [email protected](M.S. Buchsbaum).

0920-9964/$ - see front matter © 2007 Published by Elsevier B.V.doi:10.1016/j.schres.2007.04.027

Cohen et al., 1997; Holcomb et al., 1996; Potkin et al.,1994). The effect of conventional neuroleptics such ashaloperidol has primarily been to raise metabolic rates inthe striatum (Buchsbaum et al., 1992b; Desco et al.,2003; Holcomb et al., 1996), perhaps normalizing therelatively low metabolic rates reported in unmedicatedpatients with schizophrenia (Buchsbaum et al., 1999;Shihabuddin et al., 1998).

Greater increases in regional cerebral blood flow(rCBF) in the ventral striatum with haloperidol thanclozapine (Lahti et al., 2003) or olanzapine (Lahti et al.,2005) have been observed. Similarly haloperidol wasassociated with a greater increase in rCBF in the left

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http://dx.doi.org/10.1016/j.schres.2007.04.027

294 M.S. Buchsbaum et al. / Schizophrenia Research 94 (2007) 293–305

putamen than risperidone (Miller et al., 2001), and whilehaloperidol increased metabolism in the basal ganglia(Desco et al., 2003), a similar increase with olanzapinewas not observed (Molina et al., 2005). Medicated pa-tients tend to show higher caudate metabolism thancontrols (e.g. Fujimoto et al., 2007). We also observedthat clinical response to haloperidol was predicted bylow metabolic rates in the striatum (Buchsbaum et al.,1992b).

These studies have primarily assessed chronically illadult patients at a limited number of regions. FDGresponse to neuroleptics has not been studied inadolescents or in never-previously medicated patients.Since adolescents with early onset of schizophrenia maybe among the most severely ill and have relatively pooroutcome, the understanding of mediation effects is par-ticularly important. FDG studies have also been limitedbecause they have not investigated caudate/putamen anddorsoventral gradients despite the recognition (Nord-strom et al., 1993) the importance of these areas and thefinding of a dorsolateral/ventromedial gradient in D2receptors in human postmortem material. Our own datasuggest that clozapine may have more of an effect in theventral caudate and putamen (Potkin et al., 1994); bothdorsal/ventral and anterior/posterior dimensions areimportant in differentiating clozapine and haldoperidoleffects in never and once-medicated patients.

Although FDG cannot reveal functional changes thatare specific to dopamine, the nonspecific summaryinformation provided by glucose is valuable. Dopamineligand studies reveal dramatic changes in receptorfunction that occur within hours. It is well known,however, that the clinical effectiveness of neurolepticmedications generally takes 2 weeks or more to becomeapparent. Thus, effects downstream of the immediatedopamine-receptor blockade are undoubtedly important,and FDG-PET studies offer a possible window into theselater changes. Supportive of this view is that schizophre-nia with onset under age 18 shows many of theneuroimaging abnormalities found in older adult patients:ventricular enlargement, reduction in total brain andthalamus volume, changes in temporal lobe structures,and reductions in frontal metabolism (Hendren et al.,2000). Patients with childhood onset schizophrenia alsoshowed middle and superior frontal gyrus metabolicreductions, consistent with adult findings (Jacobsen et al.,1997). Lastly, significant correlations between dopamine-receptor occupancy and glucose metabolic rates havebeen found (Volkow et al., 2001).

In acute deoxyglucose studies in the rat, olanzapine,unlike haloperidol, significantly blocked the increased 2-deoxyglucose uptake with ketamine in the medial frontal

cortex and basolateral amygdala (a regionwith prefrontalconnections) (Duncan et al., 2000), although both drugsperformed similarly in chronic treatment studies (Dun-can et al., 2003). Differences between the effects ofclozapine and haloperidol were not prominent in 2-deoxyglucocose studies of acute metabolic change(Wotanis et al., 2003), but we were intrigued by thefinding that haloperidol, but not the atypical drugclozapine, significantly lowered frontal cortex 2-DGuptake while clozapine but not haloperidol significantlyaffected medial dorsal nucleus 2-DG uptake. Further,both drugs, in acute as well as chronic administration,affected most thalamic nuclei, suggesting the importanceof the thalamus in neuroleptic response.

The human and animal data clearly indicate markedeffects of neuroleptics on regional metabolic rates. In thisstudy we tested the following hypotheses in our sampleof never-previously medicated psychotic adolescents: 1)atypical neuroleptics such as olanzapine may normalizefrontal cortical activity more than typical neurolepticswhile sensory cortex may show no differential, 2) relativemetabolic rate in the striatumwill be higher on haloperidolthan olanzapine and this pattern will follow dorsoventralgradients in D2 receptors, 3) striatal metabolic rates atbaseline will predict clinical response, 4) metabolic ratesin the thalamuswill show differentmetabolic rate changeswith olanzapine and haloperidol, 5) motor and somato-sensory cortex may show more effect of haloperidol thanolanzapine, and 6) superior temporal gyrus (BA 22) willbe sensitive to drug effects since changes in this area areprominent in both activation and volumetric studies(Shenton et al., 2001).

2. Methods

2.1. Subjects

We imaged 30 never-previously neuroleptic medicat-ed psychotic adolescents, aged 13–21 (16 men, 14women, mean age 16.2±2.0). All the patients wererecruited among referrals from Mount Sinai HospitalEmergency Room Services, Adolescent Health Center,Child and Adolescent Outpatient Services and Psychiat-ric Inpatient Services. Initially, clinicians who were notrelated to the project assessed the patients as havingpsychotic symptoms and referred them for treatment withantipsychotic medications. Within the first week of theirenrollment in the study, patients were assessed with theCASH (Andreasen et al., 1992a) for diagnosis. Patientswere scanned as part of a brief inpatient stay afterdiagnostic procedures. PETandMRI were typically doneon successive days. All of the patients at least met

295M.S. Buchsbaum et al. / Schizophrenia Research 94 (2007) 293–305

diagnostic criteria for Psychosis NOS according to DSM-IV. At the end of the 6-month outpatient treatment period,patients who were diagnosed as Psychosis NOS at studyentry were reassessed by CASH and a final diagnosis wasestablished. Among the 22 completers (8 females, 14males), 9 patients initially received a diagnosis ofPsychosis NOS. At the end of their enrollment 14patients met DSM-IV criteria for Schizophrenia (7women, 7 men), 2 (males) for Schizoaffective Disorderand 4 (1 woman, 3 men) for Bipolar Affective Disorder.Four of the nine patients who had an initial diagnosis ofPsychosis NOSwere later diagnosed as Bipolar AffectiveDisorder, 1 as Schizoaffective Disorder and 3 asSchizophrenia. Patients were relatively ill (total mean18-item Brief Psychiatric Rating Scale (BPRS)score=50.4, SD=11.1). Patients received brain imagingand baseline assessment before random assignment tohaloperidol or olanzapine (up to 20 mg/day of either).Medication was titrated by a physician without knowl-edge of which drug was being administered. A secondPETscan was administered after 8–9 weeks of treatment.Twenty-two patients completed the second PET scan;changing residence, subsequent decision to remainunmedicated, lack of improvement, drug side effects,and concern about radiation effects led to patient drop-out. These patients had a similar age (15.7, sd=1.60) andillness severity (BPRS total 48.7, sd=9.1) to the entiresample. For some analyses patients were divided intoyoung (13–15) and old (16+) groups based on themedianage.

2.2. PET and MRI acquisition protocols

2.2.1. Image acquisitionPET scans (20 slices, 6.5-mm thickness) were

obtained (Hazlett et al., 1999) with a head-dedicatedGE scanner (model PC2048B) with measured resolutionof 4.5 mm in plane (4.2–4.5 mm across 15 planes). T1-weighted axial MRI scans were acquired with the GESigna 5× system (TR=24ms, TE=5ms, flip angle=40°,slice thickness=1.2 mm, pixel matrix=256×256, fieldof view=23 cm, total slices=128).

2.2.2. PET [18F]-fluorodeoxyglucose (FDG) uptaketask and procedure

Before the procedure, participants were read standardinstructions about the serial verbal learning task (SVLT)(Hazlett et al., 1998a), which was developed for the 32-minute FDG-uptake period and is analogous to theCalifornia Verbal Learning Test (Delis et al., 1987).Scores were recorded for total number of correctlyrecalled words, recall by semantic clustering, recall by

serial ordering, intrusions (words not in the list), andperseverations (repetition of a correct word on the sametrial). All patients were actively engaged in the SVLTtask (number correct 8.64, sd=2.8) during FDG uptake.

2.2.3. PET and MRI coregistrationThe PET and MRI scans were obtained in the axial

plane (canthomeatal line) through use of the sameindividually molded thermoplastic head holder. MRIswere resectioned to standard Talairach–Tournoux(Talairach and Tournoux, 1988) position. PET-MRIcoregistration used the algorithm of Woods et al.(Woods et al., 1993). Brain edges were visually tracedon all MRI axial slices. Inter-tracer reliability on 27individuals is 0.99 for area.

2.3. Segmentation

For gray matter, white matter and CSF quantification,the coronal images are segmented into gray matter, whitematter, and CSF using cutoff values individually deter-mined in each subject by examining thewithin-brain-edgehistogram of axial MRI values and choosing the lowestfrequency between white and gray and gray andcerebrospinal fluid. Validity tests of this method havebeen described elsewhere (Buchsbaum et al., 2002).

2.4. ROI selection and definition

2.4.1. Rationale for ROI methodsWe hypothesized dorsolateral and orbitofrontal cortical

effects of olanzapine and haloperidol might differ, makinga division of the frontal lobe into Brodmann regionsimportant. In order to contrast cortical areas, discreteanatomical areas needed to be identified and mean relativeuptake determined. The stereotaxic Brodmann approachyields appropriate data for these analyses. Second, wehypothesized a difference in striatal activation betweenolanzapine and haloperidol. For replication by othercenters and comparison with other literature, we chose toassess relative metabolic rate at specific x, y, z Talairachcoordinates (2.4.3). Since these coordinates were located atapproximately the stereotaxic centroid of structures, errorsassociated with stereotaxis, and biases of a structure'sshape were present. This was evaluated by also usingindividually traced striatal outlines on MRI applied to thePET. These outlines are laborious and less likely to be usedin the same way by other groups than the stereotaxiccoordinates, but they have value as an additional validitymeasure. Lastly, we used exploratory significance proba-bility mapping (2.5.2) to survey the entire brain to detectareas significant but not included in our specific


hypotheses and for comparison with other reports in thisfield.

2.4.2. Brodmann's area measurements and tissue typequantification

Perry et al. (unpublished) provided a coronal atlas,composed of 33 axial maps of Brodmann's areas (BA),based on microscopic examination of an entire hemi-sphere of a postmortem brain. Our earlier use of the Perryatlas (Hazlett et al., 1998b; Simeon et al., 2000; Steinet al., 1998) describes the method in greater detail.Coronal slices perpendicular to the anterior commis-sure–posterior commissure line were reconstructed in a256×256 pixel matrix. First we determined the front(first slice containing the cortical ribbon) and back of thebrain (last slice containing the cortical ribbon), and wethen identified 33 evenly spaced slices such that the firstslice began 1/34th of the distance from front to back. Foreach temporal lobe, we identified the temporal pole andthe most posterior extent of the Sylvian fissure, and wedivided the space into 13 equally spaced slices. The brainedge was obtained on the 33 non-temporal slices and 26(13 in each hemisphere) temporal slices by depositingpoints visually on the tips of the gyri and then fitting aspline curve to the points. Each slice was then dividedinto 20 radial sectors on each hemisphere surface and 10midline sectors (Hazlett et al., 1998b). Brodmann's areaswere then assessed for the gray, white and CSF pixelswithin each sector (see segmentation method below);means are weighted according to the number of sectors ineach region of interest and proportionately combined toobtain a single measure. Some of the smallest Brod-mann's areas are combined (e.g. 3–1–2–5) for conser-vative simplicity. Data from 39 Brodmann's areasidentified by Perry (1–2–3–5, 4, 6, 8, 9, 10, 11, 12,17, 18, 19, 20, 21, 22, 23, 24, 25, 27, 28, 29, 30, 31, 32,34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 7aand 7b) were obtained.

2.4.3. Subcortical gray and frontal regions by stereotaxisFor the first set of analyses, we located regions in

advance of any analysis (specific inspection of Talairachand Tournoux coordinates in the Talairach–Tournouxatlas and their coordinates recorded (thalamus: two slicelevels for the thalamus (z=12 and z=4) and coordinatesfor the dorsal and ventral slice, respectively, for theanterior (7,−4 and 7,−10), medialdorsal (7,−14 and 9,−15) and pulvinar (13,−26 and 16,−25) nuclei of thethalamus. The y-coordinate sign was changed to positivefor the opposite hemisphere. For the dorsal caudate(Talairach 11,11,12) and putamen (Talairach 23,0,12) weused coordinates obtained the same way and published

earlier (Buchsbaum et al., 2006b). For the ventral striatumand globus pallidus we used caudate: 7,14,−4, putamen:20,10,−4 and globus pallidus:15,−2,−4 with the caudateand putamen as used earlier (Buchsbaum et al., 2006b).

A square region of interest (ROI) (3×3 pixels) wasapplied centered on each set of coordinates and at theproportion as the brain-bounding box in the Talairach–Tournoux atlas. An adjustment was made so that ROIswere moved closer to the centroid of the slice if the boxfell partly outside the coregistered brain outline, ascould happen in brains that were especially narrow inthe x direction for boxes placed at 45° and 135°. For thesecond confirmatory approach, we used Talairach andTournoux coordinates selected from the literature.

2.4.4. Caudate and putamen assessedwith traced templateWe determined the top of the caudate and putamen as

the most dorsal axial slice showing a visible gray patchand the bottom as the slice in which the caudate andputamen are entirely merged. An automated boundary-findingmethod based on the Sobel gradient filter providesa reproducible structure edge, with little operatorvariability (Shihabuddin et al., 1998). The caudate andputamen were outlined on the MRI by depositing pointsby mouse on the magnified and enhanced white structureedge using a semiautomated 3×3 local pixel maximumsearch. This placed the point at the center of the edge,enhancing interoperator consistency. A spline curve wasfit to the points and the ROI edge stored. Two tracers'independent tracings of 10 subjects yielded ICC of 0.92for the caudate and 0.98 for the putamen area. Glucosefrom the coregistered PET was obtained for five equalventrodorsal segments by interpolation. Caudate andputamen values were entered into ANOVA as above withstructure (putamen, caudate), hemisphere (right, left) andventrodorsal position (1 through 5) and time as repeatedmeasures.

2.5. Measurement methods

2.5.1. Metabolic activity measurementThe whole brain volume derived from the tracings for

the Brodmann cortical divisions was used to computemean brain activity when applied to the FDG-PET scansand all measurements entered into statistical analysiswere divided by this mean to yield relative brain activity(global scaling). Brain edges were visually traced on all33 MRI slices. Inter-tracer reliability on 27 individualsis 0.99 for area. In one person a small portion of theextreme ventral portion of the temporal lobe wasmissing from the FDG-PET and any analyses includingthe temporal lobe omitted this person.


2.5.2. Exploratory significance probability mappingTo provide a pixel-by-pixel analysis of the striatum

and allow exploration of lateral/medial gradients withinstructures, we carried out voxel-by-voxel t-tests on thesame brain slices assessed by the stereotaxic ROImethod. The significance probability mapping tech-nique is similar to other approaches (Bartels andSubach, 1976) but uses MRI-edge-based spatial nor-malization (Buchsbaum et al., 1999). PET images forbaseline and drug were coregistered to the same MRI,similarly standardized, and between-groups t-testscarried out for drug-baseline difference scores. Toconfirm our analysis, using specific ROIs selected inadvance, of differential striatal response with haloper-idol and olanzapine, we present these images thre-sholded at pb0.05 and with a color bar showingcontinuous values to pb0.005. Since repeated measuresANOVA has greater statistical power due to theinclusion of right and left hemisphere, caudate andputamen, dorsal and ventral values, it did not seemappropriate to present only pb0.005 voxel-by-voxeltests for comparison with more powerful and hypoth-esis-driven methods.

2.6. Statistical design

We used three statistical approaches, a priori se-lection of ROIs (Buchsbaum et al., 2001), confirmatorytesting of previously reported coordinates or structures(Shihabuddin et al., 2001), and exploratory significanceprobability mapping. The selection of Talairach coordi-nates of specific regions has the advantage of compa-rability with other significance probability mapspublished and other investigators being able to easilyreplicate findings. Second, we traced the caudate andputamen on consecutive coregistered MRI axial slices.Traced areas integrate over the entire structure, reducingnoise, and use a highly accurate method independentof shape normalization, although they are more dif-ficult for other investigators to replicate and lesscomparable to significance probability map coordinates.Lastly we used exploratory significance probabilitymapping to assess the striatum, globus pallidus andsurrounding structures. Within the traced areas, thiswould explore whether subregions of the caudate orputamen were areas of particular significance, allowinghypotheses built on topographic organization of thestriatum and its relationship to the cortex to bedeveloped.

The design included drug (olanzapine, haloperidol)as an independent group factor and three repeatedmeasures factors, time (baseline, 8 weeks), hemisphere

(right, left) and structure (e.g. frontal and occipitalareas). A 2×2×2×2 repeated measures ANOVA design(StatSoft, 2003) was applied to rGMR data obtainedfrom frontal, occipital, motor, cingulate, thalamic andstriatal ROIs. In some cases, a five-way ANOVA hadrepeated measures for BAwithin a lobe (e.g. BA 17, 18,19 in the occipital lobe), to compare dorsal and ventrallevels (e.g. in the striatum where D2 receptor gradientsoccur) or to add age (13–15 and 16–21) as a factor.

All statistical analyses involving repeated measureswith more than two levels used Greenhouse–Geisserepsilon corrections to adjust probabilities for repeatedmeasures F-values where there were up to two-wayinteractions; our program yielded only Rao's R forhigher-order interactions. Uncorrected, corrected, andMANOVA degrees of freedom are reported if indicated(more than two levels) and if significant. To detect thesource of significant interactions between group andhypothesized Brodmann area, we carried out ANOVAon each Brodmann area separately. Interactions in-volving adjacent slice level, coordinated or ROI ad-jacent in position (stereotaxic ROIs close to each otherwhere the difference in position was not interpretablesuch as two adjacent boxes in a single Brodmann areaof the cortex) were not followed up as they were notpart of our hypothesis or were neuroanatomically notimportant. Data were screened for non-normality and 7of 80 BA met the pb0.05 criteria for the Kolmo-gorov–Smirnov one-sample test, well within chancelevels.

The selection of x, y, z coordinates in advance ofanalysis we have termed the “reverse Talairach hypoth-esis-driven strategy” because rather than testing allcoordinates and recording the center of significantclusters, we begin with the coordinates of severalspecific anatomical areas and test those locations only.This was used for four reasons: (1) to minimize Type Istatistical errors inherent in exploring every pixel andto avoid requiring such a low p value that the effectsizes needed for significance are so large that majoreffects are missed; (2) minimize Type I error related toevaluating approximately 10-12 ROI areas in eachhemisphere through the use of multiway repeatedmeasures ANOVA and a single F-ratio test indicatingthe hypothesized time (baseline, 8 weeks) by drug(olanzapine, haloperidol) by region interaction; (3) tominimize Type II errors resulting from assessing smallindividual, potentially noisy ROIs and failing to observeorbitofrontal system-wide response by combining ROIs;and (4) to provide standard and known brain atlaslocations for replication. We also controlled for Type Ierror by not discussing main effects or interactions that


are not interpretable (e.g. main effect of slice level acrossstructures measured at multiple axial slice levels) orperipheral to our interest (main effect of hemisphereacross conditions). Our analysis is limited in power bythe sample size (n=22) and we therefore felt it wasespecially important to test coordinates either chosen inadvance or for replication from published studies.

3. Results

3.1. Clinical response

Both patients treated with olanzapine and haloperidolimproved significantly from baseline to week 8 andweek 20 on the BPRS (positive, negative, and totalsymptom scores). This was confirmed with a main effectof time (F=3.79, df=2,28, p=0.034), and a symptomscore× time interaction indicated that positive symp-toms were relatively more improved than negative onesfor the whole group (F=3.10, df=4,56, p=0.022). Nodrug× time or higher-order interaction was confirmed.Seventeen out of the 22 patients showed lower BPRStotal scores at 8 weeks, 7 of 10 haloperidol-treatedsubjects and 10 of 12 olanzapine-treated patients.Performance on the SVLT FDG-uptake task improvedbut not significantly (F=1.27, df=1,18, p=0.027 formain effect of drug on scores for number correct,perseverations, intrusions, semantic grouping and order

Fig. 1. Motor and sensory cortex are

in MANOVA; no exploratory t-test reached signifi-cance for either drug.

3.2. Motor and somatosensory sensory cortex(BA 4, 1–2–3–5, and 7)

Both medications increased metabolic rate in themotor and sensory cortex (main effect of drug F=6.18,df=1,20, p=0.022), but this increase was greater forhaloperidol than olanzapine (time by drug interaction,F=4.36, df=1,20, p=0.049) and there was no signif-icant interaction with Brodmann areas (Fig. 1). T-tests(pb0.05, 1-tailed for cortical increases) on all Brod-mann areas confirmed significant haloperidol increasesfor left motor and sensory cortex (BA 1–2–3–5, meanincrease 0.11, t=3.63, df=1,10, p=0.0023 and BA 7,mean increase 0.079, t=2.47, p=0.017) but no increasesin frontal or temporal areas. In contrast, for olanzapine,six cortical areas were increased, exclusively represent-ing areas in the frontal and temporal lobe (right BA 9,28, 36, and 46 and left BA 22 and 37, t=2.40, 2.37,2.65, 2.16, 2.06, 2.75, respectively). No motor orsensory cortex area was significant by post-hoc t-test.For the haloperidol group, increase in relative metabolicrate in motor/somatosensory cortex BA areas 1–2–3–5,4, 6, and 7 (right and left combined) was associated withbetter scores on BPRS positive, negative and total scores(r=−0.59,−0.64,−0.17, and −0.53, respectively). In the

as and response to medication.

Fig. 2. Frontal and occipital metabolic rate.


olanzapine group all correlations were opposite (0.46,0.51, 0.75, and 0.40, respectively) and all significantlydifferent from haloperidol. No other cortical areashowed significant correlations with BPRS changescores.

3.3. Dorsolateral frontal cortex and hypofrontality

Frontal cortex metabolism (BA 9, 46, 47) wasincreased by olanzapine but was slightly decreased byhaloperidol, while in the occipital cortex (BA 17, 18,19), haloperidol increased metabolic rate more thanolanzapine (Fig. 2). Thus olanzapine but not haloperidol

Fig. 3. Superior temporal gyrus (BA 22) relative metabolic rate is increas

was associated with a lessening of hypofrontality. Thiswas confirmed by a time (baseline, 8 weeks) by drug(haloperidol, olanzapine) by brain region (frontal,occipital) interaction (F=7.41, df=1,20, p=0.013).

3.4. Temporal lobe

The relative metabolic rate in the lateral (BA 20, 21,22) but not medial temporal lobe (BA 28, 36, 38) wasincreased by both haloperidol and olanzapine (Fig. 3)and this effect was most marked in BA 22, the region ofthe superior temporal gyrus (F=3.64, df=2,40,p=0.035; Wilks F=3.93, df=2,19, p=0.037).

ed by neuroleptics while rates in medial and inferior areas are not.

Fig. 4. Thalamus metabolic rate change with medication. Note that medial dorsal nucleus shows greatest increase with medication in younger patients.

Table 1Location of regions showing differential haloperidol/olanzapineeffects on exploratory analysis

Region x y z t #voxels p-value

Z=201. BA10 31 39 20 2.71 63 0.00622. Caudate 16 −11 20 −1.88 8 0.03853. Caudate −19 −8 20 −2.46 33 0.0110

Z=121. BA10 −22 58 12 2.40 51 0.01232. BA10 5 52 12 3.05 150 0.0029

Z=41. BA10 7 55 4 3.23 31 0.00202. BA10 −18 49 4 2.50 25 0.00993. BA32 5 45 4 2.50 55 0.00994. Putamen −18 13 4 −2.28 53 0.01615. Putamen 15 6 4 −3.35 62 0.0015

Z=−41. BA10 −15 50 −4 3.24 111 0.00212. BA47 −27 21 −4 2.85 53 0.00463. Caud/GP −10 5 −4 −2.46 50 0.0110

Location at cluster center is given in Talairach coordinates (see Fig. 5).Number of pixels in slice is count for above threshold.Maximum t value is highest t-value in cluster.


3.5. Ventral striatum and hippocampus

The relative metabolic rate increased in the ventralstriatum on haloperidol but decreased slightly onolanzapine (time by drug type interaction, F=4.37,df=1,20, p=0.049; from four-way ANOVA with time,drug type, structure (Talairach coordinates chosen arecaudate: 7,14,−4, putamen: 20,10,−4 and globus palli-dus:15,−2,−4 ) and hemisphere: × coordinate withreversed sign). Analyses containing both caudate and pu-tamen and dorsal and ventral levels were not statisticallysignificant. The differential effect of olanzapine andhaloperidol was strongest in the left putamen in youngerpatients (F=7.24, df=1,18, p=0.014; time by drug by ageby hemisphere interaction). No significant effects orinteractions were found for the hippocampus (Talairachxyz 22,38,4).

3.6. Traced caudate and putamen

Younger subjects (age 13–15) had greater relativemetabolic rate elevation in both caudate and putamenwith haloperidol (0.078±0.14 than olanzapine (0.011±0.15), and this medication difference was less marked inthe older sample (F=6.96, df=1,18, p=0.017 ). Greaterelevation of metabolic rate was found for the putamen(drug minus baseline, 0.062±0.14 than the caudate0.027±0.15, F=7.29, df=1,18, p=0.014). This caudatevs. putamen difference for haloperidol vs. olanzapinewas more prominent in the putamen (F=4.71, df=1,18,p=0.044) and at dorsal levels in the putamen (F=4.36,df=4,72, p=0.0032; MANOVA Wilks 0.39, F=5.97,p=0.0044).

3.7. Thalamus and age

Nuclear region and age were significant factors inthalamic change with medication (Fig. 4). The medialdorsal nucleus and anterior region was increased bymedication while the pulvinar was decreased, and thiswas more prominent in younger patients and in the left


hemisphere (time by thalamic region by age byhemisphere interaction, F=3.622, df=2,40, p=0.036).

3.8. Prediction of drug response

We examined the baseline FDG in the dorsal caudateand found that low metabolic rates in the caudatepredicted response to haloperidol on the BPRS totalscore (dorsal right caudate at baseline vs. BPRS total

Fig. 5. Exploratory Significance Probability Maps of differencebetween activity following haloperidol and olanzapine. Blue regionsare areas where haloperidol had a significantly greater activityelevation than olanzapine and red areas are where olanzapine had agreater effect than haloperidol. These voxel-by-voxel comparisons arebased on baseline (never-medicated) minus week 8 FDG-PET. Thecolor patches have a lower threshold at N1.70 (1-tailed) and the topvalue shown is truncated at N2.83 (pb0.005) so that the four slices canbe compared on the same scale. We identified regions (with whitenumbers) which were hypothesized in advance (striatum and frontalcortex) and which appear in the a priori selected stereotaxic regions.(see Table 1). For exploratory purposes, areas previously reported canbe evaluated at the uncorrected threshold of 1.70.

change r=−0.64, positive symptoms r=−0.76) whilehigh metabolic rates at baseline predicted response toolanzapine (r=0.41, Fisher z=2.23, pb0.05). For theright and left caudate and putamen, the multiple R was0.95 (F=14.0, df=4,5). For the ventral striatum, thecaudate and putamen were not significant for haloper-idol, but positive symptoms were predicted (r=−0.69)from baseline globus pallidus. In the ventral striatum,baseline left and right putamen relative metabolic ratespredicted improvement in negative symptoms (0.78, and0.79, respectively).

Because an association between high frontal metabolicrate and negative symptom improvement with anotheratypical neuroleptic, risperidone, has been reported(Molina et al., 2003b), we examined this correlation inthe olanzapine-treated patients and found a significantcorrelation of −0.70 between Brodmann area 8 baselinemetabolic rate and change in negative symptom BPRSrating. The correlation with Brodmann area 9 was −0.53(pb0.05, 1-tailed in replication) but −0.36 and −0.27 fororbitofrontal areas 11 and 12 (p=ns).

3.9. Exploratory analyses

Voxel-by-voxel maps were used to assess differences(baseline vs 8 weeks of medication) between haloper-idol and olanzapine. These maps (Fig. 4, Table 1)confirmed the finding of higher metabolic rates in thecaudate and putamen while on haloperidol-treatedpatients and higher metabolic rates in frontal cortex inolanzapine-treated patients.

4. Discussion

This is the first demonstration of a differential effect ofatypical and typical neuroleptics on the relative metabolicrates in prefrontal cortex in adolescents with psychosis inolanzapine treated patients. Low relative metabolic rateshave been widely observed in the prefrontal region(Andreasen et al., 1992b; Buchsbaum and Hazlett,1998), both with PET and SPECT, since the pioneeringwork of Ingvar and Franzen (1974) Normalizing effects ofneuroleptics on prefrontal activity were not observed withhaloperidol (Buchsbaum et al., 1992b) and no effects onFDG in the cortex were seenwith clozapine or thiothixene(Buchsbaum et al., 1992a). We found that clozapineactually lowered frontal FDG uptake with a larger sample(Potkin et al., 1994). The current findings of increasedprefrontal activity with olanzapine might reflect ourselection of the dorsolateral prefrontal region (Brodmannareas 9–46–47) for testing rather than the less precise ringmethod used in our earlier studies, the somewhat different


receptor profile of olanzapine, or the fact that all patients inthe current study were adolescent and drug-naïve. Acomparison of FDG-PET scans in patients treated withhaloperidol and risperidone (Miller et al., 2001) showed alowering of frontal relativemetabolic rate with haloperidoland little change with risperidone (no frontal regionillustrated showed significant increase). However, asignificant dorsolateral region (−19, 43, 30) in the sameregion as our own results showed that haloperidoldecreased blood flow to a greater extent than risperidone.An fMRI study of patients tested at baseline (Honey et al.,1999) on physician's choice typical neuroleptics and thenagain after substitution of risperidone also showed anenhancement of activation in prefrontal cortex withrisperidone. While this study did not have a medication-free baseline, the results were similar generally to our owncurrent study. A different result with risperidone wasfound in a study of eight previously unmedicated patientswith FDG-PET (Ngan et al., 2002); decreases in the lateraland orbital prefrontal cortex (largest effect in BA 47) wereobserved after 6 weeks of treatment. This decreaseresembles our own result with haloperidol rather thanthe atypical drug olanzapine (see Fig. 2). This discrepancymight relate to a greater propensity of adolescents toincrease prefrontal metabolic rates or to olanzapine/risperidone differences in prefrontal effects. The findingthat elderly schizophrenia patients over 65 had decreasedHMPAO uptake after 3 weeks of risperidone (Berman etal., 1996) indicates that differential effects of atypicalneuroleptics across the lifespan should be considered.Another study compared FDG-PET scans at baseline andafter six months of risperidone with patients chronicallytreated on haloperidol (Molina et al., 2003a) and foundhaloperidol associated with greater activity in motorcortex than risperidone, similar to our findings; however,prefrontal differences between risperidone and haloperi-dol were not observed.Note that no drug-free baselinewasavailable for the chronic haloperidol patients andrisperidone patients had received a few small doses ofhaloperidol in the days before their baseline scan.Olanzapine administration was not associated withcerebral metabolic change (Molina et al., 2005) followinga switch from conventional antipsychotics (12/17 cases onhaloperidol), but a lower p-value threshold was used in theexploratory analysis in this report.

The effect of haloperidol raising relativemetabolic ratein the striatum has been reported in a number of studiesreviewed earlier (Buchsbaum et al., 1992b). A greatereffect of haloperidol increasing relative blood flow in thestriatum than risperidone was also found in patients withschizophrenia (Miller et al., 2001). Detailed examinationof the significance probability maps suggests that rostral

putamen regions may show greater differences thancaudal regions. A rostralNcaudal gradient in D1 receptorsand caudalN rostral gradient for D2 receptors was found inhuman postmortem binding studies (Piggott et al., 1999),as well as animal (Rosa-Neto et al., 2004) and human PETbinding studies (Hirvonen et al., 2006), and olanzapinehas relatively less difference in receptor binding betweenD1 and D2 than haloperidol (Bymaster et al., 1996). Thegreater D1 activity of olanzapine than haloperidol is alsonot inconsistent with the differential frontal lobe activityobserved.

These results are consistent with a normalizationof prefrontal metabolic rate with olanzapine but nothaloperidol. Examination of individual differences sug-gests that typical neuroleptics may be of greater efficacyin patients with low metabolic rates in the striatum whileother patients may be more favorably affected byolanzapine. We observed that patients with low metabolicrates in the striatum responded to haloperidol in a double-blind crossover study (Buchsbaum et al., 1992b). We alsoobserved lower relative metabolic rate in the striatum atbaseline predicted clinical improvement on risperidone inpatients with obsessive–compulsive disorder who werenon-responsive to SSRI (Buchsbaum et al., 2006). Thus inthree independent studies, low metabolism in the striatumhas been associated with response to either the typicalneuroleptic haloperidol or risperidone. Haloperidol alsoreduced prepulse inhibition in a sensory gating paradigm,suggested to be an indicator of reduced prefrontaldopaminergic activity (Oranje et al., 2004).

The greater sensitivity of the thalamus to medicationeffects in younger patients might be associated withgreater sensitivity of our younger sample to the prefron-tal activating effect of olanzapine. Lower binding po-tential for D2 receptors in the thalamus in patients withschizophrenia has been found in several recent studies(Buchsbaum et al., 2006a; Talvik et al., 2003, 2006;Yasuno et al., 2004), suggesting the importance of thisregion for medication response.

Limitations of this study clearly include the smallsample size and loss of eight patients during the study.No significant differences in age or symptom profileemerged in contrasts of completers and dropouts, butunknown aspects of side effects or regional brain effectscould have played some role in this selection. Further, wedo not yet have an adult contrast group to specificallyexamine the effects of patient age. The full relationshipof this to long-range prognosis remains to be evaluated.

Other limitations include potential diagnostic hetero-geneity, since the final lifetime diagnosis of the patientsis not yet known, and the illnesses could be evolvingduring adolescence. Further, age-related variation might


increase variation in pharmacological response andobscure or distort some pharmacological effects (al-though the olanzapine and haloperidol groups wereequal in age). Stereotaxic error may contribute to Type IIerror in detecting medication effects, although previous-ly reported FDG-PET effects of haloperidol, andprediction of haloperidol response from baseline striatalrelative metabolic rate replicated both earlier humanstudies and animal DG studies, suggesting that stereo-taxic placement was sufficiently close to correctlyobserve striatal function. Changes in SVLT performanceseem unlikely to be related to the regional metaboliceffects observed since significant changes in perfor-mance were not observed.

Role of the funding sourceThis pharmacoimaging work was supported by an investigator-

initiated grant fromEli Lilly, and by grants from the National Center forResearch Resources (M01-RR-00071), and the National Institute ofMental Health for the study of schizophrenia (MH60023, MH56489,MH60384S). The study was designed by the first author and elementsof the data collection, analysis and presentation supported by thesesources. The authors worked together on the analysis of data. Thefunding sources all favored the authors in their efforts to report thescientific findings and we appreciate their flexibility and patience.

ContributorsMonte S. Buchsbaum designed the study, carried out the scans,

supervised image analysis, carried out statistical analysis, and drafted themanuscript. Ms. Mehmet Haznedar, Jonathan Aronowitz and DesmondHeath recruited, clinically assessed, and participated in patient care.AdamBrickman, Karen Dahlman and Rachel Bloom carried out neuropsycho-logical testing and patient assessment, Jessie Brand, Kim E. Goldstein,Randall Newmark and Meghan Starson carried out image and statisticalanalysis. Erin Hazlett, Randall Newmark, Adam Brickman, and MehmetHaznedar contributed to the writing of the manuscript.

Conflict of interestThe project data collection was partly supported by Eli Lilly and

Company.

AcknowledgementsThis work was supported by an investigator-initiated grant from Eli

Lilly, and by grants from the National Center for Research Resources(M01-RR-00071), and the National Institute of Mental Health(MH60023, MH56489, MH60384S). The study was designed by thefirst author, and elements of the data analysis and presentationsupported by these other sources. The authors have no financialinterest in the project outcome.

Dr. Richard Pico contributed to the initial planning of the project. Dr.Eileen DiFrancesco assisted in the recruitment of patients. This researchwas supported by a grant from the National Intsitute of Mental Health,Anatomy and function of the thalamus in schizophreniaMH60023, and byGeneral Clinical Research Center CRC grant # 5-M01RR00071. The datacollection was supported by an investigator-initiated grant from Eli Lillyand Company.

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FDG-PET in never-previously medicated psychotic adolescents treated with olanzapine or haloperidol