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Neuroimaging and Early Diagnosis of Alzheimer Disease: A Look to the Future¹

¹ From the Departments of Radiology (J.R.P., R.E.C.) and Geriatric Medicine and Psychiatry (P.M.D.), Duke University Medical Center, Duke Hospital North, Rm 1513, Erwin Rd, Durham, NC 27710. Received September 28, 2001; revision requested December 3; revision received February 25, 2002; accepted March 14. J.R.P. supported by grants from the RSNA Research and Education Foundation and the National Institute of Aging (R01AG019728-01). P.M.D. supported by grants from the American Federation of Aging Research and the National Institutes of Health. Address correspondence to J.R.P. (e-mail: jeffrey.petrella@duke.edu).

	ABSTRACT

TOP ABSTRACT INTRODUCTION PATHOLOGY AND ETIOLOGY PATHOLOGIC DIAGNOSIS CLINICAL DIAGNOSIS ROLE OF STRUCTURAL NEUROIMAGING... ROLE OF FUNCTIONAL NEUROIMAGING PREDICTION AND EARLY DIAGNOSIS:... REFERENCES

 
Alzheimer disease (AD), a progressive neurodegenerative disorder, is the most common cause of dementia in the elderly. Current consensus statements have emphasized the need for early recognition and the fact that a diagnosis of AD can be made with high accuracy by using clinical, neuropsychologic, and imaging assessments. Magnetic resonance (MR) or computed tomographic (CT) imaging is recommended for the routine evaluation of AD. Coronal MR images can be useful to document or quantify atrophy of the hippocampus and entorhinal cortex, both of which occur early in the disease process. Both volumetric and subtraction MR techniques can be used to quantify and monitor dementia progression and rates of regional atrophy. MR measures are also increasingly being used to monitor treatment effects in clinical trials of cognitive enhancers and antidementia agents. Positron emission tomography (PET) and single photon emission CT offer value in the differential diagnosis of AD from other cortical and subcortical dementias and may also offer prognostic value. In addition, PET studies have demonstrated that subtle abnormalities may be apparent in the prodromal stages of AD and in subjects who carry susceptibility genes. PET ligands are in late-stage development for demonstration of amyloid plaques, and human studies have already begun. Functional MR–based memory challenge tests are in development as well.

© RSNA, 2003

Index terms: Alzheimer disease, 13.83 • Brain, CT, 13.12111 • Brain, function • Brain, MR, 13.121411, 13.121412, 13.121416, 13.12144, 13.12145 • Brain, radionuclide studies, 13.12162, 13.12163 • State of the Art

	INTRODUCTION

TOP ABSTRACT INTRODUCTION PATHOLOGY AND ETIOLOGY PATHOLOGIC DIAGNOSIS CLINICAL DIAGNOSIS ROLE OF STRUCTURAL NEUROIMAGING... ROLE OF FUNCTIONAL NEUROIMAGING PREDICTION AND EARLY DIAGNOSIS:... REFERENCES

 
Alzheimer disease (AD) is a progressive neurodegenerative disorder associated with disruption of neuronal function and gradual deterioration in cognition, function, and behavior (1). It is the most common cause of dementia in the elderly and affects approximately 2–4 million individuals in the United States and more than 30 million worldwide. Age is a strong risk factor, with the disease affecting approximately 8% of individuals over the age of 65 years and 30% over the age of 85 years in developed countries. The progression of AD is gradual, and the average patient lives 8–10 years after onset of symptoms. Thus, with the growth of the older population in developed nations, the prevalence of AD is expected to triple over the next 50 years (2). Female-to-male prevalence is 70%, likely related to increased life expectancy in women. The annual cost of the disease in the United States alone, including medical, long-term, and home care, as well as loss in productivity, is currently estimated at $100 billion (3). Not only is the financial burden substantial, but the psychologic and emotional burden on patients and their families is even greater.

With the recent availability of several effective pharmaceutical agents for treatment of AD symptoms, along with several new agents undergoing clinical trials, we are entering a new age in the treatment of AD. Current consensus statements have emphasized the need for early recognition; thus, there is an urgent need to develop sensitive markers that may serve as adjuncts to current clinical and neuropsychologic tests to facilitate detection and/or monitoring of early brain changes suggestive of AD. Such markers may also facilitate early-intervention studies to prevent or slow disease progression.

Conventional structural neuroimaging, such as computed tomography (CT) or magnetic resonance (MR), has long played a supportive role in the diagnosis of memory disorders and is recommended for the routine evaluation of AD. However, because structural changes may not be detected at visual inspection until late in the course of the disease, more contemporary structural imaging techniques, such as serial volumetric imaging and voxel compression subtraction, have emphasized a quantitative approach capable of aiding in detection of subtle changes not readily apparent on routine images obtained at a single time point. Likewise, functional imaging modalities that demonstrate physiologic changes in the brain, including positron emission tomography (PET), single photon emission CT (SPECT), and functional MR imaging, also have the potential to enable identification of more subtle pathologic changes earlier during the disease course and, therefore, may have equal or greater potential in comparison with structural imaging modalities such as CT and conventional MR imaging.

This article will address the evolving role of contemporary neuroimaging in the evaluation of memory disorders, particularly AD. The intent is to focus primarily on AD; therefore, discussion of other causes of dementia is presented, in less detail, for the purpose of differential diagnosis. We will begin by briefly describing the current understanding of the neuropathology and genetics of AD, because these will have a direct bearing on diagnosis and treatment. Second, we will discuss pathologic and clinical diagnosis of memory disorders, followed by a description of the current role of structural neuroimaging evaluation. Third, we will give the reader perspective on the potential role of functional imaging in the broader scheme of clinical diagnosis and conventional imaging. Last, we will address what future steps are required for the implementation of advanced imaging techniques as useful diagnostic tools for work-up in the patient with dementia.

	PATHOLOGY AND ETIOLOGY

TOP ABSTRACT INTRODUCTION PATHOLOGY AND ETIOLOGY PATHOLOGIC DIAGNOSIS CLINICAL DIAGNOSIS ROLE OF STRUCTURAL NEUROIMAGING... ROLE OF FUNCTIONAL NEUROIMAGING PREDICTION AND EARLY DIAGNOSIS:... REFERENCES

 
Over the past 2 decades, rapid advances have occurred in our molecular genetic and cell biologic understanding of the pathogenesis of AD. Pathologically, AD is characterized by damage to the large cortical neurons subserving cognition, initially in the temporal lobes and later in the remaining neocortex and association areas. Damage is believed to occur owing to mechanisms outside the neuron, as well as inside the neuron, and is characterized by the appearance of extracellular senile (amyloid) plaques and intracellular neurofibrillary tangles (4) (Fig 1). Much work over the past 2 decades has focused on these two pathologic components of the disease, with application of molecular genetic, biochemical, and morphologic techniques to study them in great detail (5).

View larger version (24K): [in this window] [in a new window] [Download PPT slide]   Figure 1a. Two theories of how damage occurs in AD. (a) From outside the cell, amyloid ß peptides secreted by brain cells are normally soluble, and any excess is cleared away. When these peptides become insoluble, however, they collect in the space between cells. Amyloid fibrils are "herded" together by chaperone proteins. The large plaques that form then damage brain cells and attract reactive cells, microglia and astrocytes, which cause further damage. (b) From inside the cell, tau proteins, which normally stabilize microtubules in brain cells, undergo abnormal chemical changes and assemble into spirals called paired helical filaments, thus creating tangles that disrupt cell functions and lead to cell death. (Images courtesy of Dr John Trojanowski and Dr Virginia M. Y. Lee, University of Pennsylvania Medical Center, Philadelphia.)

View larger version (21K): [in this window] [in a new window] [Download PPT slide]   Figure 1b. Two theories of how damage occurs in AD. (a) From outside the cell, amyloid ß peptides secreted by brain cells are normally soluble, and any excess is cleared away. When these peptides become insoluble, however, they collect in the space between cells. Amyloid fibrils are "herded" together by chaperone proteins. The large plaques that form then damage brain cells and attract reactive cells, microglia and astrocytes, which cause further damage. (b) From inside the cell, tau proteins, which normally stabilize microtubules in brain cells, undergo abnormal chemical changes and assemble into spirals called paired helical filaments, thus creating tangles that disrupt cell functions and lead to cell death. (Images courtesy of Dr John Trojanowski and Dr Virginia M. Y. Lee, University of Pennsylvania Medical Center, Philadelphia.)

Release of amyloid ß protein results from abnormal cleavage of the amyloid precursor protein, a glycoprotein found in high concentrations in the cell membrane of virtually all mammalian cells but in especially high concentrations in neuronal cell membranes. The enzymes responsible for normal and abnormal cleavage of amyloid precursor protein (, ß, secretases) have been described and targeted for drug therapy. Amyloid precursor protein is normally secreted by both brain and nonbrain cells into extracellular fluids throughout life. Increased production of amyloid ß protein leads to precipitation, aggregation, and progressive deposition in the form of plaques. Plaque buildup is thought to incite an inflammatory and/or oxidative response, leading to progressive disruption of neuronal function and injury in the hippocampal complex and cerebral cortex (6).

Recent evidence suggests that genetic alterations underlying familial AD result in increased production of amyloid ß protein (Table 1). Mutations in the gene for amyloid precursor protein, leading to abnormal cleavage, are located on chromosome 21 and are present in patients with the rare early-onset familial form of the disease. Cloning of these mutations has lead to increased production of amyloid ß protein in cell cultures, and plasma levels of amyloid ß protein are elevated in some mutation carriers, even presymptomatically. Mutations of the presenilin 1, or PS-1, and presenilin 2, or PS-2, genes, on chromosomes 1 and 14 respectively, are also associated with the early-onset familial form of AD. Moreover, postmortem studies in patients with trisomy 21 (Down syndrome) and in those who carry susceptibility genes for AD have shown that amyloid ß protein accumulation in the cortex is an early invariant event in AD pathology, sometimes occurring decades before symptoms become apparent (5). Given this evidence, current thinking suggests that AD may represent not a single disease entity but rather a syndrome resulting from different genetic determinants that lead to a common phenotype with amyloid deposition and neuronal degeneration in specific brain regions (6).

At present, the molecular and etiologic relationship between plaques and tangles is not fully understood. The bulk of current data suggests that these two lesions might be formed independently of each other. In fact, the distribution and density of both diffuse and neuritic senile plaques have not been consistently shown to correlate with the presence or severity of dementia (7), whereas the total density of neurofibrillary tangles does (8,9). Indeed, some elderly individuals without dementia have as much plaque deposition as have those with severe dementia. However, the neuritic variety of plaque associated with dystrophic axons and dendrites and reactive glial cells appears to be a more specific feature of AD than is the neurofibrillary tangle. Furthermore, results of a number of in vitro and in vivo studies have shown amyloid ß protein to be directly toxic to neurons, leading to phosphorylation of tau protein, the principal component of neurofibrillary tangles (10).

Pathologic Progression
The insidious onset and gradual progression of symptoms in patients with AD are thought to parallel the progression of AD-related brain destruction from entorhinal cortex to hippocampus to neocortex (11). In typical cases, there initially is isolated impairment of learning and short-term memory, without alteration in other domains of cognition or consciousness. This is followed by changes in long-term memory, personality, orientation, and executive function. After cognitive losses, there are behavioral problems (eg, hallucinations, delusions). Finally, there is deterioration of language, visuospatial skills, and, eventually, motor function, which leads to loss of activities of daily living.

Three stages in the gradual evolution of plaque deposition have been described (11). Stage A is characterized by deposition in the basal temporal neocortex, or entorhinal cortex. There then is extension through the hippocampal formation in stage B, eventually leading to deposits in virtually all cortical areas, including the highly myelinated primary areas of the neocortex in stage C.

There are reported to be six stages in the evolution of neurofibrillary tangles (11). Stage I is defined by the appearance of neurofibrillary tangle–bearing neurons in the transentorhinal region, with progression to the entorhinal region and hippocampal formation in stage II. These stages represent the presymptomatic phase of the disease. Further progression leads to stages III and IV, which are characterized by severe involvement of the entorhinal region, amygdala, and hippocampal formation. This involvement leads to interruption of the limbic loop, which is responsible for data transfer back and forth between the neocortex and the hippocampal formation. In addition, there is also involvement of many subcortical nuclei with diffuse projections to the cortex, among them the cholinergic system of the basal forebrain, including the nucleus basalis of Meynert. Patients with disease at these stages may present with symptoms of mild cognitive impairment (MCI) or prodromal AD, although symptoms may be masked by a high cognitive-reserve capacity. In stage V, there is extension to all major regions of the cerebral cortex, from association areas into primary areas. In stage VI, even the primary sensory areas are severely involved, although the motor area continues to be relatively spared. Stages V and VI are generally characterized by severe dementia.

	PATHOLOGIC DIAGNOSIS

TOP ABSTRACT INTRODUCTION PATHOLOGY AND ETIOLOGY PATHOLOGIC DIAGNOSIS CLINICAL DIAGNOSIS ROLE OF STRUCTURAL NEUROIMAGING... ROLE OF FUNCTIONAL NEUROIMAGING PREDICTION AND EARLY DIAGNOSIS:... REFERENCES

 
AD is characterized pathologically by reductions in the number of large cortical neurons in temporal and frontal cortex and by the appearance of senile (amyloid) plaques and neurofibrillary tangles (4). In living subjects, only a provisional diagnosis of possible or probable AD may be made, by using clinical, laboratory, and imaging evidence. Definitive diagnosis of AD is made by means of pathologic examination of tissue derived from autopsy or brain biopsy. For this reason, criteria have been created to standardize the pathologic diagnosis.

In the past, the two most extensively used pathologic criteria have been the National Institute on Aging consensus criteria (1) and the Consortium to Establish a Registry for Alzheimer’s Disease, or CERAD, criteria (12). The National Institute on Aging criteria are based on subject age and clinical history, taking into account the number of senile plaques per high-power microscopy field and the presence of neurofibrillary tangles in specific regions of the neocortex, hippocampus, and subcortical gray matter. The CERAD criteria use only the presence and density of neuritic senile plaques in the neocortex for establishment of the diagnosis of AD. The density is classified as "sparse," "moderate," or "severe" and is then combined with the age of the subject to yield an age-related plaque score. The plaque score is integrated with clinical information for the diagnosis of "definite," "probable," or "possible" AD.

More recently, the National Institute on Aging–Reagan Institute criteria, based on the number of both plaques and tangles in the neocortex and the limbic and paralimbic regions, were introduced (13,14). These criteria essentially combined the CERAD criteria, which are based on plaque frequency, and the staging criteria of Braak and Braak (15), which are based on neurofibrillary tangle distribution and frequency. The possibility of coexisting pathologic conditions other than AD is also recognized.

Unfortunately, because these criteria place varying degrees of dependence on the number and type of senile plaques and neurofibrillary tangles in various sections of the brain, as well as on the presence of a clinical history of dementia, the same diagnosis may not be rendered at autopsy in a given patient (16). In a recent study (17), however, a good correlation was shown between the National Institute on Aging–Reagan Institute criteria and the previous two criteria. The National Institute on Aging–Reagan Institute criteria offer the possibility of better diagnostic refinement because of the recognition that dementia in the elderly may arise from more than one disorder. In dementia with Lewy bodies, for example, there may be considerable clinical and pathologic overlap with AD.

	CLINICAL DIAGNOSIS

TOP ABSTRACT INTRODUCTION PATHOLOGY AND ETIOLOGY PATHOLOGIC DIAGNOSIS CLINICAL DIAGNOSIS ROLE OF STRUCTURAL NEUROIMAGING... ROLE OF FUNCTIONAL NEUROIMAGING PREDICTION AND EARLY DIAGNOSIS:... REFERENCES

 
The accuracy of a clinical diagnosis of AD depends on the stage of disease and the clinical setting. In an academic memory-disorders clinic setting, the diagnostic accuracy can exceed 90% (18–20), while accuracy may be substantially lower in the general community setting where there is less consistency and reliance on established diagnostic criteria. In this section, we will briefly review the clinical criteria for diagnosing AD and other common dementias of old age. We will also present current treatment options.

Diagnostic Criteria
AD.—Clinical criteria used for a provisional diagnosis consist of the National Institute of Neurological and Communicative Disorders and Stroke/Alzheimer’s Disease and Related Disorders Association (NINCDS/ADRDA) criteria (21) (Fig 2) for possible or probable AD or the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) criteria (22) for dementia of the Alzheimer type. Probable AD can be categorized as mild (early), moderate (middle), or severe (late) dementia. Clinical work-up includes a detailed history from the patient and/or an informant, a general physical and mental status examination, neurologic assessment, and objective tests such as the Mini-Mental State Examination (MMSE) to help assess cognitive dysfunction. In addition, tests are also available to quantify activities of daily living, behavioral dysfunction, and caregiver stress. Staging instruments such as the Clinical Dementia Rating Scale and the Global Deterioration Scale are frequently used in academic settings.

View larger version (64K): [in this window] [in a new window] [Download PPT slide]   Figure 2. NINCDS/ADRDA (National Institute of Neurological and Communicative Disorders and Stroke/Alzheimer’s Disease and Related Disorders Association) criteria (21) for probable AD. EEG = electroencephalogram.

Although variants with atypical manifestations have been described, the diagnosis of AD requires memory impairment as the most prominent manifestation, with a deficit in one or more cognitive domains, including language, orientation, or executive functioning (ie, planning, organizing, abstracting). The course of the disease is variable but is characterized by gradual onset with progressive decline in memory, with initial sparing of sensory and motor function. The memory impairment may initially manifest itself as a deficit in learning or recall of new information, followed by loss of remote memory. Behavioral and psychologic disturbances (depression, delusions, wandering, paranoia, anxiety, sleep changes) also develop in virtually 100% of patients over the course of the disease (Fig 3). Differentiation from dementia associated with depression (pseudodementia) may be difficult.

View larger version (31K): [in this window] [in a new window] [Download PPT slide]   Figure 3. Over the clinical course of AD, patients will demonstrate progressive declines in functional ability that correlate with MMSE scores. In the preclinical phase, also called MCI, patients with MMSE score greater than 23 will demonstrate minimal impairment—generally, mild memory loss—while functioning normally and independently. The typical length of the MCI phase remains undetermined. Onset of mild AD is indicated by MMSE score of 20-23; these patients exhibit gradual alterations in cognition, function, behavior, and mood. Forgetfulness and repetitive questions are hallmarks; daily function begins to become impaired. In moderate AD (MMSE score of 10-19), cognitive impairments progressively deteriorate and now include short-term memory loss (eg, difficulty in recalling recent conversations, forgetting to keep appointments, inability to remember recent events). Patients begin to have trouble with verbal fluency; specifically, increasing difficulty in remembering the correct word. Severe stage is reached when MMSE scores decline to less than 10. At this point, patients exhibit behavioral changes that include agitation, delusion, aggression, wandering, and hallucination. Sleep patterns are altered, and the patient eventually becomes completely dependent on others for dressing, feeding, and bathing. The clinical progression from onset of mild AD to onset of severe AD, although variable, is about 10 years.

Differential diagnosis with other forms of dementia.—In developed countries, AD accounts for approximately 50%–70% of all cases of dementia in the elderly. Diagnostic criteria require that AD be distinguished from other causes of dementia such as vascular dementia, frontotemporal dementia, dementia with Lewy bodies, normal-pressure hydrocephalus, depression-related cognitive impairment, and intracranial mass.

Vascular dementia, which accounts for about 15% of all dementias in the United States, can be distinguished from AD by its more sudden onset and association with vascular risk factors. Vascular dementia is characterized by a stepwise course with periods of stability followed by sudden decline in cognitive function. Patients may experience focal neurologic deficits after a sudden decline, such as slurred speech or sensorimotor dysfunction. Clinical criteria for diagnosis of probable vascular dementia were created in 1993 and are known as the National Institute of Neurological Disorders and Stroke–Association Internationale pour la Recherche et l’Enseignement en Neurosciences (NINDS-AIREN) criteria (Fig 4) (24). The term vascular dementia is preferred over multiinfarct dementia, because the former is an acknowledgment of the many vascular causes that can contribute to dementia. Control of vascular risk factors is the treatment of choice. Cholinesterase inhibitors are also increasingly being used to treat vascular dementia.

View larger version (68K): [in this window] [in a new window] [Download PPT slide]   Figure 4. NINDS-AIREN (National Institute of Neurological Disorders and Stroke and Association Internationale pour la Recherche et l’Enseignement en Neurosciences) criteria (24) for probable vascular dementia. ACA = anterior cerebral artery, CVD = cerebrovascular disease, PCA = posterior cerebral artery.

Normal-pressure hydrocephalus is characterized by a classic triad of gait disturbance (25), dementia, and incontinence. There is evidence that ventricular shunting in a select group of these patients may improve symptoms, provided either pronounced gait difficulty or the full triad are present; however, there is little effect in patients in whom dementia is the first or primary symptom (26,27).

Dementia with Lewy bodies is being diagnosed more frequently; study results have demonstrated that it is responsible for approximately 25% of dementias. The clinical manifestation may be similar to that of AD or the dementia associated with Parkinson disease. Patients typically present with one of three symptom complexes: detailed visual hallucinations, Parkinson-like symptoms, or alterations in alertness and attention (3). Pathologically, the disease is characterized by the presence of Lewy bodies in various regions of the hippocampal complex, subcortical nuclei, and neocortex, with a variable number of diffuse amyloid plaques; however, the neurites (axons and dendrites) and neurofibrillary tangles seen in AD are not seen in this disease. In 1996, consensus criteria were developed for the diagnosis of probable dementia with Lewy bodies (28) (Fig 5). Cholinesterase inhibitors are currently the treatment of choice for this condition.

View larger version (69K): [in this window] [in a new window] [Download PPT slide]   Figure 5. Proposed criteria of McKeith et al (28) for probable dementia with Lewy bodies (DLB).

Results of neuropsychologic studies of early AD have demonstrated that specific patterns of recent memory impairment help distinguish between early-stage AD, normal aging, and other dementing conditions (30). Based on these and other data, research criteria have been developed for identification of patients with MCI ("prodromal AD"), and such criteria are currently being used for selecting patients for ongoing-intervention trials (31). Specifically, MCI is characterized by a prominent and relatively isolated impairment in so-called secondary memory, or memory for information after short delays. Patients with MCI may also have impairments of working memory. This deficit in patients with MCI is believed to be to caused by impaired acquisition or consolidation of new information into permanent memory stores, presumably related to damage to the medial temporal lobe and/or specific prefrontal–temporal lobe circuits (Fig 6).

View larger version (23K): [in this window] [in a new window] [Download PPT slide]   Figure 6. Model of neural deficits in early AD. Neural connections associated with normal memory function involve frontal and temporal lobes. Somatosensory, visual, and auditory information proceed from primary and association cortex to prefrontal cortex, located in the posterior frontal lobe. This region plays a major role in executive function (ie, organizing and directing attention), as well as in working memory, acting as a "mental scratchpad" for short-term information needed to perform a task, such as dialing a phone number. Part of this information may be consolidated, branching to the medial temporal lobe region via the entorhinal cortex (medial temporal lobe) and into the hippocampal complex. Projections from the hippocampal complex can transfer long-term information back to prefrontal cortex. This back-and-forth pathway between prefrontal cortex and medial temporal lobes is known as the limbic loop and is considered important for emotional stability, learning and memory function, and regulation of autonomic and endocrine functions. It is precisely these areas that are particularly susceptible to the pathologic changes of AD (11). (Adapted, with permission, from reference 32.)

Although the definition of MCI has differed somewhat from study to study, there are now several longitudinal investigations in subjects with MCI. Peterson (34) has followed up MCI subjects and demonstrated that, on average, approximately 40% of carefully characterized subjects with MCI will progress to meet criteria for AD over a 4-year period. At present, there is no reliable test to predict which subjects will convert or progress, although all of the aforementioned risk factors may play a role. Symptoms of forgetfulness can be ambiguous and easily confused with the benign forms of memory change associated with normal aging (35) (Fig 7). Thus, there is an urgent need to develop sensitive markers that may serve as adjuncts to current clinical and neuropsychologic tests to facilitate detection and/or monitoring of early brain changes suggestive of AD. Such markers may also facilitate early intervention studies to prevent or slow further neuronal loss.

View larger version (11K): [in this window] [in a new window] [Download PPT slide]   Figure 7. Conceptual continuum of memory decline in early AD. Diagram demonstrates overlap between healthy control subjects and patients with MCI and between patients with mild AD and those with MCI.

Genetic Testing
Genetic testing can be performed by using numerous markers (Table 1), many of which facilitate a diagnosis of early-onset dementia. Mutations of the PS-1, PS-2, and amyloid precursor protein genes on chromosomes 1, 14, and 21, respectively, are associated with early onset of the familial—and extremely rare—form of AD. The only useful marker for the more common late-onset (sporadic form) dementia is the apolipoprotein allele on chromosome 19. Results of genetic studies have shown that the 4 allele is associated with a high incidence of AD, whereas the 2 allele may be a protective factor. The 3 allele is thought to represent no increased or decreased risk (36). Because the 4 allele is more prevalent in patients with AD, it may be useful for differential diagnosis in patients with memory disorders. However, it is currently not recommended as a predictor of prognosis in asymptomatic subjects. The 4 allele is found in about 30% of healthy subjects and is absent in approximately 30%–40% of patients with AD (37).

	ROLE OF STRUCTURAL NEUROIMAGING

TOP ABSTRACT INTRODUCTION PATHOLOGY AND ETIOLOGY PATHOLOGIC DIAGNOSIS CLINICAL DIAGNOSIS ROLE OF STRUCTURAL NEUROIMAGING... ROLE OF FUNCTIONAL NEUROIMAGING PREDICTION AND EARLY DIAGNOSIS:... REFERENCES

 
Conventional CT and MR Imaging
Conventional CT and MR imaging are used routinely in the work-up of patients with dementia; however, because of their low sensitivity and specificity for the diagnosis of AD, they are primarily used as an adjunct to help assess the degree of atrophy and rule out other causes of dementia such as normal-pressure hydrocephalus, vascular dementia, or intracranial mass. Currently, there is no reason to support CT over MR in the evaluation of patients with dementia, except in cases where MR is contraindicated or not readily available or affordable.

Standard MR pulse sequences at most centers consist of nonenhanced transverse spin-echo T1-weighted imaging to help assess the presence and degree of generalized (eg, AD) or focal (eg, cerebellar degenerative diseases, Pick disease, AD) atrophy (38,39). Transverse dual-echo long-repetition-time imaging, including proton-density and/or fluid-attenuated inversion-recovery and T2-weighted imaging, is also used in the assessment for periventricular and subcortical white matter hyperintensities; cortical or deep gray matter lacunar infarcts (vascular dementia); and periaqueductal, cerebellar, or dorsal thalamic changes (eg, alcohol-related dementia) (40). At centers where fast spin-echo rather than conventional spin-echo imaging is used, T2*-weighted or gradient-echo imaging may be needed to help assess the degree of iron deposition (eg, parkinsonian disorders) (41). T1-weighted and T2-weighted sequences may also be used to help assess for the presence of ventricular dilatation or intracranial mass. Thin-section (3-mm-thick) coronal T1-weighted images obtained in a plane orthogonal to the long axis of the hippocampus are useful for assessment of the degree of medial temporal lobe and hippocampal atrophy.

AD.—Medial temporal lobe atrophy, particularly of the amygdala, hippocampus, and parahippocampal gyrus, can be seen with higher frequency on structural images in patients with AD (42,43). Early investigators used CT to assess cortical, cerebellar, and hippocampal atrophy on transverse images; however, the addition of the coronal imaging plane with MR provided better qualitative assessments of the hippocampal region (Fig 8). Studies in which T1-weighted MR imaging was used in evaluation of the anterior hippocampus have been particularly useful. Data from a study (44) with 222 subjects (controls and patients with various forms of dementia) in which a visual rating scale was used to assess temporal lobe atrophy suggest that sensitivities and specificities in the area of 85% may be obtained for patients with AD.

View larger version (144K): [in this window] [in a new window] [Download PPT slide]   Figure 8a. Coronal T2-weighted fast spin-echo MR images (repetition time msec/echo time msec, 2,700/80) in (a, b) a patient with AD and (c, d) an age-matched control subject. (a, b) The patient with AD has severe bilateral hippocampal atrophy (arrows). Compare this with (c, d) normal hippocampus (arrows) in the control subject. Note that b is a close-up of a, and d is a close-up of c. (Images courtesy of Daniel P. Barboriak, MD, Duke University Medical Center, Durham, NC.)

View larger version (59K): [in this window] [in a new window] [Download PPT slide]   Figure 8b. Coronal T2-weighted fast spin-echo MR images (repetition time msec/echo time msec, 2,700/80) in (a, b) a patient with AD and (c, d) an age-matched control subject. (a, b) The patient with AD has severe bilateral hippocampal atrophy (arrows). Compare this with (c, d) normal hippocampus (arrows) in the control subject. Note that b is a close-up of a, and d is a close-up of c. (Images courtesy of Daniel P. Barboriak, MD, Duke University Medical Center, Durham, NC.)

View larger version (135K): [in this window] [in a new window] [Download PPT slide]   Figure 8c. Coronal T2-weighted fast spin-echo MR images (repetition time msec/echo time msec, 2,700/80) in (a, b) a patient with AD and (c, d) an age-matched control subject. (a, b) The patient with AD has severe bilateral hippocampal atrophy (arrows). Compare this with (c, d) normal hippocampus (arrows) in the control subject. Note that b is a close-up of a, and d is a close-up of c. (Images courtesy of Daniel P. Barboriak, MD, Duke University Medical Center, Durham, NC.)

View larger version (50K): [in this window] [in a new window] [Download PPT slide]   Figure 8d. Coronal T2-weighted fast spin-echo MR images (repetition time msec/echo time msec, 2,700/80) in (a, b) a patient with AD and (c, d) an age-matched control subject. (a, b) The patient with AD has severe bilateral hippocampal atrophy (arrows). Compare this with (c, d) normal hippocampus (arrows) in the control subject. Note that b is a close-up of a, and d is a close-up of c. (Images courtesy of Daniel P. Barboriak, MD, Duke University Medical Center, Durham, NC.)

Despite the existence of consistent imaging findings, it should be noted that the diagnosis of normal-pressure hydrocephalus is made primarily on the basis of clinical findings. Without a prior suspected clinical diagnosis, it is unlikely the diagnosis will be made on the basis of imaging results alone.

Vascular dementia.—Vascular dementia, or multiinfarct dementia, is often characterized by multiple areas of high signal intensity on T2-weighted, proton-density, or fluid-attenuated inversion-recovery MR images. The high signal intensity may be in white matter, basal ganglia, and/or thalamus. Focal infarcts or lacunae in strategic locations can also be associated with vascular dementia. Clinical onset of cognitive deficits is characterized by a stepwise decline, as opposed to the more continuous decline in AD. Periods of abrupt decline may be followed by stable periods. Patients typically have cerebrovascular risk factors, including male sex, smoking, hypertension, and/or diabetes. Clinical characteristics such as abrupt onset of symptoms of memory impairment, emotional lability, somatic complaints, and focal neurologic deficits, along with a history of stroke or transient ischemic attacks, often guide the clinician in making a diagnosis of vascular dementia.

Modern diagnostic criteria emphasize the importance of imaging to support a clinical diagnosis (24). This diagnosis cannot be made on the basis of imaging findings alone, as white matter hyperintensities or lacunae on MR images do not necessarily always lead to dementia or notable cognitive impairment. Although study results have associated cognitive impairment with MR hyperintensities, the nature and strength of these associations have varied from one study to another (44,50–52). This variability may be due in part to the confounding effects of high cognitive reserve or education level, which may mask a neurocognitive decline. The volume of white matter lesions does, however, correlate with the presence of cerebrovascular risk factors (53). Patients with AD may also have abundant white matter lesions, and there is often overlap between vascular dementia and AD, a so-called mixed dementia. Thus, the presence of white matter lesions on T2-weighted MR images should not be used to exclude a diagnosis of AD (3). Likewise, several strategically placed infarcts may be sufficient to cause symptoms of vascular dementia and should not be viewed as unimportant.

Quantitative Imaging of Atrophy
Quantitative measures of generalized cerebral atrophy were developed for both CT and MR imaging in an attempt to identify pathologic atrophy in early dementia, as distinguished from the atrophy of "normal" aging. Such approaches included linear and volumetric CT measurements of ventricles and subarachnoid spaces and MR imaging measurements of cerebrospinal fluid and gray and white matter volumes (54–56). Unfortunately, age-related atrophy in individuals without dementia also occurs, causing substantial overlap between the two groups and limiting the diagnostic utility of such measurements. Subsequent work focused on the medial temporal lobes, given that the pathologic substrate of AD is known to affect the hippocampus and anatomically related areas such as the entorhinal cortex at the earliest stages of the disease. Authors of early studies with CT who focused on this region applied a linear approach to measure medial temporal lobe atrophy (57,58) and a stereological approach to measure hippocampal volume (59). However, because of the small size and uneven shape of the hippocampus, as well as considerations of section thickness, the transverse CT approach turned out not to be well suited for volumetric assessment.

Quantitative hippocampal volume analysis with MR imaging turned out to be better than that with CT, given the superior soft-tissue contrast capabilities of MR, the lack of beam-hardening artifacts, and the multiplanar capability. Initial techniques used linear and area measurements. Subsequent techniques have used semiautomated computer algorithms to calculate hippocampal volumes. Authors of a number of initial studies describing MR-based volume measurements reported extremely high sensitivity in distinguishing patients with AD from elderly control subjects; however, many of these studies were flawed by imaging methods that were not state of the art, by variations in neuroanatomic boundary criteria, and by small and highly selected samples, which made extrapolation to diagnosis of AD in a general setting problematic (60). The most widely used volumetric technique is the semiautomated tracing-thresholding method, where a threshold is used to outline the high-contrast portions of the anatomic boundary and an interactive manual trace is used to outline the low-contrast portions (61). Using the tracing-thresholding method, Jack et al (62) reported a sensitivity of 82% and a specificity of 80% in discriminating patients with AD from control subjects in a study of 220 individuals (Fig 9).

View larger version (162K): [in this window] [in a new window] [Download PPT slide]   Figure 9. Coronal T1-weighted MR images demonstrate tracings of the hippocampus and parahippocampal gyrus in a 75-year-old female control subject (left) and 73-year-old woman with AD (right). Outlines of the amygdala and hippocampus are indicated in the bottom images.

The potential of serial volume measurements to aid in prediction of a subsequent development of AD and evaluation of the efficacy of therapeutic regimens in at-risk populations, particularly those with MCI (65,66), has been evaluated. Fox et al (67) used a voxel compression subtraction technique to assess serial volume changes in individual subjects. The technique uses scaling, interpolation, and a rigid body registration method to first bring the later and earlier images into subvoxel alignment. A nonlinear registration algorithm using a compressible viscous fluid model is then applied to track local cerebral losses and deformations, which are presented in the form of a color overlay map on the baseline anatomic image. Fox et al (67) recently reported use of voxel compression mapping to show progressive regional atrophy involving the temporoparietal cortex and medial temporal and posterior cingulate regions in four patients with autosomal dominant mutations for early onset AD, all of whom developed the disease over a 5–8-year follow-up (Fig 10). The same technique can be used to monitor the effects of therapeutic regimens in slowing the rate of brain atrophy. It has been estimated that detection of a 20% reduction in atrophy rate would require approximately 200 patients and 200 control subjects in a 1-year placebo-controlled drug trial (68).

View larger version (100K): [in this window] [in a new window] [Download PPT slide]   Figure 10a. T1-weighted MR images with color voxel compression mapping overlay in a 46-year-old man with familial AD. Images were obtained in (a) transverse, (b) coronal, and (c) sagittal planes over 30 months during which symptoms developed. Green and blue areas demonstrate interval volume loss, particularly in temporal lobes and in other neocortical areas. (Images courtesy of Nick C. Fox, MD, MRCP, National Hospital for Neurology and Neurosurgery, London, England.)

View larger version (100K): [in this window] [in a new window] [Download PPT slide]   Figure 10b. T1-weighted MR images with color voxel compression mapping overlay in a 46-year-old man with familial AD. Images were obtained in (a) transverse, (b) coronal, and (c) sagittal planes over 30 months during which symptoms developed. Green and blue areas demonstrate interval volume loss, particularly in temporal lobes and in other neocortical areas. (Images courtesy of Nick C. Fox, MD, MRCP, National Hospital for Neurology and Neurosurgery, London, England.)

View larger version (122K): [in this window] [in a new window] [Download PPT slide]   Figure 10c. T1-weighted MR images with color voxel compression mapping overlay in a 46-year-old man with familial AD. Images were obtained in (a) transverse, (b) coronal, and (c) sagittal planes over 30 months during which symptoms developed. Green and blue areas demonstrate interval volume loss, particularly in temporal lobes and in other neocortical areas. (Images courtesy of Nick C. Fox, MD, MRCP, National Hospital for Neurology and Neurosurgery, London, England.)

View larger version (107K): [in this window] [in a new window] [Download PPT slide]   Figure 11a. Three-dimensional model-based segmentation. Screenshot demonstrates elastic model-based segmentation of limbic structures, including amygdalae (green and yellow) and hippocampi (blue and red). (a) Segmentation is shown in three-dimensional surface rendering (bottom left) and two-dimensional overlay on T1-weighted MR images in three orthogonal planes (top left and right, bottom right). (b) Sagittal T1-weighted MR image demonstrates outline of hippocampus in green. (c) Hippocampus (yellow) and neighboring brain structures (blue, green, and red) are shown on three-dimensional volume rendering of the brain. (Images courtesy of Guido Gerig, PhD, University of North Carolina, Chapel Hill.)

View larger version (193K): [in this window] [in a new window] [Download PPT slide]   Figure 11b. Three-dimensional model-based segmentation. Screenshot demonstrates elastic model-based segmentation of limbic structures, including amygdalae (green and yellow) and hippocampi (blue and red). (a) Segmentation is shown in three-dimensional surface rendering (bottom left) and two-dimensional overlay on T1-weighted MR images in three orthogonal planes (top left and right, bottom right). (b) Sagittal T1-weighted MR image demonstrates outline of hippocampus in green. (c) Hippocampus (yellow) and neighboring brain structures (blue, green, and red) are shown on three-dimensional volume rendering of the brain. (Images courtesy of Guido Gerig, PhD, University of North Carolina, Chapel Hill.)

View larger version (119K): [in this window] [in a new window] [Download PPT slide]   Figure 11c. Three-dimensional model-based segmentation. Screenshot demonstrates elastic model-based segmentation of limbic structures, including amygdalae (green and yellow) and hippocampi (blue and red). (a) Segmentation is shown in three-dimensional surface rendering (bottom left) and two-dimensional overlay on T1-weighted MR images in three orthogonal planes (top left and right, bottom right). (b) Sagittal T1-weighted MR image demonstrates outline of hippocampus in green. (c) Hippocampus (yellow) and neighboring brain structures (blue, green, and red) are shown on three-dimensional volume rendering of the brain. (Images courtesy of Guido Gerig, PhD, University of North Carolina, Chapel Hill.)

	ROLE OF FUNCTIONAL NEUROIMAGING

TOP ABSTRACT INTRODUCTION PATHOLOGY AND ETIOLOGY PATHOLOGIC DIAGNOSIS CLINICAL DIAGNOSIS ROLE OF STRUCTURAL NEUROIMAGING... ROLE OF FUNCTIONAL NEUROIMAGING PREDICTION AND EARLY DIAGNOSIS:... REFERENCES

SPECT Imaging
Cerebral SPECT, which is based on brain uptake of a technetium 99m–based lipid-soluble radionuclide such as ethyl cysteinate dimer or hexamethylpropylene amine oxime, is a widely available technique for evaluation of brain perfusion with a rotating gamma camera. Although the technique does not yield absolute values for cerebral blood flow, it does yield semiquantitative or relative values for comparison within and between patients when normalization by cerebellar activity is used (70).

Patients with AD have typically demonstrated a relative paucity of activity in the temporoparietal regions, compared with the activity in control subjects. Results of several studies have also shown that the magnitude of the perfusion abnormality correlates with the severity of cognitive impairment (71). In a prospective study with histologic confirmation of over 200 dementia cases and 119 control cases (72), the technique was reported to enable differentiation of patients with AD from healthy control subjects with a high degree of sensitivity and specificity (89% and 80%, respectively). Moreover, the accuracy of a clinical diagnosis of AD is improved with the aid of this technique, especially in mild cases of dementia, or "possible AD." In a study with histologic confirmation in 70 patients with dementia and 85 control subjects (73), a positive SPECT scan increased the pretest probability from 84% to 92% in patients with a clinical diagnosis of "probable AD" and from 67% to 84% in patients with "possible AD." A negative SPECT scan decreased the probability from 84% to 70% in patients with "probable AD" and from 67% to 52% in patients with "possible AD."

SPECT imaging also aids in the differential diagnosis of patients with dementia. Numerous studies have been performed in patients with various forms of dementia, including AD, frontotemporal dementia, and vascular dementia, with demonstration of unique uptake patterns. The presence of a frontal or anterior perfusion deficit has been associated with frontotemporal dementia and not with AD. In one study (74) in which a simple decision rule based on discriminant analysis of SPECT data was applied, 20 patients with probable AD and 20 with probable frontotemporal dementia were evaluated. One hundred percent of patients with frontotemporal dementia and 90% of patients with AD were correctly classified. In another study (75) with 16 patients with frontotemporal dementia, 71 patients with other forms of dementia, and 28 control subjects, an anterior-to-posterior ratio was successfully used to classify patients with frontotemporal dementia from those with other forms of dementia and from control subjects with a sensitivity of 87.5% and a specificity of 78.6%. The effect of different SPECT uptake patterns at baseline on modification of the differential diagnosis was evaluated in a study (76) with 363 patients followed up for a median of 3 years. Patients were classified into disease groups on the basis of clinical criteria. A bilateral posterior perfusion abnormality was associated with AD, whereas a bilateral anterior abnormality was associated with frontotemporal dementia. A patchy uptake pattern significantly increased the odds of a patient having vascular dementia.

It has been suggested that dementia with Lewy bodies may demonstrate occipital hypoperfusion, differentiating it from AD (77). Recently, Lobotesis et al (78) studied 23 subjects with a clinical diagnosis of dementia with Lewy bodies that had been based on consensus criteria. SPECT measures of occipital and medial temporal perfusion enabled correct classification of 69% of all subjects, with 65% sensitivity and 87% specificity for dementia with Lewy bodies versus AD and controls.

Thus, results of numerous studies to date have demonstrated that SPECT imaging offers additional diagnostic value in the work-up of patients with dementia. The question remains as to the cost-effectiveness of this additional diagnostic value at this time. McMahon et al (79) recently examined this question by utilizing a decision model designed to calculate quality-adjusted life-years that accrue to hypothetical cohorts of patients at the time of presentation to an AD center. This model depended on the sensitivity and specificity of the standard diagnostic work-up, the effectiveness of current treatments, and the severity of disease. The authors concluded that addition of SPECT imaging to the diagnostic regimen was not cost-effective given currently available therapies (79).

The use of a temporoparietal hypoperfusion pattern on SPECT images to help predict the clinical onset of AD in at-risk populations has not been extensively studied. One study (80) in which 36 patients with MCI were followed up for 3 years failed to show a correlation between the presence of a SPECT abnormality at baseline examination and subsequent cognitive decline in MMSE score. The investigators in that study used visual inspection alone for evaluation of SPECT scans. Authors of another study (81), using a quantitative singular-value decomposition analysis of SPECT images in patients with MCI, demonstrated regional decreases in uptake in the medial temporal lobe and cingulate regions that were most prominent among patients with MCI who subsequently converted to AD over the 1- to 2-year follow-up. The same group (82) also demonstrated reduced perfusion in the hippocampal complex in asymptomatic subjects with the PS-1 gene mutation, as compared with that in control subjects and in the anterior and posterior cingulate gyrus, posterior parietal lobe, and anterior frontal lobe regions. The authors suggested that a distributed brain network pertaining to memory might be selectively affected in the earliest stages of the disease.

PET Imaging
PET has been used to study the brain’s metabolic uptake of fluorine 18 (¹⁸F)-labeled fluorodeoxyglucose (FDG) and blood flow in patients with dementia. PET has been performed at baseline, as well as during the performance of various cognitive tasks. Baseline PET studies have been successful in enabling differentiation of AD from other forms of dementia on the basis of the pattern of FDG uptake. Specifically, deficits in temporoparietal metabolism are typically seen in patients with AD and not in patients with other forms of dementia or in age-matched control subjects (Fig 12a, 12b). Asymmetry of the metabolic deficits is not uncommon (Fig 12c). There typically is sparing of the basal ganglia, thalamus, cerebellum, and primary sensorimotor cortex (83). The magnitude of these deficits correlates well with the degree of cognitive impairment.

View larger version (102K): [in this window] [in a new window] [Download PPT slide]   Figure 12a. FDG PET images demonstrate typical findings in (a-c) three patients with AD and (d) one patient with frontotemporal dementia. (a) Note bilateral parieto-occipital hypometabolism (arrows) in a 77-year-old woman with AD. (b) Bilateral parietal hypometabolism (arrows) is also noted in a 62-year-old woman with AD. (c) Changes may be asymmetric, as demonstrated in a 53-year-old woman with AD, with the metabolic defect (arrow) primarily on the left. (d) As shown in a patient with frontotemporal dementia, PET may help differentiate frontotemporal dementia from AD by demonstrating metabolic deficits (arrows) in the frontal and anterior temporal lobes (not shown).

View larger version (100K): [in this window] [in a new window] [Download PPT slide]   Figure 12b. FDG PET images demonstrate typical findings in (a-c) three patients with AD and (d) one patient with frontotemporal dementia. (a) Note bilateral parieto-occipital hypometabolism (arrows) in a 77-year-old woman with AD. (b) Bilateral parietal hypometabolism (arrows) is also noted in a 62-year-old woman with AD. (c) Changes may be asymmetric, as demonstrated in a 53-year-old woman with AD, with the metabolic defect (arrow) primarily on the left. (d) As shown in a patient with frontotemporal dementia, PET may help differentiate frontotemporal dementia from AD by demonstrating metabolic deficits (arrows) in the frontal and anterior temporal lobes (not shown).

View larger version (99K): [in this window] [in a new window] [Download PPT slide]   Figure 12c. FDG PET images demonstrate typical findings in (a-c) three patients with AD and (d) one patient with frontotemporal dementia. (a) Note bilateral parieto-occipital hypometabolism (arrows) in a 77-year-old woman with AD. (b) Bilateral parietal hypometabolism (arrows) is also noted in a 62-year-old woman with AD. (c) Changes may be asymmetric, as demonstrated in a 53-year-old woman with AD, with the metabolic defect (arrow) primarily on the left. (d) As shown in a patient with frontotemporal dementia, PET may help differentiate frontotemporal dementia from AD by demonstrating metabolic deficits (arrows) in the frontal and anterior temporal lobes (not shown).

View larger version (94K): [in this window] [in a new window] [Download PPT slide]   Figure 12d. FDG PET images demonstrate typical findings in (a-c) three patients with AD and (d) one patient with frontotemporal dementia. (a) Note bilateral parieto-occipital hypometabolism (arrows) in a 77-year-old woman with AD. (b) Bilateral parietal hypometabolism (arrows) is also noted in a 62-year-old woman with AD. (c) Changes may be asymmetric, as demonstrated in a 53-year-old woman with AD, with the metabolic defect (arrow) primarily on the left. (d) As shown in a patient with frontotemporal dementia, PET may help differentiate frontotemporal dementia from AD by demonstrating metabolic deficits (arrows) in the frontal and anterior temporal lobes (not shown).

Several investigators have demonstrated that FDG PET offers diagnostic value even in mild or very mild stages of AD, although sensitivity and specificity are greater in moderate to severe cases. In a study (84) with 129 cognitively impaired patients, the overall sensitivity for detecting temporoparietal hypometabolism in patients with probable AD was 94%. In patients with mild disease, the sensitivity was 87%, whereas in patients with moderate to severe disease, the sensitivity was 96%. In another study (86) with 23 patients with isolated mild memory impairment or MCI in whom a diagnosis of probable AD could not be made at the time the initial PET scan was obtained, eight patients subsequently progressed to AD over a 3.3-year follow-up. All patients demonstrated changes similar to those on scans in patients with probable AD; these changes, although less apparent, were still statistically significant.

Recent studies in asymptomatic at-risk populations have demonstrated abnormal temporoparietal uptake patterns at PET, including in asymptomatic members of families in which a familial form of early-onset AD is found (86). Furthermore, asymptomatic subjects with the apolipoprotein 4 allele, a genetic risk factor for the more common late-onset form of AD, have significantly lower temporoparietal metabolic activity than those without the allele (87).

The prognostic value of PET for predicting cognitive decline has also been evaluated. Drzezga et al (89) performed FDG PET in 15 patients with MCI at the time of protocol entry and at 1-year follow-up. In six of these patients, MCI progressed to a diagnosis of probable AD at 1 year; all six patients showed greater metabolic reduction in the posterior association cortex on the initial PET scan, compared with that on PET scans in those in whom the condition did not convert. These patients also showed a progressive metabolic reduction in the frontal association cortex over the 1-year follow-up.

Perhaps the most compelling evidence to date for the prognostic value of FDG PET for prediction of cognitive decline is provided by a recent multinational consortium study (90) conducted at eight academic institutions, with autopsy data in 138 of 284 patients evaluated for symptoms of dementia. Mean age was 66 years and mean MMSE score was 24, with a mean follow-up of 3.2 years (range, 2.0–9.4 years). All scans were interpreted as positive or negative on the basis of visual assessment of the metabolic distributions. In the group with longitudinal clinical follow-up (n = 146), progressive dementia was predicted with a high degree of sensitivity (93%) and moderate specificity (73%). Among the group with a pathologic diagnosis (n = 138), PET enabled correct identification of the presence of AD with similar sensitivity (94%) and specificity (73%). Because accurate diagnosis is most clinically relevant early in the course of the disease, a subset of patients with pathologic confirmation who were documented to have questionable or mild dementia at the time of the initial PET scan were analyzed separately. The overall sensitivity (95%) and specificity (71%) of PET in this group were similar.

In a number of blood flow and glucose metabolism PET activation studies obtained during the performance of memory tasks, decreased responses have been demonstrated in the brains of patients with AD, compared with responses in corresponding regions in control subjects (91–94). These data suggest there may be disease-related functional failure in these regions. In a number of other studies, additional areas of activation outside those seen in control subjects have been demonstrated during performance of the same task, indicating compensatory recruitment of additional brain regions and functional reallocation of brain resources (95–97).

The majority of PET studies in the memory impairment population have used FDG as a radiolabeled tracer. Most recently, a new radiolabeled tracer, known as 2-(1-{6-[(2-[¹⁸F]fluoroethyl)(methyl)amino]-2naphthyl}ethylidene)malononitrile, or [¹⁸F]FDDNP, has been developed. This tracer is reported (98) to target the amyloid ß senile plaques and neurofibrillary tangles in AD. An initial study in an 82-year-old woman with pathologically proved AD showed longer tracer retention times in the hippocampus, which corresponded to pathologically confirmed areas of plaque and tangle deposition seen at postmortem examination (98). In a subsequent study with the same tracer (99), nine patients with AD and seven control subjects demonstrated greater accumulation and slower clearance of the probe in brain areas worst affected by plaque and tangle deposition. Retention time of the tracer in brain regions known to be affected by AD is correlated with lower memory performance scores and is significantly greater in patients with AD than in control subjects (Fig 13). Additional ligands are in the preclinical development phase (100) (Fig 14).

View larger version (69K): [in this window] [in a new window] [Download PPT slide]   Figure 13. PET images comparing temporal lobe uptake of [18F]FDDNP (see text), an amyloid-binding radiotracer, and FDG, a marker of glucose metabolism, in a patient with AD (left) and a control subject (right). Note increased uptake and retention of [18F]FDDNP (arrowheads) in temporal lobes of the patient with AD, compared with those in control subject. The patient with AD still demonstrates typical findings of decreased temporal (arrows) and parietal (not shown) FDG uptake.

View larger version (193K): [in this window] [in a new window] [Download PPT slide]   Figure 14a. Transgenic mouse model of AD (tg2576). (a) Section from entorhinal cortex demonstrates in vivo labeling of amyloid plaques. Fluorescent labeling of plaques is seen after intravenous injection of (trans,trans)-1-bromo-2,5-bis-(3-hydroxycarbonyl-4-hydroxy)styrylbenzene, or BSB, an amyloid ß binding agent that crosses the blood-brain barrier. (Original magnification, x400.) (b) The same section was also immunostained with amyloid ß-specific antiserum 2332, as demonstrated in this light microscopy image. (Original magnification, x400.) (c) Digital overlay of a and b reveals high specificity of BSB plaque labeling. (Original magnification, x400.) (Adapted and reprinted, with permission, from reference 100.)

View larger version (203K): [in this window] [in a new window] [Download PPT slide]   Figure 14b. Transgenic mouse model of AD (tg2576). (a) Section from entorhinal cortex demonstrates in vivo labeling of amyloid plaques. Fluorescent labeling of plaques is seen after intravenous injection of (trans,trans)-1-bromo-2,5-bis-(3-hydroxycarbonyl-4-hydroxy)styrylbenzene, or BSB, an amyloid ß binding agent that crosses the blood-brain barrier. (Original magnification, x400.) (b) The same section was also immunostained with amyloid ß-specific antiserum 2332, as demonstrated in this light microscopy image. (Original magnification, x400.) (c) Digital overlay of a and b reveals high specificity of BSB plaque labeling. (Original magnification, x400.) (Adapted and reprinted, with permission, from reference 100.)

View larger version (199K): [in this window] [in a new window] [Download PPT slide]   Figure 14c. Transgenic mouse model of AD (tg2576). (a) Section from entorhinal cortex demonstrates in vivo labeling of amyloid plaques. Fluorescent labeling of plaques is seen after intravenous injection of (trans,trans)-1-bromo-2,5-bis-(3-hydroxycarbonyl-4-hydroxy)styrylbenzene, or BSB, an amyloid ß binding agent that crosses the blood-brain barrier. (Original magnification, x400.) (b) The same section was also immunostained with amyloid ß-specific antiserum 2332, as demonstrated in this light microscopy image. (Original magnification, x400.) (c) Digital overlay of a and b reveals high specificity of BSB plaque labeling. (Original magnification, x400.) (Adapted and reprinted, with permission, from reference 100.)

Because this technique is relatively new, only a few studies have been performed in patients with dementia. Nevertheless, it has been shown that MR perfusion measurements of cerebral blood volume closely parallel changes in cerebral metabolic rate of glucose consumption as determined with PET in patients with dementia and may be a lower cost alternative to PET (103). Harris et al (104,105) originally reported a 17% average reduction in temporoparietal cerebral blood volume, with 88.5% accuracy for correct categorization of 13 patients with AD and 13 control subjects. Maas et al (106) examined 16 patients with probable AD and 16 control subjects and found the technique to be 81% sensitive and 88% specific. More recently, the sensitivity and specificity of MR perfusion imaging have been shown to be superior to those of cerebral SPECT, with sensitivities in the 87%–95% range for patients with mild or moderate AD and specificities of 88%–95% in control subjects (104,107). To our knowledge, studies have yet to be performed in patients with various forms of dementia, patients with MCI, and presymptomatic patients at genetic risk for future development of AD.

Functional MR Imaging
Functional MR imaging has proved to be a powerful research technique to aid in identifying regions of brain activated by particular stimuli and tasks. With this technique, regional brain activity is measured on the basis of local changes in deoxyhemoglobin concentration in response to various stimuli and tasks (109). In brief, rapid T2*-sensitive imaging, usually gradient-echo echo-planar imaging, is performed during presentation of a stimulus or performance of a specific task and during rest periods. A voxel-by-voxel statistical comparison is then performed with images obtained during the stimulus/task periods versus those obtained during the rest periods, creating a statistical-activation map that can be "thresholded" and presented as a color overlay on anatomic T1-weighted images. Because functional MR imaging does not use ionizing radiation, it can be applied repeatedly in the same patients without risk. Although not currently used in the routine work-up of patients with memory disorders, the technique offers considerable potential in early identification of patients with prodromal dementia. We will first discuss functional MR imaging studies of normal memory. This will be followed by discussion of studies in patients with memory impairment.

Functional MR imaging activation patterns during various memory tasks have been studied in healthy volunteers. Two main groups of structures involved in working memory and secondary memory include the prefrontal cortex and the medial temporal lobe. Hence, these regions have been the focus of prior functional MR imaging studies of normal memory. In prior functional MR imaging studies (109–114), the prefrontal cortex has consistently been found to be involved in learning and recall. In these studies, specific regions or hemispheres have been localized on the basis of the cognitive paradigm used. Activation in the prefrontal cortex is greater with increasing memory loads (109) and is more pronounced during initial, as opposed to repeated, attempts at learning (113). Increased activation during learning is associated with more successful subsequent recall (113,114).

Authors of functional MR imaging studies have also documented the role of the medial temporal lobe in learning and recall. The medial temporal lobe structures most often implicated in these studies are the hippocampus and the parahippocampal cortex (115). Another area in the medial temporal lobe, the fusiform gyrus (lateral temporo-occipital cortex), is involved in the processing of faces (116).

There have been a number of recent functional MR imaging studies related to early AD, the results of which are summarized in Table 2. In the majority of these studies, diminished intensity and/or extent of activation has been demonstrated in the frontal and temporal regions in patients with AD, as compared with those in control subjects, when performance has been controlled for. Studies in which "at-risk" populations were examined have shown mixed results with increased (117) or decreased (123,124) activation in the at-risk group, as compared with activation in a control group. Authors of the studies in which increased activation was seen in the AD or at-risk groups explain their findings in terms of a compensatory-recruitment hypothesis, in which greater cognitive effort is required to perform the same task as compared with that required by a control group (Fig 15). This hypothesis presumes there is enough healthy neural tissue present to accommodate the task. In the presence of substantial neuronal loss, as may be seen when clinical manifestations of memory loss are present, decreases in activation may result (117). Such decreases may be seen only in tasks that make sufficiently high demands to exceed the subject’s compensatory reserve.

View larger version (111K): [in this window] [in a new window] [Download PPT slide]   Figure 15. Brain activation maps obtained during memory-activation task in patients at genetic risk for AD (carriers of apolipoprotein [Apo] 4 allele) compared with control subjects (apolipoprotein 3 carriers). Three-dimensional renditions of the brain surface are shown in gray, and colored areas indicate regions of significantly increased MR signal intensity during performance of memory task as compared with that during resting periods. Activation is seen in temporal and frontal regions in both groups; however, both the extent and intensity of activation are greater among the genetic risk group, which suggests compensatory brain function. (Adapted and reprinted, with permission, from reference 117.)

MR Spectroscopy
Proton MR spectroscopy is an application of MR that allows noninvasive assessment of a number of local metabolite levels in brain tissue (125). Proton MR spectroscopy allows in vivo assessment of N-acetylaspartate (NAA), glutamine and glutamate, -aminobutyric acid, myo-inositol, glycine, mobile choline moieties, creatine and phosphocreatine, lipids, and lactate. NAA is present primarily in neurons within the central nervous system but not in glial cells or other nonneuronal tissue. Although the exact metabolism of NAA remains unclear, NAA is generally thought to represent a marker of neuronal function (125,126). The NAA level is decreased in cases of neuronal loss or damage yet may return to normal levels during recovery. Elevated myo-inositol levels may mark gliosis, membrane dysfunction, and/or cytoskeletal abnormalities. Elevated choline levels may reflect cellular proliferation, as in neoplasia, or myelin breakdown. Most studies in the dementia population have used a single-voxel approach (125); however, multivoxel spectroscopic imaging techniques, known as chemical shift imaging, are also available (127).

In several in vitro studies (128–131) on postmortem brains, decreases in NAA levels have been demonstrated in patients with AD, as compared with levels in controls. Moreover, there has been a positive correlation between the magnitude of NAA decreases and the severity of neuropathologic findings (eg, counts of amyloid plaques and neurofibrillary tangles) (128,131). Similarly, in vivo studies (132–135) have also demonstrated decreases in NAA in patients with AD in both the temporal and parietal lobes. In some studies (136,137), higher choline levels have been demonstrated in the brains of patients with AD; however, these results have been inconsistent. myo-Inositol levels have been shown to be elevated in most studies (134,138–142), although myo-inositol levels may be confounded by a number of other coexisting disease processes (143–146) (Fig 16).

View larger version (104K): [in this window] [in a new window] [Download PPT slide]   Figure 16a. Multivoxel MR spectroscopic imaging in (a) a 62-year-old healthy volunteer and (b) an 80-year-old patient with AD. Sample spectra are shown from right temporal lobe (bottom left), left insula (top right) and left thalamus (bottom right). Note the increase in myo-inositol (Ino) and choline (Cho) levels and the decrease in NAA level (short arrows in b) in the right temporal lobe of the patient with AD, compared with those levels in the healthy volunteer, suggesting the presence of gliosis, increased membrane turnover, and neuronal loss in AD. (P)Cre = creatine and phosphocreatine. (Images courtesy of H. Cecil Charles, PhD, Duke University Medical Center, Durham, NC.)

View larger version (74K): [in this window] [in a new window] [Download PPT slide]   Figure 16b. Multivoxel MR spectroscopic imaging in (a) a 62-year-old healthy volunteer and (b) an 80-year-old patient with AD. Sample spectra are shown from right temporal lobe (bottom left), left insula (top right) and left thalamus (bottom right). Note the increase in myo-inositol (Ino) and choline (Cho) levels and the decrease in NAA level (short arrows in b) in the right temporal lobe of the patient with AD, compared with those levels in the healthy volunteer, suggesting the presence of gliosis, increased membrane turnover, and neuronal loss in AD. (P)Cre = creatine and phosphocreatine. (Images courtesy of H. Cecil Charles, PhD, Duke University Medical Center, Durham, NC.)

With regard to patients at risk for AD, the results of one study (140) have shown NAA and myo-inositol metabolite levels in patients with MCI to be between those of cognitively normal subjects and patients with AD. Patients who are positive for the apolipoprotein 4 allele tend to demonstrate similar findings prior to the onset of dementia or notable anatomic changes (unpublished data, 2002). Longitudinal evaluation may play an important role in determining prognosis and evaluating treatment in such at-risk groups of patients. Also, MR spectroscopic measures have been shown to be predictors of cognitive scores at 1-year follow-up (147). In addition, at least two controlled studies have used MR spectroscopy to monitor treatment effects in AD. Decreases in the choline-to–creatine and phosphocreatine ratio have been demonstrated in response to xanomeline, a muscarinic agonist; and decreases in the myo-inositol–to-NAA ratio have been seen in response to donepezil, a cholinesterase inhibitor (148,149). Doraiswamy et al (125) recently published a comprehensive review of the role of MR spectroscopy in dementia drug development and have also reviewed all the central nervous system drug trials in which MR spectroscopic results were used as an outcome measure. They concluded that MR spectroscopic measures of NAA, when combined with hippocampal volumetry, could provide highly useful surrogate markers of AD progression in trials of neuroprotective agents.

Diffusion-weighted MR Imaging
Diffusion-weighted MR imaging is a technique that is sensitive to the microscopic motion of water molecules in tissue. Its primary applications have been in the evaluation of acute cerebral ischemia. The technique has also been applied to the study of patients with AD (150–152). Most recently, Kantarci et al (153) studied various brain regions including the medial temporal lobes in a group of 19 patients with MCI, 21 with AD, and 55 age-matched control subjects. They used an index of mean diffusibility: the apparent diffusion coefficient. Confirming and expanding on the results of previous work, Kantarci et al demonstrated statistically significant differences in mean diffusibility between the AD group and the control group in a number of brain regions, most notably the hippocampus, and in temporal, cingulate, and parietal white matter. Although statistically significant differences were found only for the hippocampus, values in the MCI group were between those in the AD group and the control group for all regions studied. The authors postulated that pathologic destruction of cell membranes, with subsequent loss of myelin and axonal processes due to wallerian degeneration, lessens the restriction of water diffusion in the hippocampus and afferent white matter tracts. Such pathologic changes are manifested by an increased apparent diffusion coefficient in these regions. The value of diffusion-weighted MR imaging as a diagnostic tool is still in question, however. Kantarci et al found that at a fixed specificity of 80%, the sensitivity was only 57% for distinguishing patients with AD from control subjects by using the hippocampal apparent diffusion coefficient.

Diffusion tensor MR imaging is a more advanced application of diffusion-weighted imaging; diffusion tensor imaging enables measurement of the directionality or asymmetry of microscopic water movement in tissue (154). Such asymmetric diffusion, known as anisotropy, is seen in normal white matter, owing to the integrity of white matter tracts that preferentially allows diffusion of water parallel, rather than perpendicular, to the tracts. Primary applications of this technique are in the evaluation of cerebral white matter tracts (155). Recently, the technique has been applied in human studies of AD (156). So far, results demonstrate a statistically significant reduction in white matter integrity throughout the brain, with relative sparing of the motor tracts, reflecting the known pathologic and clinical findings in AD.

	PREDICTION AND EARLY DIAGNOSIS: THE FUTURE

TOP ABSTRACT INTRODUCTION PATHOLOGY AND ETIOLOGY PATHOLOGIC DIAGNOSIS CLINICAL DIAGNOSIS ROLE OF STRUCTURAL NEUROIMAGING... ROLE OF FUNCTIONAL NEUROIMAGING PREDICTION AND EARLY DIAGNOSIS:... REFERENCES

 
For differential diagnosis in the patient with dementia, during the middle or late stages of the disease the current clinical criteria have a high sensitivity and specificity for determination of AD. Thus, the future role of imaging in patients with dementia at these stages will likely remain to help exclude other causes of dementia. The American Academy of Neurology Quality Standards Subcommittee recently published evidence-based practice parameters for the diagnosis, management, and early detection of dementia (157–159). Current imaging recommendations for the initial evaluation of patients with dementia include nonenhanced CT or MR imaging; however, because of insufficient data on validity, no other imaging procedure is recommended in these guidelines. The subcommittee recommended further research to determine the utility of other neuroimaging modalities in the work-up of the patient with dementia (157).

PET is currently used primarily as an adjunct to clinical diagnosis, especially in differentiating AD from vascular dementia and other focal dementias such as frontal lobe dementia. Given the growing evidence, PET will likely come to the forefront both as a diagnostic tool and as a prognostic tool. This will be especially true if amyloid imaging becomes standardized and widely available. Reimbursement issues remain a problem with PET, and it is hoped scientific advances will be recognized by third-party payers.

For determination of preclinical or early-stage disease, imaging will play an increasingly greater role in the future, especially as new agents to delay the onset of dementia become available. As clinical trial results confirm the efficacy of new therapeutic agents and as combination therapies are used, earlier and more accurate diagnoses will become more crucial. The at-risk patient with MCI may also be considered for treatment options that might alter the rate of progression to dementia. No specific neuroimaging protocol is recommended in this group at present (159), although more sensitive functional imaging techniques, as well as subtraction MR imaging, seem to be logical candidates. FDG PET has demonstrated the highest prognostic utility for providing a diagnosis of AD 2–3 years before the full dementia-related symptoms manifest (160). The role of SPECT in this regard remains less promising. Further longitudinal studies must be developed to examine the predictive power of these functional techniques in order to determine which patients will ultimately develop AD. Most likely, the answer will be a battery of tests that combine functional and structural imaging with clinical, genetic, and other laboratory data (161).

The major goals in treating AD currently are to recognize the disease early in order to initiate appropriate therapy and delay functional and cognitive losses. In addition, as powerful antiamyloid therapies are developed, there will be a need to monitor brain changes and treatment efficacy at the earliest stages of the disease, perhaps even in prodromal patients. It is hoped that the widespread availability of newer MR and PET markers will supplement the strengths of the currently available structural and functional imaging techniques in helping to achieve these goals.

	ACKNOWLEDGMENTS

 
The authors thank Haris Sair, BS, and Sarah Hart, BS, for their assistance in preparing tables and figures, and Christine Hulette, MD, for consultation on neuropathologic criteria.

	FOOTNOTES

 
Abbreviations: AD = Alzheimer disease, FDG = fluorodeoxyglucose, MCI = mild cognitive impairment, MMSE = Mini-Mental State Examination, NAA = N-acetylaspartate

	REFERENCES

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