Technical aspects of amyloid imaging for Alzheimer's disease
© BioMed Central Ltd 2011
Published: 31 August 2011
[11C]Pittsburgh Compound B positron emission tomography has now been extensively used to evaluate the amyloid load in different types of dementia and has become a powerful research tool in the field of neurodegenerative diseases. In the present short review we discuss the properties of amyloid imaging agent [11C]Pittsburgh Compound B, the different modalities of molecular imaging, image processing and data analysis, and newer amyloid imaging agents.
Alzheimer's disease (AD) is the leading neurodegenerative disorder and accounts for approximately two-thirds of dementia. AD affects around 10% of people above the age of 75, and in the United States approximately 4 million people suffer from AD-related dementia with annual associated costs estimated to be approximately $100 billion.
The diagnosis of AD currently depends on patients having impairments in memory function and at least one other cognitive domain, to the extent that it impairs daily function. AD is a clinical diagnosis mainly based on NINCDS-ADRDA criteria  and DSM-IV criteria . These criteria were revised recently by the international working group for new research criteria for the diagnosis of AD . The cardinal features are late-onset impairment of short-term recall [4, 5] associated with deterioration of language and visuo-spatial functions [6, 7] in the absence of disturbance of consciousness and systemic disorders. A postmortem diagnosis of AD is based on the presence of extracellular senile plaques positive for β-amyloid protein (Aβ), dystrophic neurites, and intracellular neurofibrillary tangles in the brain. Neurofibrillary tangles contain a hyperphosphorylated form of the microtubule-associated protein, tau, and also ubiquitin . Amyloid plaques are composed of 40 to 42 amino acid Aβ-folded peptides. Two types of amyloid plaques are present in neurodegenerative diseases: one with a central core and radiating fibrils, the fibrillar amyloid; and second, the diffuse (amorphous) amyloid. A small degree of AD-like pathology can be found in cognitively normal individuals over the age of 75 but large deposits of amyloid suggest AD.
Until a few years ago, magnetic resonance imaging (MRI) and cerebral blood flow studies were the only methods by which we could gain information about the changes in the living human brain. Structural MRI and blood flow studies, however, depend on gross changes in brain structure and function that suggest gross atrophy or a functional alteration that has already occurred. These markers are thus secondary phenomena and are therefore not the primary targets for following patients over a period of time or for diagnosing very early and subtle changes. Clinico-pathological studies suggest that neuronal loss has already occurred by the time gross atrophy is detected by MRI. Positron emission tomography (PET) with [18F]fluorodeoxyglucose adds to the diagnostic and prognostic accuracy in the clinical evaluation of AD , but the technique still detects an indirect measure of disease presence or progression.
Modification of the polar amyloid binding histological dye, thioflavin T, led to the finding that neutral benzothiazoles bind to amyloid with high affinity and additionally cross the blood-brain barrier . The benzothiazole amyloid binding agent 2-(4'-methyl-aminophenyl)-benzothiazole and related compounds bind to amyloid with low nanomolar affinity, enter the brain in amounts sufficient for imaging with PET and clear rapidly from normal brain tissue [11, 12]. At the low nanomolar concentrations typically administered during PET studies, 2-(4'-methyl-amino-phenyl)-benzothiazole binds to extracellular amyloid plaques in postmortem brain slices but not to intracellular neurofibrillary tangles. In vitro studies suggest that, while 2-(4'-methyl-amino-phenyl)-benzothiazole binds to fibrillar Aβ deposits found in the cortex and striatum, it does not bind to amorphous Aβ deposits found in the cerebellum.
A hydroxylated derivative of benzothiazole, N-methyl-[11-C]2-(4'-methylaminophenyl)-6-hydroxybenzothiazole - widely known as [11C]Pittsburgh Compound B ([11C]PIB) - has been synthesised as a PET tracer and studied in humans. An initial study showed that [11C]PIB shows a significant uptake in AD subjects compared with the control subjects . Following this initial study, several other studies have shown similar findings in AD and in other dementia [14–16]. Postmortem studies have shown a direct correlation between Aβ plaque and in vivo [11C]PIB retention measured by PET imaging. Studies have shown that the fluorescent PIB analogue 6-CN-PIB labelled Aβ-containing structures, including compact/cored, diffuse, neuritic and non-neuritic Aβ plaques. 6-CN-PIB also labelled vascular amyloid, but no signal was detected in neurophil threads or dystrophic neurites and a signal was only detected sporadically on an extracellular ghost tangle. A patient who underwent postmortem neuropathological examinations 10 months after [11C]PIB PET imaging demonstrated that in vivo retention correlated directly with postmortem quantification of PIB and Aβ plaque load but not with neurofibrillary tangle or other neurofibrillary pathology .
In the present article, a review of the technical aspects of amyloid imaging for AD will be presented. We therefore first introduce the general procedure for in vivo molecular imaging in man using PET. We then go on to describe image processing and data analysis.
Molecular imaging in man
The basis of tracer imaging is the detection by external devices of the radiation emitted from the radiolabel attached to the tracer injected into humans. In most cases, the nuclear disintegration of the radioisotope is detected via registering photons that are either uncorrelated (hence single-photon imaging) or that are paired as the result of positron annihilation. This imaging technique is then known as coincidence imaging or positron imaging, and is schematically shown in the scan box of Figure 1. A pair of photons resulting from the annihilation of a positron generated by the conversion of a proton in the nucleus is recorded as a line of response by the PET scanner. Tomographic image reconstruction techniques are subsequently employed to reconstruct a dynamic sequence of emission images from the brain scan . Today, PET scanners operate in three-dimensional mode, covering the entire brain in a single scan with an axial field of view of at least 15 cm. Modern PET scanners are usually combined PET/computer tomography systems as they include an integrated X-ray computer tomograph for the acquisition of photon attenuation images required for the correction of the PET images for the effects of photon attenuation and scatter. Combined PET and MRI systems are just emerging that combine the excellent contrast between grey and white matter provided by the magnetic resonance acquisition with the molecular images of the PET study.
The most widely used method for the reconstruction of quantitative brain images using PET is filtered back projection, an analytical image reconstruction method. Filtered back projection is computationally fast and has linear properties, which means the precision of the reconstructed images is independent of the location within the image and of the intensity of the object. Iterative image reconstruction, on the other hand, is computationally expensive and often only slowly converging and in an object-dependent manner. Iteratively reconstructed images are visually more appealing, because they do not exhibit the streak artefacts typical for filtered back projection reconstructed images. As the iterative image reconstruction allows one to more accurately model the entire imaging process, resolution effects can be included in the system description - images with higher spatial resolution than those from filtered back projection can therefore be obtained.
Image processing and data analysis
The purpose of tracer kinetic analysis (centre top box in Figure 1) is to disentangle the different processes that jointly result in the tissue response curves obtained . For amyloid imaging studies, the contributions to consider are as follows. First, tracer delivery and washout - as the amyloid imaging markers currently used (for example, [11C]PIB, [18F]FDDNP, [11C]SB-13, [18F] BAY94-9172 and florbetapir ([18F]AV-45)) are thought to cross the blood-brain barrier by passive diffusion, the delivery to and washout from brain tissue of these radiotracers is governed by cerebral blood flow. A second contribution is specific binding - the association, and dissociation for reversibly binding ligands, of the radioligand with the target (that is, Aβ). Another contribution is nonspecific binding - referring to any nonsaturable binding that occurs to other sites than Aβ (for example, to membranes or lipid fractions). A fourth contribution is radiolabelled metabolites - several of the [18F]-labelled radiotracers used for amyloid imaging have been reported to form radiolabelled metabolites in vivo that are also able to cross the blood-brain barrier ; part of the radioactivity signal measured in brain tissue is therefore due to the contamination with radiolabelled metabolites. Finally, vascular activity - owing to the spatial resolution of the positron cameras of several millimetres, any VOI defined in the brain contains a few per cent blood volume; the spill in of activity from the vasculature therefore needs to be accounted for.
A variety of modelling approaches exists and they have been applied to amyloid imaging studies with [11C]PIB. These approaches range from compartmental models , through graphical analyses such as Logan plots  or Patlak plots [26, 27], to spectral analysis  and reference tissue models [29, 30]. In reference tissue models, the tissue time-activity curve of a region without specific binding is used as a substitute for the plasma input function. For studies of sporadic AD the cerebellar grey matter is widely used as a reference region because postmortem investigations confirmed negligible concentrations of Aβ in cerebellar grey matter in this disease. However, careful validation of the reference region is required for each disease population.
One of the commonly used methods of analysis is the target to cerebellar ratio, commonly referred to as the RATIO method. Different groups have used different time points to create RATIO images from 40 to 60 minutes, from 40 to 70 minutes and from 60 to 90 minutes. These different time points largely give comparable results, however - and at later time points, while the signal increases, the noise also increases. Again, in different studies, different RATIO values have used as cut-off points [31, 32]. Some studies have used a strict cut-off value of two standard deviations above the control mean for individual regions, while other studies have used much more liberal cut-off values and a RATIO value of 1.4 or even 1.5. Even though different scanners differ slightly, it is generally accepted that a RATIO value above 1.5 is clearly abnormal.
Statistical parametric mapping
The statistical parametric mapping (SPM) method of analysis is an approach used to localise significant changes in brain physiology or pharmacology. This localisation is achieved by applying the general linear model to all independent voxels and creating an image of a statistic. SPM refers to the construction of spatially extended statistical processes to test hypotheses about regionally specific effects. SPMs are image processes with voxel values that are, under the null hypothesis, distributed according to a known probability density function (usually Gaussian). These statistical parametric maps are three-dimensional projections of statistical functions that are used to characterise significant regional brain differences in imaging parameters. The theory of Gaussian fields is used to provide P values that are corrected for the brain volume analysed [34, 35].
To implement voxel-based analysis of imaging data, the data from different subjects must derive from homologous parts of the brain. Spatial transformations are therefore applied that move and warp the images such that they all conform (approximately) to some standard brain. This normalisation facilitates intersubject averaging. The normalising transformations can be computed on the basis of the PET data themselves on the basis of co-registered high-resolution anatomical MRI. Convolving the data with a smoothing kernel has several important objectives. First, it generally increases the signal relative to noise. Second, convolving with a Gaussian kernel conditions the data to conform more closely to a Gaussian field model, even though this reduces spatial resolution.
The aim of the analysis is to identify areas of cerebral [11C]PIB binding that were significantly different in patients compared with the controls. Significant differences between patients and control subjects were estimated according to the general linear model at each and every voxel . Comparison between patients and controls as groups was performed without using analysis of covariance. Linear contrasts were used to test the hypotheses for specific focal effects. The resulting set of voxel values for each contrast constitutes a statistical parametric map of the t statistic SPM[t].
Newer amyloid tracers
A fluorinated derivative of PIB, [18F]flutemetamol, is now being developed and studied . Since the half-life of this compound is considerably higher than carbon-11 compounds, a cyclotron is not necessary for routine studies as this could be manufactured at one site and could be distributed. [18F]Flutemetamol is analysed using the target to cerebellar ratio similar to [11C]PIB . Other fluorinated compounds widely tested for amyloid imaging include [18F]AV-45 [39, 40] and florbetaben . A head-to-head comparison of [18F]AV-45 against [11C]PIB is now underway. Several other imaging agents are also in development.
This article is part of a review series on Amyloid Imaging. Other articles in the series can be found online at http://alzres.com/series/amyloidimaging
high-performance liquid chromatography
magnetic resonance imaging
positron emission tomography
Pittsburgh Compound B
statistical parametric mapping
volume of interest.
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