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Original Contribution |

Linking Hippocampal Structure and Function to Memory Performance in an Aging Population FREE

Christiane Reitz, MD, PhD; Adam M. Brickman, PhD; Truman R. Brown, PhD; Jennifer Manly, PhD; Charles DeCarli, MD; Scott A. Small, MD; Richard Mayeux, MD, MSc
[+] Author Affiliations

Author Affiliations: Taub Institute for Research on Alzheimer's Disease and the Aging Brain (Drs Reitz, Brickman, Manly, Small, and Mayeux), Gertrude H. Sergievsky Center (Drs Reitz, Brickman, Manly, Small, and Mayeux), and Departments of Neurology (Drs Brickman, Manly, Small, and Mayeux), Radiology (Dr Brown), and Psychiatry (Dr Mayeux), College of Physicians and Surgeons, Columbia University, New York, New York; Department of Biomedical Engineering, Columbia University (Dr Brown); Department of Epidemiology, Joseph P. Mailman School of Public Health, Columbia University (Dr Mayeux); and Department of Neurology and Imaging of Dementia and Aging Laboratory, Center for Neuroscience, University of California, Sacramento (Dr DeCarli).


Arch Neurol. 2009;66(11):1385-1392. doi:10.1001/archneurol.2009.214.
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Background  Hippocampal atrophy and reductions in basal cerebral blood volume (CBV), a hemodynamic correlate of brain function, occur with cognitive impairment in Alzheimer disease, but whether these are early or late changes remains unclear. Magnetic resonance imaging is used to assess structure and function in the hippocampal formation.

Objective  To estimate differences in the associations of hippocampal and entorhinal cortex volumes and CBV with memory function in the early and late stages of cognitive impairment by relating these measures to memory function in persons with and without dementia who underwent detailed brain imaging and neuropsychological assessment.

Design  Multivariate regression analyses were used to relate entorhinal cortex volume, entorhinal cortex CBV, hippocampal volume, and hippocampal CBV to measurements of memory performance. The same measures were related to language function as a reference cognitive domain.

Setting  Community-based cohort.

Participants  Two hundred thirty-one elderly Medicare recipients (aged ≥65 years) residing in northern Manhattan, New York.

Main Outcome Measures  Values for entorhinal cortex volume, hippocampal volume, entorhinal cortex CBV, and hippocampal CBV and their relation to memory performance.

Results  No association was noted between entorhinal cortex volume or hippocampal CBV and memory. Decreased hippocampal volume was strongly associated with worse performance in total recall, and lower entorhinal cortex CBV was associated with lower performance in delayed recall. Excluding persons with Alzheimer disease, the association of entorhinal cortex CBV with memory measures was stronger, whereas the association between hippocampal volume and total recall became nonsignificant.

Conclusions  In the early stages of Alzheimer disease or in persons without dementia with worse memory ability, functional and metabolic hippocampal hypofunction contributes to memory impairment, whereas in the later stages, functional and structural changes play a role.

Figures in this Article

Atrophic changes in the hippocampus and the entorhinal cortex play a major role in the memory impairment observed in the early stages of Alzheimer disease (AD).1,2 The hippocampus is central to the formation of new memories and memory consolidation, the process for converting short-term memory into stored or long-term memory.3 The entorhinal cortex relays multimodal processed information from the sensory cortical areas to the hippocampus and information processed by the hippocampus to permanent storage sites in the neocortex.4

It is clear that cell loss and dysfunction in these regions lead to impairment in several types of memory, including spatial and recognition memory and forms of operant learning.57 Pathologic studies of brains from patients with AD show the earliest and greatest neurodegenerative changes in the entorhinal cortex,8,9 which then spread to the hippocampus.10 In accord with these findings, structural magnetic resonance imaging (MRI) studies have consistently shown atrophy of the hippocampal formation in patients with AD1113 in addition to generalized brain atrophy, loss of gray matter, and increased frequency and volume of white matter lesions.1418 A variety of functional imaging modalities sensitive to basal hypofunction have been applied to AD, including positron emission tomography for basal changes in glucose uptake; positron emission tomography, MRI, and single-photon emission computed tomography for basal changes in cerebral blood flow; and MRI for basal changes in cerebral blood volume (CBV). The MRI-based techniques that assess regional CBV, a hemodynamic correlate of oxygen metabolism,19 have been found to be well suited for imaging the function of the hippocampal formation and its subregions across different species.19,20 Previous studies using this technique showed that MRI measures of CBV can detect AD-related hypofunction21,22 and that in AD, CBV tightly correlates with positron emission tomography measures of glucose uptake.21 According to studies23 using this technique, of all the hippocampal subregions, the entorhinal cortex seems to be the dominant site of hypofunction observed in human and animal AD models.

Whether hippocampal atrophy (presumably related to cell loss) and reduced CBV (a surrogate measure of metabolic deficit) are associated with early or late changes in cognitive impairment remains unclear. We hypothesize that metabolic hypofunction in the hippocampus precedes changes in hippocampal volume.

The objective of this study is to estimate differences in the associations of hippocampal and entorhinal cortex volumes and CBV with memory function in the early and late stages of cognitive impairment by relating these measures to memory function in persons with and without dementia who underwent detailed brain imaging and neuropsychological assessment. Nondemented persons with worse memory function may be at higher risk for dementia.2428

PARTICIPANTS

Participants were selected from a cohort participating in a prospective study of aging and dementia in Medicare recipients 65 years and older residing in northern Manhattan, New York (the Washington Heights/Inwood Columbia Aging Project).29 These participants were recruited at 2 time points (1992 and 1999) and were followed up at regular intervals of 18 to 24 months. The sampling strategies and recruitment outcomes have been described in detail elsewhere.30 Recruitment, informed consent, and study procedures were approved by the institutional review boards of Columbia University Medical Center, Columbia University Health Sciences, and the New York State Psychiatric Institute, New York.

This MRI project was concurrent with the second follow-up visit of the cohort recruited in 1999 and the sixth follow-up visit of the cohort recruited in 1992. Participants were deemed eligible for MRI if they did not meet the criteria for dementia at the most recent visit before MRI.29 Persons with illnesses other than dementia were deemed eligible and, therefore, were included in the study. As described in detail previously,29 of 769 participants who underwent MRI, 231 (30.0%) underwent, in addition to structural imaging, assessment of entorhinal cortex and hippocampal CBV and, therefore, constituted the final analytic sample. Persons who underwent CBV assessment and who were included in the final sample were more likely to be women (59.3% vs 40.7%) than were those excluded from the final sample. No differences were noted in age, apolipoprotein E ε4 (APOE ε4) carrier status, or prevalence of vascular risk factors between included and excluded persons.

CLINICAL ASSESSMENT

At each follow-up evaluation, participants underwent an assessment of medical history, a physical and neurologic examination, and a neuropsychological test battery that included measures of memory, orientation, language, abstract reasoning, and visuospatial ability.31 Memory was evaluated using the multiple-choice version of the Benton Visual Retention Test32 and the 7 subtests of the Selective Reminding Test33: total recall, long-term recall, long-term storage, continuous long-term storage, words recalled on last trial, delayed recall, and delayed recognition. Orientation was evaluated using parts of the modified Mini-Mental State Examination.34 Language was assessed using the Boston Naming Test,35 the Controlled Word Association Test,36 category naming, and the complex ideational material and phrase repetition subtests of the Boston Diagnostic Aphasia Evaluation.37 Abstract reasoning was evaluated using the similarities subtest of the Wechsler Adult Intelligence Scale–Revised38 and the nonverbal identities and oddities subtest of the Mattis Dementia Rating Scale.39 Visuospatial ability was examined using the Rosen Drawing Test40 and a matching version of the Benton Visual Retention Test.32 This neuropsychological test battery has established norms for the same community and has been shown to effectively distinguish between normal aging and dementia.31,41,42

DIAGNOSIS OF DEMENTIA AND MCI

Diagnosis of dementia and assignment of specific cause was made by consensus of neurologists, psychiatrists, and neuropsychologists based on baseline and follow-up information. Diagnosis of dementia was based on Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, criteria43 and required evidence of cognitive deficits on the neuropsychological test battery and on evidence of impairment in social or occupational function (Clinical Dementia Rating ≥1).44 Diagnosis of AD was based on the INCDS-ADRDA (NINCDS-ADRDA [National Institute of Neurological and Communicative Diseases and Stroke/Alzheimer's Disease and Related Disorders Association]) criteria.45 Consistent with standard criteria46 for all subtypes of mild cognitive impairment (MCI), individuals considered for MCI were required to have (1) memory complaint; (2) objective impairment in at least 1 cognitive domain based on the average of the scores on the neuropsychological measures in that domain and a 1.5-SD cutoff value using normative corrections for age, sex, ethnicity, and years of education; (3) essentially preserved activities of daily living; and (4) no dementia. Participants with MCI were stratified into those with (1) isolated impairment in memory or impairment in memory and 1 or more other cognitive domains (amnestic MCI) or (2) no impairment in memory but impairment in 2 or more other cognitive domains (nonamnestic MCI), as described in detail previously.47

MAGNETIC RESONANCE IMAGING

Participants underwent imaging using a 1.5-T scanner (Intera; Royal Philips Electronics, Eindhoven, the Netherlands) at Columbia University Medical Center, New York City. For derivation of CBV, we acquired 2 sets of oblique coronal 3-dimensional T1-weighted images (repetition time, 20 milliseconds; echo time, 4.6 milliseconds; flip angle, 25°; in-plane resolution, 0.86 × 0.86 mm; and section thickness, 3 mm) for each participant perpendicular to the hippocampal long axis. The first series of images was acquired before and the second series was acquired 4 minutes after intravenous administration of a standard dose of gadodiamide, 0.1 mmol/kg (Omniscan; GE Healthcare, Ridgewood, New Jersey). For volumetric analysis of the hippocampus and the entorhinal cortex, T1-weighted images (repetition time, 20 milliseconds; echo time, 2.1 milliseconds; field of view, 240 cm; and a 25 × 160 pixel matrix with 1.3-mm section thickness) were acquired in the axial plane. The voxel size of these images was 0.9375 × 0.9375 × 1.3 mm.

Hippocampal Volume

The images were transferred electronically to the Imaging of Dementia and Aging Laboratory at the University of California, Davis, for morphometric analysis. Images were analyzed manually using a computer workstation (Ultra 5; Sun Microsystems, Santa Clara, California) by operators unaware of participant status. Before tracing of the hippocampus, the T1-weighted images were reoriented in the coronal plane perpendicular to the long axis of the left hippocampus following procedures described in more detail elsewhere (Figure 1).29 Briefly, the borders of the hippocampus were traced manually in the coronal orientation with simultaneous monitoring for accuracy in the sagittal and axial orthogonal views. The rostral end of the hippocampus was defined by emergence of the amygdala. In sections in which the uncus was ventral to the caudal amygdala, the uncus was included in the hippocampus. The superior boundary in posterior regions that do not contain amygdalae was defined by the hippocampal (choroid) fissure, and the superior portion of the inferior horn of the lateral ventricle formed the superior boundary, excluding fimbria. The inferior boundary of the hippocampus was the white matter of the parahippocampal gyrus. The lateral boundary was the inferior (temporal) horn of the lateral ventricle. The posterior boundary of the hippocampus was the first section in which the fornices were completely distinct from gray and white matter of the thalamus. Intrarater reliability in the right and left hippocampi using this method was good (intraclass correlation coefficients of 0.98 and 0.96, respectively).

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Figure 1.

T1-weighted image for acquisition of hippocampal volume. The borders of the hippocampus were traced manually in the coronal orientation with simultaneous monitoring for accuracy in the sagittal and axial orthogonal views.

Graphic Jump Location
Entorhinal Cortex Volume

Entorhinal cortex volume determination followed the protocol of Killiany et al48 and is described in greater detail elsewhere.29 Briefly, the entorhinal cortex area was manually derived on 3 consecutive coronal images, centered at the level of the mammillary bodies. The outline of the entorhinal cortex region began at the junction of the rhinal sulcus and the surface of the brain. The outline then transected the angle formed by the rhinal sulcus and the inferomedial surface of the brain, cutting across the gray matter to the level of the white matter. The edge of the white matter was then followed to the inferior surface of the hippocampus. The outline continued along the surface of the brain back to the starting point. This procedure was repeated using the same landmarks on the immediately adjacent rostral and caudal slices to calculate the total entorhinal area. Interrater reliabilities for this process averaged 0.90.

Hippocampal CBV Maps

Images acquired for CBV quantification were transferred to a computer workstation containing an analysis software package (MEDx Sensor Systems, Sterling, Virginia). An investigator unaware of participant grouping performed all image processing. To generate CBV maps, the precontrast and postcontrast images were coregistered to each other using an automated image registration program.49 A Gnu plot was generated to assess the quality of the coregistration, and an individual study was rejected if a shift greater than 1-pixel dimension was detected. Three studies (2 in patients with AD and 1 in a control subject) were rejected for poor motion correction. The precontrast image was subtracted from the postcontrast image, and the difference in the sagittal sinus, which serves as an estimate of the image intensity change of 100% blood, was recorded. The subtracted image was then divided by the difference in the 4 pixels with the highest intensity values measured from the sagittal sinus and multiplied by 100, yielding relative CBV maps.50,51 The voxel size for these CBV maps was 0.78125 × 0.78125 × 3 mm. As described previously,23 in the series of oblique coronal images, we consistently found that a section anterior to the lateral geniculate nucleus and posterior to the uncus provides optimal visualization of hippocampal morphologic features and internal architecture. The external structure of the hippocampus was manually traced, as was the internal architecture that follows the hippocampal sulcus and the internal white matter tracts (Figure 2). With the aid of standard atlases,52,53 regions of interest of 4 subregions of the hippocampal formation were identified according to the following anatomical criteria: (1) entorhinal cortex: the inferolateral boundary follows the collateral sulcus, the medial boundary is the medial aspect of the temporal lobe, and the superior boundary is the hippocampal sulcus and gray-white distinction between the subiculum and the entorhinal cortex; (2) subiculum: the medial boundary is the medial extent of the hippocampal sulcus or the horizontal inflection of the hippocampus, the inferior boundary is the white matter of the underlying parahippocampal gyrus, the superior boundary is the hippocampal sulcus, and the lateral boundary is a few pixels medial to the vertical inflection of the hippocampus; (3) CA1 subregion: the medial boundary is 2 to 3 pixels lateral to the end of the subiculum region of interest (approximately at the beginning of the vertical inflection of the hippocampus) and the extension of the hippocampal sulcus/white matter tracts, the inferior boundary is the white matter of the underlying parahippocampal gyrus, and the superior boundary is the top of the hippocampal formation; and (4) dentate gyrus: the medial boundary is the medial extent of the temporal lobe, the inferolateral boundary is the hippocampal sulcus–white matter tracts, and the superior boundary is the top of the hippocampal formation, where the alveus is typically identified.

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Figure 2.

Cerebral blood volume (CBV) maps of the hippocampal formation. A, As described in the “Methods” section of the text, a sagittal scout image is used to identify the long axis of the hippocampal formation (red stippled line), and sections are then acquired perpendicular to this axis. B and C, High-resolution T1-weighted images are subsequently acquired before (B) and after (C) injection of a contrast agent. D1-D4, The CBV maps are generated by subtracting the precontrast from the postcontrast scan and dividing the subtracting images by the degree of contrast enhancement observed in the sagittal sinus (red triangle [C]). Postacquisition anatomical criteria are used to identify regions of interest in the hippocampal subregions. The anatomical locations of the 4 hippocampal subregions are shown in a postmortem hippocampal section (D1). CA1 indicates CA1 subfield; DG, dentate gyrus; EC, entorhinal cortex; and Sub, subiculum. By identifying the external morphologic features of the hippocampal formation (D2: anatomical structure before manual tracing of subregions; white line in D3 and D4) and its internal architecture (black line in D3 and D4), regions of interest can be drawn in the entorhinal cortex (green), dentate gyrus (blue), CA1 subfield (red), and subiculum (yellow).

Graphic Jump Location

Because the border zones between any 2 subregions cannot be identified without histologic landmarks, they were excluded from the regions of interest. Mean relative CBV from the region of interest of each hippocampal subregion was measured in each participant and was used for group data analysis. Relative CBV values from the subiculum, CA1 subregion, and dentate gyrus were averaged to yield a single measurement of relative CBV in the hippocampus proper.

Examination of regional CBV vs regional volumetry yields different information. Examination of regional CBV provides an estimate of the basal metabolic rate, and regional volumetry provides a measurement of parenchymal integrity, or atrophy, due to neuronal or glial loss. Estimates of CBV are derived in voxels representative of each region of interest, whereas volume is calculated by summing across the same regions. Thus, although the 2 approaches differ in the quantification of the region, they are regionally comparable

Quality Control of MRI Measures

Each image was rated for image quality based on signal to noise ratio, susceptibility artifact, and movement. Those deemed to be of poor quality were not analyzed. Of the 769 images available, 623 were of satisfactory quality to analyze entorhinal cortex volume and 749 were of satisfactory quality to analyze hippocampal volume. After 392 images were dropped from the CBV analysis, 231 were available for this analysis.

APOE Genotyping

The APOE genotypes were determined as described by Hixson and Vernier54 with slight modification. We classified persons as homozygous or heterozygous for the APOE ε4 allele or as not having the APOE ε4 allele.

STATISTICAL METHODS

First we evaluated the demographic and clinical characteristics of the study sample at baseline. Then we used multivariate regression models to estimate all main effects of entorhinal cortex CBV, entorhinal cortex volume, hippocampal volume, and hippocampal CBV on measures of memory performance, adjusting all of the models for age, sex, ethnicity, and years of education. We focused on measures of total recall and delayed recall because learning and memory are the hallmarks and the most sensitive measures of cognitive impairment in AD. To determine whether potentially observed associations remained consistent in persons without dementia, we then repeated all analyses excluding persons with dementia (n = 17). To determine whether potentially observed associations were specific to memory function, we finally repeated all analyses using a language summary score as the outcome, which was derived by a factor analysis of data from all 15 neuropsychological measures in the entire cohort.55 Main contributors to this language factor score were the Boston Naming Test, the Controlled Oral Word Association Test, and the Wechsler Adult Intelligence Scale–Revised similarities subtest. All data analysis was performed using statistical software (SPSS version 16.0; SPSS Inc, Chicago, Illinois).

Table 1 summarizes the clinical and demographic characteristics of the study sample. The 17 persons with dementia at the time of MRI were included in the study because at the last visit before MRI they were not yet demented and, thus, met the inclusion criteria. Of the 17 persons with dementia, 10 (58.8%) had probable AD without concomitant disease, 4 (23.5%) had probable AD with stroke, and 3 (17.7%) had probable AD with other concomitant disease. Persons with MCI or dementia had, on average, smaller hippocampal volumes and worse memory function than did persons without cognitive impairment (Table 2).

Table Graphic Jump LocationTable 1. Clinical and Demographic Characteristics of the Study Samplea
Table Graphic Jump LocationTable 2. Memory Function, Hippocampal Volume, Hippocampal CBV, Entorhinal Cortex Volume, and Entorhinal Cortex CBV Across Cognitive Impairment Groupsa

No association was noted between entorhinal cortex volume or hippocampal CBV and memory as measured by total and delayed recall. However, decreased hippocampal volumes were associated with significantly worse performance in total recall (β [SE] = 26.38 [12.18], P = .03) (Table 3), and lower entorhinal cortex CBV was associated with worse performance in delayed recall (β [SE] = 8.43 [4.51], P = .05).

Table Graphic Jump LocationTable 3. Regression Coefficients Relating Hippocampal Volume, Hippocampal CBV, Entorhinal Cortex Volume, and Entorhinal Cortex CBV to Memory and Language Performancea

When we repeated all of the analyses excluding demented persons (n = 17), the strength of the association between entorhinal cortex CBV and delayed recall was increased (β [SE] = 10.92 [4.44], P = .01), whereas the association between hippocampal volume and memory performance was attenuated and was no longer significant (β [SE] = 9.07 [12.01], P = .45) (Table 3). Additional exclusion of persons with MCI (n = 52) subsequently attenuated the association between entorhinal cortex CBV and delayed recall (β [SE] = 10.24 [4.16], P = .02) and further attenuated the association between hippocampal volume and memory performance (β = 2.69 [12.29], P = .83). No associations were noted of entorhinal cortex CBV, entorhinal cortex volume, hippocampal volume, or hippocampal CBV with language performance. When we repeated all of the analyses stratifying by APOE genotype (APOE ε4 carriers vs noncarriers) or brain hemispheres, all of the results were similar across strata.

Magnetic resonance imaging technology provides the opportunity to image functional and structural correlates of changes in the hippocampal formation simultaneously. We investigated the stage at which changes in hippocampal volume, hippocampal CBV, entorhinal cortex volume, and entorhinal cortex CBV best reflected changes in memory performance. In a combined group of demented and nondemented persons, lower hippocampal volume was associated with worse total recall, and lower entorhinal cortex CBV was associated with worse delayed recall. When persons with dementia were excluded, however, the association between hippocampal volume and memory was attenuated and nonsignificant, whereas the association between entorhinal cortex CBV and delayed recall became stronger. Additional exclusion of persons with MCI subsequently attenuated the increased association between entorhinal cortex CBV and delayed recall and further attenuated the association between hippocampal volume and memory performance. No associations were noted of entorhinal cortex CBV, entorhinal cortex volume, hippocampal volume, or hippocampal CBV with language performance, suggesting that the observed effects are specific to the memory domain.

Results of human and animal studies have suggested different stages through which AD progresses: neuronal malfunction manifesting as synaptic or metabolic deficit followed by insoluble protein aggregates typified by amyloid plaques and neurofibrillary tangles and, finally, by neuronal cell death. At this point, however, this pattern of progression serves only as a working model. The functional and structural stages in AD are not categorically exclusive, and the temporal sequence of malfunction and cell loss is not proved. Structural and functional changes in the hippocampal formation could simultaneously or sequentially contribute to memory impairment. Structural and functional imaging techniques as used in the present study have the potential to help clarify the relation between structural and functional hippocampal changes during the disease and the molecular mechanisms by which these changes lead to memory impairment.

The present findings are consistent with those of previous imaging studies that reported associations between hippocampal volume and entorhinal cortex defects and memory function. After early structural MRI study results56 showed atrophy of the hippocampus in patients with dementia of moderate severity, later studies5759 found atrophy in patients with milder dementia. Atrophy on MRI is also observed in high-risk populations, such as patients with MCI57,60 or those at risk for autosomal dominant familial AD,61,62 and in persons without cognitive impairment.6368 In persons without cognitive impairment and in patients with MCI, hippocampal atrophy severity predicts conversion to dementia independently of neuropsychological performance.58,64,69 In the hippocampal formation, the entorhinal cortex was observed to be the region predominantly affected by the effects of AD,69,70 and there is evidence that it is superior to hippocampal volume in predicting future cognitive decline.1,69

Functional imaging can, in general, estimate hippocampal hypofunction by mapping disease-related changes in glucose uptake, reflecting glucose metabolism, or by mapping changes in any of the 3 correlates of oxygen metabolism: cerebral blood flow, CBV, and deoxyhemoglobin content.71 All 4 variables can successfully detect regional dysfunction in AD. However, MRI maps of CBV are preferable because they are more directly coupled to brain metabolism and give a more accurate functional view of the tissue that may indicate disease via cell dysfunction before cell loss and atrophy.72 Indeed, previous AD studies have shown that CBV tightly correlates with measures of glucose metabolism,21 obviating the concern that AD-related vascular abnormality uncouples basal CBV from underlying neuronal function. The finding of an association between lower entorhinal cortex CBV and worse delayed recall in the present study is consistent with a previous CBV study finding23 that reported that of all hippocampal subregions, the entorhinal cortex is the dominant site of dysfunction observed in humans with AD and J20 mice.

The present study extends previous works in that we explored the effects of hippocampal and entorhinal cortex volume and CBV in affected and unaffected individuals, explored at what stage of cognitive impairment these measures exert their effects on memory performance, and explored whether they are specific for memory function. The exclusion of persons with dementia from the analyses caused the associations between hippocampal volume and memory measures to attenuate, whereas the weak association between entorhinal cortex CBV and delayed recall became stronger. Additional exclusion of persons with MCI subsequently further attenuated the association between hippocampal volume and memory performance and also attenuated the increased association between entorhinal cortex CBV and delayed recall observed after the exclusion of patients with dementia. These findings suggest that in the early stages of disease (MCI) or in nondemented persons, functional and metabolic effects correlate with memory, whereas in the later stages, functional and structural changes are present. This notion is supported by the fact that not only persons with AD but also persons with amnestic MCI had, on average, smaller hippocampal CBVs than did persons without cognitive impairment. Because neuronal dysfunction is, compared with neuronal cell death, considered the disease's cytopathologic feature most amenable to pharmacologic intervention, this finding has major implications.

A limitation of this study is its cross-sectional nature, which limits the inferences that can be made from the results, and the selection of a subpopulation that limits generalization. Furthermore, we had only 17 patients with dementia, and these cases were mild. It is likely that inclusion of more persons with dementia and patients with more severe dementia would have increased the power of the study and would have led to stronger associations. Important strengths of the study include the detailed structural and functional MRI measures with CBV assessment and the detailed neuropsychological test battery, especially designed for diagnosis of cognitive impairment and dementia. To our knowledge, this is the first study to explore and demonstrate the relation between structural and functional (para)hippocampal changes in cognitive impairment and to demonstrate the specificity of this effect for the memory domain.

Mapping a temporal, cognitive, and molecular pattern of hippocampal hypofunction is an important step toward a greater mechanistic understanding of the AD disease process. These findings set the stage for future studies to focus on the molecular level of analysis. Studies are needed to clarify the mechanisms that underlie the observed temporal course of structural and functional molecular changes in the hippocampal formation.

Correspondence: Christiane Reitz, MD, PhD, Sergievsky Center and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, 630 W 168th St, New York, NY 10032 (cr2101@columbia.edu).

Accepted for Publication: April 13, 2009.

Author Contributions: All authors had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Reitz, Brickman, Brown, Small, and Mayeux. Acquisition of data: Reitz, Manly, Small, and Mayeux. Analysis and interpretation of data: Reitz, Brickman, Brown, DeCarli, Small, and Mayeux. Drafting of the manuscript: Reitz, Brickman, Small, and Mayeux. Critical revision of the manuscript for important intellectual content: Brickman, Brown, Manly, DeCarli, Small, and Mayeux. Statistical analysis: Reitz and Small. Obtained funding: Manly and Mayeux. Administrative, technical, and material support: Manly, DeCarli, and Mayeux. Study supervision: Brown, DeCarli, and Mayeux.

Financial Disclosure: None reported.

Funding/Support: This work was supported by grants AG007232 and AG029949 from the National Institutes of Health.

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Wu  WSmall  SA Imaging the earliest stages of Alzheimer's disease. Curr Alzheimer Res 2006;3 (5) 529- 539
PubMed
González  RGFischman  AJGuimaraes  AR  et al.  Functional MR in the evaluation of dementia: correlation of abnormal dynamic cerebral blood volume measurements with changes in cerebral metabolism on positron emission tomography with fludeoxyglucose F 18. AJNR Am J Neuroradiol 1995;16 (9) 1763- 1770
PubMed
Harris  GJLewis  RFSatlin  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
PubMed
Moreno  HWu  WELee  T  et al.  Imaging the Aβ-related neurotoxicity of Alzheimer disease. Arch Neurol 2007;64 (10) 1467- 1477
PubMed
Manly  JJTang  MXSchupf  NStern  YVonsattel  JPMayeux  R Frequency and course of mild cognitive impairment in a multiethnic community. Ann Neurol 2008;63 (4) 494- 506
PubMed
Bowen  JTeri  LKukull  W McCormick  W McCurry  SMLarson  EB Progression to dementia in patients with isolated memory loss. Lancet 1997;349 (9054) 763- 765
PubMed
Dickerson  BCSperling  RAHyman  BTAlbert  MSBlacker  D Clinical prediction of Alzheimer disease dementia across the spectrum of mild cognitive impairment. Arch Gen Psychiatry 2007;64 (12) 1443- 1450
PubMed
Panza  FCapurso  CD'Introno  A  et al.  Progression to dementia in probable and possible mild cognitive impairment. Arch Neurol 2007;64 (8) 1209- 1211
PubMed
Tabert  MHManly  JJLiu  X  et al.  Neuropsychological prediction of conversion to Alzheimer disease in patients with mild cognitive impairment. Arch Gen Psychiatry 2006;63 (8) 916- 924
PubMed
Brickman  AMSchupf  NManly  JJ  et al.  Brain morphology in older African Americans, Caribbean Hispanics, and whites from northern Manhattan. Arch Neurol 2008;65 (8) 1053- 1061
PubMed
Tang  MXCross  PAndrews  H  et al.  Incidence of AD in African-Americans, Caribbean Hispanics, and Caucasians in northern Manhattan. Neurology 2001;56 (1) 49- 56
PubMed
Stern  YAndrews  HPittman  J  et al.  Diagnosis of dementia in a heterogeneous population: development of a neuropsychological paradigm-based diagnosis of dementia and quantified correction for the effects of education. Arch Neurol 1992;49 (5) 453- 460
PubMed
Benton  A The Benton Visual Retention Test.  New York, NY Psychological Corp1955;
Buschke  HFuld  P Evaluating storage, retention, and retrieval in disordered memory and learning. Neurology 1974;24 (11) 1019- 1025
PubMed
Folstein  MFFolstein  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
PubMed
Kaplan  EGoodglass  HWeintraub  S Boston Naming Test.  Philadelphia, PA Lea & Febiger1983;
Benton  A FAS Test.  Victoria, Canada University of Victoria1967;
Goodglass  HKaplan  E The Assessment of Aphasia and Related Disorders. 2nd ed. Philadelphia, PA Lea & Febiger1983;
Wechsler  D Wechsler Adult Intelligence Scale–Revised.  New York, NY Psychological Corp1981;
Mattis  S Mental Status Examination for Organic Mental Syndrome in the Elderly Patient.  New York, NY Grune & Stratton1976;
Rosen  W The Rosen Drawing Test.  Bronx, NY Veterans Administration Medical Center1981;
Stricks  LPittman  JJacobs  DMSano  MStern  Y Normative data for a brief neuropsychological battery administered to English- and Spanish-speaking community-dwelling elders. J Int Neuropsychol Soc 1998;4 (4) 311- 318
PubMed
Jacobs  DMSano  MAlbert  SSchofield  PDooneief  GStern  Y Cross-cultural neuropsychological assessment: a comparison of randomly selected, demographically matched cohorts of English- and Spanish-speaking older adults. J Clin Exp Neuropsychol 1997;19 (3) 331- 339
PubMed
American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Washington, DC American Psychiatric Association1994;
Hughes  CPBerg  LDanziger  WLCoben  LAMartin  RL A new clinical scale for the staging of dementia. Br J Psychiatry 1982;140566- 572
PubMed
McKhann  GDrachman  DFolstein  MKatzman  RPrice  DStadlan  EM 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
PubMed
Petersen  RCSmith  GEWaring  SCIvnik  RJTangalos  EGKokmen  E Mild cognitive impairment: clinical characterization and outcome [published correction appears in Arch Neurol. 1999;56(6):760]. Arch Neurol 1999;56 (3) 303- 308
PubMed
Manly  JJBell-McGinty  STang  MXSchupf  NStern  YMayeux  R Implementing diagnostic criteria and estimating frequency of mild cognitive impairment in an urban community. Arch Neurol 2005;62 (11) 1739- 1746
PubMed
Killiany  RJGomez-Isla  TMoss  M  et al.  Use of structural magnetic resonance imaging to predict who will get Alzheimer's disease. Ann Neurol 2000;47 (4) 430- 439
PubMed
Woods  RPGrafton  STWatson  JDSicotte  NLMazziotta  JC Automated image registration, II: intersubject validation of linear and nonlinear models. J Comput Assist Tomogr 1998;22 (1) 153- 165
PubMed
Lin  WCelik  APaczynski  RP Regional cerebral blood volume: a comparison of the dynamic imaging and the steady state methods. J Magn Reson Imaging 1999;9 (1) 44- 52
PubMed
Lin  WPaczynski  RPKuppusamy  KHsu  CYHaacke  EM Quantitative measurements of regional cerebral blood volume using MRI in rats: effects of arterial carbon dioxide tension and mannitol. Magn Reson Med 1997;38 (3) 420- 428
PubMed
Amaral  DGInsausti  R The hippocampal formation. Paxinos  RThe Human Nervous System. San Diego, CA Academic Press1990;
Duvernoy  HM The Human Hippocampus: An Atlas of Applied Anatomy. 2nd ed. Munich, Germany JF Bergman1998;
Hixson  JEVernier  DT Restriction isotyping of human apolipoprotein E by gene amplification and cleavage with HhaI. J Lipid Res 1990;31 (3) 545- 548
PubMed
Kleinbaum  DGKupper  LLMuller  K Applied Regression Analysis and Other Multivariable Methods. 2nd ed. Boston, MA PWS-Kent1988;631
Lehéricy  SBaulac  MChiras  J  et al.  Amygdalohippocampal MR volume measurements in the early stages of Alzheimer disease. AJNR Am J Neuroradiol 1994;15 (5) 929- 937
PubMed
Du  ATSchuff  NAmend  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
PubMed
Jack  CR  JrPetersen  RCXu  YC  et al.  Medial temporal atrophy on MRI in normal aging and very mild Alzheimer's disease. Neurology 1997;49 (3) 786- 794
PubMed
Laakso  MPPartanen  KRiekkinen  P  et al.  Hippocampal volumes in Alzheimer's disease, Parkinson's disease with and without dementia, and in vascular dementia: an MRI study. Neurology 1996;46 (3) 678- 681
PubMed
Convit  Ade Leon  MJTarshish  C  et al.  Hippocampal volume losses in minimally impaired elderly [letter]. Lancet 1995;345 (8944) 266
PubMed
Fox  NCWarrington  EKFreeborough  PA  et al.  Presymptomatic hippocampal atrophy in Alzheimer's disease: a longitudinal MRI study. Brain 1996;119 (pt 6) 2001- 2007
PubMed
Schott  JMFox  NCFrost  C  et al.  Assessing the onset of structural change in familial Alzheimer's disease. Ann Neurol 2003;53 (2) 181- 188
PubMed
Golomb  JKluger  Ade Leon  MJ  et al.  Hippocampal formation size in normal human aging: a correlate of delayed secondary memory performance. Learn Mem 1994;1 (1) 45- 54
PubMed
Ikram  MAVrooman  HAVernooij  MW  et al.  Brain tissue volumes in relation to cognitive function and risk of dementia [published online ahead of print May 22, 2008]. Neurobiol Aging. 10.1016/j.neurobiolaging.2008.04.008Accessed July 28, 2008
Small  SATsai  WYDeLaPaz  RMayeux  RStern  Y Imaging hippocampal function across the human life span: is memory decline normal or not? Ann Neurol 2002;51 (3) 290- 295
PubMed
Yonelinas  APWidaman  KMungas  DReed  BWeiner  MWChui  HC Memory in the aging brain: doubly dissociating the contribution of the hippocampus and entorhinal cortex. Hippocampus 2007;17 (11) 1134- 1140
PubMed
De Leon  MJGeorge  AEGolomb  J  et al.  Frequency of hippocampal formation atrophy in normal aging and Alzheimer's disease. Neurobiol Aging 1997;18 (1) 1- 11
PubMed
Golomb  JKluger  Ade Leon  MJ  et al.  Hippocampal formation size predicts declining memory performance in normal aging. Neurology 1996;47 (3) 810- 813
PubMed
Killiany  RJHyman  BTGomez-Isla  T  et al.  MRI measures of entorhinal cortex vs hippocampus in preclinical AD. Neurology 2002;58 (8) 1188- 1196
PubMed
Pennanen  CKivipelto  MTuomainen  S  et al.  Hippocampus and entorhinal cortex in mild cognitive impairment and early AD. Neurobiol Aging 2004;25 (3) 303- 310
PubMed
Small  SA Imaging Alzheimer's disease. Curr Neurol Neurosci Rep 2003;3 (5) 385- 392
PubMed
Small  SA Measuring correlates of brain metabolism with high-resolution MRI: a promising approach for diagnosing Alzheimer disease and mapping its course. Alzheimer Dis Assoc Disord 2003;17 (3) 154- 161
PubMed

Figures

Place holder to copy figure label and caption
Figure 1.

T1-weighted image for acquisition of hippocampal volume. The borders of the hippocampus were traced manually in the coronal orientation with simultaneous monitoring for accuracy in the sagittal and axial orthogonal views.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.

Cerebral blood volume (CBV) maps of the hippocampal formation. A, As described in the “Methods” section of the text, a sagittal scout image is used to identify the long axis of the hippocampal formation (red stippled line), and sections are then acquired perpendicular to this axis. B and C, High-resolution T1-weighted images are subsequently acquired before (B) and after (C) injection of a contrast agent. D1-D4, The CBV maps are generated by subtracting the precontrast from the postcontrast scan and dividing the subtracting images by the degree of contrast enhancement observed in the sagittal sinus (red triangle [C]). Postacquisition anatomical criteria are used to identify regions of interest in the hippocampal subregions. The anatomical locations of the 4 hippocampal subregions are shown in a postmortem hippocampal section (D1). CA1 indicates CA1 subfield; DG, dentate gyrus; EC, entorhinal cortex; and Sub, subiculum. By identifying the external morphologic features of the hippocampal formation (D2: anatomical structure before manual tracing of subregions; white line in D3 and D4) and its internal architecture (black line in D3 and D4), regions of interest can be drawn in the entorhinal cortex (green), dentate gyrus (blue), CA1 subfield (red), and subiculum (yellow).

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Clinical and Demographic Characteristics of the Study Samplea
Table Graphic Jump LocationTable 2. Memory Function, Hippocampal Volume, Hippocampal CBV, Entorhinal Cortex Volume, and Entorhinal Cortex CBV Across Cognitive Impairment Groupsa
Table Graphic Jump LocationTable 3. Regression Coefficients Relating Hippocampal Volume, Hippocampal CBV, Entorhinal Cortex Volume, and Entorhinal Cortex CBV to Memory and Language Performancea

References

deToledo-Morrell  LStoub  TRBulgakova  M  et al.  MRI-derived entorhinal volume is a good predictor of conversion from MCI to AD. Neurobiol Aging 2004;25 (9) 1197- 1203
PubMed
Stoub  TRdeToledo-Morrell  LStebbins  GTLeurgans  SBennett  DAShah  RC Hippocampal disconnection contributes to memory dysfunction in individuals at risk for Alzheimer's disease. Proc Natl Acad Sci U S A 2006;103 (26) 10041- 10045
PubMed
Wittenberg  GMTsien  JZ An emerging molecular and cellular framework for memory processing by the hippocampus. Trends Neurosci 2002;25 (10) 501- 505
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Heinemann  USchmitz  DEder  CGloveli  T Properties of entorhinal cortex projection cells to the hippocampal formation. Ann N Y Acad Sci 2000;911112- 126
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Davis  AEGimenez  AMTherrien  B Effects of entorhinal cortex lesions on sensory integration and spatial learning. Nurs Res 2001;50 (2) 77- 85
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Haroutunian  VPerl  DPPurohit  DP  et al.  Regional distribution of neuritic plaques in the nondemented elderly and subjects with very mild Alzheimer disease. Arch Neurol 1998;55 (9) 1185- 1191
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Haroutunian  VPurohit  DPPerl  DP  et al.  Neurofibrillary tangles in nondemented elderly subjects and mild Alzheimer disease. Arch Neurol 1999;56 (6) 713- 718
PubMed
Braak  HBraak  EBohl  J Staging of Alzheimer-related cortical destruction. Eur Neurol 1993;33 (6) 403- 408
PubMed
Devanand  DPPradhaban  GLiu  X  et al.  Hippocampal and entorhinal atrophy in mild cognitive impairment: prediction of Alzheimer disease. Neurology 2007;68 (11) 828- 836
PubMed
Tapiola  TPennanen  CTapiola  M  et al.  MRI of hippocampus and entorhinal cortex in mild cognitive impairment: a follow-up study. Neurobiol Aging 2008;29 (1) 31- 38
PubMed
Jack  CR  JrPetersen  RCXu  Y  et al.  Rates of hippocampal atrophy correlate with change in clinical status in aging and AD. Neurology 2000;55 (4) 484- 489
PubMed
Au  RMassaro  JMWolf  PA  et al.  Association of white matter hyperintensity volume with decreased cognitive functioning: the Framingham Heart Study. Arch Neurol 2006;63 (2) 246- 250
PubMed
de Groot  JCde Leeuw  FEOudkerk  M  et al.  Cerebral white matter lesions and cognitive function: the Rotterdam Scan Study. Ann Neurol 2000;47 (2) 145- 151
PubMed
Longstreth  WT  JrManolio  TAArnold  A  et al.  Clinical correlates of white matter findings on cranial magnetic resonance imaging of 3301 elderly people: the Cardiovascular Health Study. Stroke 1996;27 (8) 1274- 1282
PubMed
Schmidt  RRopele  SEnzinger  C  et al.  White matter lesion progression, brain atrophy, and cognitive decline: the Austrian stroke prevention study. Ann Neurol 2005;58 (4) 610- 616
PubMed
Vermeer  SEPrins  NDden Heijer  THofman  AKoudstaal  PJBreteler  MM Silent brain infarcts and the risk of dementia and cognitive decline. N Engl J Med 2003;348 (13) 1215- 1222
PubMed
Small  SAChawla  MKBuonocore  MRapp  PRBarnes  CA Imaging correlates of brain function in monkeys and rats isolates a hippocampal subregion differentially vulnerable to aging. Proc Natl Acad Sci U S A 2004;101 (18) 7181- 7186
PubMed
Wu  WSmall  SA Imaging the earliest stages of Alzheimer's disease. Curr Alzheimer Res 2006;3 (5) 529- 539
PubMed
González  RGFischman  AJGuimaraes  AR  et al.  Functional MR in the evaluation of dementia: correlation of abnormal dynamic cerebral blood volume measurements with changes in cerebral metabolism on positron emission tomography with fludeoxyglucose F 18. AJNR Am J Neuroradiol 1995;16 (9) 1763- 1770
PubMed
Harris  GJLewis  RFSatlin  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
PubMed
Moreno  HWu  WELee  T  et al.  Imaging the Aβ-related neurotoxicity of Alzheimer disease. Arch Neurol 2007;64 (10) 1467- 1477
PubMed
Manly  JJTang  MXSchupf  NStern  YVonsattel  JPMayeux  R Frequency and course of mild cognitive impairment in a multiethnic community. Ann Neurol 2008;63 (4) 494- 506
PubMed
Bowen  JTeri  LKukull  W McCormick  W McCurry  SMLarson  EB Progression to dementia in patients with isolated memory loss. Lancet 1997;349 (9054) 763- 765
PubMed
Dickerson  BCSperling  RAHyman  BTAlbert  MSBlacker  D Clinical prediction of Alzheimer disease dementia across the spectrum of mild cognitive impairment. Arch Gen Psychiatry 2007;64 (12) 1443- 1450
PubMed
Panza  FCapurso  CD'Introno  A  et al.  Progression to dementia in probable and possible mild cognitive impairment. Arch Neurol 2007;64 (8) 1209- 1211
PubMed
Tabert  MHManly  JJLiu  X  et al.  Neuropsychological prediction of conversion to Alzheimer disease in patients with mild cognitive impairment. Arch Gen Psychiatry 2006;63 (8) 916- 924
PubMed
Brickman  AMSchupf  NManly  JJ  et al.  Brain morphology in older African Americans, Caribbean Hispanics, and whites from northern Manhattan. Arch Neurol 2008;65 (8) 1053- 1061
PubMed
Tang  MXCross  PAndrews  H  et al.  Incidence of AD in African-Americans, Caribbean Hispanics, and Caucasians in northern Manhattan. Neurology 2001;56 (1) 49- 56
PubMed
Stern  YAndrews  HPittman  J  et al.  Diagnosis of dementia in a heterogeneous population: development of a neuropsychological paradigm-based diagnosis of dementia and quantified correction for the effects of education. Arch Neurol 1992;49 (5) 453- 460
PubMed
Benton  A The Benton Visual Retention Test.  New York, NY Psychological Corp1955;
Buschke  HFuld  P Evaluating storage, retention, and retrieval in disordered memory and learning. Neurology 1974;24 (11) 1019- 1025
PubMed
Folstein  MFFolstein  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
PubMed
Kaplan  EGoodglass  HWeintraub  S Boston Naming Test.  Philadelphia, PA Lea & Febiger1983;
Benton  A FAS Test.  Victoria, Canada University of Victoria1967;
Goodglass  HKaplan  E The Assessment of Aphasia and Related Disorders. 2nd ed. Philadelphia, PA Lea & Febiger1983;
Wechsler  D Wechsler Adult Intelligence Scale–Revised.  New York, NY Psychological Corp1981;
Mattis  S Mental Status Examination for Organic Mental Syndrome in the Elderly Patient.  New York, NY Grune & Stratton1976;
Rosen  W The Rosen Drawing Test.  Bronx, NY Veterans Administration Medical Center1981;
Stricks  LPittman  JJacobs  DMSano  MStern  Y Normative data for a brief neuropsychological battery administered to English- and Spanish-speaking community-dwelling elders. J Int Neuropsychol Soc 1998;4 (4) 311- 318
PubMed
Jacobs  DMSano  MAlbert  SSchofield  PDooneief  GStern  Y Cross-cultural neuropsychological assessment: a comparison of randomly selected, demographically matched cohorts of English- and Spanish-speaking older adults. J Clin Exp Neuropsychol 1997;19 (3) 331- 339
PubMed
American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Washington, DC American Psychiatric Association1994;
Hughes  CPBerg  LDanziger  WLCoben  LAMartin  RL A new clinical scale for the staging of dementia. Br J Psychiatry 1982;140566- 572
PubMed
McKhann  GDrachman  DFolstein  MKatzman  RPrice  DStadlan  EM 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
PubMed
Petersen  RCSmith  GEWaring  SCIvnik  RJTangalos  EGKokmen  E Mild cognitive impairment: clinical characterization and outcome [published correction appears in Arch Neurol. 1999;56(6):760]. Arch Neurol 1999;56 (3) 303- 308
PubMed
Manly  JJBell-McGinty  STang  MXSchupf  NStern  YMayeux  R Implementing diagnostic criteria and estimating frequency of mild cognitive impairment in an urban community. Arch Neurol 2005;62 (11) 1739- 1746
PubMed
Killiany  RJGomez-Isla  TMoss  M  et al.  Use of structural magnetic resonance imaging to predict who will get Alzheimer's disease. Ann Neurol 2000;47 (4) 430- 439
PubMed
Woods  RPGrafton  STWatson  JDSicotte  NLMazziotta  JC Automated image registration, II: intersubject validation of linear and nonlinear models. J Comput Assist Tomogr 1998;22 (1) 153- 165
PubMed
Lin  WCelik  APaczynski  RP Regional cerebral blood volume: a comparison of the dynamic imaging and the steady state methods. J Magn Reson Imaging 1999;9 (1) 44- 52
PubMed
Lin  WPaczynski  RPKuppusamy  KHsu  CYHaacke  EM Quantitative measurements of regional cerebral blood volume using MRI in rats: effects of arterial carbon dioxide tension and mannitol. Magn Reson Med 1997;38 (3) 420- 428
PubMed
Amaral  DGInsausti  R The hippocampal formation. Paxinos  RThe Human Nervous System. San Diego, CA Academic Press1990;
Duvernoy  HM The Human Hippocampus: An Atlas of Applied Anatomy. 2nd ed. Munich, Germany JF Bergman1998;
Hixson  JEVernier  DT Restriction isotyping of human apolipoprotein E by gene amplification and cleavage with HhaI. J Lipid Res 1990;31 (3) 545- 548
PubMed
Kleinbaum  DGKupper  LLMuller  K Applied Regression Analysis and Other Multivariable Methods. 2nd ed. Boston, MA PWS-Kent1988;631
Lehéricy  SBaulac  MChiras  J  et al.  Amygdalohippocampal MR volume measurements in the early stages of Alzheimer disease. AJNR Am J Neuroradiol 1994;15 (5) 929- 937
PubMed
Du  ATSchuff  NAmend  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
PubMed
Jack  CR  JrPetersen  RCXu  YC  et al.  Medial temporal atrophy on MRI in normal aging and very mild Alzheimer's disease. Neurology 1997;49 (3) 786- 794
PubMed
Laakso  MPPartanen  KRiekkinen  P  et al.  Hippocampal volumes in Alzheimer's disease, Parkinson's disease with and without dementia, and in vascular dementia: an MRI study. Neurology 1996;46 (3) 678- 681
PubMed
Convit  Ade Leon  MJTarshish  C  et al.  Hippocampal volume losses in minimally impaired elderly [letter]. Lancet 1995;345 (8944) 266
PubMed
Fox  NCWarrington  EKFreeborough  PA  et al.  Presymptomatic hippocampal atrophy in Alzheimer's disease: a longitudinal MRI study. Brain 1996;119 (pt 6) 2001- 2007
PubMed
Schott  JMFox  NCFrost  C  et al.  Assessing the onset of structural change in familial Alzheimer's disease. Ann Neurol 2003;53 (2) 181- 188
PubMed
Golomb  JKluger  Ade Leon  MJ  et al.  Hippocampal formation size in normal human aging: a correlate of delayed secondary memory performance. Learn Mem 1994;1 (1) 45- 54
PubMed
Ikram  MAVrooman  HAVernooij  MW  et al.  Brain tissue volumes in relation to cognitive function and risk of dementia [published online ahead of print May 22, 2008]. Neurobiol Aging. 10.1016/j.neurobiolaging.2008.04.008Accessed July 28, 2008
Small  SATsai  WYDeLaPaz  RMayeux  RStern  Y Imaging hippocampal function across the human life span: is memory decline normal or not? Ann Neurol 2002;51 (3) 290- 295
PubMed
Yonelinas  APWidaman  KMungas  DReed  BWeiner  MWChui  HC Memory in the aging brain: doubly dissociating the contribution of the hippocampus and entorhinal cortex. Hippocampus 2007;17 (11) 1134- 1140
PubMed
De Leon  MJGeorge  AEGolomb  J  et al.  Frequency of hippocampal formation atrophy in normal aging and Alzheimer's disease. Neurobiol Aging 1997;18 (1) 1- 11
PubMed
Golomb  JKluger  Ade Leon  MJ  et al.  Hippocampal formation size predicts declining memory performance in normal aging. Neurology 1996;47 (3) 810- 813
PubMed
Killiany  RJHyman  BTGomez-Isla  T  et al.  MRI measures of entorhinal cortex vs hippocampus in preclinical AD. Neurology 2002;58 (8) 1188- 1196
PubMed
Pennanen  CKivipelto  MTuomainen  S  et al.  Hippocampus and entorhinal cortex in mild cognitive impairment and early AD. Neurobiol Aging 2004;25 (3) 303- 310
PubMed
Small  SA Imaging Alzheimer's disease. Curr Neurol Neurosci Rep 2003;3 (5) 385- 392
PubMed
Small  SA Measuring correlates of brain metabolism with high-resolution MRI: a promising approach for diagnosing Alzheimer disease and mapping its course. Alzheimer Dis Assoc Disord 2003;17 (3) 154- 161
PubMed

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For CME Course: A Proposed Model for Initial Assessment and Management of Acute Heart Failure Syndromes
Indicate what changes(s) you will implement in your practice, if any, based on this CME course.
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