- Email: [email protected]
Regional Cerebral Perfusion Alterations in Patients with Mild Cognitive Impairment and Alzheimer Disease Using Dynamic Susceptibility Contrast MRI
Regional Cerebral Perfusion Alterations in Patients with Mild Cognitive Impairment and Alzheimer Disease Using Dynamic Susceptibility Contrast MRI € nknecht, MD, Philipp A. Thomann, MD, Lars Gerigk, MD, Thomas Hauser, MD, Peter Scho € der, MD, Romy Henze, PhD, Alexander Radbruch, MD, Marco Essig, MD, PhD Johannes Schro Rationale and Objectives: The purpose of this study was to assess regional cerebral perfusion distribution in patients with Alzheimer disease (AD) or mild cognitive impairment (MCI) using dynamic susceptibility contrast magnetic resonance imaging. Materials and Methods: Regional changes of perfusion were evaluated in 34 patients with AD, 51 patients with MCI, and 23 healthy controls (HCs). Using region of interest analyses, regional cerebral blood flow (CBF), cerebral blood volume, and mean transit time were measured bilaterally in the hippocampus; the temporal, temporoparietal, frontal, and sensomotoric cortices; the anterior and posterior cingulate gyri; the lentiform nucleus; and the cerebellum. Results: A significant reduction of CBF in patients with AD compared to HCs was shown in the frontal and temporoparietal cortices bilaterally, the lentiform nuclei bilaterally, the left posterior cingulate gyrus, and the cerebellum. Compared with patients with MCI, patients with AD presented a reduction of CBF in the frontal cortices bilaterally, the left temporoparietal cortex, and the left anterior and posterior cingulate gyrus. In both hippocampi and the posterior cingulate gyrus, a trend to a slight increase of CBF in patients with MCI was noticed with a decrease in patients with AD. Conclusions: Using dynamic susceptibility contrast magnetic resonance imaging, pathologic alterations of regional brain perfusion can be demonstrated in patients with AD compared to patients with MCI or HCs. Key Words: Alzheimer dementia; cerebral blood flow; dynamic susceptibility contrast MRI; mild cognitive impairment; regional perfusion alteration. ªAUR, 2013
D
ementing disorders are the most frequent neuropsychiatric diseases of the elderly population. In about two thirds of subjects with dementia, the dementia is related to Alzheimer disease (AD) (1). AD has an insidious
Acad Radiol 2013; 20:705–711 From the Department of Radiology E010, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany (T.H., L.G., R.H., A.R., M.E.); Department of Psychiatry and Psychotherapy, Section of Geriatric Psychiatry, University of Leipzig, Germany (P.S.); Department of General Psychiatry, Section of Geriatric Psychiatry, Ruprecht-KarlsUniversity, Heidelberg, Germany (P.A.T., J.S., R.H.); Department of Diagnostic Radiology, Ruprecht-Karls University, Heidelberg, Germany (L.G.); Department of Child and Adolescent Psychiatry, Center of Psychosocial Medicine, Ruprecht-Karls-University, Heidelberg, Germany (R.H.); Department of Neuroradiology, Ruprecht-Karls University, Heidelberg, Germany (A.R.); and Department of Neuroradiology, FriedrichAlexander-University, Erlangen, Germany (M.E.). Received November 15, 2012; accepted January 18, 2013. Address correspondence to: T.H. e-mail: [email protected] ªAUR, 2013 http://dx.doi.org/10.1016/j.acra.2013.01.020
onset and progresses in a time-frame of years with decline in a broad range of neuropsychological domains such as memory, executive functions and attention, language, and apraxia. In AD, the progressive degeneration of the brain is, on the one hand, caused by changes in tau protein, which lead to destabilization of the cytoskeleton (2,3). On the other hand, increased creation of b-amyloid and its accumulation into amyloid plaques lead to an inflammatory and oxidative-toxic processes (3). Both processes result in an irreversible damage of neuronal cells. Beside the deposition of amyloid in the brain parenchyma in AD, a perivascular amyloid accumulation is present in most cases (3–6). Thus, small-vessel alterations are obvious, resulting in altered cerebral blood flow (CBF). In addition, reduced CBF and the resulting reduced elimination of amyloid may amplify further accumulation of amyloid in perivascular regions and the brain parenchyma itself, with both situations worsening the dementing disorder (5). The preclinical phase of AD is characterized by mild cognitive deficits that exceed physiologic age-related cognitive 705
HAUSER ET AL
decline. However, they are not as severe as in subjects with a confirmed dementing disorder. Clinical and epidemiologic evidence indicate that this preliminary stage, called mild cognitive impairment (MCI), remains subtle over a long phase before the threshold of dementia is reached (1). It is assumed that MCI is associated with a substantially increased risk of AD (7–10). The early diagnosis of AD and the exclusion of secondary causes of dementia are essential for optimized therapeutic management of patients. In the past years, there has been an increasing use of neuroimaging in the diagnostic workup of individuals with mental decline (11–14). Magnetic resonance imaging (MRI) is used to rule out secondary dementias, which refer to somatic disorders other than neurodegenerative diseases or concomitant conditions that may be associated with the dementing disorder. Beside the exclusion of secondary causes, the detection of subtle changes in the early stages of dementia, including the investigation of the underlying pathophysiology, has gained increasing interest. Early MRI studies revealed a significant loss of brain parenchyma in the progress of dementing disorders. According to the anatomic studies of Braak and Braak (2), the atrophy follows a predefined pattern that can be assessed with morphometric studies. Currently, different morphologic cerebral neuroimaging methods are being applied in the diagnosis of dementia (15,16). However, in the past few years, a number of advanced MRI techniques, like MR spectroscopy (17,18) or the evaluation of magnetization transfer ratios (19), have been developed that provide new insights into the pathophysiology of neurodegenerative diseases. Dynamic susceptibility contrast (DSC)-MRI is another functional method. It allows a robust quantification of perfusion and tissue microcirculation (20) after an intravenous bolus injection of contrast medium. This leads to a temporary drop in T2* signal intensity due to susceptibility effects. Several functional parameters of tissue perfusion, such as CBF, cerebral blood volume (CBV), and mean transit time (MTT), can be calculated from the signal-time curve. The arterial spin labeling (ASL) technique is another technique that allows the quantification of perfusion alterations. However, compared to the DSC approach, the technique of ASL is more prone to artifacts, especially to motion artifact. Hence, DSC-MRI provides the more robust technique in patients with dementia. Some earlier MRI studies point to changes in perfusion pattern in patients with AD (21–25). As in the progression of a cognitive decline to AD a pronounced accumulation of perivascular amyloid over a long period of time is known (3–6), altered regional cerebral perfusion in the development of AD is obvious. According to previous 18 F-fludeoxyglucose–positron emission tomography (FDGPET) studies (14,26–29), which demonstrated a reduced glucose metabolism in AD mainly in the posterior cingulate gyrus, as well as in the temporoparietal and prefrontal region, we expect changes in perfusion analyses, especially in these areas. The purpose of the current study was to assess 706
Academic Radiology, Vol 20, No 6, June 2013
regional perfusion distributions by the use of DSC-MRI in subjects with AD and MCI. MATERIALS AND METHODS Subjects
The study was approved by the institutional review board and performed in accordance with the ethical standards of the Declaration of Helsinki. Depending on the level of cognitive impairment, we obtained written informed consent from either the participants or their caregivers after the planned procedures were explained by a geriatric psychiatrist and radiologist. Exclusion criteria were general contraindication for MRI (eg, pacemaker) or for the application of gadoliniumcontrast media (eg, renal failure or known adverse reaction). Patients with known vascular dementia, depression, history of malignancy, drug, or alcohol abuse, or any other medical, neurologic, or psychiatric disorder that could result in a cognitive deterioration were not included in the study. A total number of 100 consecutive subjects with mental decline were prospectively recruited from the Memory Clinic of the Department of Geriatric Psychiatry. After clinical assessments and the MRI examination, 15 of these 100 consecutive patients had to be excluded from analyses due to previously unknown secondary causes of dementia: pronounced microvascular changes (n = 9), postischemic lesions (n = 2), normal pressure hydrocephalus (n = 1), probable postinflammatory changes (n = 1), posttraumatic lesions (n = 1), and motion artifacts in MRI (n = 1). Of these remaining 85 patients, 51 patients were assigned the diagnosis of MCI and 34 were assigned the diagnosis of AD. The definitive diagnosis in each individual was confirmed by two experienced psychiatrists with long-standing special knowledge of geriatric psychiatry. All subjects were clinically assessed according to the concept of the Aging-Associated Cognitive Decline (AACD) (30) and the criteria of the National Institute of Neurological and Communicative Disorders and Stroke in concert with Alzheimer’s Disease and Related Disorders Association (NINCDS-ADRDA) (31). For comparison, 25 age-matched healthy control subjects (HCs) with an age >55 years were included in the study. All potential healthy subjects were examined by an experienced psychiatrist with special knowledge of geriatric psychiatry to exclude cognitive impairment or dementia. Two of these healthy subjects had to be excluded from analyses after MRI examination because of pronounced microvascular changes. The three groups did not differ significantly in age (P = .151) or sex (c2 = 0.164, P = .921). Clinical Evaluation
Clinical evaluation included the ascertainment of personal and family history and detailed physical, neurologic, and neuropsychological evaluations. None of the participants had a lifetime history of neurologic or severe medical illness, head
Academic Radiology, Vol 20, No 6, June 2013
CEREBRAL PERFUSION ALTERATIONS IN AD AND MCI
Figure 1. Patient with mild cognitive impairment. The figures show an example of region of interest [placement in the cerebellum (a), the left temporoparietal cortex (b), the left frontal cortex (c), and the anterior cingulate gyrus left (d) on cerebral blood flow] maps. The sulci and adjacent vessels were excluded from analysis.
injury, or substance abuse. We assessed global cognitive deficits using the Mini Mental State Examination (MMSE) (32). We investigated cognitive performance using a standardized extensive neuropsychological test battery (Consortium to Establish a Registry for Alzheimer’s Disease) (33,34). Handedness was assessed using the Edinburgh inventory (35). All participants were dominantly right-handed.
medium was measured over a period of 2.5 minutes with a time resolution of 1.5 seconds for each repetition. Due to limitations in the number of slices, the coverage of the brain structures was limited. Depending on the head size and positioning of the patient, the perfusion could not be assessed in the most cranial brain areas, including the sensomotoric cortices. Analysis and Postprocessing
MRI
All enrolled subjects underwent a standardized MRI procedure on either a 1.5-Tor a 3-T MRI scanner (MAGNETOM Avanto and Trio, Siemens Medical Solutions, Erlangen, Germany). The MRI examinations among the three groups (AD, MCI, and HC) did not differ significantly in field strength (c2 = 0.289, P = .865). Morphologic MR images. For structural analysis, a T1weighted three-dimensional magnetization prepared rapid gradient echo sequence was performed. To exclude secondary causes of dementia or ischemic changes, T2-weighted, fluidattenuated inversion recovery and diffusion-weighted images were performed. To rule out malignant tumors, additional T1-weighted sequences were added after application of contrast medium. DSC-MRI. Perfusion MRI was performed using a T2*weighted echo planar imaging gradient echo sequence in axial orientation (3 T: repetition time [TR] = 1450 ms, echo time [TE] = 45 ms, 13 slices, flip = 90 , slice thickness [SL] = 5 mm, matrix = 128, average = 1, bandwidth = 1345 Hz/pixel; 1.5 T: TR = 1440 ms, TE = 47 ms, 12 slices, flip = 90 , SL = 5 mm, matrix = 128, average = 1, bandwidth = 1345 Hz/pixel). A rapid bolus injection of gadolinium-contrast media (0.1 mmol/kg body weight) was applied by using a power injector with an injection rate of 5 mL/sec. The contrast medium injection was followed by a flush of 30 mL physiologic saline solution at the same injection rate. The DSC imaging started with the beginning of the application of contrast medium. The distribution of the contrast
Initially, qualitative analyses of all images were performed to exclude patients with other pathologies such as neoplasms, ischemia, or vascular changes. The DSC raw data were processed and converted into parameter maps for CBV, CBF, and MTT using the software tool NordicICE (NordicICE 2.3; NordicNeuroLab AS, Bergen, Norway). A single-rater region of interest (ROI) analysis was performed to assess the regional perfusion distribution in patients and HCs. ROIs were positioned in the sensomotoric, frontal, temporal, and temporoparietal cortices bilaterally as well as in the anterior and posterior cingulate cortices, the lentiform nuclei, the hippocampus bilaterally, and the cerebellum (Fig 1). Because of limited spatial resolution of the perfusion maps, ROIs were delineated on morphologic axial fluid-attenuated inversion recovery images and overlaid on the perfusion maps. Adjacent vessels were excluded from analysis. CBF, CBV, and MTT were quantified inside these ROIs. The rater positioning the ROIs was blinded to the clinical diagnosis in all subjects. All measurements that differ >3 SDs from the mean value inside the group were eliminated due to the high probability of arterial blood vessels included in these ROIs. Statistics
Statistical analyses were performed using SPSS (version 19; IBM SPSS; Chicago, IL). First, the normal distribution of the measurements was approved with a QQ-Plot. All quantitative measurements are presented as mean standard deviation (SD). An F test (analysis of variance) was performed to 707
HAUSER ET AL
Academic Radiology, Vol 20, No 6, June 2013
TABLE 1. Region of Interest Values of Cerebral Blood Glow* HCs Region of Interest Cerebellum Right hippocampus Left hippocampus Right temporal cortex Left temporal cortex Right temporoparietal cortex Left temporoparietal cortex Right lentiform nucleus Left lentiform nucleus Right anterior cingulate gyrus Left anterior cingulate gyrus Right posterior cingulate gyrus Left posterior cingulate gyrus Right frontal cortex Left frontal cortex Right sensomotoric cortex Left sensomotoric cortex
n 19 21 21 22 22 22 22 21 21 18 18 18 18 22 22 13 13
mean SD 63.9 32.2 49.9 24.6 50.4 24.8 63.2 39.6 56.1 34.0 69.0 35.6 68.0 35.8 58.7 32.8 60.2 33.7 49.2 24.2 46.2 25.0 52.4 28.9 51.6 28.0 59.8 33.3 60.6 35.0 47.3 30.6 44.8 29.0
Patients with MCI n 46 50 51 51 50 51 50 50 50 43 43 43 43 51 51 38 38
mean SD 52.4 27.7 51.2 25.8 52.6 29.5 56.3 29.2 51.0 27.7 60.1 31.8 58.7 27.8 44.5 24.8 47.3 26.0 48.9 24.4 48.3 24.1 55.0 31.0 53.5 30.8 51.5 28.7 50.3 28.2 47.1 24.2 47.7 27.0
F Test
Patients with AD n 34 34 34 34 34 34 33 34 34 28 28 28 28 34 34 25 25
mean SD y
43.6 19.7 43.1 24.1 47.0 22.2 44.6 21.5 40.7 18.4 48.6 22.0y 46.0 19.1y,z 36.6 18.1y 38.9 19.7y 36.0 19.2 34.9 17.0z 39.2 16.9 35.7 15.7y,z 39.7 16.1y,z 39.2 15.1y,z 35.2 19.2 34.3 18.6
P .028 .334 .637 .056 .081 .042 .013 .007 .015 .051 .044 .052 .020 .018 .014 .131 .113
n, number of patients; SD, standard deviation; HC, healthy control; MCI, mild cognitive impairment; AD, Alzheimer disease. Post-hoc t tests were calculated to test for significant group differences. *P values are calculated from an F test (analysis of variance) for detecting differences between the three groups. y Indicates P values in comparison to HC of <.05. z Indicates P values in comparison to MCI of <.05.
detect significant differences among the three groups. Posthoc two-sided t tests were calculated to test for significant group differences. P values <.05 were considered to represent a significant difference.
RESULTS A total number of 34 patients with AD (mean age, 71.8 8.8 years; MMSE, 22.0 3.9; 13 men and 21 women), 51 patients with MCI (mean age, 68.1 10.6 years; MMSE, 26.6 2.8; 21 men and 30 women), and 23 age-matched HCs (mean age, 67.4 8.9 years; 10 men and 13 women) were included in the final evaluation. In the analyses of CBF, CBV, and MTT, a relatively large interindividual distribution of these perfusion data within each group was noticed. In the CBF analysis (Table 1), a significant decrease (P < .05) in patients with AD in comparison to HCs was found in the frontal and temporoparietal cortices bilaterally, the lentiform nuclei, the left posterior cingulate gyrus, and the cerebellum. In comparison to patients with MCI, in patients with AD, a significant reduction of CBF in frontal cortices bilaterally, in the left temporoparietal cortex, and in the left anterior and posterior cingulate gyrus was detected. A significant difference of CBF between patients with MCI and HCs could not be demonstrated, although there was a tendency to lower levels of CBF in patients with MCI except in the hippocampus and posterior cingulate gyrus. In these brain areas, a slight increase (P > .05) of CBF could be noticed in patients with MCI with a decrease in patients with AD. 708
In CBV analysis, a significant reduction of CBV could only be displayed in the left frontal cortex between patients with MCI and HCs. In all other evaluated brain areas, in neither patients with MCI nor patients with AD could significant changes of CBV be demonstrated, although a tendency to lower levels of CBV could be noticed according to the progression of the disease. In the MTT analysis, no significant changes among the three groups could be demonstrated.
DISCUSSION The development of AD is a dynamic pathologic process starting with an undefined long preclinical phase before the clinical manifestation of dementia symptoms (2). During this transition to AD, both increases and mainly decreases of regional cerebral perfusion have been described (24). Therefore, we explored in our analyses changes of perfusion patterns in patients with MCI, a discussed precursor, and manifest early AD compared to age-matched HCs by using DSC-perfusion imaging. Until now, only limited data are available on using DSC-MRI for an improved assessment of patients with MCI and AD (23,36,37). In our study, a large number of subjects (N = 108) were included. Comparison of CBF Values in Patients with AD and HCs
In previous FDG-PET analyses (14,26–28), the most consistent findings of a reduced glucose metabolism in AD
Academic Radiology, Vol 20, No 6, June 2013
were localized in the posterior cingulate gyrus, in the temporoparietal and the prefrontal region. According to these metabolic changes, a reduction of CBF in these areas is likely. In our evaluation, we verified these by literaturepredicted changes because a significant decrease of CBF was detected in these areas in patients with AD in comparison to HCs with exception of the right cingulate gyrus. In the right posterior cingulate gyrus, only a nonsignificant reduction of CBF was found (P = .052). However, previously published perfusion studies showed different results. By using DSCMRI, previous analyses (23,36) mainly could not detect significant changes of perfusion in patients with AD in these areas. Although Cavallin et al (36) did not find a decrease of CBF in DSC analyses, a decrease in single-photon emission computed timigraphy data was present in both temporoparietal areas and the right posterior cingulate gyrus. In addition, by using ASL perfusion, various analyses demonstrated a reduced perfusion in the temporoparietal (24,38–41) and frontal regions (24,39,40) as well as in the posterior cingulate gyrus (24,38–43), which is in good accordance with our results. Additionally, our evaluation detected a significant reduction of CBF in the lentiform nuclei and in the cerebellum, which has not been described yet. Dai et al (24) described an increase of CBF in patients with MCI in the right basal ganglia. In comparison to these changes, involvement of the basal ganglia in patients with AD is feasible. According to morphologic changes described in the cerebellum in patients with AD (44), our results also point to an involvement of the cerebellum in patients with AD. The sparing of perfusion changes in the sensomotoric area correlates well with former ASL and PET analyses (14,24,26,40). Based on previous studies (15,45–48) that demonstrated morphologic changes in the hippocampus and the fact that the hippocampal region is typically involved early in pathologic changes in patients with AD (2), it is likely that changes in perfusion pattern could be noticed in these brain areas. Besides these morphologic changes, some previous studies reported a reduction of perfusion (23,36,39) or glucose metabolism (49,50) mesiotemporal in patients with AD or MCI. In our evaluation, we did not detect any significant perfusion changes in the hippocampal region, which is in agreement with several other studies (24,40–43). However, a slight reduction could be seen in patients with AD. One previous ASL study even describes a slight hippocampal hyperperfusion in comparison to HCs (41,51). These discrepant results are probably caused by a compensatory mechanism (24,51), trying to keep the perfusion relative constant over a long time period. Comparison of CBF Values in Patients with MCI and HCs
In comparison of patients with MCI to HC, we could only demonstrate a tendency of CBF reduction in most brain areas corresponding well with former reports. In the study by Cavallin et al (36), the authors could not find any changes of CBF in patients
CEREBRAL PERFUSION ALTERATIONS IN AD AND MCI
with MCI by using DSC-MRI. Also, by using single-photon emission computed tomography analyses (36), no changes in CBF were detected in the brain areas evaluated in our study. Nevertheless, Luckhaus et al (23) showed a reduced CBF in the mesiotemporal region bilaterally as well as in the anterior cingulate gyrus. Our data also correspond well with ASL analyses, as one study (40) could not find any significant changes in these regions, whereas another study (24) could show a reduced CBF merely in the posterior cingulate gyrus and an increase in the left hippocampus and in the right basal ganglia. The fact that we found a slight increase (P > .05) of perfusion in both hippocampi in patients with MCI also fits well with similar findings of several ASL analyses (41,51). These findings are also in accordance to previous blood oxygen level–dependent functional MRI (fMRI) studies showing increased brain fMRI. RI activation in patients with MCI but not in patients with AD (52,53). Similar perfusion patterns were also detected in both posterior cingulate gyri. In these areas, a slight increase of CBF was found in patients with MCI (P > .05) with a decrease in patients with AD (significant decline only on the left side), corresponding well with data of Luckhaus et al (23). Former fMRI analyses by Dickerson et al (54,55) demonstrated a hyperactivation of the hippocampal region in patients with MCI compared to HCs without morphologic differences in these groups. However, in patients with AD, a hypoactivation and an atrophy of the medial temporal lobe were present. The authors hypothesize that there is a phase of increased activation of the hippocampal region in the early phase of the disease before clinical onset (54,55). These changes may reflect a complex mechanism of degeneration and compensatory response to accumulating AD neuropathology (56) and differences in the neuroplasticity (54,57). According to these results, our findings of slight increases of CBF in patients with MCI in some regions such as the medial temporal lobe may be the result of an early compensatory mechanism, probably determined by an elevation of neuronal activity, inflammation, or production of vasodilators (24,51). Comparison of CBF Values in Patients with AD or MCI
In line with previous DSC analyses (23,37) demonstrating a significant reduction of CBF in the posterior cingulate gyrus in patients with AD in comparison to patients with MCI, our study approved these alterations. After adjusting for global perfusion, ASL perfusion also showed a decreased perfusion in the posterior cingulate gyrus and the temporoparietal cortices (40). Although changes in temporoparietal and frontal cortices were not shown in former DSC analyses (23,37), the detected decrease in the left temporoparietal (24,40) and frontal cortices (24) is supported by prior ASL-based studies. Hippocampal differences as described in one study (24) were not verified in our analyses. In accordance with previous DSC and ASL evaluations, no further significant changes in CBF were shown in patients with AD in comparison to patients with MCI. 709
HAUSER ET AL
CBV Analyses
Although a slight regional reduction of CBV was seen in our analysis in various brain areas in patients with MCI compared to HCs (pronounced in the frontal and temporoparietal cortices bilaterally, the right temporal cortex, the right anterior cingulate gyri, and the left lentiform nucleus), it reached the level of significance only in the left frontal cortex. In patients with AD, no further significant reduction of CBV could be recognized. Our findings of CBV are in accordance with regional ASL analyses of Yoshiura et al (43). This group also showed a slight but not significant reduction of arterial blood volume in patients with AD versus HCs. In contrast to this, several previous perfusion studies with DSC-MRI showed a reduction of CBV in patients with AD in comparison to HCs in the sensomotoric (21) and temporoparietal cortices (21,22) as well as in both hippocampi (21). MTT Analyses
In contrast to vascular dementias, in which the reduced perfusion pressure results in a dilatation of the small vessels and consequently in a regional prolongation in MTT (58), in patients with AD such changes have not been detected yet (58,59). As in the development of an AD mainly microangiopathic changes (due to the deposition of perivascular amyloid) but no macroangiopathic changes are obvious, no alterations of MTT are likely. This fits with our finding of no significant changes among HCs and patients with MCI or AD in MTT analyses. It is also in line with Yoshiura et al (43), who could not find any significant changes of regional arterial transit time in ASL measurements in patients with AD. Limitations
Overall, perfusion MRI may help us in the diagnosis of AD as a decline of CBF could be demonstrated in various brain areas, similar to former FDG-PET studies. The most consistent findings in FDG-PET analyses were a reduced glucose metabolism in patients with AD in the posterior cingulate gyrus and in the temporoparietal and prefrontal cortices (27,28), similar to our perfusion results. Previously, it was assumed that perfusion changes were the result of regional brain atrophy. This assumption was disproved by a correlative study (21) demonstrating significant changes of CBV persisting after normalizing for regional atrophy. Nevertheless, an early detection of evolving dementia in the early stadium of MCI is still difficult as only a tendency to lower CBF levels was found in patients with MCI, which did not reach the level of significance in comparison to HCs. There are some other limitations in the study. One limitation is that the perfusion measurements were made at different field strength (3 and 1.5 T), which may result in slightly different values. However, the sequence parameters were only slightly different and the distribution of subjects measured within each field strength did not vary significantly between 710
Academic Radiology, Vol 20, No 6, June 2013
the groups. Although this study demonstrates several changes of CBF between the groups, an important limitation of this method is the relative high interindividual variability of perfusion data. This fact is in accordance with the interindividual variability already described in FDG-PETanalyses (60). These variabilities of perfusion data may be the effect of the interindividual severity of the cognitive decline. This assumption should be evaluated in further studies. Furthermore, the accordance between perfusion data and the conversion of MCI to AD should be part of follow-up studies. Hence, it is not possible yet to define a cut-off level for the diagnosis of MCI or AD based on perfusion parameters alone. Nevertheless, DSC-MRI may provide a method that could provide important insights for an improved diagnosis of dementias.
CONCLUSIONS The long-lasting transition from normal cognition to AD comes along with both a decrease of perfusion and several slight increases of perfusion in different regions in the early stage. This supports the concepts of regional compensatory cellular mechanisms. However, a definitive diagnosis of MCI based only on DSC-MRI is not possible yet. Nevertheless, various changes of perfusion in AD, most notable in the CBF analyses, correlated well with findings from other studies, such as PET studies. DSC-MRI therefore provides noninvasively new insights into the early pathophysiologic changes of dementing disorders and may improve the early diagnosis of AD. ACKNOWLEDGMENTS We thank Sandra Kauczor for her help with technical assistance. The study was supported by the Alzheimer Forschung Initiative (AFI).
REFERENCES 1. Thies W, Bleiler L. 2011 Alzheimer’s disease facts and figures. Alzheimers Dement 2011; 7(2):208–244. 2. Braak H, Braak E. Evolution of neuronal changes in the course of Alzheimer’s disease. J Neural Transm Suppl 1998; 53:127–140. 3. Masters CL, Beyreuther K. Alzheimer’s centennial legacy: prospects for rational therapeutic intervention targeting the Abeta amyloid pathway. Brain 2006; 129(Pt 11):2823–2839. 4. Thal DR, Griffin WS, de Vos RA, et al. Cerebral amyloid angiopathy and its relationship to Alzheimer’s disease. Acta Neuropathol 2008; 115(6):599–609. 5. Bell RD, Zlokovic BV. Neurovascular mechanisms and blood-brain barrier disorder in Alzheimer’s disease. Acta Neuropathol 2009; 118(1):103–113. 6. Weller RO, Subash M, Preston SD, et al. Perivascular drainage of amyloidbeta peptides from the brain and its failure in cerebral amyloid angiopathy and Alzheimer’s disease. Brain Pathol 2008; 18(2):253–266. 7. Busse A, Bischkopf J, Riedel-Heller SG, et al. Mild cognitive impairment: prevalence and incidence according to different diagnostic criteria. Results of the Leipzig Longitudinal Study of the Aged (LEILA75+). Br J Psychiatry 2003; 182:449–454. 8. Petersen RC, Doody R, Kurz A, et al. Current concepts in mild cognitive impairment. Arch Neurol 2001; 58(12):1985–1992. 9. Ritchie K, Artero S, Touchon J. Classification criteria for mild cognitive impairment: a population-based validation study. Neurology 2001; 56(1):37–42.
Academic Radiology, Vol 20, No 6, June 2013
10. Schonknecht P, Pantel J, Kruse A, et al. Prevalence and natural course of aging-associated cognitive decline in a population-based sample of young-old subjects. Am J Psychiatry 2005; 162(11):2071–2077. 11. Ries ML, Carlsson CM, Rowley HA, et al. Magnetic resonance imaging characterization of brain structure and function in mild cognitive impairment: a review. J Am Geriatr Soc 2008; 56(5):920–934. 12. Hsu YY, Du AT, Schuff N, et al. Magnetic resonance imaging and magnetic resonance spectroscopy in dementias. J Geriatr Psychiatry Neurol 2001; 14(3):145–166. 13. Ramani A, Jensen JH, Helpern JA. Quantitative MR imaging in Alzheimer disease. Radiology 2006; 241(1):26–44. 14. Lehericy S, Marjanska M, Mesrob L, et al. Magnetic resonance imaging of Alzheimer’s disease. Eur Radiol 2007; 17(2):347–362. 15. Pantel J, Kratz B, Essig M, et al. Parahippocampal volume deficits in subjects with aging-associated cognitive decline. Am J Psychiatry 2003; 160(2):379–382. 16. Thomann PA, Dos Santos V, Seidl U, et al. MRI-derived atrophy of the olfactory bulb and tract in mild cognitive impairment and Alzheimer’s disease. J Alzheimers Dis 2009; 17(1):213–221. 17. Jessen F, Traeber F, Freymann K, et al. Treatment monitoring and response prediction with proton MR spectroscopy in AD. Neurology 2006; 67(3):528–530. 18. Kantarci K. 1H magnetic resonance spectroscopy in dementia. Br J Radiol 2007; 80(Spec No 2):S146–S152. 19. Kabani NJ, Sled JG, Chertkow H. Magnetization transfer ratio in mild cognitive impairment and dementia of Alzheimer’s type. Neuroimage 2002; 15(3):604–610. 20. Manka C, Traber F, Gieseke J, et al. Three-dimensional dynamic susceptibility-weighted perfusion MR imaging at 3.0 T: feasibility and contrast agent dose. Radiology 2005; 234(3):869–877. 21. Bozzao A, Floris R, Baviera ME, et al. Diffusion and perfusion MR imaging in cases of Alzheimer’s disease: correlations with cortical atrophy and lesion load. AJNR Am J Neuroradiol 2001; 22(6):1030–1036. 22. Harris GJ, Lewis RF, Satlin A, et al. Dynamic susceptibility contrast MR imaging of regional cerebral blood volume in Alzheimer disease: a promising alternative to nuclear medicine. AJNR Am J Neuroradiol 1998; 19(9): 1727–1732. 23. Luckhaus C, Flub MO, Wittsack HJ, et al. Detection of changed regional cerebral blood flow in mild cognitive impairment and early Alzheimer’s dementia by perfusion-weighted magnetic resonance imaging. Neuroimage 2008; 40(2):495–503. 24. Dai W, Lopez OL, Carmichael OT, et al. Mild cognitive impairment and alzheimer disease: patterns of altered cerebral blood flow at MR imaging. Radiology 2009; 250(3):856–866. 25. Chen W, Song X, Beyea S, et al. Advances in perfusion magnetic resonance imaging in Alzheimer’s disease. Alzheimers Dement 2011; 7(2): 185–196. 26. Postiglione A, Lassen NA, Holman BL. Cerebral blood flow in patients with dementia of Alzheimer’s type. Aging (Milano) 1993; 5(1):19–26. 27. Herholz K, Salmon E, Perani D, et al. Discrimination between Alzheimer dementia and controls by automated analysis of multicenter FDG PET. Neuroimage 2002; 17(1):302–316. 28. Mosconi L. Brain glucose metabolism in the early and specific diagnosis of Alzheimer’s disease. FDG-PET studies in MCI and AD. Eur J Nucl Med Mol Imaging 2005; 32(4):486–510. 29. Matsuda H. Role of neuroimaging in Alzheimer’s disease, with emphasis on brain perfusion SPECT. J Nucl Med 2007; 48(8):1289–1300. 30. Levy R. Aging-associated cognitive decline. Working Party of the International Psychogeriatric Association in collaboration with the World Health Organization. Int Psychogeriatr 1994; 6(1):63–68. 31. McKhann G, Drachman D, Folstein M, et al. Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology 1984; 34(7):939–944. 32. Folstein MF, Folstein SE, McHugh PR. ‘‘Mini-mental state’’. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975; 12(3):189–198. 33. Morris JC, Heyman A, Mohs RC, et al. The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD). Part I. Clinical and neuropsychological assessment of Alzheimer’s disease. Neurology 1989; 39(9): 1159–1165. 34. Barth S, Schonknecht P, Pantel J, et al. [Mild cognitive impairment and Alzheimer’s disease: an investigation of the CERAD-NP test battery]. Fortschritte der Neurologie-Psychiatrie 2005; 73(10):568–576.
CEREBRAL PERFUSION ALTERATIONS IN AD AND MCI
35. Oldfield RC. The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 1971; 9(1):97–113. 36. Cavallin L, Axelsson R, Wahlund LO, et al. Voxel-based correlation between coregistered single-photon emission computed tomography and dynamic susceptibility contrast magnetic resonance imaging in subjects with suspected Alzheimer disease. Acta Radiol 2008; 49(10):1154–1161. 37. Luckhaus C, Cohnen M, Fluss MO, et al. The relation of regional cerebral perfusion and atrophy in mild cognitive impairment (MCI) and early Alzheimer’s dementia. Psychiatry Res 2010; 183(1):44–51. 38. Zhang Y, Schuff N, Ching C, et al. Joint assessment of structural, perfusion, and diffusion MRI in Alzheimer’s disease and frontotemporal dementia. Int J Alzheimers Dis 2011; 2011:546871. 39. Asllani I, Habeck C, Scarmeas N, et al. Multivariate and univariate analysis of continuous arterial spin labeling perfusion MRI in Alzheimer’s disease. J Cereb Blood Flow Metab 2008; 28(4):725–736. 40. Johnson NA, Jahng GH, Weiner MW, et al. Pattern of cerebral hypoperfusion in Alzheimer disease and mild cognitive impairment measured with arterial spin-labeling MR imaging: initial experience. Radiology 2005; 234(3):851–859. 41. Alexopoulos P, Sorg C, Forschler A, et al. Perfusion abnormalities in mild cognitive impairment and mild dementia in Alzheimer’s disease measured by pulsed arterial spin labeling MRI. Eur Arch Psychiatry Clin Neurosci 2012; 262(1):69–77. 42. Yoshiura T, Hiwatashi A, Noguchi T, et al. Arterial spin labelling at 3-T MR imaging for detection of individuals with Alzheimer’s disease. Eur Radiol 2009; 19(12):2819–2825. 43. Yoshiura T, Hiwatashi A, Yamashita K, et al. Simultaneous measurement of arterial transit time, arterial blood volume, and cerebral blood flow using arterial spin-labeling in patients with Alzheimer disease. AJNR Am J Neuroradiol 2009; 30(7):1388–1393. 44. Thomann PA, Schlafer C, Seidl U, et al. The cerebellum in mild cognitive impairment and Alzheimer’s disease - a structural MRI study. J Psychiatr Res 2008; 42(14):1198–1202. 45. Seab JP, Jagust WJ, Wong ST, et al. Quantitative NMR measurements of hippocampal atrophy in Alzheimer’s disease. Magn Reson Med 1988; 8(2): 200–208. 46. Bottino CM, Castro CC, Gomes RL, et al. Volumetric MRI measurements can differentiate Alzheimer’s disease, mild cognitive impairment, and normal aging. Int Psychogeriatr 2002; 14(1):59–72. 47. Du AT, Schuff N, Amend D, et al. Magnetic resonance imaging of the entorhinal cortex and hippocampus in mild cognitive impairment and Alzheimer’s disease. J Neurol Neurosurg Psychiatry 2001; 71(4):441–447. 48. Baron JC, Chetelat G, Desgranges B, et al. In vivo mapping of gray matter loss with voxel-based morphometry in mild Alzheimer’s disease. Neuroimage 2001; 14(2):298–309. 49. Mosconi L, Tsui WH, De Santi S, et al. Reduced hippocampal metabolism in MCI and AD: automated FDG-PET image analysis. Neurology 2005; 64(11):1860–1867. 50. Nestor PJ, Fryer TD, Smielewski P, et al. Limbic hypometabolism in Alzheimer’s disease and mild cognitive impairment. Ann Neurol 2003; 54(3): 343–351. 51. Alsop DC, Casement M, de Bazelaire C, et al. Hippocampal hyperperfusion in Alzheimer’s disease. Neuroimage 2008; 42(4):1267–1274. 52. Hamalainen A, Pihlajamaki M, Tanila H, et al. Increased fMRI responses during encoding in mild cognitive impairment. Neurobiol Aging 2007; 28(12):1889–1903. 53. Kircher TT, Weis S, Freymann K, et al. Hippocampal activation in patients with mild cognitive impairment is necessary for successful memory encoding. J Neurol Neurosurg Psychiatry 2007; 78(8):812–818. 54. Dickerson BC, Salat DH, Greve DN, et al. Increased hippocampal activation in mild cognitive impairment compared to normal aging and AD. Neurology 2005; 65(3):404–411. 55. Dickerson BC, Salat DH, Bates JF, et al. Medial temporal lobe function and structure in mild cognitive impairment. Ann Neurol 2004; 56(1):27–35. 56. Stern EA, Bacskai BJ, Hickey GA, et al. Cortical synaptic integration in vivo is disrupted by amyloid-beta plaques. J Neurosci 2004; 24(19):4535–4540. 57. Mesulam MM. Neuroplasticity failure in Alzheimer’s disease: bridging the gap between plaques and tangles. Neuron 1999; 24(3):521–529. 58. Powers WJ, Grubb RL, Jr, Raichle ME. Physiological responses to focal cerebral ischemia in humans. Ann Neurol 1984; 16(5):546–552. 59. Nagata K, Sato M, Satoh Y, et al. Hemodynamic aspects of Alzheimer’s disease. Ann N Y Acad Sci 2002; 977:391–402. 60. Del Sole A, Clerici F, Chiti A, et al. Individual cerebral metabolic deficits in Alzheimer’s disease and amnestic mild cognitive impairment: an FDG PET study. Eur J Nucl Med Mol Imaging 2008; 35(7):1357–1366.
711
D
ementing disorders are the most frequent neuropsychiatric diseases of the elderly population. In about two thirds of subjects with dementia, the dementia is related to Alzheimer disease (AD) (1). AD has an insidious
Acad Radiol 2013; 20:705–711 From the Department of Radiology E010, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany (T.H., L.G., R.H., A.R., M.E.); Department of Psychiatry and Psychotherapy, Section of Geriatric Psychiatry, University of Leipzig, Germany (P.S.); Department of General Psychiatry, Section of Geriatric Psychiatry, Ruprecht-KarlsUniversity, Heidelberg, Germany (P.A.T., J.S., R.H.); Department of Diagnostic Radiology, Ruprecht-Karls University, Heidelberg, Germany (L.G.); Department of Child and Adolescent Psychiatry, Center of Psychosocial Medicine, Ruprecht-Karls-University, Heidelberg, Germany (R.H.); Department of Neuroradiology, Ruprecht-Karls University, Heidelberg, Germany (A.R.); and Department of Neuroradiology, FriedrichAlexander-University, Erlangen, Germany (M.E.). Received November 15, 2012; accepted January 18, 2013. Address correspondence to: T.H. e-mail: [email protected] ªAUR, 2013 http://dx.doi.org/10.1016/j.acra.2013.01.020
onset and progresses in a time-frame of years with decline in a broad range of neuropsychological domains such as memory, executive functions and attention, language, and apraxia. In AD, the progressive degeneration of the brain is, on the one hand, caused by changes in tau protein, which lead to destabilization of the cytoskeleton (2,3). On the other hand, increased creation of b-amyloid and its accumulation into amyloid plaques lead to an inflammatory and oxidative-toxic processes (3). Both processes result in an irreversible damage of neuronal cells. Beside the deposition of amyloid in the brain parenchyma in AD, a perivascular amyloid accumulation is present in most cases (3–6). Thus, small-vessel alterations are obvious, resulting in altered cerebral blood flow (CBF). In addition, reduced CBF and the resulting reduced elimination of amyloid may amplify further accumulation of amyloid in perivascular regions and the brain parenchyma itself, with both situations worsening the dementing disorder (5). The preclinical phase of AD is characterized by mild cognitive deficits that exceed physiologic age-related cognitive 705
HAUSER ET AL
decline. However, they are not as severe as in subjects with a confirmed dementing disorder. Clinical and epidemiologic evidence indicate that this preliminary stage, called mild cognitive impairment (MCI), remains subtle over a long phase before the threshold of dementia is reached (1). It is assumed that MCI is associated with a substantially increased risk of AD (7–10). The early diagnosis of AD and the exclusion of secondary causes of dementia are essential for optimized therapeutic management of patients. In the past years, there has been an increasing use of neuroimaging in the diagnostic workup of individuals with mental decline (11–14). Magnetic resonance imaging (MRI) is used to rule out secondary dementias, which refer to somatic disorders other than neurodegenerative diseases or concomitant conditions that may be associated with the dementing disorder. Beside the exclusion of secondary causes, the detection of subtle changes in the early stages of dementia, including the investigation of the underlying pathophysiology, has gained increasing interest. Early MRI studies revealed a significant loss of brain parenchyma in the progress of dementing disorders. According to the anatomic studies of Braak and Braak (2), the atrophy follows a predefined pattern that can be assessed with morphometric studies. Currently, different morphologic cerebral neuroimaging methods are being applied in the diagnosis of dementia (15,16). However, in the past few years, a number of advanced MRI techniques, like MR spectroscopy (17,18) or the evaluation of magnetization transfer ratios (19), have been developed that provide new insights into the pathophysiology of neurodegenerative diseases. Dynamic susceptibility contrast (DSC)-MRI is another functional method. It allows a robust quantification of perfusion and tissue microcirculation (20) after an intravenous bolus injection of contrast medium. This leads to a temporary drop in T2* signal intensity due to susceptibility effects. Several functional parameters of tissue perfusion, such as CBF, cerebral blood volume (CBV), and mean transit time (MTT), can be calculated from the signal-time curve. The arterial spin labeling (ASL) technique is another technique that allows the quantification of perfusion alterations. However, compared to the DSC approach, the technique of ASL is more prone to artifacts, especially to motion artifact. Hence, DSC-MRI provides the more robust technique in patients with dementia. Some earlier MRI studies point to changes in perfusion pattern in patients with AD (21–25). As in the progression of a cognitive decline to AD a pronounced accumulation of perivascular amyloid over a long period of time is known (3–6), altered regional cerebral perfusion in the development of AD is obvious. According to previous 18 F-fludeoxyglucose–positron emission tomography (FDGPET) studies (14,26–29), which demonstrated a reduced glucose metabolism in AD mainly in the posterior cingulate gyrus, as well as in the temporoparietal and prefrontal region, we expect changes in perfusion analyses, especially in these areas. The purpose of the current study was to assess 706
Academic Radiology, Vol 20, No 6, June 2013
regional perfusion distributions by the use of DSC-MRI in subjects with AD and MCI. MATERIALS AND METHODS Subjects
The study was approved by the institutional review board and performed in accordance with the ethical standards of the Declaration of Helsinki. Depending on the level of cognitive impairment, we obtained written informed consent from either the participants or their caregivers after the planned procedures were explained by a geriatric psychiatrist and radiologist. Exclusion criteria were general contraindication for MRI (eg, pacemaker) or for the application of gadoliniumcontrast media (eg, renal failure or known adverse reaction). Patients with known vascular dementia, depression, history of malignancy, drug, or alcohol abuse, or any other medical, neurologic, or psychiatric disorder that could result in a cognitive deterioration were not included in the study. A total number of 100 consecutive subjects with mental decline were prospectively recruited from the Memory Clinic of the Department of Geriatric Psychiatry. After clinical assessments and the MRI examination, 15 of these 100 consecutive patients had to be excluded from analyses due to previously unknown secondary causes of dementia: pronounced microvascular changes (n = 9), postischemic lesions (n = 2), normal pressure hydrocephalus (n = 1), probable postinflammatory changes (n = 1), posttraumatic lesions (n = 1), and motion artifacts in MRI (n = 1). Of these remaining 85 patients, 51 patients were assigned the diagnosis of MCI and 34 were assigned the diagnosis of AD. The definitive diagnosis in each individual was confirmed by two experienced psychiatrists with long-standing special knowledge of geriatric psychiatry. All subjects were clinically assessed according to the concept of the Aging-Associated Cognitive Decline (AACD) (30) and the criteria of the National Institute of Neurological and Communicative Disorders and Stroke in concert with Alzheimer’s Disease and Related Disorders Association (NINCDS-ADRDA) (31). For comparison, 25 age-matched healthy control subjects (HCs) with an age >55 years were included in the study. All potential healthy subjects were examined by an experienced psychiatrist with special knowledge of geriatric psychiatry to exclude cognitive impairment or dementia. Two of these healthy subjects had to be excluded from analyses after MRI examination because of pronounced microvascular changes. The three groups did not differ significantly in age (P = .151) or sex (c2 = 0.164, P = .921). Clinical Evaluation
Clinical evaluation included the ascertainment of personal and family history and detailed physical, neurologic, and neuropsychological evaluations. None of the participants had a lifetime history of neurologic or severe medical illness, head
Academic Radiology, Vol 20, No 6, June 2013
CEREBRAL PERFUSION ALTERATIONS IN AD AND MCI
Figure 1. Patient with mild cognitive impairment. The figures show an example of region of interest [placement in the cerebellum (a), the left temporoparietal cortex (b), the left frontal cortex (c), and the anterior cingulate gyrus left (d) on cerebral blood flow] maps. The sulci and adjacent vessels were excluded from analysis.
injury, or substance abuse. We assessed global cognitive deficits using the Mini Mental State Examination (MMSE) (32). We investigated cognitive performance using a standardized extensive neuropsychological test battery (Consortium to Establish a Registry for Alzheimer’s Disease) (33,34). Handedness was assessed using the Edinburgh inventory (35). All participants were dominantly right-handed.
medium was measured over a period of 2.5 minutes with a time resolution of 1.5 seconds for each repetition. Due to limitations in the number of slices, the coverage of the brain structures was limited. Depending on the head size and positioning of the patient, the perfusion could not be assessed in the most cranial brain areas, including the sensomotoric cortices. Analysis and Postprocessing
MRI
All enrolled subjects underwent a standardized MRI procedure on either a 1.5-Tor a 3-T MRI scanner (MAGNETOM Avanto and Trio, Siemens Medical Solutions, Erlangen, Germany). The MRI examinations among the three groups (AD, MCI, and HC) did not differ significantly in field strength (c2 = 0.289, P = .865). Morphologic MR images. For structural analysis, a T1weighted three-dimensional magnetization prepared rapid gradient echo sequence was performed. To exclude secondary causes of dementia or ischemic changes, T2-weighted, fluidattenuated inversion recovery and diffusion-weighted images were performed. To rule out malignant tumors, additional T1-weighted sequences were added after application of contrast medium. DSC-MRI. Perfusion MRI was performed using a T2*weighted echo planar imaging gradient echo sequence in axial orientation (3 T: repetition time [TR] = 1450 ms, echo time [TE] = 45 ms, 13 slices, flip = 90 , slice thickness [SL] = 5 mm, matrix = 128, average = 1, bandwidth = 1345 Hz/pixel; 1.5 T: TR = 1440 ms, TE = 47 ms, 12 slices, flip = 90 , SL = 5 mm, matrix = 128, average = 1, bandwidth = 1345 Hz/pixel). A rapid bolus injection of gadolinium-contrast media (0.1 mmol/kg body weight) was applied by using a power injector with an injection rate of 5 mL/sec. The contrast medium injection was followed by a flush of 30 mL physiologic saline solution at the same injection rate. The DSC imaging started with the beginning of the application of contrast medium. The distribution of the contrast
Initially, qualitative analyses of all images were performed to exclude patients with other pathologies such as neoplasms, ischemia, or vascular changes. The DSC raw data were processed and converted into parameter maps for CBV, CBF, and MTT using the software tool NordicICE (NordicICE 2.3; NordicNeuroLab AS, Bergen, Norway). A single-rater region of interest (ROI) analysis was performed to assess the regional perfusion distribution in patients and HCs. ROIs were positioned in the sensomotoric, frontal, temporal, and temporoparietal cortices bilaterally as well as in the anterior and posterior cingulate cortices, the lentiform nuclei, the hippocampus bilaterally, and the cerebellum (Fig 1). Because of limited spatial resolution of the perfusion maps, ROIs were delineated on morphologic axial fluid-attenuated inversion recovery images and overlaid on the perfusion maps. Adjacent vessels were excluded from analysis. CBF, CBV, and MTT were quantified inside these ROIs. The rater positioning the ROIs was blinded to the clinical diagnosis in all subjects. All measurements that differ >3 SDs from the mean value inside the group were eliminated due to the high probability of arterial blood vessels included in these ROIs. Statistics
Statistical analyses were performed using SPSS (version 19; IBM SPSS; Chicago, IL). First, the normal distribution of the measurements was approved with a QQ-Plot. All quantitative measurements are presented as mean standard deviation (SD). An F test (analysis of variance) was performed to 707
HAUSER ET AL
Academic Radiology, Vol 20, No 6, June 2013
TABLE 1. Region of Interest Values of Cerebral Blood Glow* HCs Region of Interest Cerebellum Right hippocampus Left hippocampus Right temporal cortex Left temporal cortex Right temporoparietal cortex Left temporoparietal cortex Right lentiform nucleus Left lentiform nucleus Right anterior cingulate gyrus Left anterior cingulate gyrus Right posterior cingulate gyrus Left posterior cingulate gyrus Right frontal cortex Left frontal cortex Right sensomotoric cortex Left sensomotoric cortex
n 19 21 21 22 22 22 22 21 21 18 18 18 18 22 22 13 13
mean SD 63.9 32.2 49.9 24.6 50.4 24.8 63.2 39.6 56.1 34.0 69.0 35.6 68.0 35.8 58.7 32.8 60.2 33.7 49.2 24.2 46.2 25.0 52.4 28.9 51.6 28.0 59.8 33.3 60.6 35.0 47.3 30.6 44.8 29.0
Patients with MCI n 46 50 51 51 50 51 50 50 50 43 43 43 43 51 51 38 38
mean SD 52.4 27.7 51.2 25.8 52.6 29.5 56.3 29.2 51.0 27.7 60.1 31.8 58.7 27.8 44.5 24.8 47.3 26.0 48.9 24.4 48.3 24.1 55.0 31.0 53.5 30.8 51.5 28.7 50.3 28.2 47.1 24.2 47.7 27.0
F Test
Patients with AD n 34 34 34 34 34 34 33 34 34 28 28 28 28 34 34 25 25
mean SD y
43.6 19.7 43.1 24.1 47.0 22.2 44.6 21.5 40.7 18.4 48.6 22.0y 46.0 19.1y,z 36.6 18.1y 38.9 19.7y 36.0 19.2 34.9 17.0z 39.2 16.9 35.7 15.7y,z 39.7 16.1y,z 39.2 15.1y,z 35.2 19.2 34.3 18.6
P .028 .334 .637 .056 .081 .042 .013 .007 .015 .051 .044 .052 .020 .018 .014 .131 .113
n, number of patients; SD, standard deviation; HC, healthy control; MCI, mild cognitive impairment; AD, Alzheimer disease. Post-hoc t tests were calculated to test for significant group differences. *P values are calculated from an F test (analysis of variance) for detecting differences between the three groups. y Indicates P values in comparison to HC of <.05. z Indicates P values in comparison to MCI of <.05.
detect significant differences among the three groups. Posthoc two-sided t tests were calculated to test for significant group differences. P values <.05 were considered to represent a significant difference.
RESULTS A total number of 34 patients with AD (mean age, 71.8 8.8 years; MMSE, 22.0 3.9; 13 men and 21 women), 51 patients with MCI (mean age, 68.1 10.6 years; MMSE, 26.6 2.8; 21 men and 30 women), and 23 age-matched HCs (mean age, 67.4 8.9 years; 10 men and 13 women) were included in the final evaluation. In the analyses of CBF, CBV, and MTT, a relatively large interindividual distribution of these perfusion data within each group was noticed. In the CBF analysis (Table 1), a significant decrease (P < .05) in patients with AD in comparison to HCs was found in the frontal and temporoparietal cortices bilaterally, the lentiform nuclei, the left posterior cingulate gyrus, and the cerebellum. In comparison to patients with MCI, in patients with AD, a significant reduction of CBF in frontal cortices bilaterally, in the left temporoparietal cortex, and in the left anterior and posterior cingulate gyrus was detected. A significant difference of CBF between patients with MCI and HCs could not be demonstrated, although there was a tendency to lower levels of CBF in patients with MCI except in the hippocampus and posterior cingulate gyrus. In these brain areas, a slight increase (P > .05) of CBF could be noticed in patients with MCI with a decrease in patients with AD. 708
In CBV analysis, a significant reduction of CBV could only be displayed in the left frontal cortex between patients with MCI and HCs. In all other evaluated brain areas, in neither patients with MCI nor patients with AD could significant changes of CBV be demonstrated, although a tendency to lower levels of CBV could be noticed according to the progression of the disease. In the MTT analysis, no significant changes among the three groups could be demonstrated.
DISCUSSION The development of AD is a dynamic pathologic process starting with an undefined long preclinical phase before the clinical manifestation of dementia symptoms (2). During this transition to AD, both increases and mainly decreases of regional cerebral perfusion have been described (24). Therefore, we explored in our analyses changes of perfusion patterns in patients with MCI, a discussed precursor, and manifest early AD compared to age-matched HCs by using DSC-perfusion imaging. Until now, only limited data are available on using DSC-MRI for an improved assessment of patients with MCI and AD (23,36,37). In our study, a large number of subjects (N = 108) were included. Comparison of CBF Values in Patients with AD and HCs
In previous FDG-PET analyses (14,26–28), the most consistent findings of a reduced glucose metabolism in AD
Academic Radiology, Vol 20, No 6, June 2013
were localized in the posterior cingulate gyrus, in the temporoparietal and the prefrontal region. According to these metabolic changes, a reduction of CBF in these areas is likely. In our evaluation, we verified these by literaturepredicted changes because a significant decrease of CBF was detected in these areas in patients with AD in comparison to HCs with exception of the right cingulate gyrus. In the right posterior cingulate gyrus, only a nonsignificant reduction of CBF was found (P = .052). However, previously published perfusion studies showed different results. By using DSCMRI, previous analyses (23,36) mainly could not detect significant changes of perfusion in patients with AD in these areas. Although Cavallin et al (36) did not find a decrease of CBF in DSC analyses, a decrease in single-photon emission computed timigraphy data was present in both temporoparietal areas and the right posterior cingulate gyrus. In addition, by using ASL perfusion, various analyses demonstrated a reduced perfusion in the temporoparietal (24,38–41) and frontal regions (24,39,40) as well as in the posterior cingulate gyrus (24,38–43), which is in good accordance with our results. Additionally, our evaluation detected a significant reduction of CBF in the lentiform nuclei and in the cerebellum, which has not been described yet. Dai et al (24) described an increase of CBF in patients with MCI in the right basal ganglia. In comparison to these changes, involvement of the basal ganglia in patients with AD is feasible. According to morphologic changes described in the cerebellum in patients with AD (44), our results also point to an involvement of the cerebellum in patients with AD. The sparing of perfusion changes in the sensomotoric area correlates well with former ASL and PET analyses (14,24,26,40). Based on previous studies (15,45–48) that demonstrated morphologic changes in the hippocampus and the fact that the hippocampal region is typically involved early in pathologic changes in patients with AD (2), it is likely that changes in perfusion pattern could be noticed in these brain areas. Besides these morphologic changes, some previous studies reported a reduction of perfusion (23,36,39) or glucose metabolism (49,50) mesiotemporal in patients with AD or MCI. In our evaluation, we did not detect any significant perfusion changes in the hippocampal region, which is in agreement with several other studies (24,40–43). However, a slight reduction could be seen in patients with AD. One previous ASL study even describes a slight hippocampal hyperperfusion in comparison to HCs (41,51). These discrepant results are probably caused by a compensatory mechanism (24,51), trying to keep the perfusion relative constant over a long time period. Comparison of CBF Values in Patients with MCI and HCs
In comparison of patients with MCI to HC, we could only demonstrate a tendency of CBF reduction in most brain areas corresponding well with former reports. In the study by Cavallin et al (36), the authors could not find any changes of CBF in patients
CEREBRAL PERFUSION ALTERATIONS IN AD AND MCI
with MCI by using DSC-MRI. Also, by using single-photon emission computed tomography analyses (36), no changes in CBF were detected in the brain areas evaluated in our study. Nevertheless, Luckhaus et al (23) showed a reduced CBF in the mesiotemporal region bilaterally as well as in the anterior cingulate gyrus. Our data also correspond well with ASL analyses, as one study (40) could not find any significant changes in these regions, whereas another study (24) could show a reduced CBF merely in the posterior cingulate gyrus and an increase in the left hippocampus and in the right basal ganglia. The fact that we found a slight increase (P > .05) of perfusion in both hippocampi in patients with MCI also fits well with similar findings of several ASL analyses (41,51). These findings are also in accordance to previous blood oxygen level–dependent functional MRI (fMRI) studies showing increased brain fMRI. RI activation in patients with MCI but not in patients with AD (52,53). Similar perfusion patterns were also detected in both posterior cingulate gyri. In these areas, a slight increase of CBF was found in patients with MCI (P > .05) with a decrease in patients with AD (significant decline only on the left side), corresponding well with data of Luckhaus et al (23). Former fMRI analyses by Dickerson et al (54,55) demonstrated a hyperactivation of the hippocampal region in patients with MCI compared to HCs without morphologic differences in these groups. However, in patients with AD, a hypoactivation and an atrophy of the medial temporal lobe were present. The authors hypothesize that there is a phase of increased activation of the hippocampal region in the early phase of the disease before clinical onset (54,55). These changes may reflect a complex mechanism of degeneration and compensatory response to accumulating AD neuropathology (56) and differences in the neuroplasticity (54,57). According to these results, our findings of slight increases of CBF in patients with MCI in some regions such as the medial temporal lobe may be the result of an early compensatory mechanism, probably determined by an elevation of neuronal activity, inflammation, or production of vasodilators (24,51). Comparison of CBF Values in Patients with AD or MCI
In line with previous DSC analyses (23,37) demonstrating a significant reduction of CBF in the posterior cingulate gyrus in patients with AD in comparison to patients with MCI, our study approved these alterations. After adjusting for global perfusion, ASL perfusion also showed a decreased perfusion in the posterior cingulate gyrus and the temporoparietal cortices (40). Although changes in temporoparietal and frontal cortices were not shown in former DSC analyses (23,37), the detected decrease in the left temporoparietal (24,40) and frontal cortices (24) is supported by prior ASL-based studies. Hippocampal differences as described in one study (24) were not verified in our analyses. In accordance with previous DSC and ASL evaluations, no further significant changes in CBF were shown in patients with AD in comparison to patients with MCI. 709
HAUSER ET AL
CBV Analyses
Although a slight regional reduction of CBV was seen in our analysis in various brain areas in patients with MCI compared to HCs (pronounced in the frontal and temporoparietal cortices bilaterally, the right temporal cortex, the right anterior cingulate gyri, and the left lentiform nucleus), it reached the level of significance only in the left frontal cortex. In patients with AD, no further significant reduction of CBV could be recognized. Our findings of CBV are in accordance with regional ASL analyses of Yoshiura et al (43). This group also showed a slight but not significant reduction of arterial blood volume in patients with AD versus HCs. In contrast to this, several previous perfusion studies with DSC-MRI showed a reduction of CBV in patients with AD in comparison to HCs in the sensomotoric (21) and temporoparietal cortices (21,22) as well as in both hippocampi (21). MTT Analyses
In contrast to vascular dementias, in which the reduced perfusion pressure results in a dilatation of the small vessels and consequently in a regional prolongation in MTT (58), in patients with AD such changes have not been detected yet (58,59). As in the development of an AD mainly microangiopathic changes (due to the deposition of perivascular amyloid) but no macroangiopathic changes are obvious, no alterations of MTT are likely. This fits with our finding of no significant changes among HCs and patients with MCI or AD in MTT analyses. It is also in line with Yoshiura et al (43), who could not find any significant changes of regional arterial transit time in ASL measurements in patients with AD. Limitations
Overall, perfusion MRI may help us in the diagnosis of AD as a decline of CBF could be demonstrated in various brain areas, similar to former FDG-PET studies. The most consistent findings in FDG-PET analyses were a reduced glucose metabolism in patients with AD in the posterior cingulate gyrus and in the temporoparietal and prefrontal cortices (27,28), similar to our perfusion results. Previously, it was assumed that perfusion changes were the result of regional brain atrophy. This assumption was disproved by a correlative study (21) demonstrating significant changes of CBV persisting after normalizing for regional atrophy. Nevertheless, an early detection of evolving dementia in the early stadium of MCI is still difficult as only a tendency to lower CBF levels was found in patients with MCI, which did not reach the level of significance in comparison to HCs. There are some other limitations in the study. One limitation is that the perfusion measurements were made at different field strength (3 and 1.5 T), which may result in slightly different values. However, the sequence parameters were only slightly different and the distribution of subjects measured within each field strength did not vary significantly between 710
Academic Radiology, Vol 20, No 6, June 2013
the groups. Although this study demonstrates several changes of CBF between the groups, an important limitation of this method is the relative high interindividual variability of perfusion data. This fact is in accordance with the interindividual variability already described in FDG-PETanalyses (60). These variabilities of perfusion data may be the effect of the interindividual severity of the cognitive decline. This assumption should be evaluated in further studies. Furthermore, the accordance between perfusion data and the conversion of MCI to AD should be part of follow-up studies. Hence, it is not possible yet to define a cut-off level for the diagnosis of MCI or AD based on perfusion parameters alone. Nevertheless, DSC-MRI may provide a method that could provide important insights for an improved diagnosis of dementias.
CONCLUSIONS The long-lasting transition from normal cognition to AD comes along with both a decrease of perfusion and several slight increases of perfusion in different regions in the early stage. This supports the concepts of regional compensatory cellular mechanisms. However, a definitive diagnosis of MCI based only on DSC-MRI is not possible yet. Nevertheless, various changes of perfusion in AD, most notable in the CBF analyses, correlated well with findings from other studies, such as PET studies. DSC-MRI therefore provides noninvasively new insights into the early pathophysiologic changes of dementing disorders and may improve the early diagnosis of AD. ACKNOWLEDGMENTS We thank Sandra Kauczor for her help with technical assistance. The study was supported by the Alzheimer Forschung Initiative (AFI).
REFERENCES 1. Thies W, Bleiler L. 2011 Alzheimer’s disease facts and figures. Alzheimers Dement 2011; 7(2):208–244. 2. Braak H, Braak E. Evolution of neuronal changes in the course of Alzheimer’s disease. J Neural Transm Suppl 1998; 53:127–140. 3. Masters CL, Beyreuther K. Alzheimer’s centennial legacy: prospects for rational therapeutic intervention targeting the Abeta amyloid pathway. Brain 2006; 129(Pt 11):2823–2839. 4. Thal DR, Griffin WS, de Vos RA, et al. Cerebral amyloid angiopathy and its relationship to Alzheimer’s disease. Acta Neuropathol 2008; 115(6):599–609. 5. Bell RD, Zlokovic BV. Neurovascular mechanisms and blood-brain barrier disorder in Alzheimer’s disease. Acta Neuropathol 2009; 118(1):103–113. 6. Weller RO, Subash M, Preston SD, et al. Perivascular drainage of amyloidbeta peptides from the brain and its failure in cerebral amyloid angiopathy and Alzheimer’s disease. Brain Pathol 2008; 18(2):253–266. 7. Busse A, Bischkopf J, Riedel-Heller SG, et al. Mild cognitive impairment: prevalence and incidence according to different diagnostic criteria. Results of the Leipzig Longitudinal Study of the Aged (LEILA75+). Br J Psychiatry 2003; 182:449–454. 8. Petersen RC, Doody R, Kurz A, et al. Current concepts in mild cognitive impairment. Arch Neurol 2001; 58(12):1985–1992. 9. Ritchie K, Artero S, Touchon J. Classification criteria for mild cognitive impairment: a population-based validation study. Neurology 2001; 56(1):37–42.
Academic Radiology, Vol 20, No 6, June 2013
10. Schonknecht P, Pantel J, Kruse A, et al. Prevalence and natural course of aging-associated cognitive decline in a population-based sample of young-old subjects. Am J Psychiatry 2005; 162(11):2071–2077. 11. Ries ML, Carlsson CM, Rowley HA, et al. Magnetic resonance imaging characterization of brain structure and function in mild cognitive impairment: a review. J Am Geriatr Soc 2008; 56(5):920–934. 12. Hsu YY, Du AT, Schuff N, et al. Magnetic resonance imaging and magnetic resonance spectroscopy in dementias. J Geriatr Psychiatry Neurol 2001; 14(3):145–166. 13. Ramani A, Jensen JH, Helpern JA. Quantitative MR imaging in Alzheimer disease. Radiology 2006; 241(1):26–44. 14. Lehericy S, Marjanska M, Mesrob L, et al. Magnetic resonance imaging of Alzheimer’s disease. Eur Radiol 2007; 17(2):347–362. 15. Pantel J, Kratz B, Essig M, et al. Parahippocampal volume deficits in subjects with aging-associated cognitive decline. Am J Psychiatry 2003; 160(2):379–382. 16. Thomann PA, Dos Santos V, Seidl U, et al. MRI-derived atrophy of the olfactory bulb and tract in mild cognitive impairment and Alzheimer’s disease. J Alzheimers Dis 2009; 17(1):213–221. 17. Jessen F, Traeber F, Freymann K, et al. Treatment monitoring and response prediction with proton MR spectroscopy in AD. Neurology 2006; 67(3):528–530. 18. Kantarci K. 1H magnetic resonance spectroscopy in dementia. Br J Radiol 2007; 80(Spec No 2):S146–S152. 19. Kabani NJ, Sled JG, Chertkow H. Magnetization transfer ratio in mild cognitive impairment and dementia of Alzheimer’s type. Neuroimage 2002; 15(3):604–610. 20. Manka C, Traber F, Gieseke J, et al. Three-dimensional dynamic susceptibility-weighted perfusion MR imaging at 3.0 T: feasibility and contrast agent dose. Radiology 2005; 234(3):869–877. 21. Bozzao A, Floris R, Baviera ME, et al. Diffusion and perfusion MR imaging in cases of Alzheimer’s disease: correlations with cortical atrophy and lesion load. AJNR Am J Neuroradiol 2001; 22(6):1030–1036. 22. Harris GJ, Lewis RF, Satlin A, et al. Dynamic susceptibility contrast MR imaging of regional cerebral blood volume in Alzheimer disease: a promising alternative to nuclear medicine. AJNR Am J Neuroradiol 1998; 19(9): 1727–1732. 23. Luckhaus C, Flub MO, Wittsack HJ, et al. Detection of changed regional cerebral blood flow in mild cognitive impairment and early Alzheimer’s dementia by perfusion-weighted magnetic resonance imaging. Neuroimage 2008; 40(2):495–503. 24. Dai W, Lopez OL, Carmichael OT, et al. Mild cognitive impairment and alzheimer disease: patterns of altered cerebral blood flow at MR imaging. Radiology 2009; 250(3):856–866. 25. Chen W, Song X, Beyea S, et al. Advances in perfusion magnetic resonance imaging in Alzheimer’s disease. Alzheimers Dement 2011; 7(2): 185–196. 26. Postiglione A, Lassen NA, Holman BL. Cerebral blood flow in patients with dementia of Alzheimer’s type. Aging (Milano) 1993; 5(1):19–26. 27. Herholz K, Salmon E, Perani D, et al. Discrimination between Alzheimer dementia and controls by automated analysis of multicenter FDG PET. Neuroimage 2002; 17(1):302–316. 28. Mosconi L. Brain glucose metabolism in the early and specific diagnosis of Alzheimer’s disease. FDG-PET studies in MCI and AD. Eur J Nucl Med Mol Imaging 2005; 32(4):486–510. 29. Matsuda H. Role of neuroimaging in Alzheimer’s disease, with emphasis on brain perfusion SPECT. J Nucl Med 2007; 48(8):1289–1300. 30. Levy R. Aging-associated cognitive decline. Working Party of the International Psychogeriatric Association in collaboration with the World Health Organization. Int Psychogeriatr 1994; 6(1):63–68. 31. McKhann G, Drachman D, Folstein M, et al. Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology 1984; 34(7):939–944. 32. Folstein MF, Folstein SE, McHugh PR. ‘‘Mini-mental state’’. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975; 12(3):189–198. 33. Morris JC, Heyman A, Mohs RC, et al. The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD). Part I. Clinical and neuropsychological assessment of Alzheimer’s disease. Neurology 1989; 39(9): 1159–1165. 34. Barth S, Schonknecht P, Pantel J, et al. [Mild cognitive impairment and Alzheimer’s disease: an investigation of the CERAD-NP test battery]. Fortschritte der Neurologie-Psychiatrie 2005; 73(10):568–576.
CEREBRAL PERFUSION ALTERATIONS IN AD AND MCI
35. Oldfield RC. The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 1971; 9(1):97–113. 36. Cavallin L, Axelsson R, Wahlund LO, et al. Voxel-based correlation between coregistered single-photon emission computed tomography and dynamic susceptibility contrast magnetic resonance imaging in subjects with suspected Alzheimer disease. Acta Radiol 2008; 49(10):1154–1161. 37. Luckhaus C, Cohnen M, Fluss MO, et al. The relation of regional cerebral perfusion and atrophy in mild cognitive impairment (MCI) and early Alzheimer’s dementia. Psychiatry Res 2010; 183(1):44–51. 38. Zhang Y, Schuff N, Ching C, et al. Joint assessment of structural, perfusion, and diffusion MRI in Alzheimer’s disease and frontotemporal dementia. Int J Alzheimers Dis 2011; 2011:546871. 39. Asllani I, Habeck C, Scarmeas N, et al. Multivariate and univariate analysis of continuous arterial spin labeling perfusion MRI in Alzheimer’s disease. J Cereb Blood Flow Metab 2008; 28(4):725–736. 40. Johnson NA, Jahng GH, Weiner MW, et al. Pattern of cerebral hypoperfusion in Alzheimer disease and mild cognitive impairment measured with arterial spin-labeling MR imaging: initial experience. Radiology 2005; 234(3):851–859. 41. Alexopoulos P, Sorg C, Forschler A, et al. Perfusion abnormalities in mild cognitive impairment and mild dementia in Alzheimer’s disease measured by pulsed arterial spin labeling MRI. Eur Arch Psychiatry Clin Neurosci 2012; 262(1):69–77. 42. Yoshiura T, Hiwatashi A, Noguchi T, et al. Arterial spin labelling at 3-T MR imaging for detection of individuals with Alzheimer’s disease. Eur Radiol 2009; 19(12):2819–2825. 43. Yoshiura T, Hiwatashi A, Yamashita K, et al. Simultaneous measurement of arterial transit time, arterial blood volume, and cerebral blood flow using arterial spin-labeling in patients with Alzheimer disease. AJNR Am J Neuroradiol 2009; 30(7):1388–1393. 44. Thomann PA, Schlafer C, Seidl U, et al. The cerebellum in mild cognitive impairment and Alzheimer’s disease - a structural MRI study. J Psychiatr Res 2008; 42(14):1198–1202. 45. Seab JP, Jagust WJ, Wong ST, et al. Quantitative NMR measurements of hippocampal atrophy in Alzheimer’s disease. Magn Reson Med 1988; 8(2): 200–208. 46. Bottino CM, Castro CC, Gomes RL, et al. Volumetric MRI measurements can differentiate Alzheimer’s disease, mild cognitive impairment, and normal aging. Int Psychogeriatr 2002; 14(1):59–72. 47. Du AT, Schuff N, Amend D, et al. Magnetic resonance imaging of the entorhinal cortex and hippocampus in mild cognitive impairment and Alzheimer’s disease. J Neurol Neurosurg Psychiatry 2001; 71(4):441–447. 48. Baron JC, Chetelat G, Desgranges B, et al. In vivo mapping of gray matter loss with voxel-based morphometry in mild Alzheimer’s disease. Neuroimage 2001; 14(2):298–309. 49. Mosconi L, Tsui WH, De Santi S, et al. Reduced hippocampal metabolism in MCI and AD: automated FDG-PET image analysis. Neurology 2005; 64(11):1860–1867. 50. Nestor PJ, Fryer TD, Smielewski P, et al. Limbic hypometabolism in Alzheimer’s disease and mild cognitive impairment. Ann Neurol 2003; 54(3): 343–351. 51. Alsop DC, Casement M, de Bazelaire C, et al. Hippocampal hyperperfusion in Alzheimer’s disease. Neuroimage 2008; 42(4):1267–1274. 52. Hamalainen A, Pihlajamaki M, Tanila H, et al. Increased fMRI responses during encoding in mild cognitive impairment. Neurobiol Aging 2007; 28(12):1889–1903. 53. Kircher TT, Weis S, Freymann K, et al. Hippocampal activation in patients with mild cognitive impairment is necessary for successful memory encoding. J Neurol Neurosurg Psychiatry 2007; 78(8):812–818. 54. Dickerson BC, Salat DH, Greve DN, et al. Increased hippocampal activation in mild cognitive impairment compared to normal aging and AD. Neurology 2005; 65(3):404–411. 55. Dickerson BC, Salat DH, Bates JF, et al. Medial temporal lobe function and structure in mild cognitive impairment. Ann Neurol 2004; 56(1):27–35. 56. Stern EA, Bacskai BJ, Hickey GA, et al. Cortical synaptic integration in vivo is disrupted by amyloid-beta plaques. J Neurosci 2004; 24(19):4535–4540. 57. Mesulam MM. Neuroplasticity failure in Alzheimer’s disease: bridging the gap between plaques and tangles. Neuron 1999; 24(3):521–529. 58. Powers WJ, Grubb RL, Jr, Raichle ME. Physiological responses to focal cerebral ischemia in humans. Ann Neurol 1984; 16(5):546–552. 59. Nagata K, Sato M, Satoh Y, et al. Hemodynamic aspects of Alzheimer’s disease. Ann N Y Acad Sci 2002; 977:391–402. 60. Del Sole A, Clerici F, Chiti A, et al. Individual cerebral metabolic deficits in Alzheimer’s disease and amnestic mild cognitive impairment: an FDG PET study. Eur J Nucl Med Mol Imaging 2008; 35(7):1357–1366.
711