Amyloid Positivity Using [18F]Flutemetamol-PET and Cognitive Deficits in Nondemented Community-Dwelling Older Adults

Sensitivity of the African neuropsychology battery memory subtests and learning slopes in discriminating APOE 4 and amyloid pathology in adult individuals in the Democratic Republic of Congo

Background

The current study examined the sensitivity of two memory subtests and their corresponding learning slope metrics derived from the African Neuropsychology Battery (ANB) to detect amyloid pathology and APOEε4 status in adults from Kinshasa, the Democratic Republic of the Congo.

Methods

85 participants were classified for the presence of β-amyloid pathology and based on allelic presence of APOEε4 using Simoa. All participants were screened using CSID and AQ, underwent verbal and visuospatial memory testing from ANB, and provided blood samples for plasma Aβ42, Aβ40, and APOE proteotype. Pearson correlation, linear and logistic regression were conducted to compare amyloid pathology and APOEε4 status with derived learning scores, including initial learning, raw learning score, learning over trials, and learning ratio.

Results

Our sample included 35 amyloid positive and 44 amyloid negative individuals as well as 42 without and 39 with APOEε4. All ROC AUC ranges for the prediction of amyloid pathology based on learning scores were low, ranging between 0.56-0.70 (95% CI ranging from 0.44-0.82). The sensitivity of all the scores ranged between 54.3-88.6, with some learning metrics demonstrating good sensitivity. Regarding APOEε4 prediction, all AUC values ranged between 0.60-0.69, with all sensitivity measures ranging between 53.8-89.7. There were minimal differences in the AUC values across learning slope metrics, largely due to the lack of ceiling effects in this sample.

Discussion

This study demonstrates that some ANB memory subtests and learning slope metrics can discriminate those that are normal from those with amyloid pathology and those with and without APOEε4, consistent with findings reported in Western populations.

Sensitivity of memory subtests and learning slopes from the ADAS-Cog to distinguish along the continuum of the NIA-AA Research Framework for Alzheimer's Disease

Despite extensive use of the Alzheimer's Disease (AD) Assessment Scale - Cognitive Subscale (ADAS-Cog) in AD research, exploration of memory subtests or process scores from the measure has been limited. The current study sought to establish validity for the ADAS-Cog Word Recall Immediate and Delayed Memory subtests and learning slope scores by showing that they are sensitive to AD biomarker status. Word Recall subtest and learning slope scores were calculated for 441 participants from the Alzheimer's Disease Neuroimaging Initiative (aged 55 to 90). All participants were categorized using the NIA-AA Research Framework - based on PET-imaging of β-amyloid (A) and tau (T) deposition - as Normal AD Biomarkers (A-T-), Alzheimer's Pathologic Change (A + T-), or Alzheimer's disease (A + T+). Memory subtest and learning slope performances were compared between biomarker status groups, and with regard to how well they discriminated samples with (A + T+) and without (A-T-) biomarkers. Lower Word Recall memory subtest scores - and scores for a particular learning slope calculation, the Learning Ratio - were observed for the AD (A + T+) group than the other biomarker groups. Memory subtest and Learning Ratio scores further displayed fair to good receiver operator characteristics when differentiating those with and without AD biomarkers. When comparing across learning slopes, the Learning Ratio metric consistently outperformed others. ADAS-Cog memory subtests and the Learning Ratio score are sensitive to AD biomarker status along the continuum of the NIA-AA Research Framework, and the results offer criterion validity for use of these subtests and process scores as unique markers of memory capacity.

Distribution and progression of cerebral amyloid angiopathy in early-onset V30M (p.V50M) hereditary ATTR amyloidosis

BACKGROUND

Cerebral amyloid angiopathy (CAA) is becoming the most common and serious complications in long-lived hereditary ATTR amyloidosis patients. It is therefore imperative to elucidate the characteristics of ATTR-type CAA and develop useful biomarkers.

METHODS

We enrolled 34 ATTRv amyloidosis patients with the V30M (p.V50M) variant for analysis with three-dimensional stereotactic surface projection z score imaging of Pittsburgh compound B (PiB)-PET.

RESULTS

Eight patients exhibited central nervous system (CNS) symptoms. Seven patients suffered transient focal neurologic episodes, and 2 patients each experienced cerebellar haemorrhages or cognitive decline. The amount of ¹¹C-PiB accumulation increased as a function of disease duration. ¹¹C-PiB-PET abnormalities were seen at 8 years from onset and were associated with CNS manifestations from 12 years. The annual increase rate of the standardised uptake value ratio (SUVR) in female patients was significantly higher than in male patients. CNS amyloid deposition started in the upper middle surface of the cerebellar cortex, and then spread out over the entire surface of the cerebellum, Sylvian fissure, and anterior part of the longitudinal fissure of the cerebrum.

CONCLUSIONS

PiB-PET is a useful biomarker for the early detection and treatment evaluation of ATTR-type CAA. Female gender is associated with more rapid progression of ATTR-type CAA.

Repeatable battery for the assessment of neuropsychological status and its relationship to biomarkers of Alzheimer's disease

The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) has been associated with commonly used biomarkers of Alzheimer's disease (AD). However, prior studies have typically utilized small and poorly characterized samples, and they have not analyzed the subtests of the RBANS. The current study sought to expand on prior work by examining the relationship between the Indexes and subtest scores of the RBANS and three AD biomarkers: amyloid deposition via positron emission tomography, hippocampal volume via magnetic resonance imaging, and APOE ε4 status.

One-hundred twenty-one older adults across the AD continuum (intact, amnestic Mild Cognitive Impairment, mild AD), who were mostly Caucasian and well-educated, underwent assessment with the RBANS and collection of the three biomarkers.

Greater amyloid deposition was significantly related to lower scores on all five Indexes and the Total Scale score of the RBANS, as well as 11 of 12 subtests. For bilateral hippocampal volume, significant correlations were observed for 4 of the 5 Indexes, Total Scale score, and 9 of 12 subtests, with smaller hippocampi being related to lower RBANS scores. Participants with at least one APOE ε4 allele had significantly lower scores on 3 of the 5 Indexes, Total Scale score, and 8 of the 12 subtests.

In this sample of participants across the dementia spectrum, most RBANS Indexes and subtests showed relationships with the amyloid deposition, hippocampal volumes, and APOE status, with poorer performance on the RBANS being associated with biomarker positivity. Although memory scores on the RBANS have traditionally been linked to biomarkers in AD, other Index and subtest scores also hold promise as indicators of AD. Replication in a more diverse sample is needed.

Evaluation of in vivo staging of amyloid deposition in cognitively unimpaired elderly aged 78-94

Amyloid-beta (Aβ) deposition is common in cognitively unimpaired (CU) elderly >85 years. This study investigated amyloid distribution and evaluated three published in vivo amyloid-PET staging schemes from a cognitively unimpaired (CU) cohort aged 84.9 ± 4.3 years (n = 75). SUV-based principal component analysis (PCA) was applied to 18F-flutemetamol PET data to determine an unbiased regional covariance pattern of tracer uptake across grey matter regions. PET staging schemes were applied to the data and compared to the PCA output. Concentration of p-tau181 was measured in blood plasma. The PCA revealed three distinct components accounting for 91.2% of total SUV variance. PC1 driven by the large common variance of uptake in neocortical and striatal regions was significantly positively correlated with global SUVRs, APOE4 status and p-tau181 concentration. PC2 represented mainly non-specific uptake in typical amyloid-PET reference regions, and PC3 the occipital lobe. Application of the staging schemes demonstrated that the majority of the CU cohort (up to 93%) were classified as having pathological amount and distribution of Aβ. Good correspondence existed between binary (+/-) classification and later amyloid stages, however, substantial differences existed between schemes for low stages with 8-17% of individuals being unstageable, i.e., not following the sequential progression of Aβ deposition. In spite of the difference in staging outcomes there was broad spatial overlap between earlier stages and PC1, most prominently in default mode network regions. This study critically evaluated the utility of in vivo amyloid staging from a single PET scan in CU elderly and found that early amyloid stages could not be consistently classified. The majority of the cohort had pathological Aβ, thus, it remains an open topic what constitutes abnormal brain Aβ in the oldest-old and what is the best method to determine that.

Validation of HVLT-R, BVMT-R, and RBANS Learning Slope Scores along the Alzheimer's Continuum

BACKGROUND

The learning ratio (LR) is a novel learning slope score that has been developed to reduce the inherent competition between the first trial and subsequent trials in traditional learning slopes. In essence, the LR is the number of items learned after the first trial divided by the number of items yet to be learned. Criterion and convergent validation of this LR score is warranted to understand its sensitivity along the Alzheimer's disease (AD) continuum.

METHOD

The LR metric was calculated for 123 participants from standard measures of memory, including the Hopkins Verbal Learning Test-Revised, Brief Visuospatial Memory Test-Revised, Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) list learning, and RBANS story memory. All participants were categorized as normal cognition, mild cognitive impairment (MCI), or AD. LR performances were compared between groups, among other standard memory measures, and with regards to how well they discriminated cognitively impaired from unimpaired samples-and within diagnostic subgroups.

RESULTS

Lower LR scores were observed for the MCI and AD groups than the normal cognition group, with the AD group performing worse than the MCI group for several slope calculations. Lower LR scores were also consistently associated with poorer performances on traditional memory measures. LR scores further displayed excellent receiver operator characteristics when differentiating those with and without cognitive impairment-and MCI from normal cognition. Overall, LR scores consistently outperformed traditional learning slope calculations across all analyses.

CONCLUSIONS

This LR score is sensitive to memory dysfunction along the AD continuum, and results offer criterion and convergent validity for use of the LR metric to understand learning capacity.

Evaluation of semi-quantitative measures of 18F-flutemetamol PET for the clinical diagnosis of Alzheimer's disease

BACKGROUND

¹⁸F-flutemetamol positron emission tomography (PET) is used to assess cortical amyloid-β burden in patients with cognitive impairment to support a clinical diagnosis. Visual classification is the most widely used method in clinical practice although semi-quantification is beneficial to obtain an objective and continuous measure of the Aβ burden. The aims were: first to evaluate the correspondence between standardized uptake value ratios (SUVRs) from three different software, Centiloids and visual classification, second to estimate thresholds for supporting visual classification and last to assess differences in semi-quantitative measures between clinical diagnoses.

METHODS

This observational study included 195 patients with cognitive impairment who underwent ¹⁸F-flutemetamol PET. PET images were semi-quantified with SyngoVia, CortexID suite, and PMOD. Receiver operating characteristics curves were used to compare visual classification with composite SUVR normalized to pons (SUVRpons) and cerebellar cortex (SUVRcer), and Centiloids. We explored correlations and differences between semi-quantitative measures as well as differences in SUVR between two clinical diagnosis groups: Alzheimer's disease-group and non-Alzheimer's disease-group.

RESULTS

PET images from 191 patients were semi-quantified with SyngoVia and CortexID and 86 PET-magnetic resonance imaging pairs with PMOD. All receiver operating characteristics curves showed a high area under the curve (>0.98). Thresholds for a visually positive PET was for SUVRcer: 1.87 (SyngoVia) and 1.64 (CortexID) and for SUVRpons: 0.54 (SyngoVia) and 0.55 (CortexID). The threshold on the Centiloid scale was 39.6 Centiloids. All semi-quantitative measures showed a very high correlation between different software and normalization methods. Composite SUVRcer was significantly different between SyngoVia and PMOD, SyngoVia and CortexID but not between PMOD and CortexID. Composite SUVRpons were significantly different between all three software. There were significant differences in the mean rank of SUVRpons, SUVRcer, and Centiloid between Alzheimer's disease-group and non-Alzheimer's disease-group.

CONCLUSIONS

SUVR from different software performed equally well in discriminating visually positive and negative ¹⁸F-Flutemetamol PET images. Thresholds should be considered software-specific and cautiously be applied across software without preceding validation to categorize scans as positive or negative. SUVR and Centiloid may be used alongside a thorough clinical evaluation to support a clinical diagnosis.

Predicting biomarkers in intact older adults and those with amnestic Mild Cognitive Impairment, and mild Alzheimer's Disease using the Repeatable Battery for the Assessment of Neuropsychological Status

INTRODUCTION

The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) has been associated, to varying degrees, with commonly used biomarkers of Alzheimer's disease (AD). Given the ease of RBANS administration as a screening tool for clinical trials and other applications, a better understanding of how RBANS performance is associated with presence of APOE ε4 allele[s], cerebral amyloid burden, and hippocampal volume is warranted.

METHOD

One hundred twenty-one older adults who were classified as intact, amnestic Mild Cognitive Impairment, or mild AD underwent cognitive assessment with the RBANS, genetic analysis, and quantitative brain imaging. APOE ε4 carrier status, 18F-Flutemetamol composite standardized uptake value ratio (SUVR), and hippocampal volume were each regressed on demographic variables and RBANS Total Scale score, Index scores, and subtest scores.

RESULTS

Lower RBANS Total Scale score or Delayed Memory Index (DMI) predicted the presence of APOE ε4 allele[s], higher cerebral amyloid burden, and lower hippocampal volumes. DMI was a slightly better predictor than Total Scale score for most AD biomarkers. No demographic variables consistently contributed to these models.

CONCLUSIONS

The RBANS - DMI in particular - is sensitive to AD pathology. As such, it could be used as a predictive tool, particularly in clinical drug trials to enrich samples prior to less accessible AD biomarker investigation.

Clinical Utility of β-Amyloid PET Imaging in People Living With HIV With Cognitive Symptoms

BACKGROUND

Imaging with β-amyloid (Aβ) positron emission tomography (PET) has the potential to aid the diagnosis of the cause of cognitive impairment affecting people living with HIV (PLWH) when neurodegenerative disorders are considered. We evaluated the clinical utility of [18F]Florbetaben (FBB) in PLWH with cognitive symptoms.

METHODS

Imaging with FBB PET was performed in 20 patients with cognitive concerns about dementia. Neuropsychological testing, plasma neurofilament light protein, plasma Aβ40, Aβ42, and cerebrospinal fluid Aβ42, tau, and HIV RNA were obtained. FBB PET images were assessed visually by 3 readers blinded to the clinical diagnosis and quantitatively by obtaining a composite cortical to cerebellar cortex standardized uptake value ratio (SUVR). FBB SUVR from 10 age-matched healthy controls was compared with SUVR of PLWH.

RESULTS

Most participants were men (90%) of white ethnicity (90%) with a median age (interquartile range) of 59 (43-79) years. Median CD4 count was 682 (74-1056). All patients were on combination antiretroviral therapy with plasma and cerebrospinal fluid HIV RNA <40 copies/mL. Fourteen patients had objective cognitive impairment including 2 who met clinical criteria for a diagnosis of dementia. No significant differences in composite SUVRs between PLWH and controls [mean (SD): 1.18 (0.03) vs. 1.16 (0.09); P = 0.37] were observed. Four patients were FBB+ with the highest SUVR in the posterior cingulate, superior temporal, and frontal superior lobe. Amyloid PET results contributed to a change in diagnosis and treatment for 10 patients.

CONCLUSION

[18F]Florbetaben PET has potential as an adjunctive tool in the diagnosis of PLWH with cognitive impairment, increasing diagnostic certainty and optimizing management.

PET amyloid in normal aging: direct comparison of visual and automatic processing methods

Assessment of amyloid deposits is a critical step for the identification of Alzheimer disease (AD) signature in asymptomatic elders. Whether the different amyloid processing methods impacts on the quality of clinico-radiological correlations is still unclear. We directly compared in 155 elderly controls with extensive neuropsychological testing at baseline and 4.5 years follow-up three approaches: (i) operator-dependent standard visual reading, (ii) operator-independent automatic SUVR with four different reference regions, and (iii) novel operator and region of reference-independent automatic Aβ-index. The coefficient of variance was used to examine inter-individual variability for each processing method. Using visually-established amyloid positivity as the gold standard, the area under the receiver operating characteristic curve (ROC) was computed. Linear regression models were used to assess the association between changes in continuous cognitive score and amyloid uptake values. In SUVR analyses, the coefficient of variance varied from 1.718 to 1.762 according to the area of reference and was of − 3.045 for the Aβ-index method. Compared to the visual rating, Aβ-index method showed the largest area under the ROC curve [0.9568 (95% CI 0.9252, 0.98833)]. The best cut-off score was of − 0.3359 with sensitivity and specificity values of 0.97 and 0.83, respectively. Only the Aß-index was related to more severe decrement of cognitive performances [regression coefficient: 9.103 (95% CI 1.148, 17.058)]. The Aβ-index is considered as preferred option in asymptomatic elders, since it is operator-independent, avoids the selection of reference area, is closer to established visual scoring and correlates with the evolution of cognitive performances.

Deep learning-guided joint attenuation and scatter correction in multitracer neuroimaging studies

PET attenuation correction (AC) on systems lacking CT/transmission scanning, such as dedicated brain PET scanners and hybrid PET/MRI, is challenging. Direct AC in image-space, wherein PET images corrected for attenuation and scatter are synthesized from nonattenuation corrected PET (PET-nonAC) images in an end-to-end fashion using deep learning approaches (DLAC) is evaluated for various radiotracers used in molecular neuroimaging studies. One hundred eighty brain PET scans acquired using 18 F-FDG, 18 F-DOPA, 18 F-Flortaucipir (targeting tau pathology), and 18 F-Flutemetamol (targeting amyloid pathology) radiotracers (40 + 5, training/validation + external test, subjects for each radiotracer) were included. The PET data were reconstructed using CT-based AC (CTAC) to generate reference PET-CTAC and without AC to produce PET-nonAC images. A deep convolutional neural network was trained to generate PET attenuation corrected images (PET-DLAC) from PET-nonAC. The quantitative accuracy of this approach was investigated separately for each radiotracer considering the values obtained from PET-CTAC images as reference. A segmented AC map (PET-SegAC) containing soft-tissue and background air was also included in the evaluation. Quantitative analysis of PET images demonstrated superior performance of the DLAC approach compared to SegAC technique for all tracers. Despite the relatively low quantitative bias observed when using the DLAC approach, this approach appears vulnerable to outliers, resulting in noticeable local pseudo uptake and false cold regions. Direct AC in image-space using deep learning demonstrated quantitatively acceptable performance with less than 9% absolute SUV bias for the four different investigated neuroimaging radiotracers. However, this approach is vulnerable to outliers which result in large local quantitative bias.