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Review

Neuroimaging in dementia Vyara Valkanova, Klaus P. Ebmeier ∗ Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK

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Article history: Available online xxx Keywords: Dementia Alzheimer’s disease Lewy body dementia Fronto-temporal dementia Vascular dementia PET

a b s t r a c t Over the last few years, advances in neuroimaging have generated biomarkers, which increase diagnostic certainty, provide valuable information about prognosis, and suggest a particular pathology underlying the clinical dementia syndrome. We aim to review the evidence for use of already established imaging modalities, along with selected techniques that have a great potential to guide clinical decisions in the future. We discuss structural, functional and molecular imaging, focusing on the most common dementias: Alzheimer’s disease, fronto-temporal dementia, dementia with Lewy bodies and vascular dementia. Finally, we stress the importance of conducting research using representative cohorts and in a naturalistic set up, in order to build a strong evidence base for translating imaging methods for a National Health Service. If we assess a broad range of patients referred to memory clinic with a variety of imaging modalities, we will make a step towards accumulating robust evidence and ultimately closing the gap between the dramatic advances in neurosciences and meaningful clinical applications for the maximum benefit of our patients. © 2014 Elsevier Ireland Ltd. All rights reserved.

Contents 1. 2.

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Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Structural imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Alzheimer’s dementia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Fronto-temporal dementia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3. Dementia with Lewy bodies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4. Vascular dementia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Functional and molecular imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Alzheimer’s dementia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.1. Perfusion SPECT and FDG-PET imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.2. Amyloid imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Fronto-temporal dementia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3. Dementia with Lewy bodies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4. Vascular dementia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Competing interest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Funding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Provenance and peer review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Abbreviations: 123-I-FP-CIT, 123-I labelled ioflupane (DatSCAN® ); AD, Alzheimer’s dementia; bv-FTD, behavioural variant fronto-temporal dementia; CERAD, consortium to establish a registry for Alzheimer’s disease; CT, (X-ray) computed tomography; FTD, fronto-temporal dementia; LBD, dementia with Lewy bodies; lv-P, palogopenic variant PPA; MCI, mild cognitive impairment; MRI, magnetic resonance imaging; MTA, medial temporal lobe atrophy; NICE, National Institute for Health and Care Excellence; nv-PPA, non-fluent PPA; PET, positron emission tomography; PiB, Pittsburgh compound B; PPA, primary progressive aphasia; SPECT, single photon emission computed tomography; sv-PPA, semantic variant PPA; VBM, voxel-based morphometry; VD, vascular dementia; WMH, white matter magnetic resonance hyperintensities. ∗ Corresponding author. Tel.: +44 1865 226469; fax: +44 1865 793101. E-mail address: [email protected] (K.P. Ebmeier). http://dx.doi.org/10.1016/j.maturitas.2014.02.016 0378-5122/© 2014 Elsevier Ireland Ltd. All rights reserved.

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1. Introduction

an MTA score of 0 converted to AD, compared with more than 75% with baseline MTA score of 3.

Over the last few years, advances in neuroimaging have generated biomarkers, which increase diagnostic certainty, provide valuable information about prognosis, and suggest a particular pathology underlying the clinical dementia syndrome. This is an advance over the role imaging plays in simply excluding rare causes of dementia, such as mass lesions [1,2]. Although the use of specific biomarkers is generally limited to research studies, it is likely to translate into clinical practice with increased standardization and access to biomarkers. We aim to review the evidence for established imaging modalities, along with selected techniques that have the potential to guide clinical decisions in the future, focusing on the most common dementias: Alzheimer’s disease (AD), fronto-temporal dementia (FTD), dementia with Lewy bodies (DLB) and vascular dementia (VD). Discussion of other dementia syndromes and the theory behind the various imaging modalities is beyond the scope of this review. 2. Structural imaging 2.1. Alzheimer’s dementia In many centres, X-ray computed tomography is the standard investigation to exclude any space occupying and mass lesions. In fact, some authors have used this technique to estimate hippocampal atrophy and thus provide added information supporting the diagnosis of Alzheimer’s dementia [3]. However, the structural imaging technique most widely used in clinical research is T1-weighted magnetic resonance imaging (MRI). The most characteristic feature of AD is early, localized medial temporal lobe atrophy (MTA) affecting primarily the hippocampus and entorhinal cortex [4–8]. MRI evidence of disproportionate MTA has been incorporated into revised diagnostic criteria as a topographical marker of downstream neuronal injury [1,2]. In clinical practice visual assessment is used most often. One of the more widely validated rating scales is the Scheltens’ MTA rating scale [9], which assesses hippocampal atrophy according to the width of the choroid fissure, width of the temporal horn, and height of the hippocampus, using a 0–4 severity scale. Visual inspection differentiates mild AD from normal ageing with a sensitivity and specificity of 80–85% [9–11]. The specificity of MTA decreases with age because of age-related hippocampal atrophy [12]. In research studies, mainly volumetric techniques are used and they appear to correlate well with both neuropathological disease progression [13–15] and the degree of cognitive impairment [16,17]. Although MTA has been found in other dementias, including FTD, VD and PD, it is less severe there than in AD when matched for clinical severity [18,19]. Hippocampal atrophy develops gradually starting about 5 years before diagnosis of AD, while 3 years prior to diagnosis hippocampal volumes are reduced by 10% [19]. In atypical forms of AD, in younger patients, or early in the disease course it is possible to have greater atrophy of the parietal lobes and less MTA [20–25]. A rating scale based on the degree of widening of the posterior cingulate, parietal and parieto-occipital sulci has been developed [26]. Particularly in individuals with MCI, structural imaging provides valuable information about prognosis. Although the significant overlap in volumetric measures between patients with MCI and controls sets some limitations, a recent meta-analysis of 6 VBM studies found that decreased grey matter in the left hippocampus and parahippocampal gyrus was associated with conversion from MCI to AD [27]. Further, Lehmann et al. [28] found that the probability of converting from MCI to AD increased with greater baseline MTA scores; e.g. after three years, fewer than 40% of patients with Please cite this article in press as: Valkanova http://dx.doi.org/10.1016/j.maturitas.2014.02.016

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2.2. Fronto-temporal dementia FTD encompasses a heterogeneous group of conditions and can be broadly divided into behavioural variant fronto-temporal dementia (bv-FTD) and primary progressive aphasia (PPA). Bv-FTD is associated with predominant atrophy in the frontal and paralimbic areas, including the anterior cingulate cortex, as well as orbitofrontal and medial frontal cortices and subcortical structures [29–32]. Ratings of orbitofrontal atrophy in conjunction with an executive function test classified 92% of patients correctly into bvFTD or AD [33]. PPA is itself categorized into three clinical phenotypes: semantic variant PPA (sv-PPA), non-fluent PPA (nv-PPA) and logopenic variant PPA (lv-PPA). In semantic variant PPA, there is typically atrophy of the anterior and inferior temporal lobes, including the fusiform gyrus, while the non-fluent variant PPA is characterized by perisylvian atrophy and involvement of the anterior insula [31,34,35]. The logopenic variant PPA is commonly associated with Alzheimer’s type pathology and the atrophy involves the posterior temporal cortex and inferior parietal lobule [36]. In PPA the atrophy is more often asymmetrical, with the left side being more affected [31]. In addition to distinct patterns of regional atrophy that are associated with each clinical phenotype, rate of atrophy was found to be twice as great in FTD and SD, compared with AD [37]. However, in the early stages, functional imaging may be more useful because the structural scan can be normal [32,38]. The most recently published guidelines for FTD proposed, in addition to a clinical diagnosis, evidence for abnormalities on either structural or functional brain imaging as a criterion for establishing a diagnosis of ‘probable’ FTD [36,39]. 2.3. Dementia with Lewy bodies DLB is associated with diffuse atrophy, which is greater than in controls, but less than in patients with AD. Relatively focused dorsal meso-pontine grey matter atrophy, with a relative sparing of the medial temporal lobes, supports a clinical diagnosis of DLB rather than AD [40–42]. 2.4. Vascular dementia Evidence from structural neuroimaging is mandatory for diagnosing vascular dementia (VD), with MRI being the preferred modality. Small-vessel disease is the commonest cause of VD [43], although large artery ischaemic disease may lead to VD, as well. Small-vessel disease is usually defined as lesions involving >25% of the white matter. Signs of small vessel disease on MRI include white matter magnetic resonance hyperintensities (WMH), recent small subcortical infarcts, lacunes, prominent perivascular spaces, cerebral microbleeds and atrophy. Their defining features are summarized in an excellent paper aiming to provide standards for reporting vascular changes on neuroimaging (STRIVE [44]). Although white matter changes can be detected on X-ray CT scans, the tissue contrast tends to be discrete, and this method is less sensitive than MRI. White matter lesions appear as bilateral, mostly symmetrical hyperintensities on T2-weighted MRI. They become more common with advancing age and are found in 10–90% of cognitively normal elderly depending on the study. Although WMH are strongly associated with vascular risk factors, as well as predicting an increased risk of stroke and dementia [45], they are clinically and pathologically heterogeneous [46]. WMH are not specific to vascular dementia and can be found in a variety of other conditions Ebmeier

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including leucodystrophies, leucoencephalopathies, inflammatory conditions (multiple sclerosis) and infections [47]. The relationship between vascular damage and cognition is not fully understood, but it is increasingly recognized that whether cognitive deficits develop in the presence of vascular damage depends on the balance between factors conferring resilience (education, premorbid IQ) and risk (age, vascular risk factors, and lifestyle). However, as WMH become more extensive they are more likely to be clinically significant [48]. The severity of white matter disease can be graded visually using established scales such as the Fazekas scale [49]. Large irregular periventricular or confluent deep WMH (Fazekas grade 3) are characteristic of VD. Silent infarcts and lacunes are also common in healthy elderly people (between 20 and 50%), but they are associated with an increased risk of future dementia and stroke [50]. Although MRI is more sensitive than CT for detecting ischaemic injury, it was negative in up to 30% of patients with symptomatic lacunar stroke syndromes, suggesting that it cannot detect all infarcts [51]. Up to 65% of patients with VD and 10–20% of healthy elderly have microbleeds which on T2*-gradient echo image appear as focal hypointensities (typically 2–5 mm, but up to 10 mm) [52,53]. Microbleeds related to amyloid angiopathy most commonly have cortico-subcortical distribution, while microbleeds associated with hypertension are located centrally. The two conditions often coexist [54–56]. Patients with vascular dementia also have global atrophy, probably due to subclinical diffuse ischaemia, or focal atrophy corresponding to an area of infarction [57,58]. Finally, it is increasingly recognized that mixed pathologies are common. VD and AD share risk factors [59,60] and can have a synergistic relationship [61]. This implies that even when extensive vascular damage is suggested by a structural scan, the presence of mixed pathology should be considered.

3. Functional and molecular imaging 3.1. Alzheimer’s dementia 3.1.1. Perfusion SPECT and FDG-PET imaging Functional and molecular imaging has an important role in the neuroimaging of dementias. Changes in function and molecular composition of brain tissue typically precede atrophy detectable by structural imaging. Jack et al. [62] have suggested the dynamic biomarkers model of AD: at first markers of amyloidosis became positive, followed by markers of cortical hypometabolism on FDGPET, and last, markers of brain atrophy. The characteristic AD patterns of abnormal brain perfusion or metabolism are found in the association cortex while primary sensory-motor cortex is relatively preserved [63], with a ratio of association cortex activity over primary sensory-motor cortex activity being suggested as a diagnostic index for AD [64]. Early in the disease course, SPECT and FDG-PET show reduction in posterior cingulate and precuneus perfusion or metabolism, followed by bilateral posterior temporo-parietal reductions and involvement of the frontal areas in advanced disease [63–65]. The findings in functional scans correlate with CSF biomarkers [66], as well as with cognitive measures [67]. Perfusion abnormalities in AD-related regions are predictive of conversion from MCI to AD [68–70]. Hypometabolism was found even in cognitively normal individuals at increased risk of AD [71,72]. An autopsy-confirmed study found that SPECT improves the accuracy of the diagnoses, with a positive scan in patients with possible AD increasing the likelihood of pathologically confirmed AD from 67% to 84% [73]. A recent meta-analysis of 11 studies using SPECT and 20 studies using PET found pooled sensitivity of 80% and specificity of 85% for SPECT to differentiate patients with AD from controls, while PET showed pooled sensitivity of 90% and specificity Please cite this article in press as: Valkanova http://dx.doi.org/10.1016/j.maturitas.2014.02.016

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of 89% [74]. These results suggest that PET is more sensitive than clinical assessment in detecting AD (90% vs 81%), while both SPECT and PET are more specific than clinical criteria (85% and 89% vs 70%) [2]. However a prospective community-based study of 102 individuals with early-onset dementia found PET to have considerably lower sensitivity and specificity for AD (78% and 81%, respectively) than reported in the meta-analysis [75]. Although the results could be explained by sample characteristics (e.g. early-onset dementia), or the lack of pathological confirmation, this study highlights the significance of ecologically more valid research with ‘real’ world samples. It is also important to investigate the added value of imaging markers above a standard work-up, as well as how imaging markers perform in combination. A study of 154 memory clinic patients found that combined imaging (PiB and FDG-PET) led to change in 23% of the initial clinical diagnoses, while the diagnosis established after PET remained unchanged in 96% of cases after two years. Combined PiB and FDG-PET contributed to diagnosis in 104 cases, followed by PiB only (29 cases) and FDG-PET only (11 cases) [76]. While both PET and SPECT are good enough to assist in the differential diagnosis of dementia [63], SPECT is currently more widely available. This has been translated into guidelines, with NICE stating that ‘HMPAO-SPECT should be used to help differentiate between AD, VD and FTD if the diagnosis is in doubt’ [77]. 18F-FDGPET is included as a topographical biomarker of neuronal injury in the revised international diagnostic criteria for AD [1,2]. A recent review concluded that although studies suggest superiority of PET over SPECT, the evidence base for this is quite limited [78]. 3.1.2. Amyloid imaging Amyloid imaging provides direct evidence of the presence of Alzheimer’s type pathology. A␤ plaque markers become positive years before clinical symptoms and reach a plateau by the time these appear [62]. The best characterized amyloid PET tracer is Pittsburgh compound B (PiB) which is labelled with C-11 and binds mostly to fibrillar ␤-amyloid. Amyloid PET with PiB has very high sensitivity for detecting amyloid deposition. More than 90% of patients with AD show increased cortical binding [79], and false–negative cases are reported only rarely [80]. As a result, it has been included in the revised guidelines as a pathophysiological marker of AD [1,2]. Its positive predictive value is low, as some healthy elderly people show higher cortical binding. The reported proportions vary, but frequencies of 15–30% are most commonly reported. A␤ deposition is affected by the imaging method, the definition of what constitutes a positive result, and by the two main risk factors for AD, namely age and ApoE genotype [81,82]. The frequency of amyloid-positive scans increased from 0% below the age of 50 to 30% at age 80 [83]. Non-carriers of the allele were less than half as likely to have a positive scan as ApoE4 carriers (21% vs 49%) [84]. Independently of the effect of ApoE4, maternal familial history of AD has also been associated with higher cortical binding [85,86]. A major disadvantage for the clinical application of PiB PET is the short half-life of C-11, which limits its use to centres with an on-site cyclotron. However, over the last years tracers labelled with 18F such as Flumetamol, Florbetapir and Florbetaben have been developed. 18F has a longer half-life (110 min), allowing central production and distribution, which is already making amyloid imaging more widely available [87]. Clinical trials have demonstrated that the new 18F-compounds have properties similar to PiB. Comparative studies within the same subjects show excellent correlation between PiB and each of them [88–90], as well as similar effect sizes for distinguishing AD from healthy controls [89,91]. In a prospective phase 3 study with Florbetapir, the PET scan results of 59 patients were dichotomized and Ebmeier

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compared to their dichotomized CERAD neuritic amyloid plaque scores obtained from autopsy within 1 to 2 years of PET imaging. The study included healthy subjects, as well as patients with AD, VD and FTD, with a varying degree of cognitive impairment and found a sensitivity and specificity of PET for detection of moderate to frequent plaques of 92–96% and 100%, respectively [92]. Amyloid imaging has very good predictive value for conversion to AD in patients with MCI, as demonstrated in studies with up to 3 years follow-up [93–95]. Negative scans in individuals with MCI do not discount progression, as other neurodegenerative diseases without amyloidosis, such as FTD, cannot be excluded. Amyloid imaging is also excellent in differentiating AD from non-amyloid dementias such as FTD [96–98], and there is no uptake in most cases with PD dementia [99]. However positive scans are common in DLB [98,100,101] which is consistent with pathological findings [102]. This implies that amyloid imaging may be most useful in atypical presentations or in early-onset dementia, when the prevalence of AD equals that of FTD and the frequency of amyloid deposition in controls is low. Positive scan in cases with extensive vascular damage can confirm the presence of mixed pathology, which would have implications for treatment [103]. For instance, 31% of cases who met DSM-IV criteria for VD and had extensive WMH without large-vessel stroke or macro-haemorrhage were PiB positive [104]. 3.2. Fronto-temporal dementia The patterns seen on functional imaging in FTD tend to be similar to those seen on structural scans, but they are visible earlier in the disease course [105]. A study of 134 patients with suspected FTD found that SPECT/PET increased sensitivity of consensus criteria from 36.5% to 90.5%, when clinical diagnosis after 2 years was used as a gold standard [106]. Another study with pathologically confirmed diagnoses of FTD or AD also showed that PET increases diagnostic accuracy beyond clinical assessment [107]. Amyloid imaging in FTD confirms the lack of amyloid deposition in this condition, with patients showing values of cortical PiB retention close to those found in controls [108]. 3.3. Dementia with Lewy bodies There are few publications for perfusion imaging in DLB, but the typical pattern involves occipital reductions, including the primary visual cortices [109–111]. Although parieto-temporal reductions are observed in both AD and DLB, occipital hypometabolism differentiated between the two conditions with 90% sensitivity and 71–80% specificity [65,109]. Amyloid imaging in DLB shows levels of cortical PiB retention similar to those observed in AD, with higher occipital retention [100,112]. The most reliable imaging biomarker of DLB is 123-I-FP-CIT (ioflupane) SPECT of the dopamine transporter. Ioflupane shows asymmetrical (anterior-posterior) striatal uptake in DLB, with larger decrease of uptake in putamen than in caudate nucleus. In contrast, age-related nigro-striatal degeneration affects both the putamen and caudate nucleus, and the putamen-to-caudate ratio is preserved [113]. Normal ioflupane scans in patients with DLB are not common, but have been reported; it is possible that these patients have exclusive cortical involvement with relative sparing of basal ganglia [114]. Compared with autopsy results, dopamine transporter imaging is sensitive and specific (88% and 100%, respectively), whereas clinical diagnosis had a sensitivity of 75% and specificity of only 42% [115]. Abnormal ioflupane scans may be particularly valuable in the group of patients with possible DLB, as this seems to be an unstable diagnosis. A multi-centre study found that only 41% of patients with ‘possible’ DLB have this diagnosis at 12 months Please cite this article in press as: Valkanova http://dx.doi.org/10.1016/j.maturitas.2014.02.016

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follow up, compared with 93% of patients diagnosed with ‘probable’ DLB; scan results can help to classify them correctly [116]. Ioflupane scans have also an important role in the differential diagnosis of DLB from AD [117]. A recent meta-analysis of four 123I-FP-CIT SPECT studies, including a total of 419 patients, reported a pooled sensitivity of 86.5% and a specificity of 93.6% for the differentiation of DLB from non-DLB, predominantly AD [118]. However abnormal ioflupane binding is less reliable in differentiating DLB from FTD, because about 30% of FTD patients were have positive ioflupane scans [119]. Ioflupane scans also cannot differentiate between syndromes characterized by dopaminergic loss, including DLB, Parkinson’s disease, multiple system atrophy or progressive supranuclear palsy. Reflecting the increasing evidence for the clinical utility of ioflupane SPECT, it has been incorporated in revised diagnostic criteria for DLB [120]. It has also been recommended by NICE to help with the diagnosis of DLB when the diagnosis is in doubt [77].

3.4. Vascular dementia In patients with VD and no infarcts on structural imaging, functional scans typically show scattered areas of reduced perfusion or metabolism. The lesions are often multiple, asymmetrical or localized in ‘watershed’ regions of the brain [63]. Compared with AD, in VD there is more pronounced hypometabolism in subcortical areas and primary sensorimotor cortex whereas the association areas are typically less affected [121].

4. Conclusion At present, neuroimaging is most likely to be used in the differential diagnosis of dementia, as well as to aid in establishing a prognosis. When disease-modifying treatments become available, this is likely to change, and imaging methods can be used to screen patients, with function-based and ligand-based techniques having a particular role in the detection of early changes. The future of neuroimaging will involve incorporating new modalities into routine clinical practice. However, introducing imaging methods as routine in a National Health Service requires a strong evidence base for their clinical utility and added value. When considering the clinical utility of neuroimaging, it is important to realize that mixed pathologies commonly co-exist in the same individual, and there is a substantial overlap of pathological changes even with health. This will impose limitations on the diagnostic performance of any test and implies that a combination of imaging biomarkers will be most useful. Therefore, studies investigating how different modalities perform in combination will be particularly useful. In addition, strong evidence can only come from studies using representative cohorts and conducted in a naturalistic clinical environment. Currently, studies are conducted mainly in highly specialized centres and often include subjects from clear-cut diagnostic groups, which limits the generalizability of results. Establishment of pilot services is crucial, because each clinical context is associated with characteristic variables, such as demographics of the sample, a priori probability of dementia types, frequency of atypical presentations, and clinical expertise of health care professionals; all these factors have an impact on the value that imaging methods add above routine clinical assessment. If we assess a broad range of patients referred to memory clinic with a variety of imaging modalities, we will make a step towards accumulating reliable evidence and ultimately closing the gap between the dramatic advances in neurosciences and meaningful clinical applications for the maximum benefit of our patients.

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