British Journal of Radiology (2007) 80, S109-S114
© 2007 British Institute of Radiology
doi: 10.1259/bjr/63830887
Imaging of mild cognitive impairment and early dementia
N SCHUFF, PhD
and
X P ZHU, PhD, MD
University of California and Center for Imaging of Neurodegenerative Diseases Veterans Affairs Medical Center, San Francisco, California, USA
Correspondence: Norbert Schuff, 4150 Clement Street 114M, San Francisco, CA 94121, USA. E-mail: norbert.schuff{at}ucsf.edu
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Abstract
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The concept of mild cognitive impairment (MCI) has been introduced to describe older individuals who cognitively lie between normal ageing and dementia. Nowadays, there is a particular interest in MCI because this syndrome is thought to be a transitional stage to Alzheimer's disease (AD) that may define a window for effective therapeutic interventions. However, not all patients with MCI will go on to develop AD. Imaging offers an extraordinary opportunity to study MCI. We will review key findings of brain imaging studies in MCI, including structural brain changes studied with MRI, white matter changes with diffusion tensor imaging and altered brain activity and blood flow studied with various imaging modalities, such as positron emission tomography, single-photon emission computed tomography and arterial spin labelling MRI, a non-invasive approach to measure cerebral blood flow. The strength and limitations of each modality for diagnosis of MCI, prediction of MCI outcome and assessment of drug efficacy will be discussed.
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Introduction
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The observation that some older individuals neither fit into the cognitive normal group nor fit into the dementia group dates back to the earliest epidemiological studies of ageing in England [1]. More recently, the concept of mild cognitive impairment (MCI) was introduced to describe those who cognitively lie somewhere in the middle [2]. Nowadays, there is a particular interest in MCI because this syndrome is thought to be a transitional stage to Alzheimer's disease (AD) that may define a window for effective therapeutic interventions with the prospect of slowing progression or even preventing disease. It has been estimated that the rate of transition from MCI to AD can reach 10–15% annually for amnestic MCI patients, i.e. those with dominant memory impairment [3]. The transition rate for non-amnestic MCI patients, who may have impairments in multiple cognitive domains, is less understood. However, not all patients with MCI will go on to develop AD. In some patients, the cognitive deficits will stabilize; in others, conditions may improve or progress to various types of dementia [4]. Any improvement to predict the outcome of MCI is invaluable for the counselling of patients, making therapeutic decisions and planning clinical trials. Imaging offers an extraordinary opportunity to study MCI, providing spatially detailed information on the extent and propagation of pathology in the living brain. Our goal in this article is to review key findings of imaging studies in MCI and discuss their potential diagnostic and prognostic values for dementia as well as their use in clinical trials. Specifically, we review structural brain changes studied with MRI, white matter changes with diffusion tensor imaging (DTI) and altered brain activity and blood flow studied with various imaging modalities, such as positron emission tomography (PET), single-photon emission computed tomography (SPECT) and arterial spin labelling (ASL)-MRI, a relatively new and non-invasive method to measure cerebral blood flow. New trends, such as amyloid PET imaging, are also briefly discussed.
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Structural changes studied with MRI
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The vast majority of structural brain studies in MCI have used MRI. Based on histopathological evidence that the entorhinal cortex (ERC) and hippocampus are early sites affected by Alzheimer's disease (AD), most structural MRI studies in MCI have focused on these two structures located in the medial temporal lobe. In early studies, manually delineating the anatomical boundaries of the two structures on MRI as depicted in Figure 1
, we found that MCI patients have a smaller ERC (11%) and hippocampus (13%) than normal elders whereas patients with mild AD have more prominent reductions in the ERC (37%) and the hippocampus (27%) [5]. Other studies obtained similar results, although reductions in MCI have been variously reported as being either intermediate between normal and AD [6–8] or as being similar to AD [9]. A larger hippocampal volume was also associated with better performance on tests of memory, general cognition and overall clinical ratings [10]. Furthermore, the rates of volume loss in the ERC and hippocampus are significantly higher in MCI patients than in control subjects [11, 12]. However, the ERC and hippocampal measures were similarly effective for the classification of MCI patients and control subjects [5], even though atrophy is expected to affect the ERC earlier than the hippocampus; however, the anatomical boundaries of the ERC are more difficult to delineate reliably using MRI. Recent advancements in computational anatomy, a new discipline of mathematical image analysis, offer further details of volume loss, including shape deformation [13, 14]. For example, Apostolova et al [15] found in a small group of MCI patients, who were clinically followed for 3 years, that those who converted to AD showed greater volume loss in the CA1 and subiculum subregions of the hippocampus than those who improved. Those with stable conditions had an intermediate loss. The profile of volume loss of CA1 and subiculum resembles typical histopathological findings of region-specific damage to the hippocampus in AD [16]. Similar computational methods have also been used to map volume loss across the brain. Using a technique termed voxel-based morphometry (VBM), several longitudinal MRI studies [17, 18] explored the spread of grey matter loss in MCI by scanning subjects multiple times for about 2–3 years. In general, grey matter loss initially encompassed the amygdala, anterior hippocampus and ERC, then spread to the entire hippocampus and parietal lobe, and eventually extended to the temporoparietal and even frontal lobe regions by the time the patients had converted to AD. This pattern is consistent with the spread of AD pathology evidenced by histopathology.
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Figure 1. RepresentativeT1 weighted images (1 x 1 x 1.4 mm3 resolution) showing the boundaries of the entorhinal cortex and hippocampus in cognitive normal (CN) subjects and an Alzheimer's disease patient (AD).
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Overall, these studies indicate the potential of structural MRI to identify MCI patients and measure progression. However, some structural measures are not disease specific, which undercuts their value for a differential diagnosis. For example, both ERC and hippocampal volumes are also diminished in frontotemporal dementia [19] and vascular dementia [20]. Consequently, volume loss in these regions will not conclusively separate AD from these other dementias. However, volume loss could still add invaluable information when used jointly with other imaging measures (DTI, perfusion MRI, PET, SPECT, etc).
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White matter changes studied with DTI
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Although AD has long been considered a grey matter disease, imaging of white matter changes in MCI and early AD has been gaining interest as evidence has grown for a more prominent role of white matter in AD. Conventional MRI yields insufficient contrast to discriminate fibre tracts in white matter, but DTI — a new MRI variant — is sensitivity to fibre integrity as well as orientation. Several studies reported significant alterations of DTI measures in the hippocampus [21, 22], thalamus [23], posterior cingulum bundle [22, 24] and several regions in posterior white matter [24] in MCI patients relative to control subjects. Moreover, regional-specific DTI changes were found to correlate with specific cognitive functions [25]. For example, DTI changes in temporal lobe white matter correlated with episodic memory, frontal changes with executive function and parietal changes with general cognition. We found that MCI patients had marked DTI abnormalities in multiple locations along the cingulum fibre bundle, including the posterior cingulate and parahippocampal regions [26]. Representative DTI maps showing fractional anisotropy, a measure of directional diffusivity of tissue water, are shown in Figure 2. The arrows indicate locations of posterior cingulate and the parahippocampal regions. The finding suggests that the connections between hippocampus and posterior cingulate, which are important for memory processing, can be affected in MCI. In the same study, we also found that a reliable separation between MCI and normal control subjects could not be achieved based on hippocampal volume loss alone (63% accuracy), whereas DTI measures significantly improved the classification (75% accuracy). DTI of the cingulum fibre bundle could therefore be a supplementary marker to hippocampal volume for the identification of MCI. Overall, the findings substantiate the involvement of white matter pathology in MCI.
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Figure 2. Representative diffusion tensor imaging(DTI) maps of fractional anisotropy (FA), a measure of the directionality of random water diffusion in brain tissue. Arrows point to regions of diminished FA signal in the parahippocampus (top row) and posterior cingulate (bottom) in mild cognitive impairment (MCI), indicating disintegration of white matter fibres. Note also the progressive thinning of fibre tracks in the corpus callosum from the control subject to MCI and then to the Alzheimer's disease patient (AD).
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Brain activity studies
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Altered cerebral glucose metabolism studied with PET
It is well established that by the time a patient presents with clinical symptoms of AD the cerebral metabolic rate of glucose consumption (CMRglu), a measure of brain activity, is already too severely reduced in some cortical regions to be detectable with [18F]-2-fluoro-2-deoxy-D-glucose (FDG)-PET. In MCI, however, FDG-PET findings of cortical deficits are controversial. Some PET studies found CMRglu reduction was readily detectable in the cortex in MCI [27, 28], whereas others reported PET measures were insensitive for MCI outside the hippocampal formation [29–31], particularly if there was minimal impairment [32]. In general, however, FDG-PET studies found substantial CMRglu reduction in MCI throughout a network of limbic structures, which included the hippocampus, medial thalamus and posterior cingulate [30, 33]. This profile of CMRglu reduction of the hippocampal formation in MCI is strikingly similar to the profile of volume loss seen with structural MRI [17]. The findings imply a tight concordance between diminished brain activity and volume loss. Cortical deficits were seen in MCI in a longitudinal FDG-PET study on 22 MCI patients who had PET scans twice within 1 year [34]. Converters to AD had at baseline lower CMRglu in the posterior cingulate cortex and precuneus than non-converters, whereas at follow-up the converters had CMRglu reductions bilaterally in prefrontal areas along with further progression of CMRglu reduction in the posterior cingulate cortex. Overall, FDG-PET findings in MCI conform to structural MRI findings of volume loss that the first signs of cognitive decline appear in the medial temporal lobe and then spread in a systematic pattern to the cortex as cognition declines.
Altered cerebral blood flow studied with SPECT
Cerebral blood flow (CBF) imaging with SPECT was one of the earliest methods to distinguish AD patients from control subjects. Nowadays, there is a huge body of SPECT literature on measurements in MCI and AD (for an excellent review see Johnson and Albert [35]). Reduced CBF in the parietal cortex as well as in the posterior cingulate cortex and precuneus has been observed in early AD [36, 37] as well as in MCI [38, 39]. Longitudinal SPECT studies showed high rates of CBF decline in the hippocampus and parahippocampus gyrus [39, 40] in MCI. In one longitudinal SPECT study, MCI converters had a substantial reduction of CBF in the bilateral superior parietal and medial temporal lobes compared with non-converters and control subjects within 29 months [40]. Interestingly, non-converters had increased CBF in the frontal lobe, insular and subcortical regions compared with control subjects, potentially indicating compensatory mechanisms of the brain as cognitive decline sets in.
Altered cerebral blood flow studied with ASL-MRI
There are several MRI techniques to measure CBF. More recently, ASL-MRI was introduced, which uses endogenous blood water as tracer for blood flow and thus is entirely non-invasive [41]. Compared with other methods, ASL-MRI gains its power from the unique possibility to obtain CBF maps repeatedly in short succession, thus enabling dynamic measurements of CBF. ASL-MRI studies in AD have demonstrated the same profile of CBF reductions as PET and SPECT [42–44]. Recently, ASL-MRI has also been used to study MCI, revealing CBF reductions in the right parietal lobe and precuneus compared with control subjects, similar to the profile seen with SPECT and PET in AD [43]. This pattern is shown in Figure 3. In another ASL-MRI study, changes of CBF and arterial transit time were assessed together in a small number of AD patients, MCI patients and control subjects [45]. Preliminary results from a region encompassing the posterior cingulate cortex and precuneus show marked CBF reduction in AD (59%) and MCI (43%) compared with control subjects as well as substantial prolongations of arterial transit time in AD (31%) and MCI (21%). Interestingly, CBF reduction and transit time prolongation were partially unrelated, suggesting that different causes may underlie these effects. More ASL studies on a larger sample of patients are warranted to determine the power of this method.
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Figure 3. Regions of significant reductions of cerebral blood flow by group analysis of(a) mild cognitive impairment (MCI) patients compared with control subjects and (b) patients with Alzheimer's disease compared with MCI. The clusters of significance are superimposed on a brain template. The brighter area in the template indicates the sensitive region for arterial spin labelling (ASL)-MRI measurements.
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Prediction of MCI outcome
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Prediction based on structural changes
Several groups have tested the power of structural MRI to predict conversion from MCI to AD, mostly focusing on volume measurements of hippocampus and ERC. In a prospective MRI study of 32 months' duration, in which 27 individuals of initially 80 MCI patients converted to AD, the hippocampal volume at baseline was associated with a moderate risk ratio of 0.69 for conversion [7]. In another prospective MRI study, in which 139 MCI patients were clinically followed for an average of 5 years, a smaller hippocampal volume (risk ratio (RR) = 2.21) and ERC (RR = 2.48) each predicted independently time to conversion to AD [46]. Compared with age and cognitive variables, however, the added value of hippocampal and ERC volumes was small in this study. More recently, MRI on 27 MCI patients, who had follow-up scans for 36 months, showed ERC volume was the best predictor for conversion of MCI to AD with an accuracy of 93.5% [47].
Predictions based on brain activity changes
Several FDG-PET studies have also examined the prognostic value of CMRglu reductions for MCI outcome. In prospective PET studies of MCI decline over several years' clinical follow up, temporoparietal CMRglu at baseline correctly predicted decline with an accuracy between 75% [28] and 100% [48]. In another study on 77 normal subjects who had follow-up PET scans after 7.2 years on average, hippocampal CMRglu at baseline predicted decline from normal to MCI with 71% accuracy and to AD with 81% accuracy (including two post-mortem confirmed cases) [49]. A prospective SPECT study on MCI patients reported CBF reductions of multiple regions, including the parietal and temporal lobes, and the precuneus and posterior cingulate, which used together accurately separated 100% converters from non-converters [50]. Overall, however, more data are needed to evaluate the value of imaging for determining the individual risk for future development of AD.
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New development of amyloid PET imaging
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Another promising development in imaging is the recent discovery of PET tracer compounds that enable detection of amyloid plaques in the living brain, one of the defining hallmarks of AD, previously only detectable at autopsy. MCI patients can have uptake of these tracers similar to AD [51, 52], suggesting that amyloid deposition occurs early and plateaus. Furthermore, converters from MCI to AD had a significantly higher uptake of the amyloid tracer in the posterior cingulum than non-converters [52]. However, some MCI patients show no tracer binding at all [53]. Amyloid imaging could therefore become useful for predicting the future disease course in at-risk elders. However, because the early amyloid burden spares the hippocampus, amyloid PET is unlikely to replace the need for imaging the hippocampal formation by other means. It is also not yet known whether these new PET tracers correlate more tightly than structural and functional imaging with cognitive decline. Nonetheless, the development of joint analyses using amyloid PET and structural and functional imaging measures together may accomplish greater predictive power than either structural or functional imaging can provide on its own.
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Clinical trials
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Recent studies suggest that imaging can be useful as a biomarker for pharmacological interventions. However, no single imaging approach is yet ideal, as all have trade-offs in accuracy, costs, availability and speed. MRI seems particularly suitable because the technology is widely available and highly effective for quantifying effects on brain structure. In the proper clinical context, MRI may also be more specific than FDG-PET or SPECT, because pharmacological treatment may modulate metabolism without slowing the rate of tissue loss. Several MRI studies indicate greater power to detect change over time with brain volume measures than standard cognitive assessment instruments, thus improving the efficiency with which clinical trials may be conducted [54, 55]. Significant work is now also being devoted to establish imaging protocols that are compatible across imaging centres and reproducible over time [56]. PET amyloid seems extremely promising in the study of drugs that are designed to prevent formation of amyloid plaques. A crucial need at this time, however, is longitudinal data regarding the rate of change of PET amyloid measures with disease progression.
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Conclusions
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A considerable body of data shows that several imaging modalities are sensitive to changes of early AD and MCI, and can offer meaningful diagnostic predictions as well as objective measures for therapeutic effects in clinical trials. In addition, each imaging modality reveals a typical profile of regional alterations that adds specificity for AD. Moreover, joint information from structural and functional (PET, SPECT, ASL-MRI) imaging can provide additional power for detection of disease. However, more data are needed to evaluate the value of imaging for determining individual risk for future AD, which is fundamental for the counselling of patients and making therapeutic decisions. Other imaging modalities, such as functional MRI [57] and magnetic resonance spectroscopic imaging (MRSI) [58] also show promise for aiding the identification of MCI. Overall, the advances in the early diagnosis of AD made possible by imaging are encouraging for improving diagnosis of the disease at an early stage and provide the rationale for early treatment.
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Acknowledgments
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We are indebted to Dr Michael W. Weiner, Director of the Center for Imaging of Neurodegenerative Diseases (CIND), for his scientific guidance and support. We thank Dr Yu Zhang of the CIND for providing the diffusion images.
Received for publication July 24, 2007.
Accepted for publication December 6, 2007.
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Abstract
Introduction
