Journal of the Neurological Sciences 353 (2015) 1–8

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Review article

Magnetization transfer MRI in dementia disorders, Huntington's disease and parkinsonism Nicola Tambasco a,⁎, Pasquale Nigro a, Michele Romoli a, Simone Simoni a, Lucilla Parnetti a, Paolo Calabresi a,b a b

Clinica Neurologica, Azienda Ospedaliera-Università di Perugia, Perugia, Italy IRCCS Fondazione Santa Lucia, Roma, Italy

a r t i c l e

i n f o

Article history: Received 3 January 2015 Received in revised form 21 February 2015 Accepted 16 March 2015 Available online 28 March 2015 Keywords: MRI Magnetic resonance imaging Magnetization transfer Dementia Parkinson's disease Huntington's disease

a b s t r a c t Magnetic resonance imaging is the most used technique of neuroimaging. Using recent advances in magnetic resonance application it is possible to investigate several changes in neurodegenerative disease. Among different techniques, magnetization-transfer imaging (MTI), a magnetic resonance acquisition protocol assessing the magnetization exchange between protons bound to water and those bound to macromolecules, is able to identify microstructural brain tissue changes peculiar of neurodegenerative diseases. This review provides a report on the MTI technique and its use in the dementia disorders, Huntington's disease and parkinsonisms, comprehensive of the predictive values of MTI in the identification of early-phase disease. © 2015 Elsevier B.V. All rights reserved.

Contents 1. 2.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . Materials & methods . . . . . . . . . . . . . . . . . . . . . . 2.1. Search strategy . . . . . . . . . . . . . . . . . . . . . 3. MTI technique . . . . . . . . . . . . . . . . . . . . . . . . . 4. MTI changes in normal aging . . . . . . . . . . . . . . . . . . 5. Cognitive decline . . . . . . . . . . . . . . . . . . . . . . . . 5.1. Relationship with cognitive performances . . . . . . . . . 5.2. Alzheimer's disease and other dementias . . . . . . . . . . 5.3. Prediction of MCI conversion to AD, and AD progression . . . 5.4. Differential diagnosis among dementias . . . . . . . . . . 5.5. Amyloid pathology . . . . . . . . . . . . . . . . . . . . 6. Huntingt`on's disease . . . . . . . . . . . . . . . . . . . . . . 7. Parkinsonisms . . . . . . . . . . . . . . . . . . . . . . . . . 7.1. Parkinson's disease . . . . . . . . . . . . . . . . . . . . 7.2. Multiple system atrophy and progressive supranuclear palsy . 8. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . Conflict of interest . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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⁎ Corresponding author at: Clinica Neurologica, Azienda Ospedaliera, Università di Perugia, Loc. S.Andrea delle Fratte, 06156 Perugia, Italy. Tel.: +39 075 5783830; fax: +39 075 5784229. E-mail address: [email protected] (N. Tambasco).

http://dx.doi.org/10.1016/j.jns.2015.03.025 0022-510X/© 2015 Elsevier B.V. All rights reserved.

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N. Tambasco et al. / Journal of the Neurological Sciences 353 (2015) 1–8

1. Introduction In neurodegenerative diseases, conventional magnetic resonance imaging (MRI) represents the most common and less invasive technique of neuroimaging. However, MRI does not allow an accurate identification of those subtle anatomical changes which are crucial to reveal the very early stages of neurodegenerative processes. Consequently, the diagnosis is still based on neurological assessments and, often, on therapeutic response evaluation [1]. Among MRI techniques, magnetization transfer imaging (MTI) seems to detect subtle changes in patients' cerebral structures in several conditions: multiple sclerosis, infarcts, ischemic white matter lesions, and even in the white matter of patients with myotonic dystrophy [2]. Even though MTI has been more recently applied to neurodegenerative diseases, resulting in new evidences about regional and diffuse degeneration, current literature still lacks solid data about the use of this promising technique in normal and pathological brain aging. The present review provides an overview on the use of advanced magnetization transfer-MRI technique aimed at detecting and assessing the pathological aspects underpinning these neurodegenerative disorders. 2. Materials & methods 2.1. Search strategy The online databases of PubMed was searched by entering the key words “Magnetization Transfer Imaging”, “MTR” and “Magnetization Transfer Ratio”. We linked “Parkinson”, “parkinsonism”, “dementia”, “Alzheimer's disease”, “Mild Cognitive Impairment” and “Huntington”, and selected results from 1995 and 2014. 3. MTI technique Magnetization transfer imaging (MTI) is a nuclear magnetic resonance technique based on the exchange of magnetization between highly mobile protons and immobile restricted protons. In the brain, these two states correspond to free protons in bulk water and tightly bound protons on macromolecules, such as myelin or membrane lipids [3]. Conventional MRI may detect only signals from mobile water protons that have sufficiently long T2 relaxation times. In brain tissue, this signal comes from “free” mobile intra- and extracellular tissue water. By contrast, MRI cannot detect the short T2 relaxation times of about 10 s, such as those of protons bound to macromolecules [4]. Although the magnetization from these macromolecules cannot be directly observed, proton magnetization constantly exchanges between the free fluid and the macromolecules: thus, magnetization saturation and relaxation within the macromolecule affect the observable signal from the free water. The application of a radio frequency (RF) power, which selectively saturates the energy level of bound protons, induces a magnetization exchange between bound and free protons. This saturation is then transferred to the magnetic resonance visible water protons, through magnetization transfer, and determines a decrease in both longitudinal magnetization and signal intensity. We may calculate the magnetization transfer ratio (MTR), which can also be calculated on a voxel-wise basis to produce MTR maps, to measure the difference between signal intensities with and without magnetization transfer. The MTR increases with the rate of magnetization exchange and with the size of the bound pool, and can be calculated according to the formula: MTR ¼ ðM0 −MSS Þ=M0 where M0 represents the signal intensity of a voxel without any RF saturation, and MSS is the signal intensity of the same voxel that is obtained with the RF saturation pulse [2].

Alternatively, whole brain MTR changes can be measured through histogram analysis, unveiling frequencies of the MTR values of voxels in a given region of interest or in the whole brain. In the histogram, the most represented MTR value is the peak position, whose variations reflect white matter abnormalities. The peak height, which varies depending on regional lesions, is the fraction of voxels with the MTR peak-position value. The region of interest (ROI) approach enables assessment of regional MTR changes. MT-MRI uses off-resonance RF pulses to create contrast: the MTR values obtained strongly depend on the offset frequency, bandwidth, and average power of the pulses, which should be standardized to minimize the differences among centers [5]. Since macromolecule are absent in CSF, no exchange occurs in it, and the MTR approaches zero. In contrast, a 40 to 50% MTR score may be seen in healthy brain tissue, being the effect of normal water saturation transfer [6]. The degree of signal loss depends on macromolecules' tissue density. The pathological variations in macromolecular structures, such as myelin loss and axonal destruction, may decrease the exchange of magnetization between bound and free protons, calculated as magnetization transfer ratio (MTR) [7]. Low MTR, in particular, indicates a reduced capacity of free water in intimate contact with the brain tissue to exchange magnetization with it, correlated with tissue damage degree in several neurodegenerative disorders. Functional neuronal damage induces oxidative stress, causing the release of different inflammation mediators, astrocyte reaction, microglial proliferation, iron and other paramagnetic substance deposition, and pathological changes in cell membrane macromolecules, eventually reducing MTR [8]. 4. MTI changes in normal aging Age-related reduction of MTR values has been widely shown, both in gray and white matter [9–13], begins and progresses from the age of 40, and worsens when vascular risk factors are present [12,14]. Both wholebrain and lobar cortical MTR are directly and significantly related to cognitive and executive functions [15]. MTR variations of normal appearing white matter (NAWM) and deep gray matter structures (NAGM) are associated with executive functioning, independently from vascular risk factors, brain lesions or cortex volume [15]. A quadratical relation can describe cortical and subcortical gray matter; MTR variations trend with age, with a decline usually starting after midlife [16]. 5. Cognitive decline 5.1. Relationship with cognitive performances MTR correlates with cognitive performance, and lower MTR values associate with worse executive functioning [4]. Venkatraman et al. found a correspondence between worse information processing and lower MTR of the NAWM but not of the normal gray matter [17]. Others reported a weaker but evident relationship between memory impairment and lower MTR in frontal white matter [18] or whole brain [19,20]. 5.2. Alzheimer's disease and other dementias In dementias, MTI is able to reach an in-vivo quantification of tissue damages, differentiating them from the effects of aging, and allowing to start treatments as soon as possible [4,21,22]. Since neurodegeneration directly subtends cognitive impairment, MTI may close the gap between pathological processes subtending atrophy and clinical correlates, opening the way towards an early diagnosis. Among dementias, even at early stages, medial temporal lobe atrophy has been highlighted by MRI [23,24], although not being specific for AD [25,26]. Volumetric measurement of entorhinal or hippocampal region discriminates controls from very mild AD patients with an 80% specificity and a 77.8% sensibility [27–29]. Being affected by processes that invariably occur in AD, such as neurofibrillary tangles, loss of

N. Tambasco et al. / Journal of the Neurological Sciences 353 (2015) 1–8

neurons, gliosis, and degeneration of intra-hippocampal fibers [30], MTI may provide a more accurate evaluation of AD's early stages. MTR value reduction in AD patients involves the temporal and frontal lobes, and is consistent within the whole brain [31,32]. Mean MTR values of gray and white matter are significantly lower in AD than in controls, and can thus be used to distinguish AD from normal patients [33]. Hippocampal MTR evaluation discriminates controls from very mild AD with 75% sensitivity and 90% specificity (overall discrimination rate of 85%) [34], similarly to hippocampal volumetric study [4,28,35]. Lower hippocampal MTR values may individuate AD from non-AD dementia with medial temporal atrophy [36]. MTI has been investigated for the chance to detect early microstructural brain tissue changes indicative of incipient dementia. MTI has been reported able to identify pathological changes “well before plaque formation and learning and memory deficits” (never reported with other techniques) [37,38], and map amyloid pathology subtending AD [39]. Moreover, cortical temporal MTI changes are present even in asymptomatic presenilin-1 (PS1) mutated patients, anticipating regional volume loss, and in the absence of whole-brain MTR reduction, configuring an early-phase AD detection via MTI [40]. The association of lobar MTR value variations with early changes indicative of incipient dementia has also been reported, promoting lobar analysis as an easier-to-use tool than hippocampal or entorhinal manual segmentation [33]. Furthermore, Giulietti et al. hypothesized that the forward exchange rate (an MTI parameter reflecting the efficiency of the MT between free water and macromolecular pools of protons) might reflect mitochondrial dysfunction, and thus might be used to detect early neuropathological processes subtending AD [41]. MMSE (mini-mental state examination) and CDR (clinical dementia rating) are common tools to assess patients' cognitive function. Both atrophy and MTR pair with these cognitive scales [34,35]. Total hippocampal and total brain volume are significantly reduced in AD, although hippocampal volume in some cases does not correlate with MMSE scores, being the object of misleading inter-rater variability [35]. Vice versa, whole-brain volume reduction — brain atrophy — pairs with cognitive decline and worse performances in MMSE and CDR, making the rate of whole-brain atrophy an objective tool for tracking disease progression [34,35]. MT evaluation of the hippocampal region has been shown to be superimposable to whole-brain volume measurement in terms of both distinction between AD and controls and correlation with MMSE results [4,34–36]. In particular, MTRs are significantly lower passing from controls to very mild, mild and moderate probable AD patients [35]. Several studies confirmed the association of cognitive decline with MTR reduction either in specific regions, such as the hippocampus [35,42], temporal [40] and frontal lobes [31,32], or in the whole brain [43]. Bozzali et al. also showed that a composite score based on cortical gray matter MTR and whole-brain volume measurement associates with cognitive impairment [21]. Furthermore, Ropele et al. demonstrated that the left hippocampal and left basal ganglia MTR reduction parallels cognitive decline better than right sided ones do, and might reflect the progression of microstructural tissue damage underlining AD [42] (Table 1). 5.3. Prediction of MCI conversion to AD, and AD progression MTR and whole brain volume progressively reduce with time, thus being useful to monitor tissue damage leading to AD. MCI connotes a cognitive decline not fulfilling AD diagnostic criteria [44], though presenting the same microstructural brain damages [45]. MCI converts to AD with an annual rate between 6.8 and 8.1% [46], but MCI progression still remains unclear, and difficult to assess or foresee: MTI is able to differentiate MCI and AD, although its predictive value has yet to be diffusely compared with neuropsychological tests and CSF fluid examination [4,47]. MCI represents a kind of subtle state, with patients that, in terms of imaging, may differ from controls only for temporal atrophy [31,32]. Entorhinal cortex model-based multi-parameter MTI

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differentiated AD and MCI with a 94% specificity and a 100% sensitivity, and perfectly correlated with MMSE and CERAD-NAB (CERAD Neuropsychological Assessment Battery) scores [47]. Also quantitative hippocampal MTI may distinguish AD from MCI [48], while MCI conversion to AD has been linked to MTR reduction involving not only the hippocampal, temporal and frontal regions, but spreading to the prefrontal white matter and the insula [49] (Table 1). MCI to AD progression might be marked through MTR before changes on volumetric assessment [33]. A combined approach, counting on MTI and volumetric assessment, might better evaluate the complexity of cognitive impairment progression, since, in some cases, gray matter atrophy is needed to accurately discriminate between MCI or AD with equal MTR values [10]. Ropele et al. used MTI to have a longitudinal glimpse of AD progression [42]. Hippocampal, putaminal and thalamic MTR reductions, compared to baseline levels, were found already after 6 months, and paired with volume loss — 2.2%/year for the whole brain and 2.9%/year for the hippocampus [50,51] and cognition, with left hippocampal and basal ganglia MTR variations more closely correlated to MMSE scores [42]. The finding that memantine has no effect on MTR value variations, even though yet to be confirmed, might suggest no benefit for microstructural damage [42] (Table 1). 5.4. Differential diagnosis among dementias Lower MTR value relates to worse cognitive performance in normal aging, AD, HD-associated dementia and small vessel disease [4,5]. To date only few studies addressed the use of MTR to improve differential diagnosis of dementias, though it seemed to be a useful technique to achieve it. AD patients differ from controls for hippocampal lower mean MTR values with 61% sensitivity and 90% specificity, similar to volumetric evaluation [35]. MTR value decrease in the hippocampus has been widely demonstrated as a useful tool to differentiate AD patients and controls [4, 5,34–36,41]. Differential diagnosis within dementias has been poorly evaluated via MTR. However, peculiar MTI aspects of each type of dementia might be seen as a characteristic, even though needing deeper and wider demonstrations to become diagnostically specific. White matter hyperintensities (WMH), divided into periventricular (PMWMH) and deep (DWMH), are T2 abnormalities often found in the elderly, and associated with cognitive functioning — PWMH far more than DWMH [52,53]. Lower MTR associates more with PVWMH than DWMH, and thus with cognitive functioning, as for subcortical ischemic vascular dementia [54]. MTI provides a correct differential diagnosis between AD and vascular dementia in 50 to 70% of cases, with a negative predictive value higher than 80% [55]. Hanyu et al. showed hippocampal MTR superiority to visual atrophy analysis in terms of distinction between AD and non-AD dementias, including Lewy bodies dementia (LBD), frontotemporal dementia and Binswanger dementia (77% vs 65% discrimination rate) [36]. Compared to controls, DLB and AD share common profiles of MTR value reduction in the hippocampus, parahippocampal gyrus and posterior cingulate white matter [5,56]. However, hippocampal MTR value can discriminate between AD and LBD, correctly identifying 76% of LBD and 71% of AD patients [56]. Also Creutzfeldt Jakob Disease (CJD) diagnosis might benefit from MTI. Whole-brain MTR variations correlated with prion disease and clinical, functional and CDR longitudinal declines. Post-mortem evaluation significantly couples cortical MTR values and spongiosis, thus suggesting MTR as a potential tool to objectively monitor disease progression (spongiform change) [57]. 5.5. Amyloid pathology In AD one of the more evident pathological aspects are extracellular plaques of amyloid-β (Aβ) peptides. Their role in AD is still controversial but their early detection may still significantly influence the progression of the disease [58]. Amyloid plaques are successfully imaged with

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N. Tambasco et al. / Journal of the Neurological Sciences 353 (2015) 1–8

Table 1 Magnetization transfer MRI studies in dementia disorders. Author

Cohort

Mean age ± SD

Hanyu et al. (2000) [36]

35 AD

Staging (MMSE and CERAD)

Localization of MTR reduction

Relationship between MTR and cognitive scales

76.9 ± 5.5

18.1 ± 4.8

Diffuse in AD vs controls, VD and OD; higher MTR overall discrimination rate 77% compared to atrophy analysis 65%

MTR reduction correlated with MMSE scores in AD

14 VD 13 OD 23 ctr 38 AD: 12 CDR 0.5 14 CDR 1.0 12 CDR 2.0 21 ctr

78.1 ± 7.5 75.4 ± 6.5 77.8 ± 6.0

17.5 ± 4.7 18.5 ± 5.1 28.1 ± 1.2

77.8 ± 3.9 78.1 ± 7.3 77.7 ± 4.8 78.9 ± 6.3

10.9 ± 3.4 10.1 ± 3.9 9.4 ± 2.5 10.6 ± 2.8

23.5 ± 1.6 19.0 ± 2.9 12.7 ± 2.5 28.0 ± 1.0

Van der Flier et al. (2002) [31]

25 AD 13 MCI 28 ctr

74 ± 7 74 ± 8 74 ± 7

10 ± 3 9±3 9±3

19 ± 4 26 ± 2 28 ± 2

Kabani et al. (2002) [33]

11 AD

76.5

12 MCI 15 ctr 18 AD 18 ctr

77 73.92 69.1 ± 6.8 67.1 ± 8.9

6 PS1 14 ctr 28 AD baseline 27 AD after 6 months

43 ± 4 42 ± 5 76.5 ± 5.8

Hanyu et al. (2001) [34]

Ridha et al. (2007) [35]

Ginestroni et al. (2009) [40] Ropele et al. (2012) [42]

Education

19.1 ± 6.2 29.7 ± 0.6

13.5

≥24 29.4 18.9 ± 2.8

76.5 ± 5.9

18.8 ± 4.8

18 AD after 12 months

76.1 ± 5.8

18.6 ± 4.3

Fornari et al. (2012) [43]

19 ctr 15 AD 15 ctr

73.3 ± 3.2 67.93 ± 10.55 64.47 ± 11.51

11.33 ± 3.39 13.27 ± 3.43

27.6 ± 0.8 21.47 ± 4.03 28.87 ± 1.13

Wiest et al. (2013) [47]

18 AD 18 MCI

70.39 ± 9.9 70.83 ± 10.1

11.00 ± 3.30 11.28 ± 1.99

24.56 ± 3.45 28.67 ± 1.49

18 ctr 20 AD

71.61 ± 9.2 74.4 ± 7.0

12.78 ± 3.11

29.50 ± 0.7 25 ± 2.5

27 MCI 30 ctr

68.8 ± 7.8 71.9 ± 6.1

Mascalchi et al. (2013) [16]

27.9 ± 1.8 28.8 ± 1.2

No correlation with MMSE

In the hippocampus of AD vs ctr; CDR 2 hippocampal MTR was significantly lower than CDR 1 and CDR 0.5 AD patients (p b 0.0001); MTR showed higher overall discrimination rate than atrophy score between ctr and AD, and among AD subgroups In temporal and frontal lobes and the whole brain in AD and MCI vs ctr (p b 0.01), but lower atrophy in MCI vs AD (p b 0.01) In bilateral temporal lobes (p b 0.001) in AD vs ctr, but lower atrophy in MCI 3% reduction in right (p b 0.01) and left (p b 0.001) temporal lobes in MCI vs ctr In WM in AD vs ctr (p = 0.008); combination of total volume and MTR of the hippocampus had 90% specificity and sensibility in individuating AD In bilateral temporal cortex in PS1 vs ctr In global MTR values and in regional hippocampal MTR in AD vs ctr In global MTR values and in regional hippocampal MTR in AD after 6 months follow-up vs AD in global MTR values and in regional hippocampal MTR in AD after 12 months follow-up vs AD MTR reduction in: parahippocampal, posterior cingulate, precuneus, cuneus, insula, superior temporal areas (p b 0.005); frontal and inferior temporal areas (p b 0.01) In the entorhinal cortex, temporal cortex, hippocampus, and amygdala; MT values between corresponding volume of interest (entorhinal cortex, temporal cortex) discriminate with 100% sensibility and specificity AD vs ctr, with 100% and 94% AD vs MCI; with 83% and 86% MCI vs ctr; mMT was more specific than MTR in discriminating MCI and AD

Association between MTR values and CDR or MMSE scores

MTR correlates with MMSE score

No correlation with MMSE

MTR reduction correlated with memory and executive function scores Left hippocampus (p b 0.01), right hippocampus (p = 0.048), left thalamus (p b 0.01), right thalamus (p = 0.029), left putamen (p b 0.001), right putamen (p b 0.01); MTR significantly correlated with MMSE; stronger associations in the left hemisphere Demyelination of the surface white matter revealed with MTR correlated with MMSE, Lexis, and memory test scores

mMT based evaluation paired with CERAD and MMSE scores

In the bilateral hippocampus in AD vs ctr (p b 0.05); in the left amygdala in AD vs MCI In the bilateral hippocampus and amygdala in MCI vs ctr

OD: (Other dementias) 2 Parkinson's Dementia, 2 Dementia with Lewy Bodies, 4 Normal Pressure Hydrocephalus; 3 Progressive Supranuclear Palsy, 1 Frontotemporal Dementia, 1 Korsakoff. CDR, clinical dementia rating; MMSE, mini-mental state examination; MTR, magnetization transfer ratio; SD: standard deviation; WM, white matter; MCI, mild cognitive impairment; mMT, magnetization transfer model; AD: Alzheimer's disease; VD: vascular dementia; MCI: mild cognitive impairment; PS1: Pre-Senilin1 mutation; ctr: controls; WM: white matter.

positron emission tomography (PET) using the Pittsburgh-compound (PIB) [59], and more recently developed tracers, such as florbetaben [60,61]. Previous reports have developed MRI techniques to detect amyloid plaques in vivo without contrast agents based on intrinsic T2 or T2* contrast because of iron deposits from amyloid plaques [61]. Recently, approaching amyloid pathology with magnetization transfer contrast MTC MRI is more promising than the widely described T2 relaxation measurements verified in experimental model of transgenic mice [62]. A region based MTR and immunohistochemistry analysis and correlations

between MT-ratios and quantitative immunohistochemistry indicate amyloid plaques as the main substrate for altered MT-ratios in transgenic animals [62]. 6. Huntingt`on's disease Huntington's disease (HD) has been widely investigated with neuroimaging, finding a consistent progressive caudate and putamen atrophy [63]. Alternating evidences based on MTI studies showed that, in HD mutation carriers, non-significant MTR reduction is found in the

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neostriatum, cerebellum, white matter and in the whole-brain analyses and, thus, this technique does not demonstrate more evidences than volumetric or diffusion weighted evaluation [64]. MTR reduction paired with UHDRS scores and CAG repeats, with peak reduction already present in asymptomatic carriers, reflecting worse histological brain composition and suggesting a correlation between MTR peak height and genetic or subclinical disease [65]. Differently, HD gene carriers showed MTR reduction in all subcortical GM, correlating with disease duration, motor and neuropsychological test scores [66]. MTI, with MTR reduction in the GM, WM and whole brain, was confirmed as significant in early HD [67]. Moreover, increased putaminal MTR peak height in the premanifest disease was related to a pre-degenerative process or aberrant development. However, in the same study, Van den Bogaard et al. showed that MTI failed to be superior to volumetric assessment for monitoring longitudinal changes in HD during a 2-year follow-up [68] (Table 2).

7. Parkinsonisms 7.1. Parkinson's disease MR findings of Parkinson's disease (PD) include thinning of the pars compacta and loss of normal SN hyperintensity on T1 images. Aging may determine iron accumulation in the basal ganglia and T2 signal loss in the basal ganglia is generally demonstrated in Parkinson Plus syndromes and neurodegeneration with iron brain accumulation (NBIA), which also includes parkinsonism. Thus, MTI has been widely investigated, mostly using ROI approach [5], for straightforward diagnosis and to detect neurodegeneration progression.

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In early PD, a reduction of MTR values has been reported in red nucleus, pons, pars compacta (SNpc) and pars reticulata (SNpr) of the substantia nigra in both early PD [8] and late phase of the disease, as shown by our previous study [69]. A progressive MTR reduction has been observed from early PD stages, with a mean of 3 month-old diagnosis, to the late stages. In fact, MTR values of the supratentorial periventricular WM and cerebellum were normal in early stage, in contrast with late stages [8,69] (Table 3). Magnetization transfer MRI can also be used to detect neuromelanin contained in dopaminergic neurons suffering from degenerative processes peculiar of PD, thus configuring, once deeply investigated in terms of sensibility and specificity, an excellent tool to achieve an early-stage diagnosis [70,71]. Finally, MTI has been shown able to identify SN and olfactory cortex damages undetectable with MR imaging, proving to be more sensitive to map early stages of PD [72]. Advancing, PD neurodegenerative processes widen the areas affected by MTR reduction. With disease progression, the pons, globus pallidus, SNpc, SNpr, and putamen all remain to have lower MTRs than controls, consolidating and extending the pattern seen in early phases [34,69,73,74]. Likewise, gray matter and white matter show diffusely reduced MTR [74], particularly in the supratentorial [69] and frontal regions [73]. Furthermore, in advanced stages, according to our previous communication, MTR also lowers in the caudate and lateral thalamus [73] (Table 2). No significant relationship has been shown between MTR values and UPDRS scores [73], while MMSE scores closely related with WM MTR reduction in PD patients with cognitive decline [34]. Finally, MTI has been demonstrated sensitive to disease progression in the paraventricular WM, SN, and, especially, in olfactory areas and the superior temporal gyrus; bilateral SN and cortical damages are revealed

Table 2 Magnetization transfer MRI studies in Huntington's disease. Authors

Cohort

Mascalchi et al. (2004) [64]

21 HD gene carriers 21 ctr

Mean age 58 ± 11 54 ± 13

Staging

Localization

CAG N39 and b50 S&F 1 (n = 4), 2 (n = 7), 3 (n = 8), 4 (n = 2) CAG repeats 40–49; UHDRS-MS 3.5, BS 12.4

No differences between HD carriers and controls

Jurgens et al. (2010) [65]

16 HD gene carriers

41.9 ± 10

15 ctr

47.2 ± 9.2

CAG b24; UHDRS MS 2.4, BS 15.8

56 ± 13 55 ± 12

CAG 44; UHDRS MS 33 ± 18 S&F stage 1 (n = 1), 2 (n = 4), 3 (n = 6), 4 (n = 4)

Ginestroni et al. (2010) [66]

15 HD gene carriers 15 ctr

Van der Bogaard et al. (2012) [67]

25 HD gene carriers 25 early manifest HD 28 ctr

43.8 ± 8.5 48.4 ± 10.9 48.3 ± 8

H&Y 2.7 ± 0.7; UPDRS 26.2 ± 8.5 H&Y 3.3 ± 0.8; UPDRS 34.2 ± 9.0 H&Y 3.6 ± 1.1; UPDRS 37.5 ± 11.8

Van der Bogaard et al. (2013) [68]

21 HD gene carriers A = far from expected onset

45.5 ± 5.2

B = near from expected onset

42.9 ± 11.2

CAG 41.3; TMS-B 2.3 ± 1.7, TMS-FUP 6.0 ± 6.9; MMSE-B 29.0, MMSE-FUP 29.3 CAG 44.0; TMS-B 3.0 ± 1.1, TMS-FUP 6.3 ± 2.5; MMSE-B 28.4, MMSE-FUP 28.6

25 early manifest HD 9 with S&F ≤ 2

47.7 ± 11.8

12 with S&F ≥ 3

50.9 ± 9.4

28 ctr

48.3 ± 7.6

CAG 43.8; TMS-B 16.9 ± 8.8, TMS-FUP 23.0 ± 9.0; MMSE-B 29.0, MMSE-FUP 28.7 CAG 43.2; TMS-B 26.2 ± 11.7, TMS-FUP 37.8 ± 14.3; MMSE-B 26.5, MMSE-FUP 27.0 CAG normal; TMS 1.7 ± 1.4; MMSE 29.2

Lower values in GM in carriers with higher UHDRS scores; association with worse performance in Stroop color naming test CAG repeats associated with lower MTR values in the whole-brain (p = 0.00), GM (p = 0.00) and WM (p = 0.004) Lower MTR values in GM in HD carriers; all cerebral lobes showed lower MTR values in GM and all subcortical GM structures; MTR values did not correlate with CAG repeats, but putaminal MTR values paired with Stroop test and UHDRS scores Reduced MTR values in GM and WM in early manifest HD vs ctr; MTR values correlated with motor and cognitive test scores and with disease burden Decreased MTR values in the right putamen

Decreased MTR values in the left hippocampus and cortical GM

Decreased MTR values in the right amygdala during the 2 years FUP Decreased MTR values in the left amygdala during the 2 year FUP

TMS, total motor score (B = baseline, FUP = follow-up); MMSE, mini mental state examination; HD, Huntington's disease; GM, gray matter; WM, white matter; UHDRS, Unified Huntington's disease rating scale (MS = motor score, BS = behavioral score); S&F, Shoulson and Fahn; GM: gray matter. Italics values indicate significance at the subgroups of the HD patients.

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with MTI before than with T1-weighted images or volumetric assessment [72], configuring MTR as an extremely sensitive technique which detects macromolecular damage progression [69,72] (Fig. 1).

7.2. Multiple system atrophy and progressive supranuclear palsy PD, multiple system atrophy (MSA) and progressive supranuclear palsy (PSP) share common MTI findings, such as low MTR in the globus pallidus, putamen, caudate nucleus, substantia nigra, and white matter [74]. Distinguishing PD, MSA and PSP is extremely challenging, and depends on anamnesis, clinical assessment and imaging analysis, which, even though proposed as hallmarks in some cases (such as lateral putaminal T2 hyperintensity in MSA [75] or midbrain atrophy in PSP [76]) may give poor contribution to the differential diagnosis or to the evaluation of neurodegeneration, especially in the first stages [77].

Magnetization transfer measurement has been widely used in parkinsonisms, mostly with ROI approach, and with interesting results (Table 3). In MSA, the pons, middle cerebellar peduncles, putamen, and WM of the precental gyrus lower MTR values have been found. Moreover, the clinical differentiation in MSA-P and MSA-C is supported with MTI. Indeed, in patients with pyramidal signs MTR decreases in the whole corticospinal tract (precentral gyrus, posterior limb of the internal capsule, cerebral peduncle and base of the pons), differently from patients with asymmetric parkinsonian features in which a decrease was observed in the contralateral putamen [2,3,74]. Globus pallidus, putamen, SN, and caudate MTI represents a sensitive tool to discriminate PD patients from controls, PSP patients, and MSA patients, and to distinguish PSP from MSA patients — the first one being more associated to MTR reduction in the globus pallidus, the second otherwise linked to MTR reduction in the putamen [74]. MTI is also sensitive in early stages of

Table 3 Magnetization transfer MRI studies in parkinsonisms. Authors

Cohort

Mean age

Disease duration ± SD

Staging

Δ in MTR

Localization

Hanyu et al. (2001) [34]

11 PD

76.1

3.5 ± 0.6 ys

None

No differences vs ctr

6 PDD 6 PSP

78.3 74.4

4 ± 0.9 ys 3.3 ± 0.8 ys

H&Y 2 to 3; MMSE 27.1 ± 1.8 MMSE 17.3 ± 3.0 MMSE 14.8 ± 6.1

Reduction Reduction

WM vs ctr and PD GM and WM vs ctr; GP and thalamus vs PD; no differences vs PDD

12 ctr 12 MSA 11 ctr

77.6 59.5 58

4.0 ± 2.4 ys

MMSE 27.8 ± 1.3 7 MSA-C and 5 MSA-P

Reduction

11 PD 8 ctr 15 PD

62.6 57.6 65.3

6.6 ys

H&Y 2.9; UPDRS 41.9

Reduction

5.4 ± 4.0 ys

Reduction

12 MSA

62.8

3.6 ± 1.6 ys

10 PSP

66.5

4.2 ± 2.7 ys

H&Y 2.7 ± 0.7; UPDRS 26.2 ± 8.5 H&Y 3.3 ± 0.8; UPDRS 34.2 ± 9.0 H&Y 3.6 ± 1.1; UPDRS 37.5 ± 11.8

In MSA with PTS vs both ctr and MSA without PTS in the precentral gyrus WM (P b0.01), IC (P b 0.05), cerebral peduncle (P b0.05), and pons (P b0.01) SNpc (p b 0.0001), RN (p b 0.05) and pons (p b 0.04), pWM (p b 0.05), brainstem (p b 0.001) In all structures examined, mostly SN and GP vs ctr

da Rocha et al. (2006) [3]

20 ctr 10 MSA

64.7 60.7

27.8 mo

n/a

Reduction

Corticospinal tract MTRs were significantly reduced in MSA with PTS vs ctr

Anik et al. (2007) [8]

25 ctr 33 PD

59 66.9

3,3 mo

n/a

Reduction

SNpc (p b 0.001), SNpr (p = 0.006), RN (p = 0.037), and pons (p = 0.046) vs ctr

Tambasco et al. (2011) [73]

30 ctr 11 PD (mild)

66.8 60

14 ± 2.5 mo

Reduction

11 PD (advanced)

63

81 ± 16.3 mo

H&Y 1.25; UPDRS 19.125; MMSE 27.9 H&Y 3.125; UPDRS 63.142; MMSE 26.6

10 ctr

57

Morgen et al. (2011) [72]

36 PD

61

5.8 ± 3.9 ys

SNpc (p b 0.01), SNpr (p b 0.05), putamen (p b 0.01), pWM (p b 0.05) and parietal WM (p b 0.01) SNpc (p b 0.01), SNpr (p b 0.05), putamen (p b 0.05), pWM (p b 0.01) and paWM (p b 0.01); but MTR in advanced PD was lower than mild PD in Ca (p b 0.05), frontal WM (p b 0.05) pons (p b 0.01) SN, olfactory and temporal cortices, pWM vs ctr

Focke et al. (2011) [77]

23 ctr 12 PD 10 MSA

59.6 66.3 62.5

5.83 ys 4.5 ys

Increase Varies

9 PSP 13 ctr 20 PD

67 67.6 66.25

2.44 ys

Varies

Caudate in PD vs ctr No differences vs ctr; decrease MTR in putamen bilaterally, left SN in MSA vs PD Left Ca MTR increase; decreased MTR values in GP

Reduction

SN more affected than other structures vs ctr

20 ctr 10 PSP 8 ctr

66 n/a n/a

Reduction

Limbic lobes (p b 0.001), lingual solcus and left frontal lobe in both medial and inferior giri; bilateral thalamus, left Ca and claustrum

Naka et al. (2002) [2]

Tambasco et al. (2003) [69] Eckert et al. (2004) [74]

Bunzeck et al. (2013) [79]

Sandhya et al. (2014) [78]

6.27 ± 4.4 ys

n/a

H&Y 2.3 ± 0.9; UPDRS 41.9 ± 20.7; MMSE 28.6 ± 1.4

UPDRS 34.6 ± 17.4; MMSE N 25

Reduction Reduction

Reduction

Reduction

In putamen, GP and SN lower in MSA vs PD; in putamen lower MTR in MSA vs PSP GP and SN lower MTR in patients with PSP vs PD, MSA, ctr

PD: Parkinson's disease; PDD: Parkinson's disease plus dementia; PSP: progressive supranuclear palsy; MSA: multiple system atrophy; n/a: not available, ctr: control subject, ys: years, mo: months, SD: standard deviation, H&Y: Hoehn and Yahr scale, UPDRS: Unified Parkinson's disease rating scale, MMSE: Mini-mental scale examination, PTS: pyramidal tract sign; WM: white matter, GM: gray matter, SNpc: substantia nigra pars compacta, RN: red nucleus, pWM: paraventricular white matter, paWM: parietal white matter; GP: globus pallidus, SNpr: substantia nigra pars reticulate, Ca: caudate; IC: internal capsule.

N. Tambasco et al. / Journal of the Neurological Sciences 353 (2015) 1–8

Fig. 1. Progressive brain spread of MTR values reduction by ROI analysis through the different phases of the disease: early (green line), mid (red line) and advanced (blue line) stage of Parkinson's disease.

MSA with low values in the contralateral putamen but no asymmetries in T2W imaging in patients with asymmetric parkinsonian features were shown [2]. In PSP, MTI revealed wide qualitative changes in several structures, including orbital, frontal, and limbic cortices, subcortical GM, cingulate and parahippocampal giri, and deep structures such as the caudate, thalamus and claustrum [78]. Cerebellar involvement and prefrontal involvement were also linked to ataxia and dysexecutive syndrome in PSP [78]. MTR reduction in the subcortical GM, putamen and pallidal areas confirmed the findings by Hanyu et al. [34]. Focke et al. recently revalidated MTR reduction in the globus pallidus of PSP patients, which has already been shown by other authors [34,74,77]. Furthermore, MTR analysis of the globus pallidus and substantia nigra was able to distinguish PSP from MSA, PD and controls [74]. 8. Conclusion Conventional MRI has widely increased the characterization of CNS pathological changes during all the stages of neurodegenerative diseases. A major effort in terms of technique has been requested to provide new insight on the underlying pathology and to unveil early stages of diseases. For its properties, the applications of MTR-MRI have improved the detection of the related changes in different neurodegenerative disease particularly in Alzheimer's disease and Parkinson's disease. Conflict of interest The authors have nothing to disclose. References [1] Baglieri A, Marino MA, Morabito R, Di Lorenzo G, Bramanti P, Marino S. Differences between conventional and nonconventional MRI techniques in Parkinson’s disease. Funct Neurol 2013;28(2):73–82. [2] Naka H, Imon Y, Ohshita T, Honjo K, Kitamura T, Miyachi T, et al. Magnetization Transfer Measurements of Brain Structures in Patients with Multiple System Atrophy. Neuroimage 2002;17:1572–8. [3] da Rocha AJ, Jr Maia AC, da Silva CJ, Braga FT, Ferreira NP, Barsottini OG, et al. Pyramidal Tract Degeneration in Multiple System Atrophy: The Relevance of Magnetization Transfer Imaging. Mov Disord 2007;22(2):238–44. [4] Seiler S, Ropele S, Schmidt R. Magnetization transfer imaging for in vivo detection of microstructural tissue changes in aging and dementia: a short literature review. J Alzheimers Dis 2014;42(S3):S229–37. [5] Filippi M, Rocca MA. Magnetization Transfer Magnetic Resonance Imaging of the Brain, Spinal Cord, and Optic Nerve. Neurotherapeutics 2007;4:401–13.

7

[6] Stamelou M. Magnetic resonance imaging in progressive supranuclear palsy. J Neurol 2011;258:549–58. [7] Gupta D. Utility of susceptibility-weighted MRI in differentiating Parkinson’s disease and atypical parkinsonism. Neuroradiology 2010;52(12):1087–94. [8] Anik Y, Iseri P, Demirci A, Komsuoglu S, Inan N. Magnetization Transfer Ratio in Early Period of Parkinson Disease. Acad Radiol 2007;14:189–92. [9] Silver NC, Barker GJ, MacManus DG, Tofts PS, Miller DH. Magnetisation transfer ratio of normal brain white matter: a normative database spanning four decades of life. J Neurol Neurosurg Psychiatry 1997;62:223–8. [10] Benedetti B, Charil A, Rovaris M, Judica E, Valsasina P, Sormani MP, et al. Influence of aging on brain gray and white matter changes assessed by conventional, MT, and DT MRI. Neurology 2006;66(4):535–9 [28]. [11] Rovaris M, Iannucci G, Cercignani M, Sormani MP, De Stefano N, Gerevini S, et al. Age-related changes of conventional, magnetization transfer and diffusion tensor MRI findings: a study with whole brain tissue histogram analysis. Radiology 2003; 227:731–8. [12] Hofman PAM, Kemerink GJ, Jolles J, Wilmink JT. Quantitative analysis of magnetization transfer images of the brain: effect of closed head injury, age and sex on white matter. Magn Reson Med 1999;42:803–6. [13] Ge Y, Grossman RI, Babb JS, Rabin ML, Mannon LJ, Kolson DL. Age-related total gray matter and white matter changes in normal adult brain. Part II: quantitative magnetization transfer ratio histogram analysis. AJNR Am J Neuroradiol 2002; 23:1334–41. [14] Ropele S, Enzinger C, Sollinger M, Langkammer C, Wallner-Blazek M, Schmidt R, et al. The impact of sex and vascular risk factors on brain tissue changes with aging: magnetization transfer imaging results of the Austrian stroke prevention study. AJNR Am J Neuroradiol 2010;31:1297–301. [15] Seiler S, Pirpamer L, Hofer E, Duering M, Jouvent E, Fazekas F, et al. Magnetization transfer ratio relates to cognitive impairment in normal elderly. Front Aging Neurosci 2014;6:263. [16] Mascalchi M, Toschi N, Ginestroni A, Giannelli M, Nicolai E, Aiello M, et al. Gender, age-related, and regional differences of the magnetization transfer ratio of the cortical and subcortical brain gray matter. J Magn Reson Imaging 2014;40(2):360–6. [17] Venkatraman VK, Aizenstein HJ, Newman AB, Yaffe K, Harris T, Kritchevsky S, et al. Lower digit symbol substitution score in the oldest old is related to magnetization transfer and diffusion tensor imaging of the white matter. Front Aging Neurosci 2011;3:11. [18] Duzel S, Munte TF, Lindenberger U, Bunzeck N, Schutze H, Heinze HJ, et al. Basal forebrain integrity and cognitive memory profile in healthy aging. Brain Res 2010; 1308:124–36. [19] Lee KY, Kim TK, Park M, Ko S, Song IC, Cho IH. Age-related changes in conventional and magnetization transfer MR imaging in elderly people: comparison with neurocognitive performance. Korean J Radiol 2004;5:96–101. [20] Schiavone F, Charlton RA, Barrick TR, Morris RG, Markus HS. Imaging age-related cognitive decline: a comparison of diffusion tensor and magnetization transfer MRI. J Magn Reson Imaging 2009;29:23–30. [21] Bozzali M, Franceschi M, Falini A, Pontesilli S, Cercignani M, Magnani G, et al. Quantification of tissue damage in AD using diffusion tensor and magnetization transfer MRI. Neurology 2001;57:1135–7. [22] Dickerson BC, Stoub TR, Shah RC, Sperling RA, Killiany RJ, Albert MS, et al. Alzheimersignature MRI biomarker predicts AD dementia in cognitively normal adults. Neurology 2011;76:1395–402. [23] Mizuno K, Wakai M, Takeda A, Sobue G. Medial temporal atrophy and memory impairment in early stage of Alzheimer's disease: an MRI volumetric and memory assessment study. J Neurol Sci 2000;173:18–24. [24] Killiany RJ, Moss MB, Albert MS, Sandor T, Tieman J, Jolesz F. Temporal lobe regions on magnetic resonance imaging identify patients with early Alzheimer’s disease. Arch Neurol 1993;50:949–54. [25] Barber R, Gholkar A, Scheltens P, Ballard C, McKeith IG, O'Brien JT. Medial temporal lobe atrophy on MRI in dementia with Lewy bodies. Neurology 1999;52:1153–8. [26] Laakso MP, Partanen P, Riekkinen Jr M, Lehtovirta M, Helkala E-L, Hallikainen M, et al. Hippocampal volumes in Alzheimer’s disease Parkinson’s disease with and without dementia, and in vascular dementia: a MRI study. Neurology 1996;46: 678–81. [27] Xu Y, Jack Jr CR, O’'Brien PC, Kokmen E, Smith GE, Ivnik RJ, et al. Usefulness of MRI measures of entorhinal cortex versus hippocampus in AD. Neurology 2000;54: 1760–7. [28] Jack Jr CR, Petersen RC, Xu YC, Waring SC, O’Brien PC, Tagngalos E, et al. Medial temporal atrophy on MRI in normal aging and very mild Alzheimer’s disease. Neurology 1997;49:786–94. [29] Braak H, Braak E. Neuropathologic stageing of Alzheimer related changes. Acta Neuropathol 1991;82:239–59. [30] Mizutani T, Kasahara M. Hippocampal atrophy secondary to entorhinal cortical degeneration in Alzheimer type dementia. Neurosci Lett 1997;222:119–22. [31] van der Flier WM, van den Heuvel DM, Weverling Rijnsburger AW, Bollen EL, Westendorp RG, van Buchem MA, et al. Magnetization transfer imaging in normal aging, mild cognitive impairment, and Alzheimer's disease. Ann Neurol 2002; 52(1):62–7. [32] Van Der Flier WM, Van Den Heuvel DM, Weverling Rijnsburger AW, Spilt A, Bollen EL, Westendorp RG, et al. Cognitive decline in AD and mild cognitive impairment is associated with global brain damage. Neurology 2002;59:874–9. [33] Kabani NJ, Sled JG, Chertkow H. Magnetization transfer ratio in mild cognitive impairment and dementia of Alzheimer’s type. Neuroimage 2002;15:604–10. [34] Hanyu H, Asano T, Sakurai H, Takasaki M, Shindo H, Abe K. Magnetization transfer measurements of the hippocampus in the early diagnosis of Alzheimer's disease. J Neurol Sci 2001;15:79–84.

8

N. Tambasco et al. / Journal of the Neurological Sciences 353 (2015) 1–8

[35] Ridha BH, Symms MR, Tozer DJ, Stockton KC, Frost C, Siddique MM, et al. Magnetization transfer ratio in Alzheimer disease: comparison with volumetric measurements. AJNR Am J Neuroradiol 2007;28:965–70. [36] Hanyu H, Asano T, Iwamoto T, Takasaki M, Shindo H, Abe K. Magnetization transfer measurements of the hippocampus in patients with Alzheimer’s disease, vascular dementia, and other types of dementia. AJNR Am J Neuroradiol 2000;21:1235–42. [37] Pérez Torres CJ, Reynolds JO, Pautler RG. Use of magnetization transfer contrast MRI to detect early molecular pathology in Alzheimer’s disease. Magn Reson Med 2014; 71:333–8. [38] Klunk WE, Engler H, Nordberg A, Wang Y, Blomqvist G, Holt DP, et al. Imaging brain amyloid in Alzheimer’s disease with Pittsburgh compound B. Ann Neurol 2004;55: 306–19. [39] Nossek E, Bashat DB, Artzi M, Rosenberg K, Lichter I, Shtern O, et al. The role of advanced MR methods in the diagnosis of cerebral amyloidoma. Amyloid 2009; 16(2):94–8. [40] Ginestroni A, Battaglini M, Della Nave R, Moretti M, Tessa C, Giannelli M, et al. Early structural changes in individuals at risk of familial Alzheimer's disease: a volumetry and magnetization transfer MR imaging study. J Neurol 2009;256(6):925–32. [41] Giulietti G, Bozzali M, Figura V, Spanò B, Perri R, Marra C, et al. Quantitative magnetization transfer provides information complementary to grey matter atrophy in Alzheimer's disease brains. Neuroimage 2012;16:1114–22. [42] Ropele S, Schmidt R, Enzinger C, Windisch M, Martinez NP, Fazekas F. Longitudinal magnetization transfer imaging in mild to severe Alzheimer disease. AJNR Am J Neuroradiol 2012;33:570–5. [43] Fornari E, Maeder P, Meuli R, Ghika J, Knyazeva MG. Demyelination of superficial white matter in early Alzheimer’s disease: a magnetization transfer imaging study. Neurobiol Aging 2012;33(2):428.e7–428.e19. [44] Petersen RC, Smith GE, Waring SC, Ivnik RJ, Tangalos EG, Kokmen E. Mild cognitive impairment: clinical characterization and outcome. Arch Neurol 1999;56:303–8. [45] van Es AC, van der Flier WM, Admiraal Behloul F, Olofsen H, Bollen EL, Middelkoop HA, et al. Lobar distribution of changes in gray matter and white matter in memory clinic patients: detected using magnetization transfer imaging. AJNR Am J Neuroradiol 2007;28:1938–42. [46] Mitchell AJ, Shiri Feshki M. Rate of progression of mild cognitive impairment to dementia–meta analysis of 41 robust inception cohort studies. Acta Psychiatr Scand 2009;119:252–65. [47] Wiest R, Burren Y, Hauf M, Schroth G, Pruessner J, Zbinden M, et al. Classification of mild cognitive impairment and Alzheimer disease using model based MR and magnetization transfer imaging. AJNR Am J Neuroradiol 2013;34:740–6. [48] Kiefer C, Brockhaus L, Cattapan Ludewig K, Ballinari P, Burren Y, Schroth G, et al. Multi parametric classification of Alzheimer’s disease and mild cognitive impairment: the impact of quantitative magnetization transfer MR imaging. Neuroimage 2009;48:657–67. [49] Carmeli C, Donati A, Antille V, Viceic D, Ghika J, von Gunten A, et al. Demyelination in mild cognitive impairment suggests progression path to Alzheimer’s disease. PLoS One 2013;8:e72759. [50] Chan D, Fox NC, Jenkins R, Scahill RI, Crum WR, Rossor MN. Rates of global and regional cerebral atrophy in AD and frontotemporal dementia. Neurology 2001;57: 1756–63. [51] Sluimer JD, Vrenken H, Blankenstein MA, Fox NC, Scheltens P, Barkhof F, et al. Whole brain atrophy rate in Alzheimer disease: identifying fast progressors. Neurology 2008;70:1836–41. [52] Breteler MM, van Amerongen NM, van Swieten JC, Claus JJ, Grobbee DE, van Gijn J, et al. Cognitive correlates of ventricular enlargement and cerebral white matter lesions on magnetic resonance imaging: The Rotterdam Study. Stroke 1994;25: 1109–15. [53] de Groot JC, de Leeuw FE, Oudkerk M, van Gijn J, Hofman A, Jolles J, et al. Cerebral white matter lesions and cognitive function: The Rotterdam Scan Study. Ann Neurol 2000;47:145–51. [54] Tanabe JL, Ezekiel F, Jagust WJ, Reed BR, Norman D, Schuff N, et al. Magnetization transfer ratio of white matter hyperintensities in subcortical ischemic vascular dementia. AJNR Am J Neuroradiol 1999;20:839–44. [55] Hentschel F, Kreis M, Damian M, Krumm B. Does magnetization transfer ratio (MTR) contribute to the diagnosis and differential diagnosis of the dementias? Rofo 2004; 176(12):1743–9. [56] Hanyu H, Shimizu S, Tanaka Y, Kanetaka H, Iwamoto T, Abe K. Differences in magnetization transfer ratios of the hippocampus between dementia with Lewy bodies and Alzheimer's disease. Neurosci Lett 2005;380(1–2):166–9. [57] Siddique D, Hyare H, Wroe S, Webb T, Macfarlane R, Rudge P, et al. Magnetization transfer ratio may be a surrogate of spongiform change in human prion diseases. Brain 2010;133(10):3058–68.

[58] Sperling RA, Aisen PS, Beckett LA, Bennett DA, Craft S, Fagan AM, et al. Toward defining the preclinical stages of Alzheimer's disease: recommendations from the National Institute on Aging-–Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement 2011;7:280–92. [59] Klunk WE, Engler H, Nordberg A, Bacskai BJ, Wang Y, Price JC, et al. Imaging the pathology of Alzheimer's disease: amyloid-imaging with positron emission tomography. Neuroimaging Clin N Am 2003;13(4):781–9. [60] Barthel H, Luthardt J, Becker G, Patt M, Hammerstein E, Hartwig K, et al. Individualized quantification of brain β-amyloid burden: results of a proof of mechanism phase 0 florbetaben PET trial in patients with Alzheimer's disease and healthy controls. Eur J Nucl Med Mol Imaging 2011;38(9):1702–14. [61] Guo S, Getsios D, Hernandez L, Cho K, Lawler E, Altincatal A, et al. Florbetaben PET in the early diagnosis of Alzheimer's disease: a discrete event simulation to explore its potential value and key data gaps. Int J Alzheimers Dis 2012;548157. [62] Bigot C, Vanhoutte G, Verhoye M, Van der Linden A. Magnetization transfer contrast imaging reveals amyloid pathology in Alzheimer's disease transgenic mice. Neuroimage 2014;15:111–9. [63] Rosas HD, Goodman J, Chen YI, Jenkins BG, Kennedy DN, Makris N, et al. Striatal volume loss in HD as measured by MRI and the influence of CAG repeat. Neurology 2001;57:1025–8. [64] Mascalchi M, Lolli F, Della Nave R, Tessa C, Petralli R, Gavazzi C, et al. Huntington disease: volumetric, diffusion weighted, and magnetization transfer MR imaging of brain. Radiology 2004;232(3):867–73. [65] Jurgens CK, Bos R, Luyendijk J, Witjes Ané MN, van der Grond J, Middelkoop HA, et al. Magnetization transfer imaging in ‘premanifest’ Huntington's disease. J Neurol 2010; 257(3):426–32. [66] Ginestroni A, Battaglini M, Diciotti S, Della Nave R, Mazzoni LN, Tessa C, et al. Magnetization transfer MR imaging demonstrates degeneration of the subcortical and cortical gray matter in Huntington disease. AJNR Am J Neuroradiol 2010;31(10): 1807–12. [67] van den Bogaard SJ, Dumas EM, Milles J, Reilmann R, Stout JC, Craufurd D, et al. Magnetization transfer imaging in premanifest and manifest Huntington disease. AJNR Am J Neuroradiol 2012;33(5):884–9. [68] van den Bogaard SJ, Dumas EM, Hart EP, Milles J, Reilmann R, Stout JC, et al. Magnetization transfer imaging in premanifest and manifest Huntington disease: a 2 year follow up. AJNR Am J Neuroradiol 2013;34(2):317–22. [69] Tambasco N, Pelliccioli GP, Chiarini P, Montanari GE, Leone F, Mancini ML, et al. Magnetization transfer changes of grey and white matter in Parkinson’s disease. Neuroradiology 2003;45:224–30. [70] Ogisu K, Kudo K, Sasaki M, Sakushima K, Yabe I, Sasaki H, et al. 3D neuromelaninsensitive magnetic resonance imaging with semi-automated volume measurement of the substantia nigra pars compacta for diagnosis of Parkinson's disease. Neuroradiology 2013;55(6):719–24. [71] Nakane T, Nihashi T, Kawai H, Naganawa S. Visualization of neuromelanin in the Substantia nigra and locus ceruleus at 1.5 T using a 3D-gradient echo sequence with magnetization transfer contrast. Magn Reson Med Sci 2008;7(4):205–10. [72] Morgen K, Sammer G, Weber L, Aslan B, Müller C, Bachmann GF, et al. Structural brain abnormalities in patients with Parkinson disease: a comparative voxel-based analysis using T1-weighted MR imaging and magnetization transfer imaging. AJNR Am J Neuroradiol 2011;32(11):2080–6. [73] Tambasco N, Belcastro V, Sarchielli P, Floridi P, Pierguidi L, Menichetti C, et al. A magnetization transfer study of mild and advanced Parkinson's disease. Eur J Neurol 2011;18:471–7. [74] Eckert T, Sailer M, Kaufmann J, Schrader C, Peschel T, Bodammer N, et al. Differentiation of idiopathic Parkinsons disease, multiple system atrophy, progressive supranuclear palsy, and healthy controls using magnetization transfer imaging. Neuroimage 2004;21:229–35. [75] von Lewinski F, Werner C, Jorn T, Mohr A, Sixel-Doring F, Trenkwalder C. T2*weighted MRI in diagnosis of multiple system atrophy: a practical approach for clinicians. J Neurol 2007;254:1184–8. [76] Schrag A, Good CD, Miszkiel K, Morris HR, Mathias CJ, Lees AJ, et al. Differentiation of atypical parkinsonian syndromes with routine MRI. Neurology 2000;54:697. [77] Focke NK, Helms G, Pantel PM, Scheewe S, Knauth M, Bachmann CG, et al. Differentiation of typical and atypical Parkinson syndromes by quantitative MR imaging. AJNR Am J Neuroradiol 2011;32(11):2087–92. [78] Sandhya M, Saini J, Pasha SA, Yadav R, Pal PK. A voxel based comparative analysis using magnetization transfer imaging and T1-weighted magnetic resonance imaging in progressive supranuclear palsy. Ann Indian Acad Neurol 2014;17(2):193–8.