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National Cancer Institute, Bethesda, Maryland; Joseph and Kathleen Bryan Alzheimer's Disease Research Center, Duke University, Durham; Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham; Department of Radiology, Duke University Medical Center, Durham, North Carolina; Department of Pathology, Johns Hopkins University, Baltimore, Maryland; and Department of Pathology, Duke University Medical Center, Durham, North Carolina
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONREFERENCES |
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Key Words: dementia • FDG PET • Alzheimer's disease
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONREFERENCES |
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A basic deficiency with the functional imaging studies that have been performed to date has been the lack of pathologic confirmation of functional imaging diagnoses. In most published studies, the presumed diagnosis obtained from clinical criteria has been used to determine sensitivity, specificity, and diagnostic accuracy for the functional imaging study. The clinical diagnosis has rarely been confirmed by pathology. Particular patterns of resting-state hypoperfusion or hypometabolism have been described in numerous dementia syndromes as characteristic for that particular disorder. However, there are overlap and variability in these patterns. Pathologic verification of the diagnosis for the determination of sensitivity, specificity, and diagnostic accuracy of the various metabolic and perfusion patterns has not been available.
Because resting-state FDG PET studies are being used increasingly in the clinical evaluation and differentiation of dementia syndromes and diagnosis of AD (1,2,4), verification of the classic findings of temporo-parietal hypometabolism with pathologic confirmation of diagnosis is extremely important. At present, only a few cases have been reported correlating pathologic and FDG PET metabolic findings (8,16–24). In these cases, however, there is excellent agreement between histologic diagnosis of AD and the metabolic finding of temporo-parietal hypometabolism. The majority of resting-state FDG PET studies describing temporo-parietal hypometabolism have relied on the clinical diagnosis of probable AD as defined by National Institute of Neurological and Communicative Disorders and Stroke/Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) criteria (25). However, there is obvious potential for discrepancy if pathologic verification is never obtained. This study was designed to answer specific questions regarding the accuracy of both clinical evaluation and resting-state FDG PET metabolic patterns in pathologically verified dementia.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONREFERENCES |
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All FDG PET brain scans were performed on the ECAT III (CTI, Knoxville, TN) or the GE 4096 Plus tomograph (GE Medical Systems, Milwaukee, WI) using standard techniques. We administered 370 MBq (10 mCi) FDG followed by a 40-min uptake period during which the patient remained quiet in a dimly lit room. Transaxial imaging of the entire intracranial contents was obtained. The images were filtered and reconstructed using standard techniques.
The FDG PET images were displayed on film and graded for the confidence of the classic pattern of bilateral temporo-parietal hypometabolism. This grading scheme has been described and validated previously (27). The grading scale was as follows: 0 = definitely normal; 1 = probably normal; 2 = definitely abnormal with varying degree of bilateral temporo-parietal hypometabolism; 3 = classic bilateral temporo-parietal hypometabolism; and 4 = abnormal but not AD pattern (including frontal, focal, or only unilateral hypometabolism). For the purposes of statistical analysis, grades 2 and 3 FDG PET interpretations were grouped together as being metabolically diagnostic of AD. The standard CERAD battery of neuropsychologic tests (26,28,29) was obtained, and on the basis of this specific information and NINCDS-ADRDA criteria (25), the best clinical diagnosis at the time of the FDG PET study was noted.
The standard CERAD criteria for pathologic determination of AD were used in this particular study (30). These criteria have been evaluated and optimized for diagnostic accuracy in numerous multicenter studies to date.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONREFERENCES |
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A significant finding in our study was that in only 2 patients (nos. 16 and 19; Table 1) was the PET scan interpreted as abnormal but not indicative of AD when in reality the patient did have AD. In 1 case (no. 16; Table 1), coexisting PSP was present. Only patient 19's FDG PET scan (Table 1) was interpreted as abnormal but not consistent with AD when in fact the final pathologic diagnosis was AD only. In 2 patients, the PET was interpreted as AD when the pathologic diagnosis was not AD (nos. 2 and 18; Table 1); 1 was a case of Creutzfeldt-Jacob disease, which can have a metabolic pattern similar to AD (31–33) (Fig. 2) but is seldom confused with AD clinically, and the other was a case of Lewy body disease.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONREFERENCES |
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There are few previous studies examining FDG PET metabolic results or SPECT perfusion results in dementia with histologic confirmation of diagnosis. The first reports of histologic verification of AD in patients studied with PET were by Friedman et al. (16) and McGeer et al. (17). The patient described by McGeer et al. (17) had pathologically verified AD, with the most prominent pathologic findings in the right occipital, left frontal, and left parietal areas. The FDG PET study showed reduction of FDG uptake in the left frontal, left parietal, left temporal, and right parietal areas. In another study, McGeer et al. (17) described a single patient with histologically verified AD who had a PET scan (18).
In 1990, McGeer et al. (19) described 2 individuals, ages 45 and 68 y, in whom FDG PET scans were obtained that correlated with histologically verified AD. The authors did not give specific information about the histology or the FDG PET results in these 2 patients. However, they did state that a general pattern of metabolic deficits very close to the pattern of neuronal loss and plaque and tangle formation was seen in the autopsied brains. The authors further commented that they found strong correlation between regional metabolic deficits and cortical neuronal loss. McGeer et al. (20) also published the results of a study involving 9 patients with dementia and pathologic verification, including 6 patients with AD, 2 with Huntington's disease, and 1 with Parkinson's disease. The authors assessed neurochemical enzyme activity with cerebral metabolic rates and found varying correlations. They did not specifically describe the regional metabolic patterns or the histologic correlation. However, the authors did suggest that there is some correlation between the histology and metabolic pattern and described temporo-parietal metabolic abnormalities.
In 1991, Duara et al. (21) described 9 patients with the histologic confirmation of an AD diagnosis after having been assessed using FDG PET scans. Duara et al. also correlated metabolic findings with specific pathologic findings of gliosis, plaques, tangles, and neuronal loss. In 4 patients there was prominent temporo-parietal hypometabolism, in 4 patients there was a predominance of frontal metabolic abnormalities, and in 1 patient there was equivalent frontal and temporo-parietal metabolic abnormalities. Unfortunately, the authors did not provide quantitative information that would possibly show that even though in 4 patients there was a predominance of frontal metabolic dysfunction, there may have been coexisting temporo-parietal metabolic abnormalities compared with the control group. In this study, the authors concluded that the metabolic findings in AD were heterogeneous and no typical metabolic pattern existed. Furthermore, they concluded that the underlying neuropathologic findings did not correlate with a specific metabolic pattern. It was their opinion that the metabolic findings seen in AD are most likely secondary to disconnection phenomenon and synaptic loss. This particular study was performed with a scanner of poor spatial resolution compared with the scanners used in our study, and this may have contributed to the findings.
In 1992, DeCarli et al. (22) described 6 patients who had FDG PET scans and quantitative postmortem neuropathology. In 4 patients, there was a significant negative correlation between regional neurofibrillary tangle density and regional metabolic rates. In none of the patients did a correlation exist between senile plaque density and regional metabolic rates. The authors did note, however, that the associated cortical regions had the highest neurofibrillary tangle densities and the lowest metabolic rates. There was metabolic sparing of primary sensory and motor cortex.
In 1994, Salmon et al. (8) described a study of 129 individuals who underwent FDG PET imaging for differential diagnosis of dementia. Twelve patients eventually had pathologic confirmation of diagnosis. Five patients with dementia eventually had pathologic confirmation of diagnosis revealing AD. Three of the 5 patients had a characteristic pattern of bilateral temporo-parietal hypometabolism. One patient with milder clinical symptoms showed unilateral temporo-parietal involvement. Another patient had moderate dementia and unilateral frontal greater than unilateral temporo-parietal metabolic dysfunction. This particular patient had neurofibrillary tangles, amyloid angiopathy, gliosis, atrophic neurons, and plaques but no Pick bodies. The authors did note 1 patient with bilateral temporo-parietal hypometabolism who had histologic Creutzfeldt-Jacob disease. The remainder of the pathologically confirmed cases had metabolic patterns that were not confused with AD. The authors concluded that 94% of the patients with the clinical diagnosis of probable AD had a metabolic pattern of bilateral or unilateral temporo-parietal hypometabolism.
A report in 1995 by Tedeschi et al. (23) described 4 patients (out of 18 patients) with the diagnosis of normal pressure hydrocephalus (NPH) and AD who underwent FDG PET imaging and had right frontal biopsies obtained. The authors determined side-to-side and anterior-to-posterior asymmetry indices. In the 4 cases where the pathology revealed AD, 1 patient was found to have only left frontal metabolic dysfunction. In 1 patient, there was significant temporo-parietal hypometabolism. In 2 patients, there was global reduction in FDG uptake in frontal and temporo-parietal association cortices. Some asymmetry of the metabolic patterns was also noted. The authors concluded that the metabolic patterns seen in the patients with AD did not differ from those of idiopathic NPH not associated with a degenerative disease. This study is difficult to compare with other results because in the pathologically confirmed cases of AD, the coexistence of NPH may have also altered the metabolic pattern.
In 1996, Mielke et al. (24) described 4 patients with postmortem confirmation of the diagnosis of AD who had FDG PET imaging. Three of the 4 patients were studied serially during the course of their illness. The authors also correlated neuropathologic findings with regional metabolic abnormalities. All studies revealed significantly reduced temporo-parietal metabolism compared with control subjects. There was a significant relationship between regional and senile plaque density in only 1 patient. In this study, there was not a strong correlation between regional glucose metabolism and neurofibrillary tangle density. Pathologically, neurofibrillary tangles were concentrated in the hippocampus, amygdala, and entorhinal regions. The authors concluded that the metabolic abnormalities of involvement of the temporo-parietal and frontal association cortex were secondary to disruption of projection neurons in limbic areas.
Previous studies have specifically examined the characteristic pattern of temporo-parietal metabolic abnormalities in AD. A study by Powers et al. (15) found that the pattern was not adequately specific to be used as a clinical tool. In their study, however, PET brain perfusion imaging was performed with oxygen-15–labeled water, which does not have the image resolution or quality of FDG. Therefore, the lower accuracy of oxygen-15 PET perfusion studies is not unexpected compared with current high-resolution FDG PET studies.
In certain cases, overlap of metabolic patterns may exist and the interpreter needs to be aware of important and relevant clinical information. In this study, patient 2 (Table 1; Fig. 2) had the pathologic diagnosis of Creutzfeldt-Jacob disease. This particular disorder is clinically different than AD. In this study as well as in other studies (31–33), Creutzfeldt-Jacob disease may have a metabolic pattern that is indistinguishable from that of AD. In the patient in this study, the metabolic pattern was considered classic for AD (Fig. 2). Other dementing disorders may have different characteristic metabolic patterns, such as PSP with prominent frontal hypometabolism (34–36) (Fig. 4).
Because of the more widespread availability of SPECT imaging with a perfusion agent, the number of studies describing pathologic confirmation and SPECT imaging has increased. In 1993, Jagust et al. (37) reported their experience with 11 patients with AD dementia and 5 individuals with non-AD dementia confirmed by autopsy. The authors used SPECT imaging of 123I iodo-amphetamine and noted that reduction in temporal and parietal perfusion was most effective in differentiating AD from non-AD dementia. In individuals with non-AD dementia, frontal lobe hypoperfusion was a common finding.
In 1993, Bonte et al. (3) described SPECT scans in 15 individuals with histologic diagnosis of dementia. The authors used 133Xe SPECT imaging, and 3 subjects were studied with 99mTc hexamethyl propleneamine oxime (HMPAO). Seven patients had histologic confirmation of AD, 2 had AD and Parkinson's disease pathology, 1 had equivocal AD pathology, 1 had polyglucason body disease, 1 biopsy was normal, 1 had AD plus multiple infarcts, and 1 had multisystem degeneration. In the AD patients, visual findings on the SPECT scans revealed prominent temporo-parietal hypoperfusion. In the other dementia syndromes, more frontal involvement was noted.
Numerous other studies at various centers have defined and described various sensitivities and specificities for SPECT perfusion imaging in differentiating dementia syndromes. In 1995, Read et al. (38) described a series of 27 consecutively evaluated and studied patients with dementia who were evaluated at a university-based memory disorder clinic. The authors correlated clinical SPECT findings with the autopsy diagnosis. SPECT imaging accurately predicted the pathologic diagnoses in 25 of 27 patients with dementia. Read et al. determined a sensitivity for SPECT perfusion imaging of 93% compared with 74% for the clinical diagnosis confirmed at autopsy. In addition, the authors were able to characterize specific perfusion patterns associated with various dementing illnesses and conclude that SPECT imaging provided useful positive information in the differentiation of AD from other dementing illnesses. In a study by Jobst et al. (39), using HMPAO SPECT imaging, the authors reported a 96% sensitivity and a 89% specificity for parietal hypoperfusion as diagnostic of AD.
In this study, as well as those of others, the gold standard of pathologic confirmation was used to determine sensitivity, specificity, and diagnostic accuracy. Unfortunately, it is often difficult to obtain pathologic verification (40), and this is the primary reason for the lack of correlative studies to date. Another problem with clinical–radiologic–pathologic correlations of AD is that there are no universally accepted pathologic criteria for this common cause of dementia (41,42). Various organizations and individual investigators have attempted to improve diagnostic accuracy of pathologic diagnosis by describing specific neuropathologic criteria for AD (30,43–48). However, these various diagnostic algorithms place varying degrees of reliance on the number of neuritic plaques, neurofibrillary tangles, and the clinical history of dementia. These algorithms also use somewhat different sets of brain sections. Thus, a given patient may not always receive the same autopsy diagnosis. For example, in 1 study there appeared to be only about a 60% correlation between 3 widely used sets of criteria (41). In a more recent study, however, there was much better correlation among the diagnostic criteria that are most widely used, including the CERAD, Khatchaturian, and NIA-Reagan criteria (48). Finally, the neuropathologic diagnosis of AD, like the clinical and radiologic diagnoses of AD, may be much more difficult when 2 disease processes coexist (48). Therefore, the definitive gold standard has its own problems as a benchmark for the confirmatory diagnosis of both clinical and functional imaging studies. It is difficult to provide unequivocal sensitivity, specificity, and diagnostic accuracy data in dementia, particularly if 2 disease processes coexist. Despite these limitations, this study provides important confirmatory data to support the fact that bilateral temporo-parietal hypometabolism is the metabolic finding in AD.
From this study, as well as those published with and without histologic verification, a specific metabolic or perfusion pattern was noted involving temporo-parietal association cortex. The exact reason for this specific pattern has been the subject of numerous studies. An excellent review by Smith et al. (13) describes the neurochemical, neuropathologic, and functional connectivity of the hippocampus and association cortex in AD. The cognitive deficits observed in AD are secondary to hippocampal neuropathologic and neurochemical changes (4,49,50), with resultant involvement of corticolimbic pathways (51–53). Recent neuropathologic studies have demonstrated excellent neuroanatomic localization of senile plaques and, in particular, neurofibrillary tangles to the association cortical areas known to be maximally affected in FDG PET studies (54,55). The previously described studies that specifically correlated the neuropathologic findings and regional metabolic measurements showed inconsistent results. These discrepant and often contradictory findings are undoubtedly a result of the small number of patients that were studied.
It has also been postulated that an inherent defect in glucose transport may actually precede biochemical and neuropathologic changes in AD (56). This theory has been evaluated with dynamic FDG PET studies (57,58). Piert et al. (57) noted that there was diminished glucose phosphorylation and transport in the temporo-parietal cortex in AD. It has also been postulated that the metabolic and perfusion deficits in association cortex may be primarily because of neuronal cell loss and neuropathologic changes in these brain regions. Numerous studies have examined the effects of atrophy secondary to neuronal cell loss and the resultant metabolic deficit (59,60). The general concurrence of the available information is that the metabolic and perfusion defects noted cannot be explained fully by tissue volume loss (60). Therefore, the metabolic pattern seen in AD is a complex finding secondary to specific hippocampal and cortical pathologic and neurochemical changes, neuronal disconnection effects, and cortical neuronal cell loss.
Despite these limitations, it appears that the NINCDS-ADRDA clinical criteria (25) and the CERAD criteria for pathologic confirmation (30), as used in this study, provide a current state-of-the-art ability to differentiate and confirm the various etiologies for dementia when correlated with both clinical and functional imaging results. We expect that FDG PET will assume an increasingly important role in the confirmation and differentiation of AD from other causes of dementia.
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CONCLUSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONCONCLUSIONREFERENCES |
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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For correspondence or reprints contact: John M. Hoffman, MD, National Cancer Institute NCI/DCTD/DIP EPN/800, Diagnostic Imaging Program, 6130 Executive Blvd., MSC 7440, Bethesda, MD 20892-7440.
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