Brain imaging tools in neurosciences

Journal of Physiology - Paris 99 (2006) 281–292 www.elsevier.com/locate/jphysparis

Brain imaging tools in neurosciences Andreas Otte

a,b,*

, Ulrike Halsband

c

a b

Division of Nuclear Medicine, Ghent University Hospital, De Pintelaan 185, 9000 Gent, Belgium Center of Clinical Trials, University Hospital Freiburg, Elsaesser Str. 2, 79110 Freiburg, Germany c Neuropsychology, Department of Psychology, University of Freiburg, Germany

Abstract In this chapter brain imaging tools in neurosciences are presented. These include a brief overview on single-photon emission tomography (SPET) and a detailed focus on positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). In addition, a critical discussion on the advantages and disadvantages of the three diagnostic systems is added. Furthermore, this article describes the image analysis tools from visual analysis over region-of-interest technique up to statistical parametric mapping, co-registration methods, and network analysis. It also compares the newly developed combined PET/CT scanner approach with established image fusion software approaches. There is rapid change: Better scanner qualities, new software packages and scanner concepts are on the road paved for an amply bright future in neurosciences.  2006 Elsevier Ltd. All rights reserved. Keywords: PET/CT; SPET; fMRI; Statistical parametric mapping; Network analysis

‘‘In motley pictures little clarity, Much error and a spark of verity.’’ J.W. von Goethe. 1. Introduction Nuclear medicine, a relatively young discipline at the interface of nearly all medical disciplines, plays an increasing role in the understanding of functional physiology and pathophysiology of the brain. Although the basic mechanisms for nuclear medicine devices, such as single photon emission tomography (SPET) and positron emission tomography (PET), were found in the early 1960s, it should take a lot more years until the introduction of these methods into clinical routine, as one of the main challenges for this was the infancy of the computer technology at that time. We also cannot imagine neuroscience life today without functional magnetic resonance imaging (fMRI), the *

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0928-4257/$ - see front matter  2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.jphysparis.2006.03.011

rapid progress of which is especially triggered by the exponential development of high-speed computer systems. In the context of this technological development it is possible nowadays to have a spatial resolution of neuroimaging scanners allowing for resolution within very few millimetres. Likewise, neuroimaging data analysis has also changed dramatically. Recently images were only interpreted visually, leading to some confusion in their interpretation—the situation of which may well be described in the aforementioned verse from Goethe’s Faust—, whereas nowadays the region-of-interest (ROI) technique, normalization to stereotaxic atlas systems, such as the coordinate system of Talairach and Tournoux, statistical parametric and non-parametric mapping methods, the image fusion technique and kinetic modelling are state of the art and excellent tools for a correct and observer-independent image interpretation. Competitive developments in magneto-encephalographic techniques (e.g., SQUID, DC SQUID gradiometers), which allow for identification of brain signals difficult to detect with electroencephalography (EEG) only,

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should be carefully monitored. There are, however, significant opportunities for nuclear medicine techniques. In this fascinating and progressing world, additional efforts for an improved interpretation of functional neuroimaging with respect to structural MRI changes using combined voxel-based statistical mapping (Kassubek et al., 2000) along with attempts to standardize cerebral imaging in clinical neurological diagnostics (Juengling et al., 2000) have already been introduced. Both, these new developments and the basic tools which nuclear medicine offers to this field are described in the following contribution.

Without neglecting SPET, special attention is paid to PET and fMRI including modern image analysis. 2. Positron emission tomography (PET) 2.1. Technique In PET (Fig. 1A), positrons are used for labelling of tracers. These positrons do not exit the patient but travel a short distance prior to colliding and annihilating with local electrons. The masses of the positron and electron

Fig. 1. (A) Example of a PET scanner: ECAT PET from Siemens. With kind permission from Siemens AG Erlangen. (B) Example of an MRI scanner, Magnetom Harmony from Siemens. With kind permission from Siemens AG Erlangen.

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are entirely converted into two photons emitted in directly opposite directions (180) with exactly the same energy (511 keV). Photon pairs that exit the patient can be detected with PET scanners. A PET signal is only created if two facing detectors detect scintillation coincidentally. This is called electronic collimation enabling 3D and timely linkage of the created signals. With PET, also absolute quantification and kinetic modelling are possible. For further reading on the medical engineering aspects of PET, we would like to refer to the excellent compilation by Ha¨misch and Eggert (2002). It would blow up this section if these were included here. However, further points of interest with PET, especially, as we think, to the neuroscience audience, are detailed in the below sections ‘‘Advantages/disadvantages of SPET versus PET and Functional magnetic resonance imaging (fMRI)’’ and ‘‘Advantages/ disadvantages of fMRI over PET’’. 2.2. Tracers The production of positron emitters requires a nearby cyclotron or nuclear reactor. Frequently used positron emitters are 18F, 11C, 13N, and 15O (Table 1). These are nuclides with short half lives, which—in their non-radioactive form—can be found naturally in the human organism. Therefore, these positron emitters can be labelled to human molecules, like, e.g., glucose in the form of 18F-labelled 2deoxy-2-fluoro-D-glucose (FDG) (Table 2). In clinical routine, the most commonly used radiolabelled tracer is 18F-FDG, as it is easily available, has

Table 1 Examples of positron emitters for PET tracers Positron emitter

Half life

Commonly used 18 F 11 C 15 O 13 N

109.8 min 20.4 min 2.05 min 9.98 min

Rarely used 68 Ga 82 Rb 52 Fe 124 I 62 Cu

68.0 min 1.25 min 8.3 h 4.18 d 9.7 min

Table 2 Examples of radiopharmaceuticals in brain PET imaging Regional cerebral blood flow Regional cerebral blood volume Energy metabolism Protein metabolism Dopamine receptors

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an acceptable half life and is rather cheap. FDG can be used for the quantification of the regional cerebral glucose utilization. Alike unlabelled glucose, FDG is transported via glucose carrier into the cell and then phosphorylased into FDG–phosphate. By contrast to glucose-6-phosphate, FDG–phosphate is, however, not further metabolized, but accumulates in the cell. PET can regionally quantify the amount of this accumulation. By knowing the blood-activity curve, the regional cerebral glucose utilization, e.g. in lmol/100 g brain tissue/min, can be assessed via a threecompartment model. Usually, the glucose utilization correlates with the regional synaptic activity. For research purposes, especially in stimulation studies, 15 O-labelled tracers are most commonly used, like, e.g., 15 O-CO (administered via nasal catheter) to assess information on regional cerebral blood volume or 15O-H2O to allow measurement of rCBF and accurate mapping of ROIs. Pharmaceutical industry is more and more looking into the possibilities PET offers for answering questions on the mechanisms of action and bio-distribution of drugs by direct labelling of these with positron emitters. The direct labelling of pharmaceutical drugs is a new, but increasingly important field in neuroscience, which should be mentioned here, as it provides essential information on the pharmacokinetics and pharmacodynamics of the drug. E.g., in a study from Otte et al. (2003b), the anti-migraine drug eletriptan was labelled with 11C. By a combined 11Celetriptan/15O-CO/15O-H2O PET approach the intracranial distribution and uptake of 11C-eletriptan, the extent to which it crosses the blood–brain-barrier and its regional cerebral distribution was studied in migraineurs during an acute attack, migraineurs during a headache-free interval and controls. In this study it could be shown that PET was a useful technique for evaluating the intracranial uptake and distribution of eletriptan, including the assessment of blood–brain-barrier penetration or the lack thereof. In all groups, the highest eletriptan uptake was observed in the meningovascular/cerebral spinal fluid and choroid plexus ROIs. Tissue levels of the drug peaked rapidly and maintained a plateau throughout the study period. The highest intracranial eletriptan uptake occurred in migraineurs during a migraine attack and the lowest uptake in the controls. Penetration of eletriptan into the cerebrum was minimal but diffuse, with little predilection for uptake in a specific lobar pattern. Since the meningovascular tissues are considered to be crucial structures for the generation of migraine pain, these PET findings are consistent with the advantageous efficacy and CNS tolerability profile of eletriptan.

15

O-H2O O-CO 15 O-O2 18 F-FDG 11 C-methionine 18 F-DOPA 18 F-spiperone 11 C-raclopride 15

2.3. Stimulation studies There are several different methods for determining rCBF with PET. These include the use of inert gasses such as [11C]-fluoromethane (Ericksson et al., 1989) or the continuous inhalation of [15O]-CO (Lammertsma et al., 1981;

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Subramanyam et al., 1978). Furthermore, bolus injections of [15O]-H2O (Fox et al., 1984; Herscovitch et al., 1983, 1987; Raichle et al., 1983), and of [15O]-butanol (Herscovitch et al., 1983, 1987; Votaw et al., 1999) are used.

Recently, Kessler (2003) critically discussed the advantages and limitations of these methods. Nowadays, bolus injections of [15O]-H2O are most frequently used to analyse relative rCBF, combined with the use of a subtraction

Fig. 2. (A) Example of an SPM’94 plot. This shows a statistically significant voxel area in an FDG–PET study of a patient fused with the corresponding MRI images of this patient. With kind permission from Springer-Verlag, Berlin, Heidelberg, New York, Tokyo. (B) Example of a PET/CT scan of a 50year old male patient with a brain tumour; tracer: 18F-FDG. By courtesy of Professor Peter J. Ell, Institute of Nuclear Medicine, University College London.

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paradigm for neuropsychological activation (e.g. Halsband et al., 1998, 2002) and spatial normalization using the Talairach coordinates (Talairach and Tournoux, 1988). The method of choice for repeat measurements in the same subject is the use of H215O due to its short half life of 2 min. Furthermore, a detailed knowledge of the tracer kinetics of H215O indicated that studies could also be performed on a qualitative basis, as there was a predictable relationship between uptake and actual perfusion. 15 O water PET was used to study differences in cerebral activation patterns associated with verbal memory processing in the native language of the subjects (Finnish) as compared with a fluent foreign language (English). Subjects had to learn and retrieve visually presented paired word associates of highly imaginable and abstract words. An emission scan was recorded after each intravenous administration of 15O water. During memory retrieval, precuneus showed a consistent activation in both languages. By contrast, differential activations were found in Broca’s area, as well as in the angular/supramarginal gyri according to the language used (Halsband, 2006; Halsband et al., 2002). The future of PET activation studies lies in ligands under different conditions (Lammertsma, 2001). As it is now possible to generate functional images of receptor binding parameters (Gunn et al., 1997), statistical packages can be applied to these images, thereby directly detecting changes in binding on a pixel-by-pixel level (Koepp et al., 1998). 3. PET–CT The availability of accurately aligned anatomical (computed tomography, CT) and functional (PET) images has a significant impact in oncology. Although algorithms to align CT and PET images acquired on different scanners have generally been successful for the brain, a combined PET/CT ad hoc approach in this region is currently one of the most fascinating endeavours, especially if there are structural alterations which have to be aligned to the brain function, as is, e.g., after severe traumatic brain injury, after surgical intervention, or in brain tumour lesions (Fig. 2B). The PET/CT scanner was originally developed as a combination of a Siemens Somatom AR.SP spiral CT and a partial-ring, rotating ECAT ART PET scanner (Beyer et al., 2000). The leading other companies in the field now also have added a PET/CT scanner to their product portfolio. Indeed, industry is also currently working on a SPET/CT scanner. The economy of a combined PET/CT may be subject to discussion, as the acquisition times of PET and CT are quite contrary and the CT is not effectively used. This also applies to a SPET/CT scanner. Further points for discussion in terms of advantages and disadvantages of a combined PET/CT approach versus the electronic (software) fusion imaging approach are raised below in section ‘‘Image analysis–Image fusion’’.

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In agreement with Ell and von Schulthess (2002) we think that PET/CT is neither only PET nor only CT, but is a completely new imaging tool that will change not only the use of PET but also the use of CT. It will also broaden the view of both nuclear medicine specialists and radiologists fostering further multidisciplinary approaches. 4. Single-photon emission tomography (SPET): a brief overview Over the past decennium, SPET has become a routine tool of nuclear medicine enabling tomographic images of organs and body systems with a meanwhile very acceptable resolution within few millimetres. Some new triple- or quadruple-headed SPET cameras are even successfully used for imaging of small animal brains. Radioisotopes used for SPET tracers are listed in Table 3. From these radioisotopes, 99mTc and 123I have become most favourable for labelling of pharmaceuticals. Common radiopharmaceuticals are listed in Table 4. From these radiopharmaceuticals, the two perfusion markers 99mTc-HMPAO (hexamethylpropylene amine oxim; CeretecTM) and 99mTcECD (ethylene biyldicysteinate dimer; NeuroliteTM) are widely used in clinical routine for a great variety of brain diagnostics. SPET has its place in the clinical routine. Costs are rather low and handling, including training of staff and preparation of radiopharmaceuticals, is easy. Often developments of PET radiopharmaceuticals and clinical research experience from PET studies are triggering the pathway of SPET (Tables 3 and 4). 5. Advantages/disadvantages of SPET versus PET The main differences between PET and SPET are based on the presence of coincidence detection in PET, the need Table 3 Examples of radioisotopes for SPET tracers Radioisotope

Half life

Commonly used 99m Tc 123 I

6.0 h 13.3 h

Rarely used 133 Xe

5.27 d

Table 4 Examples of radiopharmaceuticals in brain SPET imaging Brain perfusion

99m

Tc-HMPAO Tc-ECD 133 Xe-NaCl 99m

Benzodiazepine receptors Dopamin-D2 receptors Protein metabolism

123

I-Iomazenil I-IBZM 123 I-a-methyltyrosine 123

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for collimators in SPET, and the type and configuration of the scintillation crystals differing between the two camera systems. The major advantage of SPET over PET is cost. Due to the cost of scintillation crystals, SPET cameras are about five times cheaper than PET cameras. Furthermore, PET needs a cyclotron in its neighbourhood and experienced staff for labelling the tracers. By contrast, labelling of SPET tracers is mostly possible with 99mTc allowing for easy labelling by radiopharmaceutical kits and a cheapness by 99 Mo/99mTc generators which can be placed at any site. A second advantage of SPET over PET can be found within the usable routine radiopharmaceuticals: PET is logistically challenging due to the short half life of the most common tracers (e.g., 18F: 110 min; 11C: 20 min), whereas SPET emitters are more amenable to routine use owing to much lower costs, advantageous half-lives (e.g., 99mTc: 6 h; 123I: 13 h) and better suitability to the study of metabolic processes that take longer than a few hours to occur, e.g., protein synthesis. A further advantage of perfusion SPET over PET is that with SPET the brain state is ‘‘frozen’’ immediately after injection of the perfusion tracer and the brain scan can be performed hours later. This has some advantages in the logistics of diagnosing certain brain states, e.g., in ictal epilepsy diagnostics (e.g., Otte, 2000) or in sleep research (Otte et al., 2002, 2003a). Last but not least, SPET emitters require less dense scintillators, and NaI, which is a readily available high light output scintillator, can be used. With PET, there is a need for extremely dense detectors to stop the energetic annihilation photons (511 keV). In addition, SPET emitters have an intrinsically lower radiation dose as opposed to PET emitters. This is due to the photon emission being direct from the nucleus rather than secondary to a particle emission, with its associated higher linear energy transfer and radiation damage to surrounding cells. The major three disadvantages of SPET over PET are: (1) the inferior image quality due to lower image resolution and sensitivity caused by the missing electronic annihilation coincidence detection to provide collimation of the photons (as opposed to the lead collimator in SPET). (2) Whereas with PET usually chemical elements already naturally present in the human organism are used for labelling of organic molecules, such as oxygen, fluorine, carbon, or nitrogen, SPET preponderantly utilizes 99mTc-labelled tracers, which often behave differently and are designed with certain compromises. Also, the variety of radiopharmaceuticals with SPET is limited, whereas PET isotopes can be labelled to nearly every organic molecule. (3) Due to the spatial independence of the signal detection, PET measurements can be quantified absolutely, whereas this is not possible with SPET. Despite some disadvantages of PET over SPET, the aforementioned three advantages of PET propel this diagnostic tool to one of the most attractive imaging devices within nuclear medicine and radiology.

6. Functional magnetic resonance imaging (fMRI) 6.1. Technique Functional MRI (fMRI) (Fig. 1B) is based on the increase in blood flow to the local vasculature that accompanies neural activity in the brain. The response to a local increase in metabolic rate is increased delivery of blood to the activated region. It is the iron in blood haemoglobin which serves as an inherent magnetic susceptibility-induced T2*-shortening intravascular contrast agent and is used as a local indicator of functional activation. T2*-weighted sequences are by far the most widely used in fMRI because of their superior sensitivity as compared to spin–echo sequences (Bandettini et al., 1994). Oxygenated arterial blood contains oxygenated haemoglobin, which is diamagnetic and has a small magnetic susceptibility effect. The local T2* critical in fMRI contrast is determined by the balance of deoxygenated to oxygenated haemoglobin in blood within a voxel, which in turn is a function of local arterial auto regulation or vasodilatation. The observed T2* is dependent on the presence of blood deoxygenation. Since deoxyhemoglobin is paramagnetic, it alters the T2* weighted magnetic resonance image signal (Ogawa et al., 1990a,b, 1992, 1993, 2000; Tank et al., 1992; Turner et al., 1991). Deoxygenated haemoglobin is a ‘‘blood oxygenation level dependent’’ or ‘‘BOLD’’ effect that can be observed by non-invasive MR imaging at high magnetic fields. Such changes in the oxygenation level of the blood occur as a consequence of neuronal activity and so the magnitude of change in signal intensity can be used as an indirect measure of excitatory input to neurons. The BOLD effect has provided the basis for most fMRI experiments conducted to date. BOLD was first described by Ogawa and co-workers (Ogawa and Lee, 1990; Ogawa et al., 1990b,a) in rat brain studies using strong magnetic fields (7 and 8.4 T). It was found that the contrast of high resolution brain images acquired with a gradient-echo pulse sequence depicted a number of dark lines of varying thickness that could not be seen when the usual spin echo sequences were used. Their findings referred to a contrast mechanism reflecting the blood oxygen level. A change in haemodynamics produces small alterations in T1, T2 or T2*, which can be visualized as a change in MR image intensity. The pioneering work of Ogawa and co-workers stimulated the interest in the application of BOLD fMRI to humans. Initial studies reported about MR-detectable changes in cerebral blood volume using high-speed echo planar imaging techniques and exogenous paramagnetic contrast agents (gadolinium) (Rosen et al., 1991). One year later, three groups obtained the first results in humans applying the BOLD mechanism without the use of exogenous contrast agents (Bandettini et al., 1992; Kwong et al., 1992; Ogawa et al., 1992). One ought to be aware that BOLD responses can only measure haemodynamic changes, such as alterations in

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flow, blood volume, or intravascular magnetic susceptibility, leaving many open questions concerning the relationship between such cerebral haemodynamic changes and actual neural activation. It has been shown that BOLD contrast depends not only on blood oxygenation but also on cerebral blood flow and volume, representing a complex response controlled by several parameters (Boxerman et al., 1995; Buxton and Frank, 1997; Ogawa et al., 1998). To study the relationship between the BOLD signal and its underlying neural activity, Logothetis and co-workers (2001) did pioneering work. They examined in the visual cortex of monkeys the degree of correlation of the haemodynamic response to single- and multi-unit activity (MUA), as well as to local field potentials (LFP) of the stimulus. For the majority of recording sites, the BOLD signal was found to be a linear but not time-invariant function of LFPs, MUA, and the firing rate of small neural populations. Largest magnitude changes were observed in LFPs. At recording sites characterized by transient responses this was the only signal that significantly correlated with the haemodynamic response. The authors concluded that BOLD activation may actually reflect more the neural activity related to the input and the local processing in any given area, rather than the spiking activity commonly thought of as the output of the area. Interestingly, fMRI experiments may reveal activation in areas in which physiological experiments find no single-unit activity (Logothetis, 2003). Developing successful fMRI experiments is a complex undertaking, requiring careful attention to experimental design, data acquisition techniques, and data analysis (Chein and Schneider, 2005). The experimental paradigms that have been used for fMRI research can be categorized into one of two broad design classes, blocked and eventrelated. In a blocked design, each of the task conditions comprising an experiment are performed for an extended period of time that is typically longer than the evolution of the haemodynamic response. Due to the additive nature of the haemodynamic response, this blocking of tightly spaced trials produces roughly homogeneous periods of fMRI signals attributable to the specific experimental conditions. In contrast, event-related designs aim to characterize the transient changes in fMRI signals that result from individual trials. The major dimension of variation in event-related designs is the rate at which events are presented, and therefore, the extent to which the haemodynamic response evoked by neighbouring events will overlap. Using event-related designs it is possible to randomly intermix trial types. Hence, trials can be presented in an unpredictable order, which implies that the confounding effects of habituation and anticipation are reduced. Furthermore, event-related designs allow us to separate sub-processes within multi-componential trials. The advantages and disadvantages of blocked designs vs. event related designs were critically discussed by Chein and Schneider, 2005 (see also Buckner, 1998; Josephs and Henson, 1999; Rosen et al., 1998).

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6.2. Combined studies A most challenging approach is to combine neuronal data from multiple methods. This multi modality approach raises some fundamental questions on data fusions when combining (i) high-quality localization information provided by the haemodynamic-based brain imaging methods PET and fMRI with high-quality temporal data generated by electrophysiological techniques such as electroencephalography (EEG) and magneto encephalography (MEG) (Dale and Halgren, 2001; Horwitz and Po¨ppel, 2002) and (ii) when combining fMRI-activation maps with neurotransmitter transporter availability as measured with PET (Alpert et al., 2003; Lotze et al., submitted for publication). 6.2.1. Combined fMRI/PET and EEG/MEG data Methods based on PET and fMRI have a good spatial resolution but are limited in terms of time resolution, the former because scanning requires 45–90 s to accumulate a sufficient number of counts for statistically meaningful image data (Fox et al., 1984; Silbersweig et al., 1993), the latter, because the physical on and off half-times of the recorded signals are measured in seconds. In contrast, MEG has an excellent temporal resolution but has a poor spatial localizing power (Ro¨sler et al., 1995). One can argue that when the spatial resolution of fMRI and PET technology is combined with the good temporal resolution that is possible with MEG techniques, specific functions and sub functions can be related to distinct anatomical structures in the human brain, thus allowing a number of unresolved issues about the functional architecture of cognitive, motor and emotional processes to be addressed. A critical issue is that the complexity of the brain with its many interacting elements makes it difficult to interpret whether or not two findings based on methods with different spatial and temporal components do or do not match with each other (Horwitz and Po¨ppel, 2002). For instance, as yet we do not have a solid understanding of the underlying neural substrates of fMR activations, nor of specific EEG/MEG components nor on how the cortical reorganization of a focal lesion affects the complex neural networks of the brain. Therefore it is difficult to say whether, e.g., a statistically highly significant Z score obtained with fMRI or PET in area A and a large negativity at 200 msec in this area after stimulus presentation actually correspond to the same thing. Horwitz (2004) critically discussed three different approaches of combined data acquisition: (i) converging evidence across recording techniques, i.e. repeating the experiment using different recording techniques (see, e.g., Disbrow et al., 2001), (ii) direct data fusion whereby two data sets are directly combined using mathematical/ statistical algorithm (see, e.g. George et al., 1995) and (iii) computational neural modelling which implies to construct a computational biologically realistic neural network model that can perform the cognitive tasks under consideration (Horwitz et al., 1999, 2000).

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6.2.2. Combined fMRI-activation/PET neurotransmitter transporter availability studies Functional activation studies using PET and fMRI are a useful tool to describe changes in cerebral blood flow (CBF) elicited by cognitive tasks. But these studies do not provide any information about the underlying neurochemistry. One would expect an interaction between changes in CBF and neurotransmitter activity: cognitive activation increases neuronal firing rate, increasing the endogenous neurotransmitter level (Alpert et al., 2003). Hence, a most challenging approach is not only to identify the regions of the brain that are activated by a stimulus, but also to identify the neurotransmitter systems that mediate these responses (Alpert et al., 2003; Coull, 1998; Granon et al., 2000; Kahkonen et al., 2001; Lotze et al., submitted for publication; Lawrence et al., 1998). Most recently, Alpert et al. (2003) described a new approach using PET, a single-scan session design, and a linear extension of the simplified reference region model (LSSRM) that accounts for changes in ligand binding induced by cognitive tasks or drug challenge. In the LSSRM, an ‘‘activation’’ parameter is included that represents the presence or absence of change in apparent dissociation rate. Activation of the neurotransmitter is detected statistically when the activation parameter is shown to violate the null hypothesis. The authors conducted an experiment to confirm the predictions of simulation using 11 C-raclopride and a motor planning task. Image analysis was performed using a combination of ROIs, parametric imaging of transport, binding potential, areas of significant dopamine release, and statistical parameters. Results showed that maximum dopamine release occurred immediately following task initiation and thereafter decreased with a half-time of about 3 min (Alpert et al., 2003).

Fig. 3. Example of a combined fMRI-activation/PET neurotransmitter transporter availability study. Parkinson patients showed marked decreases of PET–DTA; DTA correlated negatively with motor deficits and mistakes in gesture recognition. DTA = dopamine transporter availability measured with [11C] Ritalin PET (Lotze et al., submitted for publication).

The significance of the basal ganglia for expressive gesture perception in patients suffering from Parkinson’s disease and in normal controls (Lotze et al., submitted for publication) was evaluated. We compared their fMRI-activation maps and mistakes in recognition of expressive gestures. In addition, we measured the decrease of dopamine transporter availability (DTA) with [11C]-methylphenidate PET. Our results indicate that DTA in the putamen was negatively correlated with gesture recognition, the Hoehn and Yahr score, emotional valence ratings and the fMRIBOLD effect within the putamen during observation of expressive gestures (Fig. 3). 6.3. Advantages/disadvantages of fMRI over PET One major advantage of fMRI over PET is that this technique does not need radioactive tracers, which is of value especially in studies with repetitive measurements, follow-up investigations, or in paediatric indications. A further advantage is a better spatial and time resolution: the in-plane resolution of the functional image is generally about 1.5 · 1.5 mm although resolutions less than 1 mm are possible, whereas state of the art PET scanners have a spatial resolution of about 4 mm full width at half maximum. Furthermore, the total scan time required by fMRI can be very short, i.e., in the order of 1.5–2.0 min per scan (depending on the paradigm), whereas with PET this is in the range of 15–30 min and can be even longer depending on the indication and radiotracer used. In addition, fMRI does not require an additional scan to allow for neuroanatomical correlative information, which is essential in stimulation studies with PET. Last but not least, the fMRI studies are also cheaper than PET studies, as no expensive PET tracer and staffing has to be used. Apart from the aforementioned advantages of fMRI over PET, there are also disadvantages. This applies especially to certain research areas, like, e.g., sleep research (Otte et al., 2002). Here, fMRI has rarely been applied. Potential reasons for this may be safety concerns of the patients, the magnet disrupting EEG signals, the noise of the scanner, and the inconvenient sleep condition in the scanner. Portas et al. (2000) reported a successful fMRI study on auditory processing across the sleep wake cycle in healthy subjects. In this study, however, sleep propensity was increased via 24 h sleep deprivation prior to the acquisition to ensure that subjects would sleep with their heads restrained in the noisy MRI scanner environment. This shows the limitation of fMRI only to study sleep in certain applications. By contrast, PET imaging has been more frequently applied, as patients can be injected with the radiopharmaceutical, while they are sleeping, and scanned at a later time, while they are awake. In addition, PET scans can capture the exact sleep stage of interest by simultaneous polysomnography (PSG) monitoring: After the sleep stage of interest is stable in the PSG, the tracer is injected. Given the favourable tracer logistics in terms of brain uptake (for example, about 20–30 min for 18F-FDG),

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most of the patient studies do not have to be discarded after injection, unless the post-injection PSG-monitoring indicates this within the tracer-specific timeframe. Similar constraints with fMRI may be found, e.g., in auditory stimulation studies (Seifritz et al., 2001), and in studies on deep relaxation and trance induction (e.g., Halsband, 2004). 7. Image analysis 7.1. Background Image analysis has gone through many changes during the past years. Whereas the visual image analysis may still be found at some places in clinical routine, new techniques, among them the region-of-interest technique and the statistical parametric mapping (SPM) method, have been introduced enabling an objective and observer-independent state-of-the-art diagnostics. Although standardization of imaging procedures is essential, it is not yet established everywhere. One explanation for this may be that recently described procedures use either in-house developments of restricted access or commercial software not available (as not affordable) at all institutions. By contrast, the software package SPM by Friston et al. (1995a,b) is freely available to the public and has gained a high general recognition. SPM also allows for exact anatomical localization by normalization to the internationally accepted stereotaxic atlas by Talairach and Tournoux (1988). Clinical use of SPM for automated voxel-based quantification usually includes the comparison of individual PET data with a group of normal controls and utilizes a standard morphological template (‘‘standard brain’’) for the visualization of results. However, massive alterations of brain structure in the course of several diseases (e.g., focal atrophy, tumour or surgical lesions) can lead to misinterpretation of functional effects caused by their lesions. Thus, the ‘‘standard brain’’ template is of limited applicability in many cases of pathological change. Therefore, the individual morphological information gained by 3-D MRI image fusion should also be taken into consideration. This also helps to reach a better understanding of the correlation between function and individual morphology. In this context, the recently developed PET–CT scanners may play an important role not only for oncology but also in neurology and psychiatry. 7.2. Visual interpretation In previous research days but often also nowadays in the clinical routine with lack of time, the visual interpretation of functional neuroimages was or is utilized. Routine image software offers many colour and grey scales for the user, and projections in transaxial, sagittal and coronal planes are semi-automatically reconstructed. Grey scales usually show large pixel values in white and small pixel values in

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black, and all intermediate values through a series of shades of grey. Grey scales offer the advantage of reducing the bias in the reader’s perception, as differences in pixel values and in perception between the associated grey values are similar. Nevertheless, many observers prefer colour scales, as they can highlight relevant differences and remove differences of no interest. However, by doing so, one should always be aware that colour scales may be misleading, as the visual perception of two colours might differ much more than the visual perception of two different shades of the same colour, even though the differences in absolute pixel value might be the same. Therefore, subtle changes may remain undetected upon using colour scales. A further ‘‘tool’’ in visual image interpretation is increasing the slice width, which can help decrease image noise, but also degrades the spatial resolution. Whatever the re-orientation and display regimen is in visual interpretation, the methods used should be consistent to rule out confounders by different image displays. The interpretation of the images, even if more than one physician looks at them (so-called consensus meetings), remains, however, observer- and training (experience)dependent. The subsequent variability in the interpretation of brain images also helped to convey research results in certain diseases which at later stages using objective quantification devices had to be revised. Especially in court, with referees relying on only visually interpreted brain images, this can have dramatic impact. Of course, the visual interpretation may always remain the first diagnostic step for the specialized physician; however, in cases of any uncertainty it should always be supplemented by quantification: if not an observer-independent statistical parametric mapping method at least using region-of-interest technique. 7.3. Region-of-interest (ROI) technique Nearly all SPET or PET camera suppliers offer software for ROI technique. With this technique, regions (circular, elliptical or irregular) can be drawn manually or semi-automatically by a software algorithm in brain regions which are of interest for the investigator to reach his or her diagnosis. Standard software normally offers a left-to-right hemisphere and anterior-to-posterior comparison showing maximum, minimum and average count rates and pixel number and size (semi-quantification). For special research projects the standard ROI software is not sufficient. In these cases, templates can be created by the user, which then semiautomatically are retrievable for all brain studies of interest. The ROIs of these templates can also be programmed to be normalized to, e.g., the global uptake at mid-brain level. This enables the comparison of relative uptakes of special regions, e.g., the right thalamus, over all patients and controls of a certain research study. As for visual image interpretation, all images for ROI analysis should first be spatially re-oriented into a standard

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space. For further semi-quantitative analysis, this image registration should be performed more accurately than with the images subject to visual interpretation, so that predefined ROIs can be used and similar pixels in all images refer to identical locations in the brain. By carefully selecting the standard space, the results of different inter- and intra-subject studies can then be compared and linked to functional brain atlas coordinate systems. 7.4. Statistical parametric mapping (SPM) The recent software package from the Wellcome Department of Cognitive Neurology, London, known as SPM (versions SPM’94 and SPM’95, SPM’96, SPM’99, and SPM2, which are all based on SPM’94) has helped in the standardization of measurement and data analysis in functional neuroimaging. Generally, its idea is based on the ROI technique with the difference that the regions-ofinterest are now voxels in a standardized stereotaxic room. This software not only spatially normalises PET, SPET or fMRI images to the standardized stereotaxic atlas of Talairach and Tournoux (1988), but can then also perform statistical analyses on study groups on a voxel-by-voxel basis (Friston et al., 1991, 1995a,b); this allows for reliable and objective image handling that could improve inter-study variability due to the analytical process itself. An example of SPM used in PET taken from Otte (2001) is given in Fig. 2A. The various versions of SPM and a detailed description of the procedure can be retrieved from the following internet homepage for free: http://www.fil.ion.ucl.ac.uk/spm/. 7.5. Image fusion Co-registration in 3D space of PET (or SPET) and MRI and of PET (or SPET) and CT image volumes has become a matter of routine in the analysis of functional brain images (Myer, 2002). Consequently, this image fusion has contributed to a better effective resolution of PET and SPET imaging. The freely available co-registration algorithm named Automatic Image Registration (AIR 3.08, Woods et al., 1998) is a widely accepted and thoroughly evaluated standard for multimodality co-registration procedures. Accuracy using this algorithm has been proven to be at least acceptable for clinical use with maximum mean errors in co-registration not larger than 1.7 mm in any direction (Kiebel et al., 1997). As recently postulated (Juengling et al., 2000), we think that for any clinical diagnosis a proposal for a standardized procedure using a functional and a structural imaging device should include: • Inter-modality co-registration using AIR. • Anatomical realignment according to the Talairach coordinate system.

• Single versus normal data base comparison using SPM creating statistical parametric maps. • Interpretation of the results in the context of the clinical findings. Newly emerging hardware such as the aforementioned combined PET/CT scanners may prove the worth of image fusion software. The discussion in the field of neurosciences on the question of whether the post hoc software approach (image fusion) or the ad hoc hardware approach (combined PET/CT scanning) should be favoured is still ongoing, and a conclusion is certainly not yet reached. However, it has to be mentioned that despite all of the efforts of PET/CT only a few units over the world have introduced this very expensive new technique into their routine. Hence, for the time being most institutions still have to rely on the established image fusion software. A further advantage of image fusion software over PET/CT is its flexibility of fusing multiple imaging modalities with PET or SPET as well as image fusion over time, both of which will be increasingly important for PET- or SPET-based molecular and metabolic imaging. At least in brain disorders where there are no severe anatomical alterations, the value of PET/CT or even SPET/CT may be revisited. 7.6. Network analysis The term ‘functional connectivity’ has been used to describe correlations of activity between neural elements and brain imaging (Friston et al., 1993). However, one confounder of effective connectivity is that inter-regional covariances may be influenced by direct interactions, indirect interactions or common influences. The application of structural equation modelling to brain imaging data has been proposed in order to differentiate between these influences (Horwitz et al., 1999, 2000; McIntosh and GonzalesLima, 1991, 1992; McIntosh et al., 1994). Structural equation modelling is a data-analysis technique allowing one to assess the numerical value or weight that each path in a given model should have for the model to account for the observed patterns of covariances. It is important to recognize that the use of structural equation modelling (McIntosh et al., 1994) allows functional interactions between brain regions, and not just the levels of activity, to be ascertained during a task. Using PET we applied this technique in a verbal episodic memory task during encoding or retrieval of visually presented semantically unrelated paired word associates (Krause et al., 1999). 15O-butanol was used as a tracer of rCBF. Anatomical connections between brain areas were based on known anatomy. Structural equation modelling was used to calculate the path coefficients representing the magnitudes of the functional influences of each area on the ones to which it is connected by anatomical pathways. The encoding and the retrieval network was found to elicit similarities in a general manner but also differences. Strong functional

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linkages involving visual integration areas, parahippocampal regions, left precuneus and cingulate gyrus were found in both encoding and retrieval; the functional linkages between posterior regions and prefrontal regions were more closely linked during encoding, whereas functional linkages between the left parahippocampal region and posterior cingulate as well as extrastriate areas and posterior cingulate gyrus were stronger during retrieval. Findings support the idea of a global bihemispheric, asymmetric encoding/ retrieval network subserving episodic declarative memory (Krause et al., 1999; see Krause et al., 2006).

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