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Original Contribution |

Comparing Fludeoxyglucose F18–PET Assessment of Regional Cerebral Glucose Metabolism and [11C]Dihydrotetrabenazine–PET in Evaluation of Early Dementia and Mild Cognitive Impairment FREE

Roger L. Albin, MD; Robert A. Koeppe, PhD; James F. Burke, MD; Bruno Giordani, PhD; Michael R. Kilbourn, PhD; Sid Gilman, MD; Kirk A. Frey, MD, PhD
[+] Author Affiliations

Author Affiliations: VA Ann Arbor Health System Geriatrics Research, Education, and Clinical Center (Dr Albin); and Department of Neurology (Drs Albin, Burke, Gilman, and Frey), Division of Nuclear Medicine, Department of Radiology (Drs Koeppe, Kilbourn, and Frey), and Department of Psychiatry (Dr Giordani), University of Michigan, Ann Arbor.


Arch Neurol. 2010;67(4):440-446. doi:10.1001/archneurol.2010.34.
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Objective  To compare assessment of regional cerebral metabolic changes with [11C]dihydrotetrabenazine (DTBZ)–positron emission tomography (PET) measurement of regional cerebral blood flow (K1) and fludeoxyglucose F18 (FDG)–PET measurement of regional cerebral glucose uptake (CMRglc) in a clinically representative sample of subjects with mild dementia and mild cognitive impairment (MCI).

Design  [11C]Dihydrotetrabenazine-PET K1 and FDG-PET CMRglc measurements were performed.

Setting  University-based cognitive disorders clinic.

Participants  Fifty subjects with either mild dementia (Mini-Mental State Examination score ≥ 18) or MCI. Their results were compared with those of 80 normal control subjects.

Main Outcome Measures  The DTBZ-PET regional K1 and FDG-PET CMRglc measurements were compared with standard correlation analysis. The overall patterns of DTBZ-PET K1 and FDG-PET CMRglc deficits were assessed with stereotaxic surface projections (SSPs) of parametric images.

Results  The DTBZ-PET regional K1 and FDG-PET CMRglc measurements were highly correlated, both within and between subjects. The SSP maps of deficits in DTBZ-PET regional K1 and FDG-PET CMRglc measurements were markedly similar. The DTBZ-PET K1 SSP maps exhibited a mild decrease in sensitivity relative to FDG-PET CMRglc maps.

Conclusions  Both DTBZ-PET K1 and FDG-PET CMRglc measurements provide comparable information in assessment of regional cerebral metabolic deficits in mild dementia and MCI. Blood flow measures can assess regional cerebral metabolism deficits accurately in mild dementia and MCI. Blood flow assessments of regional cerebral metabolic deficits can be combined with tracer binding results to improve utility of PET imaging in mild dementia and MCI.

Figures in this Article

The present approach to diagnosis of dementia relies on clinical characterization, psychometric evaluation, and application of standardized clinical criteria.1 There is overlap in clinical criteria for the 3 major forms of degenerative dementia—Alzheimer disease (AD), Lewy body dementia (LBD), and the frontotemporal dementias (FTDs)—and clinical diagnosis has relatively poor specificity.15 Differentiation is particularly difficult in individuals with early, mild dementia. Positron emission tomography (PET) is a useful technique for evaluation of dementias. Fludeoxyglucose F18–PET (FDG-PET) assessment of the regional cerebral metabolic rate for glucose (CMRglc) is the most widely studied PET method for evaluation of dementias.68 Fludeoxyglucose F18–PET is useful in determining whether individuals have an underlying cerebral problem, differentiating types of dementia, identifying cerebral abnormalities in individuals with mild cognitive impairment (MCI), predicting the likelihood of progression from MCI, and predicting the rate of progression of dementia.926 Fludeoxyglucose F18–PET identifies characteristic patterns of regional cerebral metabolic changes in AD, LBD, FTDs, and vascular dementia.2737

Positron emission tomographic methods identifying characteristic pathologic features of dementias are being explored. Diminished dopaminergic nigrostriatal terminals are a feature of LBD.38,39 Single-site studies and a recent multicenter clinical trial indicate that PET or single-photon emission computed tomographic methods measuring nigrostriatal dopaminergic terminal density are useful in establishing a diagnosis of LBD.4042 Tracers binding to characteristic histopathologic features of dementias, such as the amyloid ligand 2-(4-methylaminophenyl) benzothiazole (Pittsburgh Compound B), may provide an in vivo analogue of histopathologic diagnosis.4352 Determining patterns of altered regional cerebral metabolism and abnormal retention of tracers aimed at characteristic pathologic features should provide complementary information. This can be accomplished by studying patients with FDG-PET and a second PET study using one of the nigrostriatal dopaminergic terminal ligands or [11C] Pittsburgh Compound B.53 This approach requires at least 2 scans with accompanying increased expense, radiation exposure, and demands on patients.

Regional cerebral metabolism and regional cerebral blood flow are tightly coupled.5456 Data analysis for some PET tracers allows determination of the regional cerebral tracer blood-to-brain transport rate (K1) as a measure of regional cerebral blood flow. We reported previously that assessment of regional cerebral K1 of the dopaminergic terminal ligand [11C]dihydrotetrabenazine (DTBZ) produced results closely comparable with measurement of CMRglc with FDG-PET.57 Our prior study was a retrospective analysis of subjects drawn from a well-characterized research cohort not representative of clinical practice. These subjects had moderate AD (mean Mini-Mental State Examination [MMSE] score = 15), LBD (mean MMSE score = 17), and FTD (mean MMSE score = 23), contrasting with subjects with early, mild dementia/MCI, in whom accurate clinical diagnosis is most difficult. To confirm the utility of K1 assessments, we report the comparison of FDG-PET assessment of CMRglc with measurements of DTBZ-PET K1 in a prospective series of representative subjects undergoing initial characterization of mild dementia and MCI.

SUBJECTS

Fifty subjects were recruited through the Michigan Alzheimer Disease Research Center as part of an ongoing project studying the utility of PET imaging in early dementia and MCI. Subjects were drawn from the Cognitive Disorders Clinic at the University of Michigan. Subjects were excluded if their MMSE score was lower than 18 or if they had a confounding neurologic or psychiatric disorder that prevented establishment of a clear diagnosis of dementia or MCI. Subjects were also excluded if clinical evaluation (including routine structural imaging) indicated a diagnosis of vascular dementia. While this is not a population-based cohort, subjects enrolled for this study are representative of patients seen for initial evaluation in tertiary referral cognitive disorders clinics. There is no overlap in subjects between those enrolled in this study and our prior study of DTBZ K1 and FDG-PET CMRglc.

All subjects underwent standardized clinical and psychometric evaluations. Clinical evaluations consisted of a history and standard neurologic examination performed by a neurologist experienced in evaluating dementias. All subjects underwent evaluation for treatable causes of dementia with recommended serum and structural imaging studies.1 Psychometric evaluation included the Alzheimer Disease Research Center Unified Data Set measures (Digit Span, Category Fluency, Trails Test, Digit Symbol, Wechsler Memory Scale–Revised Logical Memory Story A, 30-item Boston Naming Test, Geriatric Depression Scale, and Neuropsychiatric Inventory Questionnaire) plus additional standard measures of memory, executive function, attention, language, visuospatial function, mood, and anxiety. Clinical and psychometric data were abstracted into a standard form stripped of identifiers by 1 of the authors (J.F.B.). Standardized data forms were reviewed in a consensus conference by 3 authors (R.L.A., K.A.F., and B.G.) to assign a consensus diagnosis. Standard criteria were used to assign diagnoses of AD, LBD, and FTD.5860 For diagnosis of MCI, standard clinical and psychometric criteria were applied.61 Subjects with MCI were classified as having single-domain MCI (amnestic or nonamnestic) or multidomain MCI. All subjects underwent PET imaging within 3 months of initial evaluation. Scans of 80 age-matched, normal subjects studied previously in our center were used as control data (supplementary table at http://sitemaker.umich.edu/albinsuppldata).

PET IMAGING

All subjects underwent DTBZ- and FDG-PET either in the same imaging session or on consecutive days if they were not able to tolerate the 4-hour procedure. The DTBZ scans were performed on a Siemens ECAT Exact HR+ scanner (Siemens, Knoxville, Tennessee), while FDG scans were performed on a Siemens BioGraph Classic PET/CT scanner. Subjects were awake and supine in a quiet, dimly lit room with their eyes open. For DTBZ, a mean dose of 666 MBq (SD, 66 MBq [mean, 18 mCi; SD, 1.8 mCi]) of DTBZ was administered intravenously. An equilibrium protocol was used, infusing 55% of the dose for 30 seconds, followed by continuous infusion of the remaining 45% for 60 minutes.62 The FDG studies were performed as a single 20-minute scan acquired 30 minutes after intravenous injection of a mean dose of 296 MBq (SD, 29 MBq [mean, 8.0 mCi; SD, 0.8 mCi]) of FDG. All scans were acquired in 3-dimensional mode. Measured attenuation correction was performed using a 5-minute 2-dimensional transmission scan followed by segmentation and reprojection. Scatter correction was performed on all scans. After Fourier rebinning of the 3-dimensional projection sinograms into 2-dimensional data sets, images were reconstructed using ordered subset expectation maximization, with 4 iterations and 16 subsets with no additional smoothing, providing both in-plane and axial image resolution of approximately 5.5-mm full-width at half-maximum.

IMAGE PROCESSING AND DATA ANALYSIS

The single 20-minute FDG image acquired starting 30 minutes postinjection provided an index of CMRglc. For the DTBZ scan, the average of the first 4 minutes of uptake provided our index of ligand transport, K1. The PET images for both measures for each subject were reoriented to a common coordinate system based on the stereotactic atlas of Talairach and Tournoux.63 After reorientation, all images underwent linear scaling and nonlinear warping.64 A single transformation based on the individual's summed FDG and DTBZ K1 images was calculated for each subject and then applied to both image sets.

All transaxial levels of the Talairach and Tournoux atlas have been digitized, and a set of standardized cortical and subcortical volumes of interest (VOIs) was defined on the atlas images.57 A subset of 34 cortical VOIs (17 per hemisphere) was selected for analysis and applied automatically to all images for all subjects with mild dementia and MCI and the 15 control subjects for correlation analysis of DTBZ K1 and FDG CMRglc. This set of regions included cortical areas hypothesized to provide the best differentiation between groups. We expected frontal regions, particularly medial, to be affected more in FTD than AD or LBD and posterior parietal/posterior cingulate regions to be more affected in AD and LBD than FTD. We expected the occipital region to be more affected in LBD than AD or FTD and to be the region that best differentiates LBD from AD. Sensorimotor cortex was included as a cortical region likely to be least affected in these dementias. The FDG and DTBZ K1 images were normalized to the mean VOI value obtained from the pons and cerebellar vermis.65 These 2 regions were selected as the normalizing factor because they are structures known to be minimally involved in these disorders, enhancing the ability to detect regional cortical deficits by removal of the more variable global factor in these measures.

STATISTICAL ANALYSIS

Both within-subject and across-subject correlations were performed. Within-subject correlations were calculated for each of the 50 subjects with mild dementia or MCI and 15 controls who received both FDG and DTBZ scans. The VOI FDG CMRglc and DTBZ K1 normalized values were correlated for all 34 selected cortical regions. Across-subject correlations were calculated for each of the 34 regions separately for the 50 subjects with mild dementia or MCI and 15 controls.

STEREOTACTIC SURFACE PROJECTIONS

The use of stereotactic surface projections (SSPs) is a standard method for processing FDG CMRglc data to produce easily interpretable parametric images.66 In this voxel-based method, gray matter activity is projected to the cortical surface in an anatomically standardized manner. The resulting map of brain activity is compared with a database of appropriate matched subjects to generate a z-score map of deviations from normal. The z-score maps permit ready visual interpretation of CMRglc deficit patterns. We used the Neurostat program and a control database of the 27 FDG controls to generate z-score maps of FDG CMRglc deficits for all subjects. The SSP approach was also used for processing of DTBZ K1 images. We constructed a control database from 68 subjects of similar age without clinical evidence of any neurologic disease. These 68 individuals were studied previously in our center using the same scan protocol used in this project.

SUBJECTS

Fifty subjects with dementia or MCI participated. Their mean age was 70 years (SD, 10 years; range, 51-91 years; 28 women; 22 men). There were 19 subjects with AD, 5 with LBD, and 9 with FTD. Sixteen subjects were classified as having MCI, with 9 subjects with amnestic MCI, 4 with nonamnestic MCI, and 3 with multidomain MCI. One subject refused psychometric evaluation and was classified as indeterminate. Of the 80 control subjects scanned, 27 received FDG (mean age, 71 years; SD, 9 years; range 55-88 years; 13 women, 14 men), and 68 received DTBZ (mean age, 68 years; SD, 8 years; range, 55-86 years; 38 women; 37 men). Fifteen control subjects received both FDG and DTBZ scans (mean age, 70 years; SD, 9 years; range 55-86 years; 8 women; 7 men).

FDG CMRglc AND DTBZ K1 CORRELATION ANALYSIS

There was excellent correspondence between regional cerebral metabolism assessed with FDG and regional cerebral blood flow assessed with DTBZ K1. Regional deficits averaged across all subjects with mild dementia or MCI, reported as percentage of the control mean, were similar for the 2 PET measures in most regions examined (Figure 1). Frontal cortical regions did exhibit slightly greater deficits in FDG than in DTBZ K1, reaching significance both laterally and medially. In other regions, both the magnitude of the declines and the variability across patients were comparable. Individual within-subject correlations between normalized FDG and DTBZ K1 (across the regions examined; left and right hemisphere for the 17 regions shown in Figure 2) averaged 0.88 (SD, 0.07) for the 50 subjects with mild dementia or MCI (range, 0.73-0.96; Figure 2). Within-subject correlations for controls were lower owing to the smaller range of values, averaging 0.78 (SD, 0.08; range 0.64-0.88). Besides the similarity in image pattern between the measures, the magnitude of the deficits correlated highly. Within-subject correlations of the z scores relative to controls averaged 0.74 (SD, 0.14; range, 0.37-0.96; supplementary figure 1 at http://sitemaker.umich.edu/albinsuppldata). Z-score correlations for controls averaged 0.54 (SD, 0.25; range, 0.05-0.82). The much broader range of z-score correlations is due to the nature of the z-score measure. Control and subjects with mild dementia or MCT who have image patterns similar to the normal mean pattern will have low correlations owing to the limited range of data values.

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Figure 1.

Regional metabolic and perfusion deficits in 50 subjects with dementia or mild cognitive impairment. Magnitudes of the deficits observed by either fludeoxyglucose F18 (FDG) regional cerebral glucose uptake (CMRglc) or [11C]dihydrotetrabenazine (DTBZ) blood-to-brain transport rate (K1) vary similarly across regions. Error bars represent 1 SD of the percent of normal mean for all subjects with mild dementia and mild cognitive impairment. SMC indicates sensorimotor cortex.

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Figure 2.

Within-subject correlations. Representative within-subject correlations (across the 34 regions examined) between fludeoxyglucose F18 (FDG) and [11C]dihydrotetrabenazine (DTBZ) blood-to-brain transport rate (K1) for an individual subject with Alzheimer disease (AD), 1 with frontotemporal dementia (FTD), and 1 control subject. The FDG and DTBZ K1 values are each normalized to the average of the pons and cerebellar vermis. Each data point represents the normalized K1 and FDG values for 1 of the 34 regions.

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Across-subject correlations between FDG and DTBZ K1 varied considerably across the regions examined. Correlations across the 34 regions average 0.78 (SD, 0.14; range, 0.51-0.94) in subjects with mild dementia or MCI and 0.76 (SD, 0.13; range, 0.48-0.91) in controls. Correlations across the patient-subjects were uniformly high (r > 0.83) in cortical regions that show deficits in these patient groups (parietal, frontal cortex, and posterior cingulate), while correlations in regions not primarily involved in disease (subcortical structures) were typically much lower. Correlations for a highly affected region, the parietal cortex, are seen in Figure 3.

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Figure 3.

Across-subject correlations of z scores for the parietal cortex. Across-subject correlations of z scores between fludeoxyglucose F18 (FDG) regional cerebral glucose uptake and [11C]dihydrotetrabenazine (DTBZ) blood-to-brain transport rate (K1) in the parietal cortex for subjects with dementia or mild cognitive impairment and controls. Each data point represents the z score from normalized K1 and FDG values for a single subject.

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SSP ANALYSIS

Stereotaxic surface projection analysis was applied to FDG CMRglc and DTBZ K1 images for each subject as described above. The resulting z-score maps were compared for qualitative similarity. The FDG and DTBZ K1z-score maps were similar for all patients, regardless of diagnosis (Figure 4). In general, DTBZ K1z-score maps tended to identify a smaller number of abnormal surface map pixels. This is due primarily to the slightly higher noise at the pixel level of DTBZ K1 images than FDG images. For all surface pixels, the coefficient of variation of DTBZ K1 control subjects averaged 10.4%; that of FDG was 9.6%. In all cases, however, DTBZ K1z-score maps were readily identifiable as abnormal and qualitatively identical to FDG-PET CMRglcz-score maps. The number of surface map pixels found to be abnormal (more than 2.5 SDs below the normal mean) in the most affected regions was higher for FDG than DTBZ K1 (Figure 5). The total surface map pixels in the most affected areas (posterior cingulate, lateral parietal, lateral temporal, and lateral and medial frontal areas) was 8920 (supplementary figure 2 at http://sitemaker.umich.edu/albinsuppldata). In the most severe patients, more than half the surface pixels have z-score deficits of greater than 2.5. The regression line of DTBZ K1 on FDG shows a slope of less than unity (0.863), indicating fewer significant pixels for DTBZ. Many of the pixels found to be significant in FDG but not DTBZ K1 are located in the frontal cortex.

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Figure 4.

Stereotaxic surface projection images. Stereotaxic surface projection images of z scores of fludeoxyglucose F18 (FDG) regional cerebral glucose uptake and [11C]dihydrotetrabenazine (DTBZ) blood-to-brain transport rate (K1) deviations relative to control data sets for 6 representative subjects with dementia or mild cognitive impairment. Each data set is scaled to show a range of deficits from 0.0 to 5.0 SDs below the control mean. The patterns of deviation from normal are markedly similar. L indicates left; Lat, lateral; Med, medial; and R, right.

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Figure 5.

Extent of deficits in an affected cortex. Number of stereotaxic surface projection map pixels in an affected cortex with greater than a 2.5-SD decrease from normal control. Each point on the plot represents 1 of the 50 subjects with dementia or mild cognitive impairment (see supplementary figure 2 for description of affected cortex). DTBZ indicates [11C]dihydrotetrabenazine; FDG, fludeoxyglucose F18; and K1, blood-to-brain transport rate.

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Our results indicate similar properties of FDG-PET assessment of CMRglc and DTBZ-PET K1 assessment of regional cerebral blood flow to identify regional cerebral metabolic deficits in subjects with MCI and early, mild dementia. Regional cerebral metabolic deficits are characteristic of dementias and specific patterns of deficits are associated with each major form of degenerative dementia.615,2735 We did find that DTBZ K1 assessments tended to be somewhat less sensitive in SSP analysis because of higher variation in surface pixel values. This was most noticeable in frontal regions. This could reduce sensitivity of DTBZ K1 assessments in FTDs and related disorders.

Differentiation of dementias, based on clinical criteria and using structural imaging and laboratory studies to exclude other causes of dementia, has relatively poor specificity.1 Fludeoxyglucose F18–PET is suggested to improve diagnosis of dementias and may be cost-effective in evaluating patients with early, mild dementia.6769 Recent work demonstrates that FDG-PET with SSP analysis differentiates early dementia and controls in a clinically representative population of early dementia and MCI.70 The gold standard for diagnosis of dementias remains histopathologic evaluation. Small series with FDG-PET evaluations followed by histopathologic analysis indicate that FDG-PET evaluation significantly improves specificity without sacrificing sensitivity.8,9,29,71 These results are consistent with studies in which FDG-PET results were compared with systematic, longitudinal clinical evaluations.67 Differentiation of dementias at initial evaluation is particularly difficult. Jagust et al67 found that initial clinical evaluation of a series of mildly demented patients who were followed up to autopsy had relatively poor sensitivity (76%) and specificity (56%) for diagnosis of pathologically confirmed AD, and that diagnostic precision improved significantly with addition of FDG-PET imaging data. Diagnostic sensitivity and specificity of FDG-PET evaluation was comparable with clinical evaluation after several years of follow-up.

While characteristic metabolic deficits occur in many individuals with dementia, confounding features can reduce accuracy of FDG-PET. There is considerable overlap between AD and LBD. Not all individuals with LBD exhibit the typical visual cortex abnormalities; the sensitivity and specificity of FDG-PET for differentiating AD and LBD are not significantly better than application of clinical criteria.2,30 Pathologic studies indicate that a high percentage of individuals with focal cortical syndromes typical of FTDs exhibit AD pathology.72 These AD focal cortical syndromes are likely to be classified as FTDs by both clinical criteria and FDG-PET criteria.49,73 Positron emission tomography tracers aimed at characteristic pathologic features of dementias are likely to be useful in overcoming the limitations of FDG-PET. Positron emission tomography and single-photon emission tomography ligands identifying the characteristic nigrostriatal dopaminergic deficit of LBD improve differentiation of AD and LBD. Similarly, [11C]Pittsburgh Compound B is likely to be useful in identifying dementias characterized by substantial β amyloid deposition, such as AD and cases of LBD with substantial fibrillary amyloid burden.

Ligand-binding results and assessment of regional cerebral metabolic deficits may be complementary. [11C]Dihydrotetrabenazine–PET studies, for example, could identify nigrostriatal dopaminergic deficits in both LBD and some cases of FTDs.74 The pattern of regional cerebral metabolic deficits would be useful in differentiating these different syndromes. [11C]Dihydrotetrabenazine itself is not likely to become a clinically used ligand, but fluorinated DTBZ analogues or another tracer quantifying nigrostriatal terminal density may become available for clinical use. Obtaining both ligand binding and regional cerebral metabolic deficit data from a single PET study will be advantageous in terms of cost, safety, and patient convenience. Positron emission tomography ligands with high brain-to-blood extraction fractions yield K1 parametric image data comparable with those obtained with FDG-PET, and K1 parametric image data can be represented in SSP maps. Use of K1 parametric image data from PET ligands aimed at characteristic pathologic features of dementias is likely to enhance the clinical utility of PET methods for characterization of MCI and early, mild dementias.

Correspondence: Roger L. Albin, MD, University of Michigan, 5023 BSRB, 109 Zina Pitcher Pl, Ann Arbor, MI 48109-2200 (ralbin@umich.edu).

Accepted for Publication: September 14, 2009.

Author Contributions: Dr Albin had full access to all of the data in the study and takes full responsibility for data integrity and data analysis. Study concept and design: Albin, Giordani, Gilman, and Frey. Acquisition of data: Albin, Koeppe, Giordani, and Gilman. Analysis and interpretation of data: Albin, Koeppe, Burke, Giordani, Kilbourn, Gilman, and Frey. Drafting of the manuscript: Albin, Koeppe, Giordani, Kilbourn, and Frey. Critical revision of the manuscript for important intellectual content: Albin, Koeppe, Burke, Giordani, Gilman, and Frey. Statistical analysis: Koeppe and Burke. Obtained funding: Albin, Gilman, and Frey. Administrative, technical, and material support: Burke, Giordani, Kilbourn, Gilman, and Frey. Study supervision: Albin and Gilman.

Financial Disclosure: None reported.

Funding/Support: This study was supported by grants AG08671 and NS15655 from the National Institutes of Health.

Role of the Sponsors: The sponsors had no role in data collection, analysis, interpretation, or manuscript preparation.

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PubMed
Ishii  KSakamoto  SSasaki  M  et al.  Cerebral glucose metabolism in patients with frontotemporal dementia. J Nucl Med 1998;39 (11) 1875- 1878
PubMed
Jeong  YCho  SSPark  JM  et al.  18F-FDG PET findings in frontotemporal dementia: an SPM analysis of 29 patients. J Nucl Med 2005;46 (2) 233- 239
PubMed
Tullberg  MFletcher  EDeCarli  C  et al.  White matter lesions impair frontal lobe function regardless of their location. Neurology 2004;63 (2) 246- 253
PubMed
Kerrouche  NHerholz  KMielke  RHolthoff  VBaron  JC 18FDG PET in vascular dementia: differentiation from Alzheimer's disease using voxel-based multivariate analysis. J Cereb Blood Flow Metab 2006;26 (9) 1213- 1221
PubMed
Piggott  MAMarshall  EFThomas  N  et al.  Striatal dopaminergic markers in dementia with Lewy bodies, Alzheimer's and Parkinson's diseases: rostrocaudal distribution. Brain 1999;122 (pt 8) 1449- 1468
PubMed
Suzuki  MDesmond  TJAlbin  RLFrey  KA Striatal monoaminergic terminals in Lewy body and Alzheimer's dementias. Ann Neurol 2002;51 (6) 767- 771
PubMed
Walker  ZCosta  DCWalker  RW  et al.  Differentiation of dementia with Lewy bodies from Alzheimer's disease using a dopaminergic presynaptic ligand. J Neurol Neurosurg Psychiatry 2002;73 (2) 134- 140
PubMed
Gilman  SKoeppe  RALittle  R  et al.  Striatal monoamine terminals in Lewy body dementia and Alzheimer's disease. Ann Neurol 2004;55 (6) 774- 780
PubMed
McKeith  IO'Brien  JWalker  Z  et al. DLB Study Group, Sensitivity and specificity of dopamine transporter imaging with 123I-FP-CIT SPECT in dementia with Lewy bodies: a phase III, multicentre study. Lancet Neurol 2007;6 (4) 305- 313
PubMed
Klunk  WEEngler  HNordberg  A  et al.  Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound-B. Ann Neurol 2004;55 (3) 306- 319
PubMed
Villemagne  VLFodero-Tavoletti  MTPike  KECappai  RMasters  CLRowe  CC The ART of loss: Aβ imaging in the evaluation of Alzheimer's disease and other dementias. Mol Neurobiol 2008;38 (1) 1- 15
PubMed
Verhoeff  NPWilson  AATakeshita  S  et al.  In-vivo imaging of Alzheimer disease beta-amyloid with [11C]SB-13 PET. Am J Geriatr Psychiatry 2004;12 (6) 584- 595
PubMed
Rowe  CCNg  SAckermann  U  et al.  Imaging beta-amyloid burden in aging and dementia. Neurology 2007;68 (20) 1718- 1725
PubMed
Price  JCKlunk  WELopresti  BJ  et al.  Kinetic modeling of amyloid binding in humans using PET imaging and Pittsburgh Compound-B. J Cereb Blood Flow Metab 2005;25 (11) 1528- 1547
PubMed
Buckner  RLSnyder  AZShannon  BJ  et al.  Molecular, structural, and functional characterization of Alzheimer's disease: evidence for a relationship between default activity, amyloid, and memory. J Neurosci 2005;25 (34) 7709- 7717
PubMed
Rabinovici  GDFurst  AJO’Neil  JP  et al.  11C-PIB PET imaging in Alzheimer disease and frontotemporal lobar degeneration. Neurology 2007;68 (15) 1205- 1212
PubMed
Engler  HSantillo  AFWang  SX  et al.  In vivo amyloid imaging with PET in frontotemporal dementia. Eur J Nucl Med Mol Imaging 2008;35 (1) 100- 106
PubMed
Drzezga  AGrimmer  THenriksen  G  et al.  Imaging of amyloid plaques ad cerebral glucose metabolism in semantic dementia and Alzheimer's disease. Neuroimage 2008;39 (2) 619- 633
PubMed
Gomperts  SNRentz  DMMoran  E  et al.  Imaging amyloid deposition in Lewy body diseases. Neurology 2008;71 (12) 903- 910
PubMed
Li  YRinne  JOMosconi  L  et al.  Regional analysis of FDG and PIB-PET images in normal aging, mild cognitive impairment, and Alzheimer's disease. Eur J Nucl Med Mol Imaging 2008;35 (12) 2169- 2181
PubMed
Roy  CSSherrington  CS On the regulation of the blood supply of the brain. J Physiol 1890;11 (1-2) 85- 158, 17
PubMed
Sokoloff  L Relationships among local functional activity, energy metabolism, and blood flow in the central nervous system. Fed Proc 1981;40 (8) 2311- 2316
PubMed
Raichle  MEMintun  MA Brain work and brain imaging. Annu Rev Neurosci 2006;29449- 476
PubMed
Koeppe  RAGilman  SJoshi  A  et al.  [11C]DTBZ and [18F]FDG PET measures in differentiating dementias. J Nucl Med 2005;46 (6) 936- 944
PubMed
McKhann  GDrachman  DFolstein  MKatzman  RPrice  DStadlan  EM Clinical diagnosis of Alzheimer disease: report of 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
McKeith  IGDickson  DWLowe  J  et al. Consortium on DLB, Diagnosis and management of dementia with Lewy bodies: third report of the DLB consortium. Neurology 2005;65 (12) 1863- 1872
PubMed
Neary  DSnowden  JSGustafson  L  et al.  Frontotemporal lobar degeneration: a consensus on clinical diagnostic criteria. Neurology 1998;51 (6) 1546- 1554
PubMed
Petersen  RC Mild cognitive impairment as a diagnostic entity. J Intern Med 2004;256 (3) 183- 194
PubMed
Koeppe  RAFrey  KAKume  AAlbin  RKilbourn  MRKuhl  DE Equilibrium versus compartmental analysis for assessment of the vesicular monoamine transporter using (+)-alpha-[11C]dihydrotetrabenazine (DTBZ) and positron emission tomography. J Cereb Blood Flow Metab 1997;17 (9) 919- 931
PubMed
Talariach  JTournoux  P Co-Planar Stereotaxic Atlas of the Human Brain: 3-D Proportional System—An Approach to Cerebral Imaging.  New York, NY Thieme Medical Publishers1988;
Minoshima  SKoeppe  RAFrey  KAKuhl  DE Anatomic standardization: linear scaling and nonlinear warping of functional brain images. J Nucl Med 1994;35 (9) 1528- 1537
PubMed
Minoshima  SFrey  KAFoster  NLKuhl  DE Preserved pontine glucose metabolism in Alzheimer disease: a reference region for functional brain image (PET) analysis. J Comput Assist Tomogr 1995;19 (4) 541- 547
PubMed
Minoshima  SFrey  KAKoeppe  RAFoster  NLKuhl  DE A diagnostic approach in Alzheimer's disease using three-dimensional stereotactic surface projections of fluorine-18-FDG PET. J Nucl Med 1995;36 (7) 1238- 1248
PubMed
Jagust  WReed  BMungas  DEllis  WDecarli  C What does fluorodeoxyglucose PET imaging add to a clinical diagnosis of dementia? Neurology 2007;69 (9) 871- 877
PubMed
Silverman  DHS Brain 18F-FDG PET in the diagnosis of neurodegenerative dementias: comparison with perfusion SPECT and with clinical evaluations lacking nuclear imaging. J Nucl Med 2004;45 (4) 594- 607
PubMed
Silverman  DHGambhir  SSHuang  HW  et al.  Evaluating early dementia with and without assessment of regional cerebral metabolism by PET: a comparison of predicted costs and benefits. J Nucl Med 2002;43 (2) 253- 266
PubMed
Mosconi  LTsui  WHHerholz  K  et al.  Multicenter, standardized 18F-FDG PET diagnosis of mild cognitive impairment, Alzheimer's disease, and other dementias. J Nucl Med 2008;49 (3) 390- 398
PubMed
Hoffman  JMWelsh-Bohmer  KAHanson  M  et al.  FDG PET imaging in patients with pathologically verified dementia. J Nucl Med 2000;41 (11) 1920- 1928
PubMed
Alladi  SXuereb  JBak  T  et al.  Focal cortical presentations of Alzheimer's disease. Brain 2007;130 (pt 10) 2636- 2645
PubMed
Rabinovici  GDJagust  WJFurst  AJ  et al.  Aβ amyloid and glucose metabolism in three variants of primary progressive aphasia. Ann Neurol 2008;64 (4) 388- 401
PubMed
Rinne  JOLaine  MKaasinen  VNorvasuo-Heilä  MKNågren  KHelenius  H Striatal dopamine transporter and extrapyramidal symptoms in frontotemporal dementia. Neurology 2002;58 (10) 1489- 1493
PubMed

Figures

Place holder to copy figure label and caption
Figure 1.

Regional metabolic and perfusion deficits in 50 subjects with dementia or mild cognitive impairment. Magnitudes of the deficits observed by either fludeoxyglucose F18 (FDG) regional cerebral glucose uptake (CMRglc) or [11C]dihydrotetrabenazine (DTBZ) blood-to-brain transport rate (K1) vary similarly across regions. Error bars represent 1 SD of the percent of normal mean for all subjects with mild dementia and mild cognitive impairment. SMC indicates sensorimotor cortex.

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

Within-subject correlations. Representative within-subject correlations (across the 34 regions examined) between fludeoxyglucose F18 (FDG) and [11C]dihydrotetrabenazine (DTBZ) blood-to-brain transport rate (K1) for an individual subject with Alzheimer disease (AD), 1 with frontotemporal dementia (FTD), and 1 control subject. The FDG and DTBZ K1 values are each normalized to the average of the pons and cerebellar vermis. Each data point represents the normalized K1 and FDG values for 1 of the 34 regions.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 3.

Across-subject correlations of z scores for the parietal cortex. Across-subject correlations of z scores between fludeoxyglucose F18 (FDG) regional cerebral glucose uptake and [11C]dihydrotetrabenazine (DTBZ) blood-to-brain transport rate (K1) in the parietal cortex for subjects with dementia or mild cognitive impairment and controls. Each data point represents the z score from normalized K1 and FDG values for a single subject.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 4.

Stereotaxic surface projection images. Stereotaxic surface projection images of z scores of fludeoxyglucose F18 (FDG) regional cerebral glucose uptake and [11C]dihydrotetrabenazine (DTBZ) blood-to-brain transport rate (K1) deviations relative to control data sets for 6 representative subjects with dementia or mild cognitive impairment. Each data set is scaled to show a range of deficits from 0.0 to 5.0 SDs below the control mean. The patterns of deviation from normal are markedly similar. L indicates left; Lat, lateral; Med, medial; and R, right.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 5.

Extent of deficits in an affected cortex. Number of stereotaxic surface projection map pixels in an affected cortex with greater than a 2.5-SD decrease from normal control. Each point on the plot represents 1 of the 50 subjects with dementia or mild cognitive impairment (see supplementary figure 2 for description of affected cortex). DTBZ indicates [11C]dihydrotetrabenazine; FDG, fludeoxyglucose F18; and K1, blood-to-brain transport rate.

Graphic Jump Location

Tables

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Minoshima  SFoster  NLSima  AAFFrey  KAAlbin  RLKuhl  DE Alzheimer's disease versus dementia with Lewy bodies: cerebral metabolic distinction with autopsy confirmation. Ann Neurol 2001;50 (3) 358- 365
PubMed
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PubMed
Salmon  EGarraux  GDelbeuck  X  et al.  Predominant ventromedial frontopolar metabolic impairment in frontotemporal dementia. Neuroimage 2003;20 (1) 435- 440
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Diehl-Schmid  JGrimmer  TDrzezga  A  et al.  Decline of cerebral glucose metabolism in frontotemporal dementia: a longitudinal 18F-FDG-PET-study. Neurobiol Aging 2007;28 (1) 42- 50
PubMed
Foster  NLHeidebrink  JLClark  CM  et al.  FDG-PET improve accuracy in distinguishing frontotemporal dementia and Alzheimer's disease. Brain 2007;130 (pt 10) 2616- 2635
PubMed
Ishii  KSakamoto  SSasaki  M  et al.  Cerebral glucose metabolism in patients with frontotemporal dementia. J Nucl Med 1998;39 (11) 1875- 1878
PubMed
Jeong  YCho  SSPark  JM  et al.  18F-FDG PET findings in frontotemporal dementia: an SPM analysis of 29 patients. J Nucl Med 2005;46 (2) 233- 239
PubMed
Tullberg  MFletcher  EDeCarli  C  et al.  White matter lesions impair frontal lobe function regardless of their location. Neurology 2004;63 (2) 246- 253
PubMed
Kerrouche  NHerholz  KMielke  RHolthoff  VBaron  JC 18FDG PET in vascular dementia: differentiation from Alzheimer's disease using voxel-based multivariate analysis. J Cereb Blood Flow Metab 2006;26 (9) 1213- 1221
PubMed
Piggott  MAMarshall  EFThomas  N  et al.  Striatal dopaminergic markers in dementia with Lewy bodies, Alzheimer's and Parkinson's diseases: rostrocaudal distribution. Brain 1999;122 (pt 8) 1449- 1468
PubMed
Suzuki  MDesmond  TJAlbin  RLFrey  KA Striatal monoaminergic terminals in Lewy body and Alzheimer's dementias. Ann Neurol 2002;51 (6) 767- 771
PubMed
Walker  ZCosta  DCWalker  RW  et al.  Differentiation of dementia with Lewy bodies from Alzheimer's disease using a dopaminergic presynaptic ligand. J Neurol Neurosurg Psychiatry 2002;73 (2) 134- 140
PubMed
Gilman  SKoeppe  RALittle  R  et al.  Striatal monoamine terminals in Lewy body dementia and Alzheimer's disease. Ann Neurol 2004;55 (6) 774- 780
PubMed
McKeith  IO'Brien  JWalker  Z  et al. DLB Study Group, Sensitivity and specificity of dopamine transporter imaging with 123I-FP-CIT SPECT in dementia with Lewy bodies: a phase III, multicentre study. Lancet Neurol 2007;6 (4) 305- 313
PubMed
Klunk  WEEngler  HNordberg  A  et al.  Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound-B. Ann Neurol 2004;55 (3) 306- 319
PubMed
Villemagne  VLFodero-Tavoletti  MTPike  KECappai  RMasters  CLRowe  CC The ART of loss: Aβ imaging in the evaluation of Alzheimer's disease and other dementias. Mol Neurobiol 2008;38 (1) 1- 15
PubMed
Verhoeff  NPWilson  AATakeshita  S  et al.  In-vivo imaging of Alzheimer disease beta-amyloid with [11C]SB-13 PET. Am J Geriatr Psychiatry 2004;12 (6) 584- 595
PubMed
Rowe  CCNg  SAckermann  U  et al.  Imaging beta-amyloid burden in aging and dementia. Neurology 2007;68 (20) 1718- 1725
PubMed
Price  JCKlunk  WELopresti  BJ  et al.  Kinetic modeling of amyloid binding in humans using PET imaging and Pittsburgh Compound-B. J Cereb Blood Flow Metab 2005;25 (11) 1528- 1547
PubMed
Buckner  RLSnyder  AZShannon  BJ  et al.  Molecular, structural, and functional characterization of Alzheimer's disease: evidence for a relationship between default activity, amyloid, and memory. J Neurosci 2005;25 (34) 7709- 7717
PubMed
Rabinovici  GDFurst  AJO’Neil  JP  et al.  11C-PIB PET imaging in Alzheimer disease and frontotemporal lobar degeneration. Neurology 2007;68 (15) 1205- 1212
PubMed
Engler  HSantillo  AFWang  SX  et al.  In vivo amyloid imaging with PET in frontotemporal dementia. Eur J Nucl Med Mol Imaging 2008;35 (1) 100- 106
PubMed
Drzezga  AGrimmer  THenriksen  G  et al.  Imaging of amyloid plaques ad cerebral glucose metabolism in semantic dementia and Alzheimer's disease. Neuroimage 2008;39 (2) 619- 633
PubMed
Gomperts  SNRentz  DMMoran  E  et al.  Imaging amyloid deposition in Lewy body diseases. Neurology 2008;71 (12) 903- 910
PubMed
Li  YRinne  JOMosconi  L  et al.  Regional analysis of FDG and PIB-PET images in normal aging, mild cognitive impairment, and Alzheimer's disease. Eur J Nucl Med Mol Imaging 2008;35 (12) 2169- 2181
PubMed
Roy  CSSherrington  CS On the regulation of the blood supply of the brain. J Physiol 1890;11 (1-2) 85- 158, 17
PubMed
Sokoloff  L Relationships among local functional activity, energy metabolism, and blood flow in the central nervous system. Fed Proc 1981;40 (8) 2311- 2316
PubMed
Raichle  MEMintun  MA Brain work and brain imaging. Annu Rev Neurosci 2006;29449- 476
PubMed
Koeppe  RAGilman  SJoshi  A  et al.  [11C]DTBZ and [18F]FDG PET measures in differentiating dementias. J Nucl Med 2005;46 (6) 936- 944
PubMed
McKhann  GDrachman  DFolstein  MKatzman  RPrice  DStadlan  EM Clinical diagnosis of Alzheimer disease: report of 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
McKeith  IGDickson  DWLowe  J  et al. Consortium on DLB, Diagnosis and management of dementia with Lewy bodies: third report of the DLB consortium. Neurology 2005;65 (12) 1863- 1872
PubMed
Neary  DSnowden  JSGustafson  L  et al.  Frontotemporal lobar degeneration: a consensus on clinical diagnostic criteria. Neurology 1998;51 (6) 1546- 1554
PubMed
Petersen  RC Mild cognitive impairment as a diagnostic entity. J Intern Med 2004;256 (3) 183- 194
PubMed
Koeppe  RAFrey  KAKume  AAlbin  RKilbourn  MRKuhl  DE Equilibrium versus compartmental analysis for assessment of the vesicular monoamine transporter using (+)-alpha-[11C]dihydrotetrabenazine (DTBZ) and positron emission tomography. J Cereb Blood Flow Metab 1997;17 (9) 919- 931
PubMed
Talariach  JTournoux  P Co-Planar Stereotaxic Atlas of the Human Brain: 3-D Proportional System—An Approach to Cerebral Imaging.  New York, NY Thieme Medical Publishers1988;
Minoshima  SKoeppe  RAFrey  KAKuhl  DE Anatomic standardization: linear scaling and nonlinear warping of functional brain images. J Nucl Med 1994;35 (9) 1528- 1537
PubMed
Minoshima  SFrey  KAFoster  NLKuhl  DE Preserved pontine glucose metabolism in Alzheimer disease: a reference region for functional brain image (PET) analysis. J Comput Assist Tomogr 1995;19 (4) 541- 547
PubMed
Minoshima  SFrey  KAKoeppe  RAFoster  NLKuhl  DE A diagnostic approach in Alzheimer's disease using three-dimensional stereotactic surface projections of fluorine-18-FDG PET. J Nucl Med 1995;36 (7) 1238- 1248
PubMed
Jagust  WReed  BMungas  DEllis  WDecarli  C What does fluorodeoxyglucose PET imaging add to a clinical diagnosis of dementia? Neurology 2007;69 (9) 871- 877
PubMed
Silverman  DHS Brain 18F-FDG PET in the diagnosis of neurodegenerative dementias: comparison with perfusion SPECT and with clinical evaluations lacking nuclear imaging. J Nucl Med 2004;45 (4) 594- 607
PubMed
Silverman  DHGambhir  SSHuang  HW  et al.  Evaluating early dementia with and without assessment of regional cerebral metabolism by PET: a comparison of predicted costs and benefits. J Nucl Med 2002;43 (2) 253- 266
PubMed
Mosconi  LTsui  WHHerholz  K  et al.  Multicenter, standardized 18F-FDG PET diagnosis of mild cognitive impairment, Alzheimer's disease, and other dementias. J Nucl Med 2008;49 (3) 390- 398
PubMed
Hoffman  JMWelsh-Bohmer  KAHanson  M  et al.  FDG PET imaging in patients with pathologically verified dementia. J Nucl Med 2000;41 (11) 1920- 1928
PubMed
Alladi  SXuereb  JBak  T  et al.  Focal cortical presentations of Alzheimer's disease. Brain 2007;130 (pt 10) 2636- 2645
PubMed
Rabinovici  GDJagust  WJFurst  AJ  et al.  Aβ amyloid and glucose metabolism in three variants of primary progressive aphasia. Ann Neurol 2008;64 (4) 388- 401
PubMed
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PubMed

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The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
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