Measurement of GABAA receptor binding in vivo with [11C]Flumazenil: A test–retest study in healthy subjects

www.elsevier.com/locate/ynimg NeuroImage 41 (2008) 260 – 269

Measurement of GABAA receptor binding in vivo with [ 11 C]Flumazenil: A test–retest study in healthy subjects☆ Elina Salmi,a,⁎ Sargo Aalto,b Jussi Hirvonen,c Jaakko W. Långsjö,c Anu T. Maksimow,c Vesa Oikonen,d Liisa Metsähonkala,e Jussi Virkkala,f Kjell Någren,g and Harry Scheininh Investigator, Turku PET Centre, University of Turku and Department of Otorhinolaryngology — Head and Neck Surgery, Turku University Hospital, Finland Investigator, Department of Psychology, Åbo Akademi University and Turku PET Centre, University of Turku, Finland c Investigator, Turku PET Centre, University of Turku, Finland d Modeller, Turku PET Centre, University of Turku, Finland e Child Neurologist, Department of Child Neurology, Helsinki University Hospital, Finland f Department of Clinical Neurophysiology, Medical Imaging Centre, Pirkanmaa Hospital District, Tampere, Finland g Radiochemist, Turku PET Centre, University of Turku, Finland h Professor, Turku PET Centre and Department of Anesthesiology and Intensive Care, University of Turku, Finland a

b

Received 27 June 2007; revised 24 February 2008; accepted 26 February 2008 Available online 4 March 2008

[11C]Flumazenil is widely used in positron emission tomography (PET) studies to measure GABAA receptors in vivo in humans. Although several different methods have been applied for the quantification of [11C]flumazenil binding, the reproducibility of these methods has not been previously examined. The reproducibility of a single bolus [11C]flumazenil measurements was studied by scanning eight healthy volunteers twice during the same day. Grey matter regions were analyzed using both regions-of-interest (ROI) and voxel-based analysis methods. Compartmental kinetic modelling using both arterial and reference region input function were applied to derive the total tissue distribution volume (VT) and the binding potential (BP) (BPP and BPND) of [11C]flumazenil. To measure the reproducibility and reliability of each [11C]flumazenil binding parameter, absolute variability values (VAR) and intraclass correlation coefficients (ICC) were calculated. Tissue radioactivity concentration over time was best modelled with a 2-tissue compartmental model. VT showed with all methods good to excellent reproducibility and reliability with low VARs (mean of all brain regions) (5.57%–6.26%) and high ICCs (mean of all brain regions) (0.83–0.88) when using conventional ROI analysis. Also voxel-based analysis methods yielded excellent reproducibility (VAR 5.75% and ICC 0.81). In contrast, the BP estimates using pons as the reference tissue yielded higher VARs (8.08%–9.08%) and lower ICCs (0.35–0.80). In conclusion, the reproducibility of [11C]flumazenil measurements is considerably better with outcome measures based on arterial input function than those using pons as the reference tissue. The voxel-based ☆

From the Turku PET Centre and the Department of Anesthesiology and Intensive Care, Turku University Hospital, Turku, Finland. ⁎ Corresponding author. Turku PET Centre, PO Box 52, FIN-20521 Turku, Finland. Fax: +358 2 231 8191. E-mail address: [email protected] (E. Salmi). Available online on ScienceDirect (www.sciencedirect.com). 1053-8119/$ - see front matter © 2008 Elsevier Inc. All rights reserved. doi:10.1016/j.neuroimage.2008.02.035

analysis methods are proper alternative as the reliability is preserved and analysis automated. © 2008 Elsevier Inc. All rights reserved.

Introduction The benzodiazepine antagonist flumazenil labelled with carbon11 ([11C]flumazenil) is widely used in positron emission tomography (PET) studies to quantify the cerebral GABAA receptors in vivo in human. Because of its high specific to non-specific binding ratios with the regional uptake presenting the known distribution of benzodiazepine receptors in the brain (Möhler and Richards, 1981; Hunkeler et al., 1981), it is highly suitable for this purpose. [11C] Flumazenil has been used in several PET studies to quantify GABAA receptor binding in neurological and psychiatric disorders, such as epilepsy, stroke, congenital syndromes, anxiety disorders and dementia (Savic et al., 1988; Heiss et al., 1998; Lucignani et al., 2004; Malizia et al., 1998; Ihara et al., 2004). Recently, [11C] flumazenil binding has also been used to study the GABAergic effects of different anesthetics (Gyulai et al., 2001; Salmi et al., 2004; Salmi et al., 2005; Salmi et al., 2008). The binding of [11C]flumazenil has earlier been assessed as the total tissue distribution volume (VT) derived with the methods utilizing arterial input function (Holthoff et al., 1991; Koeppe et al., 1991; Ihara et al., 2004, Hammers et al., 2001; Hammers et al., 2005) or as the binding potential (BP) derived with methods using pons as the reference region (Millet et al., 2002; Lucignani et al., 2004). Although several studies have assessed different aspects of

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validity of single bolus injection [11C]flumazenil measurements (Holthoff et al., 1991; Koeppe et al., 1991; Lassen et al., 1995; Millet et al., 2002; Klumpers et al., 2005), the reproducibility and reliability of these methods have not been properly examined (Holthoff et al., 1991). The aim of the present study was to evaluate the reproducibility and reliability of single bolus [11C]flumazenil measurements in eight healthy male volunteers scanned twice during the same day. Region-of-interest (ROI) analysis with compartmental kinetic modelling using both arterial input function and reference region input were applied as well as voxel-based image analysis techniques with optimized preprocessing of imaging data. Materials and methods Human subjects Eight healthy subjects with no history of psychiatric disorder, somatic illness or substance abuse were included in the study. All were right-handed, non-smoking males with (mean ± SD; herinafter presented similarly) age of 24 ± 2.3 years. The height, weight and the body mass index were 181 ± 7 cm, 84.8 ± 8.5 kg and 26.0 ± 2.2 kg/m2, respectively. Laboratory data, physical examination and 12-lead ECGs were normal. In order to exclude any structural brain abnormalities and for anatomical reference, all subjects underwent a 1.5 T magnetic resonance imaging (MRI) scan (Siemens Magnetom, Siemens Medical Solutions, Erlangen, Germany). Subjects refrained from using alcohol, coffee or any drugs for 48 h before the study. The Hospital Ethics Committee approved the study protocol and all subjects gave written informed consent. This study was performed according to the Declaration of Helsinki. Left radial artery was cannulated for arterial sampling and one large vein of the right forearm for administration of [11C]flumazenil and physiological saline to keep the intravenous line open. Each subject underwent two [11C]flumazenil PET scans during the same day between 10.30 a.m. and 5.30 p.m., at least 2 h apart. While waiting for the second [11C]flumazenil PET scan, the subjects rested without any particular stimuli.

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tests on this camera indicate transaxial and axial spatial resolution (full width at half maximum) of 4.3 mm and 4.3 mm, respectively. Before each experiment, a 9-min transmission scan was performed with [68Ge] rod sources. All PET studies were performed in a dimly lit room with no sudden loud noises. The subjects kept their eyes shut during the scanning. A plastic head holder was used to minimize head movement. Two laser beams parallel to canthomeatal and sagittal lines were used in head positioning. To control any movement and assure the exactly same head position during both scans, several points were marked with ink on the facial skin of the subject. The ink markings were visually inspected every 5–10 min during the scans to ensure the accurate positioning of the head in the scanner. Heart rate, oxygen saturation and blood pressure were monitored throughout the study and they remained stable. An intravenous bolus of [11C]flumazenil was administered manually in 60 s and flushed with saline. The image acquisition was started at the same time with dosing and was performed for 60 min. The 26-frame sequence consisted of six 30-second frames followed by seven 1-min, five 2-min and eight 5-min frames. To obtain arterial input function for modeling, twenty-one arterial plasma samples were taken during the study (at 40 s, 50 s, and 1, 1.5, 2, 2.5, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 40, 50 and 60 min after the dosing of [11C]flumazenil) and analyzed with an automatic gamma counter (Wizard 1480; Wallac, Turku, Finland) cross-calibrated with the PET scanner. No blood volume subtraction was employed. Furthermore, seven arterial plasma samples (at 4, 10, 20, 30, 40, 50 and 60 min) were taken for flumazenil metabolite analysis. No fitting was applied to the metabolite curve. Plasma proteins were precipitated with acetonitrile containing flumazenil. The solution obtained after centrifugation was separated with reversed-phase HPLC and a gradient of acetonitrile in phosforic acid. The results were calculated as the fraction of decay corrected radioactivity in all peaks. The clearance of [11C]flumazenil was calculated as the injected dose divided by area under the metabolite-corrected arterial plasma time–activity curve and is expressed in L/h. ROI analysis

Radiochemistry of [11C]flumazenil [11C]Flumazenil was prepared by the reaction of [11C]methyl triflate and Ro 15-5528, followed by high performance liquid chromatography (HPLC) purification and formulation of the product according to a published procedure (Någren and Halldin, 1998). The radiochemical purity (N 99%) and the specific radioactivity of the product were determined using HPLC and UVdetection at 246 nm. [11C]Flumazenil was administered manually in 60 s. At the time of the administration the specific radioactivities were 37.66 ± 7.81 and 39.02 ± 7.09 MBq/nmol for test and retest scan, respectively. Injected doses were 247.21 ± 7.57 and 243.04 ± 7.32 MBq and masses 2.1 ± 0.4 and 1.9 ± 0.4 µg, respectively. There were no statistically significant differences in any of these parameters between the scans. Data acquisition PET experiments were performed using a GE Advance PET scanner (General Electric Medical Systems, Milwaukee, WI, USA) in 3D mode (septa retracted) with 35 slices of 4.25 mm thickness covering the whole brain. The basic performance characteristics

The dynamic [11C]flumazenil images were realigned (withinsubject) with parameters estimated from [11C]flumazenil summation images (frames 1–26) using Statistical Parametric Mapping (SPM) version 99 (Friston et al., 1995). The individual MRIs were coregistered using mutual information procedure to the withinsubject mean summation images calculated from the realigned images. ROIs were drawn using Imadeus software (version 1.15, Forima Inc, Turku, Finland) on the coregistered individual MRIs in the caudate (3 planes), putamen (3 planes), the medial and lateral thalamus (3 planes), pons (3 planes), the dorsolateral prefrontal cortex (4 planes), the medial part of the superior frontal gyrus (4 planes), the inferior, middle and superior temporal gyrus (4 planes), the posterior cingulate cortex (3 planes), anterior cingulate cortex (4 planes), the angular gyrus (3 planes), the supramarginal gyrus (3 planes), and the cerebral white matter (5 planes). The following ROI combinations were also examined: the angular gyrus and the supramarginal gyrus comprising the inferior parietal cortex and the inferior, middle and superior temporal gyrus comprising the temporal cortex. Mean tissue time–activity data for quantification was calculated from the realigned dynamic images for each ROI.

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Table 1 Summary of [11C]flumazenil binding parameters Estimate Method Abbreviation VT interpretation Kinetic interpretation VT-2TM VT-1TM VT-LOGAN BPP-2TM

VT VT VT

BPP

2TM 1TM Logan 2TM

BPND

2TM

BPND-2TM

VTROI
1 VND

k3/k4

VTROI
1 VND

k3/k4

VT

VTROI
VND

K1/k2(1 + k3/k4) K1/k2 N.A. K1k3/k2k4

cignani et al., 2004). Since some studies have used the white matter as reference tissue input (Savic et al., 1990; Magata et al., 2003), the applicability of this structure as a reference region was also considered in this study by calculating the VT-2TM of the white matter and the BPP and BPND estimates by using the 2TM and the white matter as the reference tissue. For a summary of the different [11C]flumazenil binding estimates, see Table 1. Voxel-based image analysis methodology

SRTM

BPND-SRTM

VT = total tissue distribution volume. BP = binding potential. 2TM = 2-tissue compartmental model. 1TM = 1-tissue compartmental model. SRTM = simplified reference tissue model. VND = distribution volume of the nondisplaceable tissue compartment. ROI = region of interest. K1 = rate constant for transit from plasma to tissue. k2 = rate constant for transit from tissue to plasma. k3 = rate constant for transit from free plus non-specific binding compartment to specific binding compartment. k4 = rate constant for transit from specific binding compartment to free plus non-specific binding compartment. N.A. = not applicable.

Quantification of [11C]flumazenil binding VT was estimated using metabolite-corrected arterial plasma time–activity curve as the input function. VT values were obtained both directly without division using a linearized method based on non-negative least squares optimization (Zhou et al., 2002; Zhou et al., 2003), and the graphical analysis for reversible binding by Logan (Logan et al., 1990; Logan et al., 1996), where the measured dynamic data is converted into a linear plot, the slope of which represents the VT: the latter measure of VT will be termed VT-LOGAN. A subset of 10–60 min were used to determine VT-LOGAN In addition, VT was calculated for the 1-tissue compartmental model (1TM) and 2-tissue compartmental model (2TM) (see Table 1) (Innis et al., 2007), and Akaike information criteria (AIC) were used to evaluate and compare goodness of fit between 1TM and 2TM. BP values were calculated in order to estimate the specific binding to receptors. BP represents the ratio of concentration of specific binding and a reference concentration at equilibrium (Innis et al., 2007). There are three commonly used BP estimates that differ in terms of the reference concentration used: BPF, BPP, and BPND are ratios of concentration of specific binding to free radioligand in plasma, total radioligand in plasma, and nondisplaceable (free plus non-specifically bound) radiotracer in tissue. BPF requires the measurement of the free fraction in plasma ( fP) and was thus not used in the current analysis. BPP and BPND values were calculated indirectly from regional VT values (Innis et al., 2007). BPP-1TM, BPP-2TM, BPND-1TM, and BPND-2TM represent BPP and BPND values calculated from VT-1TM and VT-2TM, respectively. BPND was also calculated with the simplified reference tissue model (SRTM), where a single-tissue compartmental model is used to describe tissue concentration in both target and reference regions (Lammertsma and Hume, 1996); these values are termed BPND-SRTM. Pons was used as the reference region for BP calculations, as many previous studies have done before (Millet et al., 2002; Lu-

Calculation of parametric images Parametric images were calculated representing the VT of [11C] flumazenil at voxel-level in native space. As the voxel-wise AIC favoured the 2TM (data not shown), this model was applied to calculation of the parametric images. [11C]flumazenil template Ligand-specific [11C]flumazenil template was created for spatial normalization of images according to previously presented procedure (Meyer et al., 1999). In brief, the template was generated from ten [11C]flumazenil scans included in a different study sample from the present study. First, individual MRIs were coregistered to summated [11C]flumazenil images and then MRIs were normalized using T1 weighted MRI template delivered with SPM99. Normalization parameters were finally used to create normalized [11C] flumazenil summated images written onto the template bounding box. In the template, we used summated images from all frames (1–26) as it yielded the most accurate normalization results when evaluated using intraclass correlation coefficient (ICC) criterion (data not shown). The [11C]flumazenil template image was calculated as a mean of these images. To assure the symmetry of the template, the mean image was left-right flipped (mirrored), and the template was calculated as an average image of original and flipped mean images. Finally, template was smoothed using 8 mm Gaussian kernel as 8 mm smoothing is used in SPM99 standard normalization estimation.

Fig. 1. Mean (SD) fraction of unchanged [11C]flumazenil values in arterial plasma in test scan (black squares) and retest scan (open squares). Fraction of unchanged [11C]flumazenil at 50 min and 60 min is not included as the total radioactivity at these time points is very low and data from all test and retest scans was not reliably achieved.

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Table 2 VT values and test–retest characteristics of [11C]flumazenil measurements using the 2TM model Brain area

Anterior cingulate cortex Posterior cingulate cortex Dorsolateral prefrontal cortex Medial part of the superior frontal gyrus Temporal cortex Inferior parietal cortex Thalamus Caudate Putamen Pons

Side

Left Right Left Right Left Right Left Right Left Right Left Right Left Right Left Right Left Right

Scan 1

Scan 2

Absolute variability⁎ (%)

Range of difference

Mean ± SD

COV (%)

Mean ± SD

COV (%)

Mean ± SD

COV (%)

(%)

5.62 ± 0.84 5.73 ± 0.87 5.95 ± 0.93 6.06 ± 0.87 5.72 ± 0.66 5.86 ± 0.74 5.79 ± 0.91 5.83 ± 0.94 5.66 ± 0.68 5.63 ± 0.65 5.45 ± 0.62 5.47 ± 0.69 3.25 ± 0.47 3.25 ± 0.44 2.68 ± 0.35 2.69 ± 0.40 3.10 ± 0.34 3.00 ± 0.33 1.16 ± 0.11

15.01 15.19 15.65 14.29 11.53 12.58 15.71 16.10 12.00 11.61 11.44 12.67 14.46 13.62 12.89 15.01 10.86 11.12 9.60

5.66 ± 0.84 5.72 ± 0.80 6.01 ± 0.84 6.19 ± 0.82 5.77 ± 0.64 5.88 ± 0.78 5.80 ± 0.90 5.81 ± 0.90 5.72 ± 0.63 5.68 ± 0.66 5.47 ± 0.64 5.50 ± 0.70 3.28 ± 0.40 3.21 ± 0.36 2.70 ± 0.39 2.65 ± 0.39 3.11 ± 0.28 3.10 ± 0.40 1.14 ± 0.12

14.93 14.01 13.92 13.29 11.05 13.25 15.50 15.47 10.98 11.69 11.74 12.74 12.13 11.22 14.43 14.76 9.12 12.79 10.89

7.26 ± 3.21 6.40 ± 3.53 7.15 ± 3.71 7.90 ± 5.28 5.51 ± 2.46 4.92 ± 2.47 5.69 ± 2.72 5.21 ± 3.74 5.75 ± 2.72 6.02 ± 2.02 5.72 ± 2.46 6.16 ± 2.31 7.67 ± 3.10 6.59 ± 4.39 6.27 ± 5.01 6.99 ± 5.29 8.35 ± 4.65 5.61 ± 3.37 4.62 ± 3.76

42.12 55.14 51.87 66.88 44.56 50.18 47.80 71.78 47.28 33.53 43.03 37.51 40.36 66.52 79.91 75.68 55.64 60.06 81.43

−7.46–14.98 −10.34–11.46 −8.73–14.04 −11.41– 19.21 −7.90–8.52 −9.68–6.87 −8.76–10.11 −10.43–9.90 −7.92–9.62 −7.56–7.94 −8.33–7.50 −8.35–7.94 −11.93–12.33 −9.72–14.29 −10.72–14.74 −15.08–9.41 −16.24–13.31 −6.97–10.77 −12.23–6.59

ICC

0.85 0.88 0.85 0.80 0.87 0.92 0.92 0.94 0.85 0.85 0.86 0.87 0.82 0.83 0.83 0.85 0.52 0.86 0.84

VT = total tissue distribution volume. 2TM = 2-tissue compartmental model. COV = coefficient of variation, i.e. (SD/mean) × 100%. ⁎|scan 2 − scan 1|)/[(scan 1 + scan 2] × 0.5] × 100% (disregarding the direction of change). ICC = intraclass correlation coefficient. Inferior parietal cortex = angular gyrus (Brodman's area 39) + supramarginal gyrus (Brodman's area 40), thalamus = lateral thalamus + medial thalamus, temporal cortex = inferior + middle + superior temporal gyrus.

Spatial normalization of parametric images Parametric images were spatially normalized to SPM (Montreal Neurological Institute [MNI]) space using standard estimation procedure implemented in SPM99 (Ashburner and Friston, 1997; Ashburner and Friston, 1999) and [11C]flumazenil template described above. Normalization parameters for parametric images were estimated from the mean summated images created with withinsubject realign procedure, and both realigned images (test and retest scan) of each individual were written using the same parameters. The

normalized images were written using bilinear interpolation. In addition, after spatial normalization, parametric images were smoothed using 10 mm Gaussian kernel. Automated ROI analysis To evaluate the reproducibility of VT-2TM values calculated at voxel-level and to achieve quantitative regional estimates of VT-2TM values, an automated ROI analysis was performed. ROIs for automated ROI analysis were defined on the same brain regions as in the conventional ROI analysis but using MRI image fitted onto common stereotactic space in accordance with coordinates of MNI database. To assure the common stereotactic space, a mean image of twelve spatially normalized MRIs was used instead of a single MRI image. This method is not hampered by operator induced errors in drawing ROIs individually for each subject, and it enables objective and rapid image analysis where the accuracy of the analysis depends solely on the quality of spatial normalization of images. Using regional values provided by automated ROI analysis, a further confirmation and estimation of the results of voxel-based statistical image analysis can be achieved (see e.g. Kemppainen et al., 2006; Brück et al., 2005). Evaluation of reproducibility and reliability To measure the reproducibility and reliability of different quantification methods the calculation of absolute variability (VAR) and ICC have been found to be a suitable method (Laruelle, 1999). VAR was calculated as follows:

Fig. 2. VT values yielded with VT-2TM versus the VT values yielded with VT-1TM; VT-2TM = 1.05 ⁎ VT-1TM – 0.02. All brain regions studied and individual VT values are included. The solid line represents the best fit line and the dotted line is the identity line.

VAR ¼

jscan2
scan1j  100k 0:5ðscan1 þ scan2Þ

ð1Þ

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Fig. 3. VT values yielded with VT-LOGAN versus the VT values yielded with VT-1TM; VT-LOGAN = 1.05 ⁎ VT-1TM + 0.02. All brain regions studied and individual VT values are included. The solid line represents the best fit line and the dotted line is the identity line.

performed using SPSS for Windows (Release 12.0.1, SPSS Inc., 1989–2003, Chicago, IL, USA). ICC and VAR values were calculated for each voxel separately from VT images that were prepared for SPM analysis, that is, spatially normalized and smoothed using 10 mm Gaussian kernel. The calculation produced 3-dimensional maps representing spatial distribution of ICC and VAR values. The regional average values of voxel-level ICC and VAR were calculated using the ROIs included in the automated ROI analysis. Region-level ICC and VAR values were also calculated directly from the spatially normalized non-smoothed parametric images to evaluate reproducibility of automated ROI analysis per se. Voxel-level reproducibility is essential when evaluating the feasibility of voxel-based statistical image analysis methods such as SPM analysis (Salmi et al., 2004; Salmi et al., 2005) in which statistical test is calculated independently for each voxel. Region-level reproducibility on the other hand is essential when evaluating whether conventional ROI analysis can be replaced by automated ROI analysis (see e.g. Brück et al., 2005; Kemppainen et al., 2006). Results Plasma analysis

Here scan1 and scan2 refer to parameter estimates of interest (e.g., BP) in test and retest scans, respectively. VAR under 10% was considered as excellent and VAR over 10% as moderate. Test–retest reliability was evaluated in terms of ICC:

ICC ¼

BSMS
WSMS BSMS þ ðn
1ÞWSMS

ð2Þ

Here BSMS is the between-subject mean square, WSMS is the within-subject mean square, and n is the number of repeated observations (in this case, n = 2). ICC can have values between − 1 and 1; values close to 1 indicate that most variance is due to between-subject rather than within-subject variation (good reliability), whereas values below zero imply greater within-subject than between-subject variation (poor reliability). ICC over 0.90 was considered as excellent, ICC between 0.70 and 0.90 as good and ICC under 0.70 as poor. Student's t-test of paired samples was used to test for differences in the parameters of interest between the scans, between the different compartmental models, fractions of unchanged [11C]flumazenil and the amount of injected doses and specific radioactivities of [11C] flumazenil. P b 0.05 was considered statistically significant and data are presented as mean ± SD unless otherwise stated. Analyses were

[11C]Flumazenil was metabolized as described in Fig. 1. During the test scan at 4 min 94 ± 3% of the total radioactivity and at 10 min 48 ± 12% of the total radioactivity originated from unchanged [11C]flumazenil. During the retest scan the comparable percentages were 92 ± 4% and 42 ± 6%, respectively. Data points from 50 min and 60 min were not used in the metabolite analysis as the total radioactivity at these time points is very low and data from all test and retest scans was not reliably achieved, but it was assumed that there were no significant changes in the fraction of [11C]flumazenil after 40 min. Clearance of unchanged [11C] flumazenil was 65 ± 10 L/h and 71 ± 18 L/h during test and retest scans, with no statistically significant differences between the scans (P= 0.38). Clearance showed moderate to poor reproducibility (VAR 20.3 ± 12.9%) and weak reliability (ICC 0.28). Brain uptake All quantification methods of [11C]flumazenil binding yielded higher uptake levels in the cortical regions than in the thalamus, caudate or in the putamen. As the results from ROI combinations (the inferior parietal cortex and the temporal cortex) were highly congruent with the ROIs comprising these ROI combinations, the results of the combinations are presented.

Table 3 The test–retest results of different quantification methods of [11C]flumazenil binding Estimate

Method

Abbreviation

Intraclass correlation coefficient

Absolute variability (%)

Difference (%)

VT

2TM 1TM Logan 2TM 2TM SRTM

VT-2TM VT-1TM VT-LOGAN BPP-2TM BPND-2TM BPND-SRTM

0.85 (0.52–0.94) 0.83 (0.50–0.92) 0.88 (0.63–0.96) 0.80 (0.29–0.93) 0.35 (− 0.09–0.68) 0.24 (− 0.08–0.62)

6.26 (4.62–8.92) 5.57 (4.10–8.79) 5.57 (4.06–5.08) 8.08 (5.43–14.27) 9.08 (6.63–16.30) 9.08 (6.22–17.35)

0.78 (− 1.83–3.03) 1.43 (− 1.49–3.36) 0.67 (− 3.36–2.79) 2.01 (− 1.00–6.36) 4.08 (1.17–8.56) 6.18 (3.89–9.53)

BPP BPND

It should be noted that the intraclass correlation coefficient, absolute variability and difference are the mean (range) of all brain regions measured. VT = total tissue distribution volume. BP = binding potential. 2TM = 2-tissue compartmental model. 1TM = 1-tissue compartmental model. SRTM = simplified reference tissue model.

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VT-2TM and VT-LOGAN values (data not shown). The 2TM produced higher VT values than the 1TM in all ROIs (on average 4.56%, all P b 0.001), but VT-2TM values were not substantially different from those produced by the Logan analysis (on average − 0.72%). Regarding the goodness of fit for the 1TM and 2TM, AIC values were significantly lower for the 2TM in all brain regions, even in the pons which was considered the reference region (all P b 0.001). VT values produced with 1TM, 2TM, and the Logan model were all highly reproducible as indicated by low VAR values and also highly reliable as reflected in high ICC values in most brain regions (Table 3). Time stability analysis for VT-2TM estimates and their reproducibility (Fig. 4.) suggested that a scanning time of 60 min cannot be significantly reduced without compromising accurate VT-2TM estimates and good reproducibility. In fact, the time-curve for VT-2TM estimates suggest that even higher values might be obtained with longer scanning times. 11

Estimates for specific binding of [ C]flumazenil As the 2TM provided a significantly better fit to the data than the 1TM, BP estimates from VT-2TM were considered primary outcome variables. BPND-2TM and BPND-SRTM values are given in Tables 4 and 5. Generally, regardless of the model configuration, BPND values for [11C]flumazenil demonstrated good VAR but poor ICC (Tables 4 and 5). In contrast, BPP values showed slightly better VAR and considerably better ICC (Table 6). BPP-2TM and BPND-2TM values were also calculated using the white matter as a reference region (data not shown). Similar pattern of results than with using pons as the reference region was observed: BPND-2TM demonstrated good reproducibility (average VAR 7.72%) and poor reliability (average ICC 0.42), whereas BPP-2TM values showed good reproducibility (average VAR 6.44%) and reliability (average ICC 0.83). As expected based on lower VT-2TM values in the white matter compared with the pons, BPP-2TM values using white matter as the reference region were on average 5.94% higher than those using pons as the reference region. Voxel-based image analysis methods

Fig. 4. Time stability of VT-2TM measurements. The effects of progressive truncating the brain data on the mean estimates (top) as well as their variability (middle) and ICC (bottom) was evaluated. In the top figure, points represent the mean estimate (N = 16) in each time point as percentage of the terminal VT-2TM value acquired using whole data (60 min), and the dashed reference line represents − 10% of the reference value. In the middle and bottom figures, solid lines represent the mean of terminal VAR and ICC values, respectively.

The VT-2TM values in different brain regions as well as their reproducibility and reliability are presented in Table 2. VT-1TM values (data not shown) correlated tightly (Figs. 2 and 3) with

The regional estimates calculated from spatially normalized [11C]flumazenil VT-2TM images, and the reproducibility of voxelbased image analysis methods at region-level and voxel-level are given in the Table 7. Regional estimates of VT are in good agreement with values obtained with manual ROI analysis as they were only 0.25% ± 3.59% higher. Region-level analysis yielded good to excellent reproducibility (average VAR 5.75%) and reliability (average ICC 0.81). Also the regional mean values of reproducibility calculated at voxel-level indicated good to excellent reproducibility (average VAR 6.04%) and reliability (average ICC 0.80). Discussion Conventionally [11C]flumazenil has been used in PET studies to measure cerebral GABAA receptors in vivo in human and several different analysis methods have been introduced to quantify [11C] flumazenil binding. Despite several studies focused on the validity aspects of single-injection [11C]flumazenil measurements (Holthoff et al., 1991; Koeppe et al., 1991; Lassen et al., 1995; Millet et al.,

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Table 4 BPND values and test–retest characteristics of [11C]flumazenil measurements using the 2TM model Brain area

Anterior cingulate cortex Posterior cingulate cortex Dorsolateral prefrontal cortex Medial part of the superior frontal gyrus Temporal cortex Inferior parietal cortex Thalamus Caudate Putamen

Side

Left Right Left Right Left Right Left Right Left Right Left Right Left Right Left Right Left Right

Scan 1

Scan 2

Absolute variability⁎ (%)

Range of difference

Mean ± SD

COV (%)

Mean ± SD

COV (%)

Mean ± SD

COV (%)

(%)

3.48 ± 0.42 3.93 ± 0.40 4.12 ± 0.48 4.22 ± 0.42 3.94 ± 0.28 4.05 ± 0.28 3.97 ± 0.41 4.02 ± 0.47 3.88 ± 0.28 3.85 ± 0.25 3.70 ± 0.22 3.71 ± 0.26 1.80 ± 0.28 1.80 ± 0.21 1.31 ± 0.22 1.32 ± 0.22 1.68 ± 0.19 1.60 ± 0.20

11.02 10.13 11.67 9.85 7.19 6.81 10.27 11.76 7.10 6.50 5.87 6.90 15.35 11.86 16.64 17.68 11.13 12.62

3.96 ± 0.36 4.02 ± 0.31 4.27 ± 0.39 4.43 ± 0.37 4.07 ± 0.22 4.16 ± 0.29 4.08 ± 0.34 4.09 ± 0.39 4.03 ± 0.33 4.00 ± 0.33 3.80 ± 0.24 3.83 ± 0.25 1.88 ± 0.21 1.82 ± 0.19 1.37 ± 0.25 1.33 ± 0.21 1.74 ± 0.17 1.72 ± 0.19

9.16 7.61 9.08 8.29 5.41 7.08 8.42 9.58 8.20 8.19 6.22 6.61 11.00 10.67 18.14 15.94 9.77 10.94

9.52 ± 6.82 9.28 ± 5.65 8.79 ± 5.81 10.34 ± 8.18 6.98 ± 5.03 6.63 ± 4.57 6.64 ± 5.82 7.89 ± 5.47 7.52 ± 5.69 7.52 ± 4.67 7.62 ± 4.19 7.61 ± 4.42 9.90 ± 7.73 10.85 ± 10.01 13.88 ± 7.94 16.30 ± 9.03 11.48 ± 5.93 11.18 ± 6.20

71.62 60.82 66.09 79.12 72.10 68.94 87.65 69.35 75.68 62.16 55.01 58.13 78.05 92.25 57.20 55.37 51.62 55.49

− 15.04–25.24 − 10.24–20.46 − 7.48–23.77 − 10.79–30.49 − 6.48–14.68 − 8.74–12.54 − 9.92–18.73 − 9.66–16.66 − 5.46–17.67 − 6.11–15.33 − 7.17–14.36 − 7.21–15.70 − 14.16–27.79 − 20.11–29.65 − 12.52–35.66 − 22.15–35.92 − 19.61–17.82 − 6.65–20.51

ICC

0.39 0.30 0.54 0.08 0.16 0.37 0.64 0.64 0.27 0.31 0.00 0.19 0.61 0.26 0.62 0.47 0.18 0.47

BP = binding potential. 2TM = 2-tissue compartmental model. COV = coefficient of variation, i.e. (SD/mean)× 100%. ⁎|scan 2− scan 1|) /[(scan 1+ scan 2] ×0.5]× 100% (disregarding the direction of change). ICC = intraclass correlation coefficient. Inferior parietal cortex = angular gyrus (Brodman's area 39) + supramarginal gyrus (Brodman's area 40), thalamus = lateral thalamus + medial thalamus, temporal cortex = inferior + middle + superior temporal gyrus.

2002; Klumpers et al., 2005), the reproducibility of these different methods has not been properly studied. Holthoff et al. (1991) studied the stability of measurements of 2-compartment, 2-parameter model (Koeppe et al., 1991) and found that there was no significant changes in VT of [11C]flumazenil between the scans. In the present study we show that the reproducibility and reliability of measurements based on arterial plasma input (VT, BPP) were excellent. However, both reproducibility and reliability of BPND estimates for [11C]flumazenil

binding are poor when reference region input is utilized, thus implying that arterial blood sampling may be required for this radioligand to attain the most reliable and reproducible results. The rank order of [11C]flumazenil VT was consistent with the human post mortem studies of GABAA receptors (Braestrup et al., 1977; Zezula et al., 1988). Our estimates yielded with VT-1TM are in line with the earlier estimates produced with 2-parameter, 2-compartmental model (Koeppe et al., 1991; Holthoff et al 1991).

Table 5 BPND values and test–retest characteristics of [11C]flumazenil measurements using the SRTM analysis Brain area

Side

Scan 1

Scan 2

Absolute variability⁎ (%) Range of difference ICC

Mean ± SD COV (%) Mean ± SD COV (%) Mean ± SD Anterior cingulate cortex

Left Right Posterior cingulate cortex Left Right Dorsolateral prefrontal cortex Left Right Medial part of the superior frontal gyrus Left Right Temporal cortex Left Right Inferior parietal cortex Left Right Thalamus Left Right Caudate Left Right Putamen Left Right

3.61 ± 0.39 3.67 ± 0.35 3.86 ± 0.48 3.97 ± 0.42 3.69 ± 0.28 3.79 ± 0.27 3.73 ± 0.37 3.74 ± 0.40 3.61 ± 0.26 3.58 ± 0.24 3.45 ± 0.25 3.46 ± 0.26 1.76 ± 0.27 1.74 ± 0.21 1.27 ± 0.21 1.28 ± 0.22 1.62 ± 0.16 1.54 ± 0.17

10.89 9.47 12.30 10.53 7.54 7.05 9.92 10.72 7.34 6.69 7.32 7.50 15.36 12.21 16.49 17.34 9.89 11.10

3.77 ± 0.27 7.04 3.84 ± 0.21 5.41 4.09 ± 0.32 7.78 4.25 ± 0.29 6.73 3.89 ± 0.19 4.83 3.98 ± 0.21 5.40 3.91 ± 0.24 6.26 3.90 ± 0.28 7.22 3.82 ± 0.28 7.26 3.79 ± 0.27 7.03 3.62 ± 0.19 5.12 3.64 ± 0.19 5.31 1.86 ± 0.19 10.34 1.81 ± 0.17 9.40 1.36 ± 0.23 16.79 1.33 ± 0.21 15.70 1.71 ± 0.15 8.68 1.68 ± 0.16 9.72

COV (%) (%)

8.75 ± 7.49 85.67 8.56 ± 6.81 79.52 8.69 ± 7.19 82.69 9.79 ± 9.24 94.35 6.45 ± 6.46 100.19 6.61 ± 5.53 83.61 7.31 ± 6.99 95.61 7.20 ± 6.53 90.79 7.37 ± 6.75 91.61 7.06 ± 6.60 93.46 7.33 ± 6.07 82.78 7.08 ± 6.24 88.11 10.94 ± 8.63 78.88 11.33 ± 11.12 98.21 14.85 ± 9.38 63.17 17.35 ± 9.06 52.23 11.66 ± 6.60 56.59 10.75 ± 8.29 77.10

−13.06–25.67 −7.72–22.32 −3.55–27.26 −6.64–31.52 −2.98–17.95 −4.04–15.53 −8.51–22.81 −4.75–18.20 −3.22–20.84 −3.56–19.30 −5.76–18.26 −4.37–19.17 −14.95–31.02 −16.52–34.38 −13.31–40.52 −18.45–42.10 −17.34–23.42 −6.05–27.55

0.30 0.13 0.51 0.07 0.17 0.22 0.42 0.54 0.20 0.16 0.03 0.11 0.51 0.08 0.51 0.39 −0.05 0.26

BP = binding potential. SRTM = simplified reference tissue model. COV = of variation, i.e. (SD/mean)×100%. ⁎|scan 2 − scan 1|)/[(scan 1 + scan 2] × 0.5] × 100% (disregarding the direction of change). ICC = intraclass correlation coefficient. Inferior parietal cortex = angular gyrus (Brodman's area 39) + supramarginal gyrus (Brodman's area 40), thalamus = lateral thalamus + medial thalamus, temporal cortex = inferior + middle + superior temporal gyrus.

E. Salmi et al. / NeuroImage 41 (2008) 260–269

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Table 6 BPP values and test–retest characteristics of [11C]flumazenil measurements using the 2TM model Brain area

Side

Anterior cingulate cortex Posterior cingulate cortex Dorsolateral prefrontal cortex Medial part of the superior frontal gyrus Temporal cortex Inferior parietal cortex Thalamus Caudate Putamen

Left Right Left Right Left Right Left Right Left Right Left Right Left Right Left Right Left Right

Scan 1

Scan 2

Absolute variability⁎ (%)

Range of difference

Mean ± SD

COV (%)

Mean ± SD

COV (%)

Mean ± SD

COV (%)

(%)

4.46 ± 0.75 4.57 ± 0.77 4.79 ± 0.84 4.90 ± 0.77 4.56 ± 0.57 4.70 ± 0.64 4.63 ± 0.81 4.67 ± 0.85 4.50 ± 0.58 4.47 ± 0.56 4.29 ± 0.52 4.31 ± 0.59 2.09 ± 0.40 2.09 ± 0.35 1.52 ± 0.28 1.54 ± 0.33 1.94 ± 0.26 1.85 ± 0.26

16.87 16.91 17.59 15.76 12.42 13.55 17.51 18.11 12.99 12.46 12.18 13.76 18.99 16.87 18.46 21.45 13.46 14.27

4.52 ± 0.74 4.58 ± 0.69 4.87 ± 0.73 5.05 ± 0.72 4.63 ± 0.53 4.75 ± 0.67 4.66 ± 0.79 4.67 ± 0.79 4.58 ± 0.53 4.55 ± 0.57 4.33 ± 0.53 4.36 ± 0.59 2.14 ± 0.31 2.07 ± 0.27 1.56 ± 0.33 1.52 ± 0.30 1.97 ± 0.20 1.96 ± 0.30

16.28 15.02 15.02 14.17 11.35 14.09 16.86 16.93 11.60 12.47 12.26 13.47 18.99 13.18 20.82 20.03 10.26 15.25

9.29 ± 4.49 7.78 ± 4.82 8.21 ± 5.33 9.13 ± 7.50 6.16 ± 3.81 5.43 ± 3.66 6.84 ± 3.28 5.95 ± 5.28 6.44 ± 4.35 6.77 ± 3.49 6.58 ± 3.68 7.01 ± 3.68 10.41 ± 6.19 10.22 ± 7.45 11.06 ± 8.74 13.63 ± 9.03 11.35 ± 7.48 8.38 ± 6.40

48.31 61.90 64.86 82.13 61.76 67.40 47.96 88.72 67.53 51.49 55.87 52.48 59.42 72.86 79.02 66.26 65.85 76.30

−9.44–20.58 −11.90–15.98 −10.11–19.16 −13.33–25.63 −9.14–11.55 −11.34–9.45 −7.93–14.31 −12.24–13.54 −8.89–13.29 −8.78–11.03 −9.28–10.40 −9.85–11.39 −16.61–23.03 −14.84–26.19 −15.69–32.04 −24.37–21.94 −22.52–17.58 −9.31–16.49

ICC

0.82 0.85 0.83 0.75 0.84 0.91 0.92 0.93 0.81 0.82 0.83 0.84 0.78 0.73 0.76 0.75 0.29 0.77

BP = binding potential. 2TM = 2-tissue compartmental model. COV = coefficient of variation, i.e. (SD/mean)×100%. ⁎|scan 2− scan 1|)/[(scan 1 +scan 2] ×0.5] ×100% (disregarding the direction of change). ICC = intraclass correlation coefficient.t Inferior parietal cortex = angular gyrus (Brodman's area 39) + supramarginal gyrus (Brodman's area 40), thalamus = lateral thalamus + medial thalamus, temporal cortex = inferior + middle + superior temporal gyrus.

Table 7 The regional estimates calculated from spatially normalized [11C]flumazenil VT-2TM images and the test–retest characteristics of voxel-based analysis on regionlevel and voxel-level Brain area

Anterior cingulate cortex Posterior cingulate cortex Dorsolateral prefrontal cortex Medial part of the superior frontal gyrus Temporal cortex Inferior parietal cortex Thalamus Caudate Putamen Pons

Side

Range of difference (%)

Absolute variability⁎of the region-level analysis (%)

Scan 1

Scan 2

ICC of the region-level analysis

Mean ± SD

Mean ± SD

Left

5.55 ± 0.68

5.47 ± 0.63

− 9.77–12.21

6.26 ± 3.92

0.81

6.45

0.79

Right Left

5.59 ± 0.64 5.62 ± 0.66

5.57 ± 0.62 5.56 ± 0.65

− 9.71–12.15 − 10.95–15.33

5.52 ± 3.71 6.62 ± 4.90

0.83 0.75

5.53 6.61

0.83 0.75

Right Left

5.62 ± 0.61 5.97 ± 0.63

5.59 ± 0.57 5.85 ± 0.61

− 8.95–18.32 − 9.06–7.89

6.72 ± 5.14 5.31 ± 3.26

0.69 0.83

6.70 5.56

0.73 0.82

Right Left

6.11 ± 0.59 6.09 ± 0.82

6.03 ± 0.64 5.98 ± 0.83

− 9.27–7.97 − 8.93–7.74

5.03 ± 2.96 4.45 ± 3.19

0.85 0.93

5.18 5.30

0.84 0.89

Right Left Right Left Right Left Right Left Right Left Right

6.02 ± 0.74 5.79 ± 0.65 5.82 ± 0.63 5.60 ± 0.63 5.57 ± 0.59 3.23 ± 0.38 3.22 ± 0.35 2.62 ± 0.30 2.61 ± 0.33 2.95 ± 0.38 2.99 ± 0.31 1.12 ± 0.10

5.92 ± 0.79 5.73 ± 0.59 5.78 ± 0.61 5.50 ± 0.60 5.50 ± 0.56 3.21 ± 0.35 3.14 ± 0.30 2.55 ± 0.29 2.55 ± 0.33 2.87 ± 0.31 2.99 ± 0.33 1.13 ± 0.11

− 9.97–8.87 − 9.01–10.59 − 8.52–10.46 − 10.32–10.76 − 9.40–10.88 − 10.57–12.86 − 8.75–11.13 − 13.06–5.73 − 10.79–5.18 − 15.15–12.96 − 9.37–11.78 − 7.37–11.88

5.64 ± 3.78 5.17 ± 3.69 5.59 ± 3.14 5.92 ± 3.89 5.72 ± 3.70 7.76 ± 2.69 5.23 ± 3.67 5.02 ± 3.77 4.96 ± 3.74 7.74 ± 5.07 5.16 ± 4.56 5.45 ± 3.37

0.88 0.82 0.81 0.80 0.79 0.75 0.81 0.83 0.89 0.69 0.81 0.76

5.31 5.53 5.81 5.85 5.60 7.80 5.92 5.46 5.41 7.02 5.92 7.84

0.88 0.81 0.80 0.82 0.80 0.74 0.78 0.84 0.87 0.73 0.79 0.61

Mean ± SD

Absolute variability⁎of the voxel-level analysis (%)

ICC of the voxel-level analysis

Mean

VT-2TM = total volume of distribution yielded with the 2-tissue compartmental model. ⁎|scan 2 − scan 1|) / [(scan 1 + scan2] × 0.5] × 100% (disregarding the direction of change). ICC = intraclass correlation coefficient. Inferior parietal cortex = angular gyrus (Brodman's area 39) + supramarginal gyrus (Brodman's area 40), thalamus = lateral thalamus + medial thalamus, temporal cortex = inferior + middle + superior temporal gyrus.

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VT-1TM values were 5.05 ± 0.61% lower than VT-LOGAN values. Recently, Klumpers et al. (2005) found that for cortical structures the 2TM provides slightly better fits and that the 1TM may underestimate VT. Consistent with these findings, we found that the AIC preferred the 2TM fit which also showed 5.10% ± 0.29% and 3.48% ± 0.58% higher VT values in cortical and subcortical regions than the 1TM, respectively. Nonetheless, the reproducibility was equally excellent with both models as indicated by low VAR and high ICC values. Time stability analysis suggested that at least 60 min is required to yield accurate and reproducible estimates of VT-2TM. The specific binding of [11C]flumazenil was calculated in both BPP and BPND estimates using VT-2TM as well as with SRTM in the case of BPND. Regardless of the method, the reliability of BPND estimates was considerably inferior to the reliability of BPP estimates. When calculating BPND estimates, the VND (distribution volume of the non-displaceable tissue compartment, VT in the reference region) is used as the denominator, and any error in the latter term will propagate into BPND. Thus, arterial plasma input seems to be required for yielding appropriate reproducibility in [11C]flumazenil PET studies. Moreover, there appears to be a trade-off between better reproducibility (VT) and validity (BPP) when choosing the outcome measure based on arterial plasma input given that the former includes a component of non-specific binding but has better reproducibility than the latter; this choice will ultimately depend on the study design. There are implications that pons might not represent an ideal reference region for [11C]flumazenil studies. Due to the small volume and caudal location of the pons, the signal from this region may be adversely affected by partial volume effects and out of fieldof-view scatter especially when the 3D mode is applied (Accorsi et al., 2004). In addition, GABAA receptors are expressed in the pons and this violates the assumption of a receptor-free reference region (Delforge et al., 1995). It has been shown earlier that the binding of [11C]flumazenil in the pons tends to increase during sevoflurane and propofol anesthesia, which were not likely due to changes in plasma protein binding or non-specific binding in the brain as similar changes were not seen in the cerebral white matter (Salmi et al., 2004). In summary, despite of good reproducibility, the VT of [11C] flumazenil in the pons does not appear to be a robust estimate of the non-displaceable tissue compartment for BPND calculations. White matter has also been used as a reference tissue (Savic et al., 1990; Magata et al., 2003). However, it cannot be considered as an ideal reference tissue as the amount of non-specific binding cannot be assumed to be the same as in the gray matter (Lassen et al., 1995). Furthermore, the cerebral white matter ROI is often contaminated by spill-in radioactivity from adjacent gray matter high-activity regions, which have very high uptake. Finally, BPND values estimated using white matter as the reference region were as poorly reliable as were those estimated using pons, thus suggesting that validity issues aside, white matter is not an appropriate reference region for [11C]flumazenil studies. The GABAergic system has been known to be affected in many neurological and psychiatric diseases, as epilepsy, stroke, congenital syndromes, anxiety disorders and dementia (Savic et al., 1988; Heiss et al., 1998; Lucignani et al., 2004; Malizia et al., 1998; Ihara et al., 2004). The poor reproducibility of methods based on reference region input described here does not preclude the use of [11C]flumazenil PET in diagnostic study settings where focal alterations of GABAA distribution are looked for and where arterial cannulation may be considered too invasive. Voxel-based image analysis techniques are frequently used at present, as they enable automated image analysis and provide il-

lustrative visualization of the results (e.g. Kemppainen et al., 2006). Since they are based on image analysis in a common stereotactic brain space, they require spatial normalization of individual images. Although the images are smoothed before statistical analysis, the accuracy of spatial normalization is critical as the statistical tests are made at the level of individual voxels. It has been demonstrated that spatial normalization with a ligand-specific template provides more accurate spatial normalization than MRI-aided spatial normalization (Meyer et al., 1999), and a ligand-specific template was therefore prepared for [11C]flumazenil. To evaluate reproducibility at the voxellevel, VAR and ICC maps were calculated from parametric [11C] flumazenil images representing the spatial distribution of VT values. Regional average voxel-level VT values were consistent with those obtained from the conventional ROI analysis, and reproducibility at the voxel-level was generally equally good as that obtained by manual ROI analysis. The proper reproducibility and congruent results with the conventional ROI analysis suggests that voxel-based analyses with e.g. SPM are sensitive enough even in fairly small samples. Recent studies have indicated that automated ROI analysis of spatially normalized parametric images is feasible for several PET tracers (Kemppainen et al., 2005; Kemppainen et al., 2006; Brück et al., 2005). The reproducibility of region-level automated ROI analysis appeared to be equal to the reproducibility of manual ROI analysis. The good reproducibility and validity of the automated ROI estimation argues for using automated ROI analysis instead of conventional manual ROI analysis in [11C]flumazenil PET studies. In conclusion, the results of the present study indicate that the reproducibility of [11C]flumazenil BPND using reference tissue as the input function is poor. Thus, outcome measures utilizing arterial input function (VT, BPP) should be preferred with this radiotracer whenever possible. The reproducibility and validity of estimates is maintained when quantification is made at voxel-level and analysis is conducted in standard brain space indicating that the conventional ROI analysis can be replaced with the voxelbased analysis in [11C]flumazenil PET studies. Acknowledgments The study was supported by Turku University Hospital EVOgrant No. 13323, Turku, Finland; The Paulo Foundation, Espoo, Finland; Instrumentarium Science Foundation, Helsinki, Finland; Research Foundation of Orion Corporation, Espoo, Finland and Alfred Kordelin Foundation, Helsinki, Finland. We would like to thank Professor W. Hunkeler (Roche, Basel, Switzerland) for kindly supplying the precursor des-methyl flumazenil, Ro 15-5528 and flumazenil, Ro 15-1788. References Accorsi, R., Adam, L.E., Werner, M.E., Karp, J.S., 2004. Optimization of a fully 3D scatter simulation algorithm for 3D PET. Phys. Med. Biol. 49, 2577–2598. Ashburner, J., Friston, K., 1997. Multimodal image coregistration and partitioning—a unified framework. NeuroImage 6, 209–217. Ashburner, J., Friston, K.J., 1999. Nonlinear spatial normalization using basis functions. Hum. Brain Mapp. 7, 254–266. Braestrup, C., Albrechtsen, R., Squires, R.F., 1977. High densities of benzodiazepine receptors in human cortical areas. Nature 269, 702–704. Brück, A., Aalto, S., Nurmi, E., Bergman, J., Rinne, J.O., 2005. Cortical 6-[18F] fluoro-L-dopa uptake and frontal cognitive functions in early Parkinson's disease. Neurobiol. Aging 26, 891–898.

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