Amyloid Imaging: Poised for Integration into Medical Practice

Clinical use of biomarkers in the era of Alzheimer's disease treatments

With the advent of treatments that specifically target Alzheimer's disease brain pathology, biomarker tests will become an increasingly important part of the routine clinical evaluation of cognitive impairment and guide clinical decision making. Clinicians must ensure they are using accurate and well-validated biomarker tests and select the most appropriate testing modality for each patient based on individual and practical considerations. The interpretation of test results may be complex and depends on the pre-test probability and test-specific factors. Biomarker results must be presented and discussed with patients in a process that is sensitive to the major implications of the results and is carefully connected to diagnosis, prognosis, and management. Advances in treatments for Alzheimer's disease will likely require non-dementia specialists to use biomarkers, necessitating major educational efforts. In the new era of Alzheimer's disease treatments, biomarkers are essential tools that will be integrated into all aspects of dementia diagnosis and care.

Memories and mimics: unveiling the potential of FDG-PET in guiding therapeutic approaches for neurodegenerative cognitive disorders

Fluorodeoxyglucose F18 (FDG) positron emission tomography (PET) imaging can help clinicians pursue the differential diagnosis of various neurodegenerative diseases. It has become an invaluable diagnostic tool in routine clinical practice in conjunction with computed tomography (CT) imaging, magnetic resonance imaging (MRI), and biomarker studies. We present a single-institution case series and systematic literature review, showing how FDG-PET imaging has helped physicians diagnose neurodegenerative diseases and their mimickers and how patient care was amended. A single institution analysis and comprehensive literature search were completed following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. These medical subjects' headings (MeSH) terms were used: "FDG-PET" AND "dementia" OR "Alzheimer's" OR "neurodegeneration" OR "frontotemporal dementia" OR "atypical parkinsonian syndrome" OR "primary progressive aphasia" OR "lewy body dementia." The inclusion criteria included studies with uncertain diagnoses of neurocognitive disease resolved with FDG-PET, PET/MRI, or PET/CT hybrid imaging. A literature search resulted in 3,976 articles. After considering inclusion and exclusion criteria, 14 case reports and 1 case series were selected, representing 19 patients. The average age of patients was 70.8 years (range: 54-83 years). Five of the 19 patients were females. Dementia with Lewy bodies (DLB) had the highest propensity for being misidentified as another neurodegenerative disease, followed by Alzheimer's disease (AD) and frontotemporal dementia (FTD). Without accurate molecular imaging, neurodegenerative diseases may be missed or misdiagnosed. Our single-institution case series and literature review demonstrate how FDG-PET brain imaging can be used to correct and clarify preexisting clinical diagnoses of neurodegenerative disease.

Acceptable performance of blood biomarker tests of amyloid pathology - recommendations from the Global CEO Initiative on Alzheimer's Disease

Anti-amyloid treatments for early symptomatic Alzheimer disease have recently become clinically available in some countries, which has greatly increased the need for biomarker confirmation of amyloid pathology. Blood biomarker (BBM) tests for amyloid pathology are more acceptable, accessible and scalable than amyloid PET or cerebrospinal fluid (CSF) tests, but have highly variable levels of performance. The Global CEO Initiative on Alzheimer's Disease convened a BBM Workgroup to consider the minimum acceptable performance of BBM tests for clinical use. Amyloid PET status was identified as the reference standard. For use as a triaging test before subsequent confirmatory tests such as amyloid PET or CSF tests, the BBM Workgroup recommends that a BBM test has a sensitivity of ≥90% with a specificity of ≥85% in primary care and ≥75-85% in secondary care depending on the availability of follow-up testing. For use as a confirmatory test without follow-up tests, a BBM test should have performance equivalent to that of CSF tests - a sensitivity and specificity of ~90%. Importantly, the predictive values of all biomarker tests vary according to the pre-test probability of amyloid pathology and must be interpreted in the complete clinical context. Use of BBM tests that meet these performance standards could enable more people to receive an accurate and timely Alzheimer disease diagnosis and potentially benefit from new treatments.

Comparison of consistency in centiloid scale among different analytical methods in amyloid PET: the CapAIBL, VIZCalc, and Amyquant methods

OBJECTIVE

The Centiloid (CL) scale is a standardized measure for quantifying amyloid deposition in amyloid positron emission tomography (PET) imaging. We aimed to assess the agreement among 3 CL calculation methods: CapAIBL, VIZCalc, and Amyquant.

METHODS

This study included 192 participants (mean age: 71.5 years, range: 50-87 years), comprising 55 with Alzheimer's disease, 65 with mild cognitive impairment, 13 with non-Alzheimer's dementia, and 59 cognitively normal participants. All the participants were assessed using the three CL calculation methods. Spearman's rank correlation, linear regression, Friedman tests, Wilcoxon signed-rank tests, and Bland-Altman analysis were employed to assess data correlations, linear associations, method differences, and systematic bias, respectively.

RESULTS

Strong correlations (rho = 0.99, p < .001) were observed among the CL values calculated using the three methods. Scatter plots and regression lines visually confirmed these strong correlations and met the validation criteria. Despite the robust correlations, a significant difference in CL value between CapAIBL and Amyquant was observed (36.1 ± 39.7 vs. 34.9 ± 39.4; p < .001). In contrast, no significant differences were found between CapAIBL and VIZCalc or between VIZCalc and Amyquant. The Bland-Altman analysis showed no observable systematic bias between the methods.

CONCLUSIONS

The study demonstrated strong agreement among the three methods for calculating CL values. Despite minor variations in the absolute values of the Centiloid scores obtained using these methods, the overall agreement suggests that they are interchangeable.

Clinical and Neuroimaging Predictors of Alzheimer's Dementia Conversion in Patients with Mild Cognitive Impairment Using Amyloid Positron Emission Tomography by Quantitative Analysis over 2 Years

Patients with mild cognitive impairment (MCI) have a relatively high risk of developing Alzheimer's dementia (AD), so early identification of the risk for AD conversion can lessen the socioeconomic burden. In this study, 18F-Florapronol, newly developed in Korea, was used for qualitative and quantitative analyses to assess amyloid positivity. We also investigated the clinical predictors of the progression from MCI to dementia over 2 years. From December 2019 to December 2022, 50 patients with MCI were recruited at a single center, and 34 patients were included finally. Based on visual analysis, 13 (38.2%) of 34 participants were amyloid-positive, and 12 (35.3%) were positive by quantitative analysis. Moreover, 6 of 34 participants (17.6%) converted to dementia after a 2-year follow-up (p = 0.173). Among the 15 participants who were positive for amyloid in the posterior cingulate region, 5 (33.3%) patients developed dementia (p = 0.066). The Clinical Dementia Rating-Sum of Boxes (CDR-SOB) at baseline was significantly associated with AD conversion in multivariate Cox regression analyses (p = 0.043). In conclusion, these results suggest that amyloid positivity in the posterior cingulate region and higher CDR-SOB scores at baseline can be useful predictors of AD conversion in patients with MCI.

Classifying Alzheimer's Disease Neuropathology Using Clinical and MRI Measurements

Background

Computer-aided machine learning models are being actively developed with clinically available biomarkers to diagnose Alzheimer's disease (AD) in living persons. Despite considerable work with cross-sectional in vivo data, many models lack validation against postmortem AD neuropathological data.

Objective

Train machine learning models to classify the presence or absence of autopsy-confirmed severe AD neuropathology using clinically available features.

Methods

AD neuropathological status are assessed at postmortem for participants from the National Alzheimer's Coordinating Center (NACC). Clinically available features are utilized, including demographics, Apolipoprotein E(APOE) genotype, and cortical thicknesses derived from ante-mortem MRI scans encompassing AD meta regions of interest (meta-ROI). Both logistic regression and random forest models are trained to identify linearly and nonlinearly separable features between participants with the presence (N = 91, age-at-MRI = 73.6±9.24, 38 women) or absence (N = 53, age-at-MRI = 68.93±19.69, 24 women) of severe AD neuropathology. The trained models are further validated in an external data set against in vivo amyloid biomarkers derived from PET imaging (amyloid-positive: N = 71, age-at-MRI = 74.17±6.37, 26 women; amyloid-negative: N = 73, age-at-MRI = 71.59±6.80, 41 women).

Results

Our models achieve a cross-validation accuracy of 84.03% in classifying the presence or absence of severe AD neuropathology, and an external-validation accuracy of 70.14% in classifying in vivo amyloid positivity status.

Conclusions

Our models show that clinically accessible features, including APOE genotype and cortical thinning encompassing AD meta-ROIs, are able to classify both postmortem confirmed AD neuropathological status and in vivo amyloid status with reasonable accuracies. These results suggest the potential utility of AD meta-ROIs in determining AD neuropathological status in living persons.

The Major Hypotheses of Alzheimer's Disease: Related Nanotechnology-Based Approaches for Its Diagnosis and Treatment

Alzheimer's disease (AD) is a well-known chronic neurodegenerative disorder that leads to the progressive death of brain cells, resulting in memory loss and the loss of other critical body functions. In March 2019, one of the major pharmaceutical companies and its partners announced that currently, there is no drug to cure AD, and all clinical trials of the new ones have been cancelled, leaving many people without hope. However, despite the clear message and startling reality, the research continued. Finally, in the last two years, the Food and Drug Administration (FDA) approved the first-ever medications to treat Alzheimer's, aducanumab and lecanemab. Despite researchers' support of this decision, there are serious concerns about their effectiveness and safety. The validation of aducanumab by the Centers for Medicare and Medicaid Services is still pending, and lecanemab was authorized without considering data from the phase III trials. Furthermore, numerous reports suggest that patients have died when undergoing extended treatment. While there is evidence that aducanumab and lecanemab may provide some relief to those suffering from AD, their impact remains a topic of ongoing research and debate within the medical community. The fact is that even though there are considerable efforts regarding pharmacological treatment, no definitive cure for AD has been found yet. Nevertheless, it is strongly believed that modern nanotechnology holds promising solutions and effective clinical strategies for the development of diagnostic tools and treatments for AD. This review summarizes the major hallmarks of AD, its etiological mechanisms, and challenges. It explores existing diagnostic and therapeutic methods and the potential of nanotechnology-based approaches for recognizing and monitoring patients at risk of irreversible neuronal degeneration. Overall, it provides a broad overview for those interested in the evolving areas of clinical neuroscience, AD, and related nanotechnology. With further research and development, nanotechnology-based approaches may offer new solutions and hope for millions of people affected by this devastating disease.

Should artificial intelligence be used in conjunction with Neuroimaging in the diagnosis of Alzheimer's disease?

Alzheimer's disease (AD) is a progressive, neurodegenerative disorder that affects memory, thinking, behavior, and other cognitive functions. Although there is no cure, detecting AD early is important for the development of a therapeutic plan and a care plan that may preserve cognitive function and prevent irreversible damage. Neuroimaging, such as magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET), has served as a critical tool in establishing diagnostic indicators of AD during the preclinical stage. However, as neuroimaging technology quickly advances, there is a challenge in analyzing and interpreting vast amounts of brain imaging data. Given these limitations, there is great interest in using artificial Intelligence (AI) to assist in this process. AI introduces limitless possibilities in the future diagnosis of AD, yet there is still resistance from the healthcare community to incorporate AI in the clinical setting. The goal of this review is to answer the question of whether AI should be used in conjunction with neuroimaging in the diagnosis of AD. To answer the question, the possible benefits and disadvantages of AI are discussed. The main advantages of AI are its potential to improve diagnostic accuracy, improve the efficiency in analyzing radiographic data, reduce physician burnout, and advance precision medicine. The disadvantages include generalization and data shortage, lack of in vivo gold standard, skepticism in the medical community, potential for physician bias, and concerns over patient information, privacy, and safety. Although the challenges present fundamental concerns and must be addressed when the time comes, it would be unethical not to use AI if it can improve patient health and outcome.

19F Solid-state NMR characterization of pharmaceutical solids

Solid-state NMR has been increasingly recognized as a high-resolution and versatile spectroscopic tool to characterize drug substances and products. However, the analysis of pharmaceutical materials is often carried out at natural isotopic abundance and a relatively low drug loading in multi-component systems and therefore suffers from challenges of low sensitivity. The fact that fluorinated therapeutics are well represented in pipeline drugs and commercial products offers an excellent opportunity to utilize fluorine as a molecular probe for pharmaceutical analysis. We aim to review recent advancements of ¹⁹F magic angle spinning NMR methods in modern drug research and development. Applications to polymorph screening at the micromolar level, structural elucidation, and investigation of molecular interactions at the Ångström to submicron resolution in drug delivery, stability, and quality will be discussed.

Dissecting the clinical heterogeneity of early-onset Alzheimer's disease

Early-onset Alzheimer's disease (EOAD) is a rare but particularly devastating form of AD. Though notable for its high degree of clinical heterogeneity, EOAD is defined by the same neuropathological hallmarks underlying the more common, late-onset form of AD. In this review, we describe the various clinical syndromes associated with EOAD, including the typical amnestic phenotype as well as atypical variants affecting visuospatial, language, executive, behavioral, and motor functions. We go on to highlight advances in fluid biomarker research and describe how molecular, structural, and functional neuroimaging can be used not only to improve EOAD diagnostic acumen but also enhance our understanding of fundamental pathobiological changes occurring years (and even decades) before the onset of symptoms. In addition, we discuss genetic variation underlying EOAD, including pathogenic variants responsible for the well-known mendelian forms of EOAD as well as variants that may increase risk for the much more common forms of EOAD that are either considered to be sporadic or lack a clear autosomal-dominant inheritance pattern. Intriguingly, specific pathogenic variants in PRNP and MAPT-genes which are more commonly associated with other neurodegenerative diseases-may provide unexpectedly important insights into the formation of AD tau pathology. Genetic analysis of the atypical clinical syndromes associated with EOAD will continue to be challenging given their rarity, but integration of fluid biomarker data, multimodal imaging, and various 'omics techniques and their application to the study of large, multicenter cohorts will enable future discoveries of fundamental mechanisms underlying the development of EOAD and its varied clinical presentations.

Deciphering the contributions of neuroinflammation to neurodegeneration: lessons from antibody-mediated encephalitis and coronavirus disease 2019

PURPOSE OF REVIEW

Does neuroinflammation promote neurodegeneration? Does neurodegeneration promote neuroinflammation? Or, is the answer to both questions, yes? These questions have proven challenging to answer in patients with typical age-related neurodegenerative diseases in whom the onset of neuroinflammation and neurodegeneration are largely unknown. Patients recovering from diseases associated with abrupt-onset neuroinflammation, including rare forms of antibody-mediated encephalitis (AME) and common complications of novel coronavirus disease 2019 (COVID-19), provide a unique opportunity to untangle the relationship between neuroinflammation and neurodegeneration. This review explores the lessons learned from patients with AME and COVID-19.

RECENT FINDINGS

Persistent cognitive impairment is increasingly recognized in patients recovering from AME or COVID-19, yet the drivers of impairment remain largely unknown. Clinical observations, neuroimaging and biofluid biomarkers, and pathological studies imply a link between the severity of acute neuroinflammation, subsequent neurodegeneration, and disease-associated morbidity.

SUMMARY

Data from patients with AME and COVID-19 inform key hypotheses that may be evaluated through future studies incorporating longitudinal biomarkers of neuroinflammation and neurodegeneration in larger numbers of recovering patients. The results of these studies may inform the contributors to cognitive impairment in patients with AME and COVID-19, with potential diagnostic and therapeutic applications in patients with age-related neurodegenerative diseases.

Practical recommendations for timely, accurate diagnosis of symptomatic Alzheimer's disease (MCI and dementia) in primary care: a review and synthesis

The critical role of primary care clinicians (PCCs) in Alzheimer's disease (AD) prevention, diagnosis and management must evolve as new treatment paradigms and disease-modifying therapies (DMTs) emerge. Our understanding of AD has grown substantially: no longer conceptualized as a late-in-life syndrome of cognitive and functional impairments, we now recognize that AD pathology builds silently for decades before cognitive impairment is detectable. Clinically, AD first manifests subtly as mild cognitive impairment (MCI) due to AD before progressing to dementia. Emerging optimism for improved outcomes in AD stems from a focus on preventive interventions in midlife and timely, biomarker-confirmed diagnosis at early signs of cognitive deficits (i.e. MCI due to AD and mild AD dementia). A timely AD diagnosis is particularly important for optimizing patient care and enabling the appropriate use of anticipated DMTs. An accelerating challenge for PCCs and AD specialists will be to respond to innovations in diagnostics and therapy for AD in a system that is not currently well positioned to do so. To overcome these challenges, PCCs and AD specialists must collaborate closely to navigate and optimize dynamically evolving AD care in the face of new opportunities. In the spirit of this collaboration, we summarize here some prominent and influential models that inform our current understanding of AD. We also advocate for timely and accurate (i.e. biomarker-defined) diagnosis of early AD. In doing so, we consider evolving issues related to prevention, detecting emerging cognitive impairment and the role of biomarkers in the clinic.

Neurotoxic Soluble Amyloid Oligomers Drive Alzheimer's Pathogenesis and Represent a Clinically Validated Target for Slowing Disease Progression

A large body of clinical and nonclinical evidence supports the role of neurotoxic soluble beta amyloid (amyloid, Aβ) oligomers as upstream pathogenic drivers of Alzheimer's disease (AD). Recent late-stage trials in AD that have evaluated agents targeting distinct species of Aβ provide compelling evidence that inhibition of Aβ oligomer toxicity represents an effective approach to slow or stop disease progression: (1) only agents that target soluble Aβ oligomers show clinical efficacy in AD patients; (2) clearance of amyloid plaque does not correlate with clinical improvements; (3) agents that predominantly target amyloid monomers or plaque failed to show clinical effects; and (4) in positive trials, efficacy is greater in carriers of the ε4 allele of apolipoprotein E (APOE4), who are known to have higher brain concentrations of Aβ oligomers. These trials also show that inhibiting Aβ neurotoxicity leads to a reduction in tau pathology, suggesting a pathogenic sequence of events where amyloid toxicity drives an increase in tau formation and deposition. The late-stage agents with positive clinical or biomarker data include four antibodies that engage Aβ oligomers (aducanumab, lecanemab, gantenerumab, and donanemab) and ALZ-801, an oral agent that fully blocks the formation of Aβ oligomers at the clinical dose.

Neuroimaging advances regarding subjective cognitive decline in preclinical Alzheimer's disease

Subjective cognitive decline (SCD) is regarded as the first clinical manifestation in the Alzheimer’s disease (AD) continuum. Investigating populations with SCD is important for understanding the early pathological mechanisms of AD and identifying SCD-related biomarkers, which are critical for the early detection of AD. With the advent of advanced neuroimaging techniques, such as positron emission tomography (PET) and magnetic resonance imaging (MRI), accumulating evidence has revealed structural and functional brain alterations related to the symptoms of SCD. In this review, we summarize the main imaging features and key findings regarding SCD related to AD, from local and regional data to connectivity-based imaging measures, with the aim of delineating a multimodal imaging signature of SCD due to AD. Additionally, the interaction of SCD with other risk factors for dementia due to AD, such as age and the Apolipoprotein E (ApoE) ɛ4 status, has also been described. Finally, the possible explanations for the inconsistent and heterogeneous neuroimaging findings observed in individuals with SCD are discussed, along with future directions. Overall, the literature reveals a preferential vulnerability of AD signature regions in SCD in the context of AD, supporting the notion that individuals with SCD share a similar pattern of brain alterations with patients with mild cognitive impairment (MCI) and dementia due to AD. We conclude that these neuroimaging techniques, particularly multimodal neuroimaging techniques, have great potential for identifying the underlying pathological alterations associated with SCD. More longitudinal studies with larger sample sizes combined with more advanced imaging modeling approaches such as artificial intelligence are still warranted to establish their clinical utility.

Molecular Imaging of Fluorinated Probes for Tau Protein and Amyloid-β Detection

Alzheimer’s disease (AD) is the most common form of dementia and results in progressive neurodegeneration. The incidence rate of AD is increasing, creating a major public health issue. AD is characterized by neurofibrillary tangles (NFTs) composed of hyperphosphorylated tau protein and senile plaques composed of amyloid-β (Aβ). Currently, a definitive diagnosis of AD is accomplished post-mortem. Thus, the use of molecular probes that are able to selectively bind to NFTs or Aβ can be valuable tools for the accurate and early diagnosis of AD. The aim of this review is to summarize and highlight fluorinated molecular probes that can be used for molecular imaging to detect either NFTs or Aβ. Specifically, fluorinated molecular probes used in conjunction with ¹⁹F MRI, PET, and fluorescence imaging will be explored.

Concordance of Lumipulse cerebrospinal fluid t-tau/Aβ42 ratio with amyloid PET status

INTRODUCTION

Cerebrospinal fluid (CSF) biomarkers can identify individuals with Alzheimer's disease (AD) pathology (eg, amyloid plaques, neurofibrillary tangles), but defined analyte cut-points using high-throughput automated assays are necessary for general clinical use.

METHODS

CSF amyloid β42 peptide (Aβ42), t-tau, and t-tau/Aβ42 were quantified by the Lumipulse platform in two test cohorts (A/B: Eisai BAN2401-201/MISSION AD E2609-301/302, n = 138; C: Knight Alzheimer's Disease Research Center (ADRC), n = 198), and receiver operating characteristic (ROC) curve analyses defined cut-points corresponding best to amyloid determinations using positron emission tomography (PET) imaging. The best-performing cut-point was then validated as a predictor of amyloid status in an independent cohort (D: MISSION AD E2609-301/302, n = 240).

RESULTS

Virtually identical t-tau/Aβ42 cut-points (∼0.54) performed best in both test cohorts and with similar accuracy (areas under ROC curve [AUCs] [A/B: 0.95; C: 0.94]). The cut-point yielded an overall percent agreement with amyloid PET of 85.0% in validation cohort D.

DISCUSSION

Lumipulse CSF biomarker measures with validated cut-points have clinical utility in identifying AD pathology.

The Who, When, Why, and How of PET Amyloid Imaging in Management of Alzheimer's Disease-Review of Literature and Interesting Images

Amyloid imaging using positron emission tomography (PET) has an emerging role in the management of Alzheimer’s disease (AD). The basis of this imaging is grounded on the fact that the hallmark of AD is the histological detection of beta amyloid plaques (Aβ) at post mortem autopsy. Currently, there are three FDA approved amyloid radiotracers used in clinical practice. This review aims to take the readers through the array of various indications for performing amyloid PET imaging in the management of AD, particularly using 18F-labelled radiopharmaceuticals. We elaborate on PET amyloid scan interpretation techniques, their limitations and potential improved specificity provided by interpretation done in tandem with genetic data such as apolipiprotein E (APO) 4 carrier status in sporadic cases and molecular information (e.g., cerebral spinal fluid (CSF) amyloid levels). We also describe the quantification methods such as the standard uptake value ratio (SUVr) method that utilizes various cutoff points for improved accuracy of diagnosing AD, such as a threshold of 1.122 (area under the curve 0.894), which has a sensitivity of 92.3% and specificity of 90.5%, whereas the cutoff points may be higher in APOE ε4 carriers (1.489) compared to non-carriers (1.313). Additionally, recommendations for future developments in this field are also provided.

Alzheimer's disease

Alzheimer's disease (AD) dementia refers to a particular onset and course of cognitive and functional decline associated with age together with a particular neuropathology. It was first described by Alois Alzheimer in 1906 about a patient whom he first encountered in 1901. Modern clinical diagnostic criteria have been developed, and criteria have also been proposed to recognize preclinical (or presymptomatic) stages of the disease with the use of biomarkers. The primary neuropathology was described by Alzheimer, and in the mid-1980s subsequently evolved into a more specific neuropathologic definition that recognizes the comorbid neuropathologies that frequently contribute to clinical dementia. Alzheimer's disease is now the most common form of neurodegenerative dementia in the United States with a disproportionate disease burden in minority populations. Deficits in the ability to encode and store new memories characterizes the initial stages of the disease. Subsequent progressive changes in cognition and behavior accompany the later stages. Changes in amyloid precursor protein (APP) cleavage and production of the APP fragment beta-amyloid (Aβ) along with hyperphosphorylated tau protein aggregation coalesce to cause reduction in synaptic strength, synaptic loss, and neurodegeneration. Metabolic, vascular, and inflammatory changes, as well as comorbid pathologies are key components of the disease process. Symptomatic treatment offers a modest, clinically measurable effect in cognition, but disease-modifying therapies are desperately needed.

Posterior cortical atrophy: A rare variant of Alzheimer's disease

Posterior cortical atrophy is a rare condition first described in 1988 involving progressive degeneration and atrophy of the occipital cortex, often recognized after an unexplained homonymous hemianopsia may be discovered. We report a case in association with Alzheimer’s disease in a 77-year-old female, who underwent brain single-photon emission computed tomography as well brain positron emission tomography using Florbetapir to further evaluate progressive cognitive decline. The patient had also been followed in Ophthalmology for glaucoma, where a progressive unexplained change in her visual field maps were noted over one year consistent with a progressive right homonymous hemianopsia. This rare combination of findings in association with her dementia led to a detailed review of all her imaging studies, concluding with the surprising recognition for a clear hemi-atrophy of the primary left occipital cortex was occurring, consistent with Alzheimer’s disease affecting the primary visual cortex. Further awareness of this disease pattern is needed, as Alzheimer’s disease typically does not affect the primary visual cortex; other conditions to consider in general include Lewy Body dementia, cortico-basal degeneration and prion disease.

The Role of Neuroimaging in the Assessment of the Cognitively Impaired Elderly

This article reviews the current diagnostic tools that are available for structural, functional, and molecular imaging of the brain, summarizing some of the key findings that have been reported in individuals diagnosed with Alzheimer disease, mild cognitive impairment, prodromal AD, or other prevalent dementias. Given recent advances in the development of amyloid PET tracers, current guidelines for the use of amyloid PET imaging in patients with cognitive complaints are reviewed. In addition, data addressing the potential value of amyloid PET imaging in the clinical setting are highlighted.