The relation of regional cerebral perfusion and atrophy in mild cognitive impairment (MCI) and early...

To be submitted to:

Psychiatry Research: Neuroimaging

The relation of regional cerebral perfusion and atrophy in mild cognitive

impairment (MCI) and early Alzheimer’s dementia

Christian Luckhaus*a, Mathias Cohnenb, Michael Oliver Flüßc, Michaela Jännera,

Brigitte Grass-Kapanked, Stefan J. Teipele, Harald Hampelf,g, Tillmann Suppriana,

Hans-Jörg Wittsackf

a. Department of Psychiatry and Psychotherapy, Heinrich-Heine-University,

Duesseldorf, Germany

b. Department of Radiology, Städtische Kliniken Neuss, Lukaskrankenhaus

GmbH, Neuss, Germany

c. Institute of Radiology and Nuclear Medicine, Mönchengladbach, Germany

d. Department of Geriatric Psychiatry, Alexian Hospital, Krefeld, Germany

e. Department of Psychiatry and Psychotherapy, University of Rostock, Germany

f. Department of Psychiatry, Ludwig-Maximilian University, Munich, Germany

g. Discipline of Psychiatry, School of Medicine & Trinity College Institute of

Neuroscience (TCIN), Laboratory of Neuroimaging and Biomarker Research,

Trinity College Dublin, The Adelaide and Meath Hospital incorporating the

National Children’s Hospital (AMiNCH), Dublin, Ireland

h. Department of Diagnostic Radiology, Heinrich-Heine-University, Duesseldorf,

Germany

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* Address for Correspondance:

Christian Luckhaus, M.D. Department of Psychiatry and Psychotherapy Heinrich-Heine-University Bergische Landstrasse 2 40629 Düsseldorf Tel.: xx49-211-9222741 Fax: xx49-211-9222745 Email: [email protected]

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Abstract

The spatial and temporal relationship between regional cerebral blood flow (rCBF)

and brain volume changes in incipient and early Alzheimer’s dementia (AD) are not

yet fully understood.

In the present study a cohort of 30 subjects with mild cognitive impairment (MCI) and

15 patients with mild AD were examined by structural perfusion weighted magnetic

resonance imaging (MRI). Hippocampus and amygdala volumes were measured

using manual volumetry. Using a region of interest (ROI) based co-localisation

methodof structural and perfusion weighted MRIs rCBF values of various brain

regions were calculated. From a total of 36 subjects DNA samples were available for

ApoE4 genotyping.

The main findings are: (1) Reduced rCBF of the posterior cingulum and reduced

volumes of both amygdala and the right hippocampus in mild AD vs. MCI. (2) No

correlation hippocampus and amygdale perfusion and volumes in MCI or AD. (3)

Negative correlations of left hippocampal volume with bilateral frontobasal perfusion

and with perfusion of left thalamus in MCI. (4) Positive correlations in mild AD of right

hippocampal volume with perfusion of both thalami and of right amygdalon volume

with perfusion of bilateral mesotemporal regions. (5) Association of reduced

hippocampal but not amygdala volume with presence of one or two apoE ε4 alleles in

MCI and mild AD; no apoE ε4 allele association with rCBF.

The present data support the concept of functional compensatory brain activation in

MCI and the diachisis hypothesis in early AD. rCBF and brain volume changes are at

least partly dissociated in the early pathogenesis of AD and heterogeneously

associated with the ApoE risk allele for AD.

Kommentar [T1]: Singular ist amygdalon, Plural amygdala

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Keywords:

cerebral perfusion, cerebral blood flow, brain volume, atrophy, ApoE, mild cognitive

impairment, MCI, Alzheimer’s disease, dementia

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1. Introduction

Mild cognitive impairment (MCI) is a condition that is often transitional to Alzheimer’s

disease (AD) (Petersen et al., 1999, 2001). It likely resembles pre-dementia stages of

AD in the majority of cases and is, therefore, an approximate model to study early

disease mechanisms. The ApoE 4 genotype is a genetic at risk marker for sporadic

AD, its prevalence is increased in MCI patients that later develop AD (Modrego PJ.

(2006): Predictors of conversion to dementia of probable Alzheimer type in patients

with mild cognitive impairment. Curr. Alzheimer Res. 3(2):161-70).

. Recent reports have demonstrated reductions of regional cerebral blood flow (rCBF)

in MCI employing arterial spin labelling (Johnson et al., 2005) or perfusion weighted

magnetic resonance imaging (MRI) (Luckhaus et al., 2008). Hypopersfusion

compared to cognitively normal controls was most pronounced in the mesiotemporal

regions in MCI (-23 %) with no further decline in mild AD and in the amygdala in MCI

(-20%) and mild AD (-28%) (Luckhaus et al., 2008).

A large range of morphometric MRI studies have shown regional brain volume loss in

MCI compared to healthy controls, particularly of mediotemporal structures, using

both region of interest (ROI) methods (Devanand et al., 2007; Horinek et al., 2007;

Colliot et al., 2008) and automated voxel-based analysis (Duarte et al., 2006; Teipel

et al., 2007).

The question of the temporal sequence, spatial relationship and causality of brain

perfusion and volume changes in MCI and AD is still unsolved.

In the presenmt study, we report a correlation analysis of rCBF and brain volume

data of hippocampi and amygdala that have been obtained in the same set i of

Kommentar [T2]: Mit dem aktuellen Ansatz können Sie keine kausalen Aussagen ma-chen. Dazu müssten Sie z.B. Pfadmodelle verwenden. Wenn da Interesse besteht, können wir eine solche Analyse mal bespre-chen.

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patients with MCI or mild AD. Furthermore, we analyse the association of ApoE

genotypes with regional brain perfusion and volume, respectively.

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2. Materials and Methods

2.1. Subjects

The original study cohort comprised a total of 68 cognitively normal, MCI or mild AD

subjects recruited from the memory clinic of our institute or from a community-based

senior citizen organisation. The MR-based rCBF data from these subjects have

recently been described (Luckhaus et al., 2008).

From a reduced cohort of 30 subjects with MCI and 15 subjects with mild AD brain

volume data were calculated. DNA samples for ApoE genotyping were available in

the majority of these cases.

All subjects had received a thorough diagnostic assessment prior to study inclusion

which comprised of a detailed psychiatric, medical and neurological history, a

physical examination, an extensive laboratory blood screen and a CT- or MR-

structural brain image. The comprehensive psychometric testing applied consisted of

the Test for the Early Detection of Dementia with Differentiation from Depression (Ihl

& Grass-Kapanke, 2000), the neuropsychological test battery of the Consortium to

Establish a Registry for Alzheimer´s Disease (CERAD-NP, Thalmann et al., 1998)

including the Mini-Mental-Status-Examination (MMSE, Folstein et al. 1975), the

Clock-Drawing-Test (CDT, Shulman et al., 2000), the Wechsler Memory Scale

Revised, Subtest Logical Memory (WMS-R-LM, Härting et al., 2000), the Trail Making

Test (TMT-A and –B, Reitan, 1979), the Brief Cognitive Rating Scale and the Global

Detoriation Scale (BCRS and GDS, both: Reisberg et al., German translation by Ihl &

Frölich 1991) and the Clinical Dementia Rating Scale (CDR, Morris, 1997). A

caregiver interview consisted of the Informant Questionnaire on Cognitive Decline in

Kommentar [T3]: Warum wurde gerade diese Subgruppe ausgewählt?

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the Elderly (IQCODE, Jorm, 1994) , the Bayer Activities of Daily Living (B-

ADL,Hindmarch et al. 1998) and the Frontal Behavioral Interview (Kertesz, 2000).

A consensus-based diagnosis for each subject had been made by a senior

psychiatrist, a psychologist and a radiologist based upon the results of the above

examinations. MCI was defined according to the diagnostic criteria of Petersen et al.,

(1999). These define MCI as a decline in memory function, isolated or associated

with a decline in intellectual abilities, such as abstract thinking, judgement and

problem solving. These symptoms may interfere with complex Activities of Daily

Living (ADL), e.g. handling finances, whereas basic ADL skills are preserved.

AD-diagnosis was based on the NINCDS-ADRDA-criteria (McKhann et al., 1984) for

probable AD. Only mildly demented AD subjects (GDS 3-4) had been included.

Prior to study enrolment, informed consent had been obtained from all subjects or, in

case of impaired capacity to consent, from their legally authorised guardians. The

study had been approved by the local ethics review board.

2.2. Image acquisition

All MRI investigations were performed using a 1.5-T hole-body MR scanner

(Magnetom Vision Plus, Siemens Medical Solutions, Erlangen, Gemany). The

imaging protocol comprised a high-resolution 3D gradient echo sequence (3D-MPR),

a fluid attenuated inversion recovery sequence (FLAIR), a T2-weighted gradient echo

sequence (T2W), a dynamic T2*-weighted echo planar imaging sequence for the

imaging of perfusion (PWI) and a T1-weighted spin echo sequence after the

administration of gadolinium-containing contrast agent (gadopentetate dimeglumine

[Magnevist], Schering Berlin, Germany). The MR measurement sequences had the

following characteristics:

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3D-MPR: gradient echo, TR = 11.6 ms, TE = 4.9 ms, flip angle = 12°, slab thickness

= 180 mm, 180 partitions, field of view (FOV) = 256 mm, matrix = 256 x 256, scan

time = 11min 30 sec.

FLAIR: turbo inversion recovery, TR = 9000ms, TE = 105ms, TI = 2500ms, flip angle

= 180°, 21 slices, thickness = 5mm, distance factor = 0.3, FOV = 250mm, matrix =

224 x 256, scan time = 4min 57sec.

T2W: gradient echo, TR = 840ms, TE = 26ms, flip angle = 25°, 21 slices at 5mm

thickness, distance factor = 0.3, FOV = 250mm, matrix = 224 x 256, scan time =

3min 10sec.

PWI: single shot echo planar imaging, TE = 54ms, flip angle = 90°, FOV = 240mm,

12 slices, distance factor = 0.3, matrix = 128 x 128, 50 measurements at an interscan

interval of 1600ms, scan time 1min 20sec.

T1W: spin echo, TR = 560ms, TE = 17ms, flig angle = 70°, 19 slices, distance factor

= 0.1, matrix = 192 x 256, FOV = 230mm, scan time = 3min 38sec.

During the dynamic perfusion imaging sequence 10 seconds after starting the

measurement a 15ml bolus of gadolinium-containing contrast agent [Magnevist] was

injected in an antecubital vein at a rate of 5 ml/sec and was immediately followed by

15 ml of sodium chloride injected at the same rate.

2.3. Perfusion image analysis

The employed method was described recently (Luckhaus et al., 2008).

For the sake of completeness the procedure of PWI analysis is described in brief in

the following. The dynamic EPI data were transferred to an external workstation and

processed using the software stroketool (http://www.digitalimagesolutions.de,

Frechen, Germany). Maps of the regional cerebral blood flow (rCBF), the regional

http://www.digitalimagesolutions.de/

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cerebral blood volume (rCBV) and the mean transit time (MTT) were calculated using

the singular value decomposition (SVD) technique (Ostergaard et al., 1996). For the

quantification of rCBF normal white matter served as an internal standard

(Ostergaard et al. 1996, Leenders et al. 1990, Luckhaus et al. 2008).

For the regional analysis of the cerebral perfusion rCBF images were coregistered to

the high resolution 3D gradient echo images using rigid body transformation on a

patient by patient basis. The cerebral blood flow then was determined in manually

placed regions of interest (ROI’s). The ROI’s were drawn in the 3D anatomical

images guided by anatomical landmarks. Then the ROI’s were copied to the rCBF

maps.

The following cerebral regions were analyzed: frontobasal (FROB) including parts of

the superior and medial frontal gyrus, temporoparietal (TPAR, superior temporal and

angulate gyrus), mesotemporal (MTMP, hippocampus), anterior/posterior cingular

cortex (ACING, PCING, cingulate gyrus), amygdalae (AMYG), thalami (THAL) and

cerebellar cortex (CEREBELL). ->Figure???

(Further details in Luckhaus et al. 2008).

2.4. Volumetric image analysis

Volumetric analyses were performed with the interactive software package Display,

developed at McConnell Brain Imaging Centre at the Montreal Neurologic Institute.

Four raters blinded to subjects identity, clinical diagnosis and left/right orientation of

scans conducted the volumetry. The number of scans per rater was balanced for

diagnosis. The anatomical boundaries used for segmentation of hippocampus and

amygdala have been described in detail in a previous study (Pruessner JC, Li LM,

Serles W, Pruessner M, Collins DL, Kabani N, Lupien S, Evans AC. (2000):

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Volumetry of hippocampus and amygdala with high-resolution MRI and three-

dimensional analysis software: minimizing the discrepancies between laboratories.

Cerebral Cortex 10(4):433-442).

Inter-rater reliability was established through four raters independently measuring the

same set of 10 MRI scans The relative error for each pairwise comparison between

the four raters was below 5% for all volumetric measures obtained by the four raters.

The intra-class correlation coefficients across the four raters were 0.92 for right and

0.93 for left hippocampus, and 0.69 for right and 0.80 for left amygdala.

2.5. Apolipoprotein E genotyping

Blood samples for DNA acquisition were available from a total of 36 MCI and AD

subjects. For DNA analysis, leukocyte DNA was isolated with the Qiagen blood

isolation kit (Qiagen, Hilden, Germany). The apoE ε4 genotyped was studied as

previously described (Hixson and Vernier, 1990)

2.6. Statistical analysis The two groups MCI and AD were compared by t-tests in case of continuous data

and χ²-test in case of categorical data. Correlation analysis were carried out using the

Pearson product-moment correlation coefficient, whereas correlations were

computed separately for MCI and AD. Differences between patients without apoE ε4

allels and patients with 1 or 2 apoE ε4 allels referring to brain volume were again

investigated by t-tests.

A value of p <= 0.05 was defined to be significant.

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3. Results

Table 1 gives basic demographic and psychometric data of the two groups under

study. MMSE and GDS psychometric scores were significantly different between the

MCI and AD group, while group differences in age and gender distribution were non-

significant.

Table 2 summarizes rCBF values of MCI and AD patients. A lower rCBF (-11 %) was

detected in the posterior cingulum of AD vs. MCI subjects. The perfusion of all other

cerebral regions under study was not different between both groups.

Table 3 gives regional brain volume data of MCI and AD patients. Significant volume

reductions in AD vs. MCI were found for both amygdala (left: -15 %; right: -21 %)

and the right hippocampus (-14 %), while the left hippocamal volume (-11 %)

reduction was not significant.

Tables 4 and 5 show correlations between regional perfusion and volumes for the

MCI and AD group, respectively.

In MCI left hippocampal volume was negatively correlated with frontobasal perfusion

of both hemispheres and with perfusion of the left thalamus (Fig. 1). All other

examined regions showed no significant correlations between perfusion and volume.

In mild AD right hippocampal volume was positively correlated with perfusion of left

and right thalami. Also right amygdala volume was positively correlated with left and

right mesotemporal perfusion. (Fig. 2)

Kommentar [T4]: Beii 13*4 Einzelvergleichen/Gruppe macht man sich schon etwas Sorgen wegen des Alphafehlers. Sollte zumindest diskutiert werden

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Tables 6 depicts the association of the apoE ε4 allele with regional brain volume in

the merged group of MCI and AD. Decreased volumes of the right hippocampus and,

as a trend, of the left hippocampus, but not of amygdala were associated with the

presence of the apoE ε 4 allele. In contrast rCBF of all analysed regions including the

mesiotemporal and amygdala regions were not assciated with apoE ε4 genotype

(data not shown).

4. Discussion

The major findings of our study are:

1. Significant brain volume reductions were observed in mild AD vs. MCI for both

amygdala and the right hippocampus.

2. No rCBF changes were apparent in mild AD vs. MCI in the above brain

regions or in all other analysed regions except for reduced rCBF in the

posterior cingulum.

3. There was no correlation between rCBF and volumes in hippocampi or

amygdala, neither in MCI nor in mild AD.

4. In MCI we found negative correlations of left hippocampal volume with

frontobasal perfusion of both hemispheres and with perfusion of left thalamus.

5. In AD we found positive correlations of the right hippocampal volume with

perfusion of both thalami and of right amygdala volume with perfusion of left

and right mesotemporal regions.

6. Presence of one or more apoE ε4 alleles was associated with reduced

hippocampal but not amygdala volumes in MCI and mild AD, while there was

no association with rCBF.

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The observed hippocampal volume reductions in mild AD vs. MCI are in close

accordance with Colliot et al. (2008), who reported reductions of 15 %. They also

described a substantial hippocampal volume loss in MCI vs. controls, as did

Devanand et al. (2007), suggesting that hippocampal atrophy begins in preclinical

AD and continues throughout the clinical onset of dementia. Amygdala volume

reductions have previously been described in very mild AD patients vs. controls

(Basso et al., 2006), and further reductions have been reported in mild to

moderate AD (Horínek et al., 2006). Volume losses of both structures have been

associated with compromised memory performance in AD (Basso et al., 2006).

Significant rCBF reductions in MCI vs. controls have been described for the

hippocampi, amygdalae and anterior cingulum (Johnson et al., 1998; Fakhri et al.,

2003; Luckhaus et al., 2008). Regarding the transition from MCI to AD, further

rCBF reductions seem to be largely limited to the posterior cingulum (Ishiwata et

al., 2006; Luckhaus et al., 2008). This suggests that hypoperfusional changes in

hippocampi and amygdalae occur in incipient AD and reach a plateau at the MCI

stage, while cerebral volume loss of the same regions continues further into

clinical AD stages. Regional CBF and volume changes, thus, appear to be

dissociated in early AD in respect to time course and localisation. Accordingly, we

saw no correlations of hippocampal and amygdala volumes with the respective

mesiotemporal and amygdala rCBF in MCI or mild AD.

On the other hand, in MCI we found negative correlations of left hippocampal

volume with frontobasal perfusion of both hemispheres and with perfusion of the

left thalamus (Fig. 1). Prefrontal cortex function is particularly involved in strategic

aspects of memory retrieval, such as establishing a retrieval mode and goals,

initiating and guiding search, and monitoring and verifying the memories that have

Kommentar [T5]: Wahrschein-lich meinen Sie das umgekehrt: zunächst MCI dann AD

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been retrieved, while the thalamus subserves as a relay station (Moscovitch et al.,

2005). Frontal brain regions are typically spared from atrophy in MCI (Pennanen

et al., 2006). Increased prefrontal activation, as depicted by increased blood flow

or BOLD response, may, thus, constitute a functional compensatory mechanism

of hippocampal dysfunction in incipient AD. In accordance, analysis of regional

low-frequency fluctuations of fMRI signal intensity showed increased left

hippocampal connectivity with the right prefrontal cortex in early AD (Wang et al.,

2006). Gould et al. (2005) described a corresponding trend towards increased

BOLD responses in frontal brain areas during an associate learning task in mild

AD.

In contrast to the findings in MCI, we saw positive correlations in mild AD of

hippocampal and amygdala volume loss with reduced rCBF in functionally

connected brain areas, i.e. both thalami and mediotemporal regions, respectively

(Fig. 2). These results match the diachisis hypothesis of morphological and

functional brain changes in early Alzheimer’s disease, which postulates distant

hypofunctional effects caused by neuronal damage in the hippocampus via a

disconnection process (Villain et al., 2008). A recent voxel-based comparison of

structural MRI- and 18FDG-PET-data in early AD showed opposite atrophy –

hypometabolism ratios of the hippocampus (atrophy > hypometabolism) as

compared to other functionally connected brain areas (hypometabolism > atrophy)

(Chételat et al., 2008). Regarding white matter loss in relation to glucose

metabolism, deterioration of the cingular bundle, a major fibre tract linking the

hippocampi with functionally related structures, was highly correlated with

hypometabolism of the thalami (Villain et al., 2008).

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The observed dissociation of regional cerebral atrophy and perfusion in incipient

and early AD suggests that underlying pathogenetic mechanisms may also

diverge. We, therefore, analysed the association of both variables with the ApoE

ε4 allele. ApoE ε4 is the most consistently confirmed genetic risk factor of AD and

has been implicated in biochemical disease mechanisms (Saunders et al., 2000).

In the merged group of MCI and mild AD subjects we distinguished ApoE ε4

carriers with one or two alleles from non-carriers. We found significantly reduced

hippocampal, but not amygdala volume in carriers. Wang et al. (2006) also

described the association of the ApoE ε4 allele with smaller hippocampal volume

in MCI and mild AD. Van de Pol et al. (2007) found a higher hippocampal atrophy

rate in MCI subjects carrying a ApoE ε4 allele. Regarding amygdala atrophy, two

studies suggest that an association with the ApoE ε4 genotype in MCI and early

AD becomes apparent in ApoE ε4 homocygotes only (Lehtovirta et al., 1995;

Pennanen et al., 2006). Hashimoto et al. (2001) described a negative correlation

of the number of ApoE ε4 alleles with both hippocampal and amygdala volume in

probable AD. Possibly, a higher ApoE ε4 gene dose effect underlies the

association with amygdala atrophy, as is also suggested by the data of Pennanen

et al., 2006. Alteratively, amygdala volume association with the ApoE genotype

may be detectable in ApoE ε4 homocygotes only, because of limitations in

imaging technology and sample sizes.

The observed lack of ApoE genotype association with rCBF is in association with

findings by Sakamoto et al. (2003). They used SPECT longitudinally in

conjunction with MRI in very mild AD and found that declines of rCBF did not

differ in ApoE ε4 carriers vs. non-carriers, when partial volume effects were

corrected. An earlier report by Lehtovirta et al. (1998) on a positive association of

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the ApoE ε4 allele with temporoparietal hypoperfusion in AD using SPECT

images uncorrected for partial volume effects is probably spurious due to the

above methodological concern.

Regarding the collective evidence, one can conclude that in MCI and early AD an

ApoE ε4 genetic effect is stronger on hippocampal than amygdala atrophy and

that functional rCBF changes are not driven by ApoE ε4. This divergent genetic

effect on regional brain atrophy and perfusion strengthens the argument that

these variables, although functionally interacting, are dissociated regarding their

causation and pattern of occurence in the complex AD process.

Prospective longitudinal studies assessing combined structural and functional

imaging data together with genotypes in incipient AD are thought to be promising

for further research on this topic.

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Acknowledgement

This study was carried out in association with the German Competence Network for

Dementias (Kompetenznetz Demenzen), which is supported by the Federal Ministry

for Education and Research (Bundesministerium für Bildung und Forschung, grant

no. 01GI0420).

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- 25 -

Figure Legends

Table 1: Psychometric and demographic data of study groups (MCI, mild cognitive

impairment; AD, Alzheimer’s dementia).

Table 2: Regional cerebral blood flow (rCBF) in millilitres per 100 g brain matter per

minute in various brain regions of subjects with mild cognitive impairment (MCI) vs.

Alzheimer’s dementia (AD). (L, left hemisphere; R, right hemisphere; FROB,

frontobasal; MTMP, mesotemporal; TPAR, temporoparietal; AMYG, amygdale;

ACING, anterior cingulum; PCING, posterior cingulum; THAL, thalamus; CEREBELL,

cerebellum)

Table 3: Regional brain volumes in ??Herr Teipel, bitte Maßeinheit ergänzen?? of

hippocampi (HIPPOCAMP) and amygdalae (AMYG) of subjects with mild cognitive

impairment (MCI) vs. Alzheimer’s dementia (AD). (L, left hemisphere; R, right

hemisphere)

Table 4: Pearson’s correlation analysis of regional cerebral blood flow (rCBF) of

various brain regions and hippocampal (HIPPOCAMP) and amygdalar (AMYG)

volumes in subjects with mild cognitive impairment (MCI). Yellow markings denote

significant correlations. (L, left hemisphere; R, right hemisphere; FROB, frontobasal;

MTMP, mesotemporal; TPAR, temporoparietal; AMYG, amygdale; ACING, anterior

cingulum; PCING, posterior cingulum; THAL, thalamus; CEREBELL, cerebellum)

- 26 -

Table 5: Pearson’s correlation analysis of regional cerebral blood flow (rCBF) of

various brain regions and hippocampal (HIPPOCAMP) and amygdalar (AMYG)

volumes in subjects with Alzheimer’s dementia (AD). Yellow markings denote

significant correlations. (L, left hemisphere; R, right hemisphere; FROB, frontobasal;

MTMP, mesotemporal; TPAR, temporoparietal; AMYG, amygdale; ACING, anterior

cingulum; PCING, posterior cingulum; THAL, thalamus; CEREBELL, cerebellum)

Table 6: Regional brain volumes of MCI and AD subjects in relation to the absence

or presence of apoE ε4 alleles. (L, left hemisphere; R, right hemisphere;

HIPPOCAMP, hippocampus; AMYG, amygdale).

Figure 1: Schematic picture of correlative changes of regional brain volumes and

perfusion in mild cognitive impairment (MCI). (L, left hemisphere; R, right

hemisphere; FROB, frontobasal; HIPPOCAMP, hippocampus; AMYG, amygdale;

THAL, thalamus)

Figure 2: Schematic picture of correlative changes of regional brain volumes and

perfusion in mild Alzheimer’s dementia (AD). (L, left hemisphere; R, right

hemisphere; FROB, frontobasal; HIPPOCAMP, hippocampus; MTMP, mesotemporal;

AMYG, amygdale; THAL, thalamus)

Kommentar [T6]: Unklar, insbesodnere werden auch Farben nicht erklärt, eher weg-lassen.

- 27 -

L-FROB

R-FROB Perfusion ↑

L-

CAMP

R-IPPO

CAMP HIPPO- H -

Volumen ↓

L-AMYG

R-AMYG

L-THAL

R-THAL

Perfusion ↑

- 28 -

Volumen ↓

Perfusion ↓

Perfusion ↓

Volumen ↓

THAL

right

THAL

left

AMYG

right

AMYG

left

L-MTMP

R-HIP-

POCA

L-HIP-

POCA

L-MTMP

R-FROB

L-FROB

- 29 -

group N mean s.d. p (t-test)

MMSE MCI 30 27.5 1.8

AD 15 23.3 2.0 0.0001

GDS MCI 30 2.2 0.4

AD 15 3.5 0.5 0.0001

age MCI 30 63.9 9.5

AD 15 68.7 7.6 0.091

% male p (χ²-test)

gender MCI 30 56.7

AD 15 26.7 0.057

- 30 -

regional cerebral blood flow (rCBF)

brain region diagnostic

group N

mean s.d.

p (t-test)

MCI 30 36.48 6.69 L-FROB

AD 15 38.54 5.35 n.s.

MCI 30 37.14 7.10 R-FROB

AD 15 37.63 5.65 n.s.

MCI 30 38.19 12.12 L-MTMP

AD 15 36.69 9.70 n.s.

MCI 30 36.63 9.53 R-MTMP

AD 15 36.75 8.28 n.s.

MCI 30 43.52 5.61 L-TPAR

AD 15 43.65 5.73 n.s.

MCI 30 43.73 6.38 R-TPAR

AD 15 43.88 7.14 n.s.

MCI 30 37.77 11.69 L-AMYG

AD 15 31.81 9.37 n.s.

MCI 30 36.14 11.56 R-AMYG

AD 15 32.56 9.53 n.s.

MCI 30 45.46 8.39 ACING

AD 15 47.79 8.04 n.s.

MCI 30 47.04 6.03 PCING

AD 15 42.03 4.73 0.004

MCI 19 46.84 7.82 L-THAL

AD 11 49.57 9.43 n.s.

MCI 19 46.31 7.48 R-THAL

AD 11 47.79 6.80 n.s.

MCI 19 39.71 5.35 CEREBELL

AD 11 38.40 6.87 n.s.

- 31 -

brain volume brain region

diagnosticgroup

N mean s.d.

p (t-test)

MCI 30 1975.5 378.0 L-HIPPOCAMP

AD 15 1759.8 438.2

0.094

MCI 30 1999.5 385.7 R-HIPPOCAMP

AD 15 1716.5 526.3

0.046

MCI 30 556.3 127.1 L-AMYG

AD 15 473.0 107.2

0.035

MCI 30 579.8 163.2 R-AMYG

AD 15 458.9 91.6

0.011

- 32 -


regional brain volume

L-HIPPOCAMP R-HIPPOCAMP L-AMYG R-AMYG Pearson correlation -0.407 -0.292 -0.223 -0.359 significance (2-sided) 0.026 0.118 0.236 0.051

L-FROB N 30 30 30 30

Pearson correlation -0.484 -0.334 -0.179 -0.308 significance (2-sided) 0.007 0.072 0.345 0.098

R-FROB N 30 30 30 30

Pearson correlation -0.123 0.058 0.025 -0.258 significance (2-sided) 0.517 0.762 0.896 0.169

L-MTMP N 30 30 30 30


R-MTMP N 30 30 30 30


L-TPAR N 30 30 30 30


R-TPAR N 30 30 30 30

Pearson correlation -0.155 0.008 0.103 0.034 significance (2-sided) 0.415 0.967 0.588 0.858

L-AMYG N 30 30 30 30

Pearson correlation -0.004 0.063 0.089 0.096 significance (2-sided) 0.981 0.742 0.640 0.613

R-AMYG N 30 30 30 30


ACING N 30 30 30 30


PCING N 30 30 30 30

Pearson correlation -0.460 -0.219 -0.152 0.161 significance (2-sided) 0.047 0.368 0.533 0.510

L-THAL N 19 19 19 19

Pearson correlation -0.329 -0.201 -0.116 0.095 significance (2-sided) 0.169 0.409 0.636 0.700

R-THAL N 19 19 19 19

Pearson correlation 0.284 0.426 0.213 0.255 significance (2-sided) 0.239 0.069 0.381 0.292

CEREBELL N 19 19 19 19

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regional brain volume

L-HIPPOCAMP R-HIPPOCAMP L-AMYG R-AMYG L-FROB Pearson correlation -0.190 0.022 -0.144 -0.114

significance (2-sided) 0.498 0.938 0.610 0.686 N 15 15 15 15

R-FROB Pearson correlation -0.389 -0.229 -0.261 0.081 significance (2-sided) 0.151 0.412 0.348 0.775 N 15 15 15 15

L-MTMP Pearson correlation -0.072 0.116 0.373 0.571 significance (2-sided) 0.799 0.681 0.171 0.026 N 15 15 15 15

R-MTMP Pearson correlation -0.216 0.038 0.140 0.609 significance (2-sided) 0.440 0.893 0.620 0.016 N 15 15 15 15

L-TPAR Pearson correlation 0.126 0.342 0.186 0.460 significance (2-sided) 0.654 0.212 0.507 0.085 N 15 15 15 15

R-TPAR Pearson correlation 0.018 0.202 0.081 0.496 significance (2-sided) 0.950 0.471 0.774 0.060 N 15 15 15 15

L-AMYG Pearson correlation -0.141 -0.201 0.166 0.081 significance (2-sided) 0.617 0.472 0.555 0.774 N 15 15 15 15

R-AMYG Pearson correlation 0.001 -0.162 -0.015 -0.199 significance (2-sided) 0.998 0.563 0.959 0.477 N 15 15 15 15

ACING Pearson correlation 0.149 0.311 0.177 0.098 significance (2-sided) 0.597 0.259 0.528 0.729 N 15 15 15 15

PCING Pearson correlation -0.295 -0.001 0.048 0.465 significance (2-sided) 0.285 0.997 0.865 0.081 N 15 15 15 15

L-THAL Pearson correlation 0.258 0.694 0.057 -0.126 significance (2-sided) 0.444 0.018 0.869 0.711 N 11 11 11 11

R-THAL Pearson correlation 0.251 0.654 0.111 -0.109 significance (2-sided) 0.456 0.029 0.746 0.749 N 11 11 11 11

CEREBELL Pearson correlation -0.168 0.092 0.306 0.551 significance (2-sided) 0.621 0.788 0.361 0.079 N 11 11 11 11

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brain volume

??Einheit, Herr Teipel???

brain region

apoE ε4 alleles

N

mean

s.d.

p (t-test)

none 18 2083,7 407,5 L-HIPPOCAMP

1 or 2 18 1809,6 427,9

0,057

none 18 2149,3 362,5 R-HIPPOCAMP

1 or 2 18 1788,7 507,7

0,019

none 18 544,9 138,8 L-AMYG

1 or 2 18 501,7 116,1

0,319

none 18 568,9 184,3 R-AMYG

1 or 2 18 508,6 133,1

0,268

The relation of regional cerebral perfusion and atrophy in mild cognitive impairment (MCI) and early...

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