Amyloid PET Scans Research Articles

Comparison of Expert Reads vs. Local Clinical Reads of Amyloid PET Scans in IDEAS

AbstractBackgroundAmyloid‐directed therapies will increase the clinical use of amyloid PET. IDEAS captured >17,000 clinical scan interpretations from local radiologists and nuclear medicine physicians. This study aimed to establish accuracy of these interpretations by comparison to expert readers across identical scans.MethodRandomly selected amyloid PET/CT scans performed using one of three FDA‐approved agents [18F‐Florbetaben (FBB), 18F‐Florbetapir (FBP), 18F‐Flutemetamol (FMM)] and previously interpreted by local readers from the Imaging Dementia ‐ Evidence for Amyloid Scanning (IDEAS) study were assigned to vendor‐selected panels of 3 expert readers for interpretation; 500 scans per agent and 1 panel per agent. Scans were stratified to match frequencies observed in the overall study by 1) participant age; 2) MCI vs dementia; 3) positive/negative interpretation; and 4) type of PET facility. Respective vendors performed quality control on attenuation‐corrected PET/CT images.Visual interpretations (positive or negative for Aβ cortical deposition) were performed according to agent‐specific validated interpretation criteria. Expert panel readers were blinded to clinical and demographic data. Cohen’s kappa statistic with two‐sided 95% confidence interval estimates examined agreement between local reader and majority expert panel visual interpretation.ResultExpert panel readers’ visual interpretations totaled 4489. Median age for scanned participants was 75 (range 65‐96), 51.4% were female and 60.5% had MCI. Local readers interpreted 60.9% of scans positive and 39.1% negative (Table 1).Across all radiotracers, agreement between majority expert read and local readers was excellent (k coefficient 0.76; 95% CI 0.73 – 0.80, p<.0001) with 86.6% (791/913) agreement for positive scans and 90.9% (532/585) agreement for negative scans (Figure 1). Agreement by individual radiopharmaceuticals was good to excellent: k coefficient 0.78 (95% CI 0.72 – 0.83, p<.001) for FBB, k coefficient 0.72 (95% CI 0.66 – 0.78, p<.001) for FBP, and k coefficient 0.78 (95% CI 0.73 – 0.84) for FMM (Figure 1). Agreement levels between local readers and individual experts varied from good to excellent (Figure 2).ConclusionWe found good to excellent agreement between local readers and majority assessment of three‐member expert panels for all combined scans and scans by individual agents. Visual interpretation of Aβ PET can be performed in a clinical setting with high reliability.

The use of Event Related Potentials to predict amyloid PET status among patients from a memory disorders clinic

AbstractBackgroundAmyloid PET scans provide in vivo evidence of Alzheimer’s Disease (AD) however, due to high cost and limited insurance coverage, they are not available as part of standard clinical care. Event Related Potentials (ERPs) are inexpensive, and non‐invasive method to directly measure brain physiology that may allow an alternative method for detection of AD pathology.MethodWe investigated whether ERPs together with neuropsychological data are predictors of amyloid PET status in patients with memory complaints. Older veterans aged 50‐100 were recruited from a memory disorders clinic at VA Boston Healthcare System. Participants underwent a standard neuropsychological battery and an ERP auditory oddball protocol. Twenty‐eight patients had a positive amyloid PET scan, and thirty‐nine patients had a negative amyloid PET scan.ResultsTwo neuropsychological measures (CERAD Delayed Recall and MMSE) were predictors of amyloid PET status. Increased P200 target amplitude (Figure 1B), and decreased P200 standard latency (Figure 1A) in patients with amyloid PET positive scan were found. ERP‐P200 amplitude in response to target tones and ERP‐P200 latency in response to standard tones were also predictors of amyloid PET status. The highest classification accuracy was obtained when combining CERAD Delayed Recall, MMSE and ERP‐P200 standard latency.ConclusionERP‐P200, especially when combined with cognitive measures of delayed memory and overall cognitive function, was predictive of amyloid beta (Aβ) load in the brain of patients from a memory disorder clinic. Increased P200 amplitude, and decreased P200 latency in patients with amyloid PET positive scan might suggest hyperactivation of perceptual bottom‐up processes to compensate for AD‐related synaptic loss in the fronto‐parietal networks.

3 Stricker Learning Span criterion validity: remote self-administration of a computer adaptive word list memory test shows similar ability to differentiate PET-defined biomarker groups as in-person Rey Auditory Verbal Learning Test performance in cognitively unimpaired individuals on the Alzheimer’s continuum

Objective:The Stricker Learning Span (SLS) is a computer-adaptive word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). Given recent evidence suggesting the prominence of learning impairment in preclinical Alzheimer’s disease (AD), the SLS places greater emphasis on learning than delayed memory compared to traditional word list memory tests (see Stricker et al., Neuropsychology in press for review and test details). The primary study aim was to establish criterion validity of the SLS by comparing the ability of the remotely-administered SLS and inperson administered Rey Auditory Verbal Learning Test (AVLT) to differentiate biomarkerdefined groups in cognitively unimpaired (CU) individuals on the Alzheimer’s continuum.Participants and Methods:Mayo Clinic Study of Aging CU participants (N=319; mean age=71, SD=11; mean education=16, SD=2; 47% female) completed a brief remote cognitive assessment (∼0.5 months from in-person visit). Brain amyloid and brain tau PET scans were available within 3 years. Overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (A+, n=110) or not (A-, n=209), and for 2) those with biological AD (A+T+, n=43) vs no evidence of AD pathology (A-T-, n=181). Primary neuropsychological outcome variables were sum of trials for both the SLS and AVLT. Secondary outcome variables examined comparability of learning (1-5 total) and delay performances. Linear model ANOVAs were used to investigate biomarker subgroup differences and Hedge’s G effect sizes were derived, with and without adjusting for demographic variables (age, education, sex).Results:Both SLS and AVLT performances were worse in the biomarker positive relative to biomarker negative groups (unadjusted p’s<.05). Because biomarker positive groups were significantly older than biomarker negative groups, group differences were attenuated after adjusting for demographic variables, but SLS remained significant for A+ vs A- and for A+T+ vs A-T- comparisons (adjusted p’s<.05) and AVLT approached significance (p’s .05-.10). The effect sizes for the SLS were slightly better (qualitatively, no statistical comparison) for separating biomarker-defined CU groups in comparison to AVLT. For A+ vs A- and A+T+ vs A-T- comparisons, unadjusted effect sizes for SLS were -0.53 and -0.81 and for AVLT were -0.47 and -0.61, respectively; adjusted effect sizes for SLS were -0.25 and -0.42 and for AVLT were -0.19 and -0.26, respectively. In secondary analyses, learning and delay variables were similar in terms of ability to separate biomarker groups. For example, unadjusted effect sizes for SLS learning (-.80) was similar to SLS delay (.76), and AVLT learning (-.58) was similar to AVLT 30-minute delay (-.55) for the A+T+ vs AT- comparison.Conclusions:Remotely administered SLS performed similarly to the in-person-administered AVLT in its ability to separate biomarker-defined groups in CU individuals, providing evidence of criterion validity. The SLS showed significantly worse performance in A+ and A+T+ groups (relative to A- and A-T-groups) in this CU sample after demographic adjustment, suggesting potential sensitivity to detecting transitional cognitive decline in preclinical AD. Measures emphasizing learning should be given equal consideration as measures of delayed memory in AD-focused studies, particularly in the preclinical phase.

50 Effects of Cerebrovascular Risk Factors and Alzheimer’s Disease Pathology on Executive Function and Memory Changes: Analysis of the National Alzheimer’s Coordinating Center Cohort

Objective:A common assumption in clinical neuropsychology is that cerebrovascular risk is adversely associated with executive function, while Alzheimer’s disease (AD) primarily targets episodic memory. The goal of the present study was to determine the cross-sectional and longitudinal validity of these assumptions using validated markers of cerebrovascular and AD burden.Participants and Methods:19271 longitudinally-followed participants from the National Alzheimer Coordinating Center (NACC) database (Mean age= 72.25; SD age= 10.42; 58% women; 51.6% CDR= 0, 33.7% CDR= 0.5, 14.7% CDR> 1) were included. Cognitive outcomes were a composite memory score and an executive function composite score (UDS3-EF; Staffaroni et al., 2020). Baseline presence of cerebrovascular disease was indexed by the presence of moderate to severe white matter hyperintensities or lacunar infarct on brain MRI (yes/no), while baseline AD pathology was indexed by the presence of a positive amyloid PET scan or elevated CSF AD biomarkers (yes/no). We used linear mixed effect models to assess the effects of baseline cerebrovascular disease, baseline AD pathology, and their interactions with time in study (years post baseline) controlling for baseline age, sex, education, and baseline MoCA score.Results:Baseline cerebrovascular disease was significantly associated with a lower intercept on executive functioning (between-person effect) (p < -0.001, 95% CI -0.37, -0.14) but not memory, while presence of AD biomarkers was associated with a lower memory intercept (p < -0.001, 95% CI -0.52, -0.39) but not executive function. However, only presence of AD pathology at baseline was associated with faster longitudinal decline on both memory and executive functioning over time. Baseline cerebrovascular disease did not independently relate to rate of cognitive decline.Conclusions:Consistent with widely held assumptions, our between-person analyses showed that MRI evidence of cerebrovascular disease was associated with worse executive functioning but not memory, while biomarker evidence of AD pathology was associated with worse memory but not executive function. Longitudinally, however, AD is the primary driver of decline in both executive and memory function. These results extend our understanding of how pathology impacts cognition in aging cohorts and highlight the importance of using longitudinal models.

57 Clinical Utility of Neuropsychological Evaluation in the Differential Diagnosis Between Late-Onset Primary Progressive Aphasia Semantic Variant (PPA-SV) Versus Limbic Predominant Age-Related TDP-43 Encephalopathy (LATE): A Case Report

Objective:Primary progressive aphasia semantic variant (PPA-SV) is an atypical dementia subtype on the frontotemporal dementia (FTD) spectrum. PPA-SV is clinically defined by naming and semantic deficits, with progressive language decline that generalizes to other domains over time. Typically, it presents as an early-onset dementia with TDP-43 pathology, but 33-46% of PPA-SV cases display initial onset after age 65 with potentially different clinical features. Limbic Predominant Age-Related TDP-43 Encephalopathy (LATE), a more recently discovered neurodegenerative entity, is defined by an older age of onset, hippocampal sclerosis/atrophy, and TDP-43 pathology with a gradually progressive amnestic profile that expands to other cognitive deficits over time. The authors present a case report with overlapping features and suspected TDP-43 neuropathology ante-mortem for two reasons: first, to highlight the need for clinical criteria to formally diagnose LATE, and second, to address a gap in the literature on the possible clinical differences of late-onset PPA-SV.Participants and Methods:The authors present a case of a 78-year-old Indian bilingual man (English dominant) with 18 years of education, noncontributory medical history, and gradually progressive cognitive complaints reported over the past few years who was seen for outpatient neuropsychological evaluation. Prior workup was notable for negative amyloid PET scan, negative p-tau 217 blood test, and abnormal brain MRI revealing marked bilateral hippocampal atrophy with ex vacuo ventriculomegaly and minimal cerebrovascular disease. He scored 23/30 on prior MMSE, was diagnosed with amnestic MCI, prescribed Namenda and Exelon, and complained of minor memory and word-finding difficulties with reportedly intact IADLs and no signs of NPH.Results:Neuropsychological testing revealed a profound dysnomia (RBANS Naming raw score = 1/10), and he provided 0 words on two semantic fluency tasks but 15 words on letter fluency. Receptive vocabulary score was also impaired (PPVT-4, <1st %). Memory performance also demonstrated rapid forgetting of information (RBANS List Recall raw = 0/10, Story Recall raw = 0/12) with no benefit to recognition cues (RBANS List Recognition raw = 12/20), but slightly better visual memory recall, albeit still impaired (RBANS Figure Recall raw = 4/20). Grooved pegboard scores were significantly worse with right-hand than left-hand. Irregular word reading (NAART = 16th %ile) was significantly below expectations and thought to reflect more of a surface dyslexia rather than a cultural confounder given that he has lived in the US for over 50 years and his occupational and educational history was completed in English.Conclusions:Results support the clinical utility of neuropsychological evaluation in the differential diagnosis to support a predominant clinical syndrome of PPA-SV despite overlapping features with LATE and suspected TDP-43 pathology. This case report highlights the diagnostic issue with the lack of literature describing the typical clinical progression or suggested diagnostic criteria of LATE. These findings also indicate that late-onset PPA-SV may include greater memory deficits earlier in the course, but this may also be a clinical masquerade that is more reflective of the extent of language deficits. Further research on late-onset manifestations of PPA-SV and LATE consensus clinical guidelines is advised.

Agreement of cerebrospinal fluid biomarkers and amyloid-PET in a multicenter study.

Core Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers have shown incomplete agreement with amyloid-positron emission tomography (PET). Our goal was to analyze the agreement between AD CSF biomarkers and amyloid-PET in a multicenter study. Retrospective multicenter study (5 centers). Participants who underwent both CSF biomarkers and amyloid-PET scan within 18months were included. Clinical diagnoses were made according to latest diagnostic criteria by the attending clinicians. CSF Amyloid Beta1-42 (Aβ1-42, A), phosphorliated tau 181 (pTau181, T) and total tau (tTau, N) biomarkers were considered normal (-) or abnormal ( +) according to cutoffs of each center. Amyloid-PET was visually classified as positive/negative. Agreement between CSF biomarkers and amyloid-PET was analyzed by overall percent agreement (OPA). 236 participants were included (mean age 67.9years (SD 9.1), MMSE score 24.5 (SD 4.1)). Diagnoses were mild cognitive impairment or dementia due to AD (49%), Lewy body dementia (22%), frontotemporal dementia (10%) and others (19%). Mean time between tests was 5.1months (SD 4.1). OPA between single CSF biomarkers and amyloid-PET was 74% for Aβ1-42, 75% for pTau181, 73% for tTau. The use of biomarker ratios improved OPA: 87% for Aβ1-42/Aβ1-40 (n = 155), 88% for pTau181/Aβ1-42 (n = 94) and 82% for tTau/Aβ1-42 (n = 160). A + T + N + cases showed the highest agreement between CSF biomarkers and amyloid-PET (96%), followed by A-T-N- cases (89%). Aβ1-42/Aβ1-40 was a better marker of cerebral amyloid deposition, as identified by amyloid tracers, than Aβ1-42 alone. Combined biomarkers in CSF predicted amyloid-PET result better than single biomarkers.

Impact of simulated reduced injected dose on the assessment of amyloid PET scans

PurposeTo investigate the impact of reduced injected doses on the quantitative and qualitative assessment of the amyloid PET tracers [18F]flutemetamol and [18F]florbetaben.MethodsCognitively impaired and unimpaired individuals (N = 250, 36% Aβ-positive) were included and injected with [18F]flutemetamol (N = 175) or [18F]florbetaben (N = 75). PET scans were acquired in list-mode (90–110 min post-injection) and reduced-dose images were simulated to generate images of 75, 50, 25, 12.5 and 5% of the original injected dose. Images were reconstructed using vendor-provided reconstruction tools and visually assessed for Aβ-pathology. SUVRs were calculated for a global cortical and three smaller regions using a cerebellar cortex reference tissue, and Centiloid was computed. Absolute and percentage differences in SUVR and CL were calculated between dose levels, and the ability to discriminate between Aβ- and Aβ + scans was evaluated using ROC analyses. Finally, intra-reader agreement between the reduced dose and 100% images was evaluated.ResultsAt 5% injected dose, change in SUVR was 3.72% and 3.12%, with absolute change in Centiloid 3.35CL and 4.62CL, for [18F]flutemetamol and [18F]florbetaben, respectively. At 12.5% injected dose, percentage change in SUVR and absolute change in Centiloid were < 1.5%. AUCs for discriminating Aβ- from Aβ + scans were high (AUC ≥ 0.94) across dose levels, and visual assessment showed intra-reader agreement of > 80% for both tracers.ConclusionThis proof-of-concept study showed that for both [18F]flutemetamol and [18F]florbetaben, adequate quantitative and qualitative assessments can be obtained at 12.5% of the original injected dose. However, decisions to reduce the injected dose should be made considering the specific clinical or research circumstances.

A - 36 Neuroprotective and Resilience Factors in an Individual with Positive ad Biomarkers.

There is conflicting research on risk indicators relating to the diagnosis of early-onset Alzheimer's disease (EOAD). We assessed an individual with numerous factors that are associated with EOAD including the presence of two APOE e4 alleles, family history of EOAD, and positive biomarkers (i.e., Amyloid PET Scan; CSF). Longitudinal neuropsychological data reflect minimal cognitive decline through age 73, suggesting substantial mediating effects of cognitive reserve and neuroprotective measures: aerobic exercise, cognitive stimulation, and psychological health. A 73-year-old man was seen for repeat neuropsychological evaluation in 2022 at an academic medical center following his baseline evaluation in 2019, which did not reveal cognitive deficits. Testing was conducted and interpreted by a clinical neuropsychologist in the context of available neuroimaging and neurodiagnostic information. Results of the neuropsychological assessment were interpreted in the context of High Average to Superior premorbid functioning, a significant family history of EOAD, a positive Amyloid PET scan and two ApoE4 alleles (4/4). Results of his 2022 evaluation remain consistent or improved from 2019 and do not suggest mild cognitive impairment (MCI). Functionally, this individual is fully independent in IADLs and does not report significant subjective cognitive concerns. Phenotypic expression of ad symptoms are delayed in this individual despite his genetic risk and pathologic biomarkers; the reason is likely multifactorial but includes several resilience factors, including good cardiovascular health (i.e., aerobic exercise 5x/week), continued cognitive stimulation, and psychological health. These are areas worthy of further research.

“And Does That Necessarily Mean Absolutely Alzheimer's?” An Analysis of Questions Raised Following Amyloid PET Results Disclosure

Amyloid PET scans provide individuals with mild cognitive impairment (MCI) information about their risk of progressing to Alzheimer's dementia (AD). Given the wide-ranging implications of this information, best practice guidelines are needed to support researchers and clinicians disclosing these high-stakes test results. To inform the development of such guidelines, this analysis aims to describe questions and concerns raised during the disclosure of amyloid PET results in the context of MCI. Qualitative description was performed to analyze (n=34) transcripts of audio-recorded amyloid PET results disclosure sessions involving MCI care dyads. The analysis focused on characterizing the frequency and nature of questions raised during an open question-and-answer (Q&A) period following the return of scan results using a standardized protocol. Nearly all (n=32/34) dyads posed questions during Q&A. Questions fell within six main categories with the most common being requests for clarification regarding AD/MCI, and next steps given the result. Questions were interspersed with comments reflecting the need for emotional support. Independently administered assessments of comprehension of results showed that, following the disclosure and Q&A, 31/32 participants with MCI and 31/31 care partners scored ≥4 on a 5-point scale. The number of questions asked by care partners during Q&A positively correlated with their level of comprehension (n=31, Spearman's r=0.370, p=0.040). This analysis highlights the value of providing opportunities for patients and their family members to ask questions upon learning patients' brain amyloid status. Disclosing clinicians should be prepared to provide clarification, resources, and support to patients and families during the return of amyloid PET results.

The impact of tau deposition and hypometabolism on cognitive impairment and longitudinal cognitive decline.

Tau and neurodegeneration strongly correlate with cognitive impairment, as compared to amyloid. However, their contribution in explaining cognition and predicting cognitive decline in memory clinics remains unclarified. We included 94 participants with Mini-Mental State Examination (MMSE), tau positron emission tomography (PET), amyloid PET, fluorodeoxyglucose(FDG) PET, and MRI scans from Geneva Memory Center. Linear regression and mediation analyses tested the independent and combined association between biomarkers, cognitive performance, and decline. Linear mixed-effects and Cox proportional hazards models assessed biomarkers' prognostic values. Metabolism had the strongest association with cognition (r=0.712; p<0.001), followed by tau (r=-0.682; p<0.001). Neocortical tau showed the strongest association with cognitive decline (r=-0.677; p<0.001). Metabolism mediated the association between tau and cognition and marginally mediated the one with decline. Tau positivity represented the strongest risk factor for decline (hazard ratio=32). Tau and neurodegeneration synergistically contribute to global cognitive impairment while tau drives decline. The tau PET superior prognostic value supports its implementation in memory clinics. Hypometabolism has the strongest association with concurrent cognitive impairment. Neocortical tau pathology is the main determinant of cognitive decline over time. FDG-PET has a superior value compared to MRI as a measure of neurodegeneration. The prognostic value of tau-PET exceeded all other neuroimaging modalities.

Tear biomarkers for Alzheimer’s disease screening and diagnosis (the TearAD study): design and rationale of an observational longitudinal multicenter study

BackgroundAlzheimer’s disease (AD) is the most common cause of dementia, and due to increasing life expectancy the number of patients is expected to grow. The diagnosis of AD involves the use of biomarkers determined by an amyloid PET scan or cerebrospinal fluid analyses that are either invasive or expensive, and not available in each hospital, thus limiting their usage as a front-line screener. The TearAD study aims to use tear fluid as a potential source for AD biomarkers. In previous reports, we demonstrated that AD biomarkers amyloid-beta and tau, are measurable in tear fluid and are associated with disease severity and neurodegeration. This study aims to validate previous results in a larger cohort and evaluate the diagnostic accuracy of tear biomarkers to discriminate between individuals with and without neurodegeneration as determined by hippocampal atrophy.MethodsThe TearAD study is an observational longitudinal multi-center study that will enroll 50 cognitively healthy controls, 50 patients with subjective cognitive decline, 50 patients with mild cognitive impairment and 50 patients with AD dementia from the memory clinic. Participants will be examined at baseline, after one year, and after two years follow-up. Study assessments include neuropsychological tests and ophthalmic examination. All participants will receive a MRI scan, and a subset of the study population will undergo cerebral spinal fluid collection and an amyloid PET scan. Tear fluid will be collected with Schirmer strips and levels of Aβ38, Aβ40, Aβ42, t-tau and p-tau in tear fluid will be determined using multiplex immunoassays. Blood samples will be collected from all participants. Images of the retina will be obtained with a standard, hyperspectral and ultra-wide field fundus camera. Additionally, macular pigment optical density will be measured with the macular pigment reflectometer, and cross-sectional images of the retina will be obtained through optical coherence tomography imaging.DiscussionThe TearAD study will provide insight into the potential diagnostic use of tear biomarkers as a minimally invasive and low cost tool for the screening and diagnosis of AD.Trial registrationRetrospectively registered at clinicaltrials.gov (NCT05655793).

The Effect of Gender and APOE ɛ4 Status on Brain Amyloid-β Deposition in Different Age Groups of Mild Cognitively Impaired Individuals: A PET-CT Study.

Gender, APOE ɛ4 status and age have different effects on brain amyloid deposition in patients with mild cognitively impaired (MCI). To investigate the effect of gender×APOE ɛ4 status interaction on Aβ deposition in the brains of individuals with MCI in different age groups by PET scanning. 204 individuals with MCI were classified into younger or older groups based on whether they were under or over 65 years of age. APOE genotyping, structural MRI, amyloid PET scans, and neuropsychological tests were performed. The effect of gender×APOE ɛ4 status interaction on Aβ deposition was assessed in different age groups. APOE ɛ4 carriers had higher amyloid deposition than noncarriers in the whole group. Females with MCI had more amyloid deposition in the medial temporal lobe than males in the whole cohort and younger group. Older individuals with MCI had higher amyloid deposition than younger individuals. In stratified analysis by age, female APOE ɛ4 carriers had significantly increased amyloid deposition compared to their male counterparts only in the medial temporal lobe in the younger group. Amyloid deposition was increased in female APOE ɛ4 carriers compared to noncarriers in the younger group, whereas higher amyloid deposition was observed in male APOE ɛ4 carriers in the older group. Women in the younger group with MCI who were APOE ɛ4 carriers had more amyloid deposition in the brain, while men in the older group with MCI who were APOE ɛ4 carriers had higher amyloid deposition.

Stability in cognitive classification as a function of severity of impairment and ethnicity: A longitudinal analysis

Objective The interaction of ethnicity, progression of cognitive impairment, and neuroimaging biomarkers of Alzheimer’s Disease remains unclear. We investigated the stability in cognitive status classification (cognitively normal [CN] and mild cognitive impairment [MCI]) of 209 participants (124 Hispanics/Latinos and 85 European Americans). Methods Biomarkers (structural MRI and amyloid PET scans) were compared between Hispanic/Latino and European American individuals who presented a change in cognitive diagnosis during the second or third follow-up and those who remained stable over time. Results There were no significant differences in biomarkers between ethnic groups in any of the diagnostic categories. The frequency of CN and MCI participants who were progressors (progressed to a more severe cognitive diagnosis at follow-up) and non-progressors (either stable through follow-ups or unstable [progressed but later reverted to a diagnosis of CN]) did not significantly differ across ethnic groups. Progressors had greater atrophy in the hippocampus (HP) and entorhinal cortex (ERC) at baseline compared to unstable non-progressors (reverters) for both ethnic groups, and more significant ERC atrophy was observed among progressors of the Hispanic/Latino group. For European Americans diagnosed with MCI, there were 60% more progressors than reverters (reverted from MCI to CN), while among Hispanics/Latinos with MCI, there were 7% more reverters than progressors. Binomial logistic regressions predicting progression, including brain biomarkers, MMSE, and ethnicity, demonstrated that only MMSE was a predictor for CN participants at baseline. However, for MCI participants at baseline, HP atrophy, ERC atrophy, and MMSE predicted progression.

Stricker Learning Span criterion validity: a remote self-administered multi-device compatible digital word list memory measure shows similar ability to differentiate amyloid and tau PET-defined biomarker groups as in-person Auditory Verbal Learning Test.

The Stricker Learning Span (SLS) is a computer-adaptive digital word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). We aimed to establish criterion validity of the SLS by comparing its ability to differentiate biomarker-defined groups to the person-administered Rey's Auditory Verbal Learning Test (AVLT). Participants (N = 353; mean age = 71, SD = 11; 93% cognitively unimpaired [CU]) completed the AVLT during an in-person visit, the SLS remotely (within 3 months) and had brain amyloid and tau PET scans available (within 3 years). Overlapping groups were formed for 1) those on the Alzheimer's disease (AD) continuum (amyloid PET positive, A+, n = 125) or not (A-, n = 228), and those with biological AD (amyloid and tau PET positive, A+T+, n = 55) vs no evidence of AD pathology (A-T-, n = 195). Analyses were repeated among CU participants only. The SLS and AVLT showed similar ability to differentiate biomarker-defined groups when comparing AUROCs (p's > .05). In logistic regression models, SLS contributed significantly to predicting biomarker group beyond age, education, and sex, including when limited to CU participants. Medium (A- vs A+) to large (A-T- vs A+T+) unadjusted effect sizes were observed for both SLS and AVLT. Learning and delay variables were similar in terms of ability to separate biomarker groups. Remotely administered SLS performed similarly to in-person-administered AVLT in its ability to separate biomarker-defined groups, providing evidence of criterion validity. Results suggest the SLS may be sensitive to detecting subtle objective cognitive decline in preclinical AD.

Prognostic value of imaging-based ATN profiles in a memory clinic cohort.

The ATN model represents a research framework used to classify subjects based on the presence or absence of Alzheimer's disease (AD) pathology through biomarkers for amyloid (A), tau (T), and neurodegeneration (N). The aim of this study was to assess the relationship between ATN profiles defined through imaging and cognitive decline in a memory clinic cohort. One hundred-eight patients from the memory clinic of Geneva University Hospitals underwent complete clinical and neuropsychological evaluation at baseline and 23 ± 5months after inclusion, magnetic resonance imaging, amyloid and tau PET scans. ATN profiles were divided into four groups: normal, AD pathological change (AD-PC: A + T-N-, A + T-N +), AD pathology (AD-P: A + T + N-, A + T + N +), and suspected non-AD pathology (SNAP: A-T + N-, A-T-N + , A-T + N +). Mini-Mental State Examination (MMSE) scores were significantly different among groups, both at baseline and follow-up, with the normal group having higher average MMSE scores than the other groups. MMSE scores changed significantly after 2years only in AD-PC and AD-P groups. AD-P profile classification also had the largest number of decliners at follow-up (55%) and the steepest global cognitive decline compared to the normal group. Cox regression showed that participants within the AD-P group had a higher risk of cognitive decline (HR = 6.15, CI = 2.59-14.59), followed by AD-PC (HR = 3.16, CI = 1.17-8.52). Of the different group classifications, AD-P was found to have the most significant effect on cognitive decline over a period of 2years, highlighting the value of both amyloid and tau PET molecular imaging as prognostic imaging biomarkers in clinical practice.

Amyloid PET ordering practices in a memory disorders clinic

AbstractBackgroundThe objective of the current study was to assess amyloid PET scan ordering practices in a Veterans Affairs memory disorders clinic, where such scans are readily available, and the extent to which amyloid PET ordering may occur in memory disorders clinics if covered by insurance in the future.MethodsUsing retrospective chart review over a three‐year period, we compared patient demographic, clinical, and MRI structural features that were predictive of ordering an amyloid PET scan in a memory disorders clinic to those of patients who did not have one ordered. The percentage of patients who met previously published appropriate use criteria were evaluated.ResultOverall 34.9% of patients received an amyloid PET scan as part of their diagnostic workup and 97.9% of these ordered scans were consistent with appropriate use criteria. Patients who received an amyloid PET were younger on average and more likely to have an initial diagnosis of suspected AD. Overall, 64.4% of patients without an amyloid PET scan ordered would have met appropriate use criteria for amyloid PET. Thus, fewer patients received an amyloid PET scan than were eligible according to current appropriate use criteria.ConclusionA little more than a third of veterans in a memory disorders clinic received an amyloid PET scan as part of their diagnostic work up when ordering was freely available to cognitive behavioral neurologists and not constrained by third‐party reimbursement. The vast majority of amyloid PET scans ordered were consistent with current appropriate use criteria. Future versions of the appropriate use criteria for amyloid PET could address ordering in patients with subjective cognitive decline with behavioral/functional impairments as well as patients under consideration for possible anti‐amyloid therapy treatment with Aducanumab and other medications in this class.

Novel residual neural network approach for analyzing amyloid PET scans: Associations with cerebrospinal fluid beta amyloid and episodic memory

AbstractBackgroundDiagnosing Alzheimer’s disease (AD) based on the biological definition depends on accurately determining amyloid‐β (Aβ) status. In this research, we aimed to create a deep learning model for predicting Aβ cerebral spinal fluid (CSF) measures directly from amyloid PET scans, and compare the result with AD clinical hallmarks.MethodWe developed a novel residual neural network (ResNet) model to predict CSF Aβ from amyloid PET scans and trained the model using 1,870 scans from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Episodic memory (EM) was measured with immediate and delayed recall in the Rey Auditory Verbal Learning Test (AVLTim/AVLTdel) and in Logical Memory (LMim/LMdel) subtest from the Wechsler Memory Scale. We investigated associations of predicted CSF values with EM measures and compared our model against the traditional approach of determining cortical amyloid with a standardized uptake value ratio (SUVR) measure. We used Pearson correlations to investigate the associations of cortical amyloid with CSF and AD clinical markers. Further, we looked at these correlations separately in different clinically defined groups (cognitively normal, mild cognitive impairment (MCI), and AD).ResultResNet accurately predicted Aβ CSF measures (r = 0.93, p&lt;1e‐10). SUVR significantly correlated with clinical CSF (r←0.65, p&lt;1e‐10) and with ResNet model predicted CSF (r←0.67, p&lt;1e‐10). The predicted CSF is also significantly associated with EM (LMim and LMdel, r = 0.46; AVLTim, r = 0.40; AVLTdel, r = 0.34; p&lt;1e‐10). Correlations in those with AD were generally weaker (SUVR, r←0.37; EM, 0.02&lt;r&lt;0.29) than in those with MCI (SUVR, r←0.70; EM, 0.27&lt;r&lt;0.43) or in cognitively healthy (SUVR, r←0.56; EM, 0.16&lt;r&lt;0.28).ConclusionWe developed to our knowledge the first ResNet model, which predicts Aβ CSF measures with high accuracy. Predicted CSF values strongly correlate with clinical AD hallmarks. However, there are many questions that warrant further study, and we aim to investigate our model in relation to early prediction and diagnosis of AD, and in studying the discordance between biological and clinical AD classifications.

Apolipoprotein C proteins in plasma non‐high‐density lipoprotein fractions and development of Alzheimer’s disease, central arterial stiffness, and cerebral small vessel disease in older adults

AbstractBackgroundPlasma non‐high‐density lipoproteins impact development of central arterial stiffness and cerebral small vessel disease (cSVD), significantly contributing to Alzheimer’s disease (AD) and related dementias (ADRDs) through an increase in cerebral amyloid beta (Aβ) burden and acceleration of atrophy in susceptible brain regions. We sought to identify proteins in three non‐HDL plasma lipoproteins (very‐low density lipoprotein [VLDL], intermediate‐density lipoprotein [IDL], low‐density lipoprotein [LDL]) and their cross‐sectional associations with brain amyloid deposition, central arterial stiffness, neuroimaging features of cSVD (e.g., white matter hyperintensity volume), brain volumes susceptible to AD and cSVD, and incidence of dementia.MethodPlasma samples from 66 participants of the Atherosclerosis Risk in Communities (ARIC) study were fractionated to isolate VLDL, IDL, and LDL and analyzed using label‐free liquid chromatography‐mass spectrometry (LC‐MS) with Data‐Independent Acquisition. Acquired MS spectra were processed using Spectronaut™ to give protein identification and relative protein abundances were calculated using R. Linear regression models were used to examine the cross‐sectional associations between protein abundances in VLDL, IDL or LDL and brain amyloid deposition (measured by amyloid PET scan), white matter hyperintensities (WMH) volume (measured by brain MRI), central arterial stiffness (carotid‐femoral and heart‐femoral pulse wave velocity), AD‐signature region, frontal, parietal, and hippocampal brain region volumes (measured by brain MRI), and incidence of dementia. Regression models were adjusted for age, sex, race, number of APOε4 alleles, and cholesterol level (if applicable). Additionally, differential analysis (student’s t‐test) was used to compare protein abundances in non‐HDL lipoproteins between participants with elevated versus normal brain amyloid deposition.ResultWe identified 50, 78, 81 proteins in VLDL, IDL, and LDL, respectively. The most significant findings were: 1) higher levels of apolipoprotein C proteins in VLDL, IDL, and LDL were associated with lower WMH volume or less central arterial stiffness; 2) lower levels of apolipoprotein C proteins in VLDL, IDL, and LDL were associated with less incidence of dementia; 3) lower levels of apolipoprotein C proteins in VLDL, IDL, and LDL for participants with elevated amyloid deposition.ConclusionThese results suggest the possible role of apolipoprotein C proteins present in non‐HDL‐lipoproteins in the development of AD, central arterial stiffness, and cSVD.

Effects of APOE genotype on amyloid PET positivity according to cognitive status and ethnicity

AbstractBackgroundAmong the various risk factors for Alzheimer disease (AD), apolipoprotein E (APOE) genotype ε4 is known to be a strong factor. On the other hand, ε2 is known to have a protective effect. It is not yet clear how amyloid positivity according to the APOE genotype differs by diagnostic criteria. Also, there were no studies showing the ethnic difference in the effects of APOE genotype on amyloid‐beta (Aβ) between American and Asian. The aim of this study was to investigate how Aβ positivity (Aβ+) according to APOE genotypes differs by ethnicity and cognition.MethodWe recruited 4,203 Korean subjects from multi‐centers in South Korea and 1,069 subjects from Alzheimer’s Disease Neuroimaging Initiative database. All subjects underwent neuropsychological tests, APOE genotype tests, and amyloid PET (FMM/FBB/AV45) scans. Subjects with the ε2/ε4 genotype were excluded due to the opposing effects of the ε4 and ε2 alleles. The degree of influence on amyloid positivity by each factor was analyzed by logistic regression.ResultThe frequency of Aβ+ in normal cognition (NC) group was higher in ADNI than in Korean group (p &lt;0.001). Amnestic mild cognitive impairment and AD dementia (ADD) groups showed no difference in the frequency of Aβ+ between ADNI and Korean groups. Relative to APOE ε3/ε3 group, APOE ε4 carriers showed higher frequent Aβ+ regardless of cognitive status and ethnicity (Figure). ADNI and Korean groups showed APOE ε2 carriers less frequent Aβ+ in ADD but not in NC relative to APOE ε3/ε3 group.ConclusionOur findings suggested that there were no differences in effects of APOE ε4 genotype on Aβ+ between European and Korean. These findings will be helpful in predicting amyloid positivity and AD intervention according to APOE genotype and ethnicity.

Classification of amyloid positivity in PET imaging using end‐to‐end deep learning: a multi‐cohort, multi‐tracer analysis

AbstractBackgroundPositron emission tomography (PET) imaging with amyloid‐specific tracers is the gold standard for assessing amyloid positivity in vivo. However, visual interpretation of PET images is limited by availability of clinicians and interobserver variability. Classification of amyloid status typically requires calculation of standardized uptake value ratios (SUVRs), correspondence with neuroanatomy from magnetic resonance imaging, and additional complex, computationally intensive preprocessing steps requiring specialized software. We developed a deep learning model that can automatically classify unprocessed PET images as amyloid positive or negative.MethodFlorbetapir (AV45), florbetaben (FBB), and Pittsburgh compound B (PiB) images from the Alzheimer’s Disease Neuroimaging Association (ADNI), AV45 and PiB images from the Open Access Series of Imaging Studies 3 (OASIS3), and FBB, flutametamol (FMT), and flutafuranol (NAV4694) images from the Australian Imaging Biomarkers and Lifestyle Study of Ageing (AIBL) were used (Table 1). Each image was resized to isotropic 2 mm voxels, and voxel intensities between the 5th and 95th percentile were normalized to zero mean and unit variance. We trained and internally validated a convolutional neural network (CNN) on AV45 images from ADNI before testing it on images from an independent cohort and/or acquired with a different tracer.ResultThe model achieved an AUC of 0.98 [0.97, 1.0] on test AV45 images from ADNI and generalized well to AV45 images from OASIS3, achieving an AUC of 0.95 [0.92, 0.97] (Table 2). Critically, the model’s performance remained robust even when evaluating imaging from different tracers, including FBB, FMT, PiB, and NAV4694, scoring an AUC of at least 0.97 on each and demonstrating its ability to learn a tracer‐agnostic pattern of abnormality. Similar conclusions can be drawn from other performance metrics.ConclusionWe developed a deep learning model that can classify amyloid PET scans with a high degree of accuracy. We demonstrated that the model generalizes well to unseen images acquired from an independent cohort, under a different protocol, and/or with tracers unseen during training. Our model may usefully provide concise metrics for amyloid research as well as support clinical assessment of amyloid‐specific PET when expertise or computational resources are limited.