Amyloid brain-dedicated PET images can diagnose Alzheimer's pathology with Centiloid Scale

PURPOSE

To evaluate whether the Centiloid Scale may be used to diagnose Alzheimer's Disease (AD) pathology effectively with the only use of amyloid PET imaging modality from a brain-dedicated PET scanner.

METHODS

This study included 26 patients with amyloid PET images with 3 different radiotracers. All patients were acquired both on a PET/CT and a brain-dedicated PET scanner (CareMiBrain, CMB), from which 4 different reconstructions were implemented. A new pipeline was proposed and used for the PET image analysis based on the original Centiloid Scale processing pipeline, but with only PET images. The Youden's Index was employed to calculate the optimal cutoffs for diagnosis and evaluated by the AUC, accuracy, precision, and recall metrics.

RESULTS

The Centiloid Scale (CL) processing pipeline was validated with and without the use of MR images. The CL cutoffs for AD pathology diagnosis on the PET/CT and the 4 CMB reconstructions were 34.4 ± 2.2, 43.5 ± 3.5, 51.9 ± 12.5, 57.5 ± 6.8 and 41.8 ± 1.2 respectively. Overall, for these cutoffs all metrics obtained the maximum score.

CONCLUSION

The Centiloid scale applied to PET images allows for AD pathology diagnosis. The CMB scanner can be used with the Centiloid scale to automatically assist in the diagnosis of AD pathology, relieving the large burden of neurodegenerative diseases on a traditional PET/CT.

Human in vivo evidence of associations between herpes simplex virus and cerebral amyloid-beta load in normal aging

BACKGROUND

Mounting data suggests that herpes simplex virus type 1 (HSV-1) is involved in the pathogenesis of AD, possibly instigating amyloid-beta (Aβ) accumulation decades before the onset of clinical symptoms. However, human in vivo evidence linking HSV-1 infection to AD pathology is lacking in normal aging, which may contribute to the elucidation of the role of HSV-1 infection as a potential AD risk factor.

METHODS

To shed light into this question, serum anti-HSV IgG levels were correlated with 18F-Florbetaben-PET binding to Aβ deposits and blood markers of neurodegeneration (pTau181 and neurofilament light chain) in cognitively normal older adults. Additionally, we investigated whether associations between anti-HSV IgG and AD markers were more evident in APOE4 carriers.

RESULTS

We showed that increased anti-HSV IgG levels are associated with higher Aβ load in fronto-temporal regions of cognitively normal older adults. Remarkably, these cortical regions exhibited abnormal patterns of resting state-functional connectivity (rs-FC) only in those individuals showing the highest levels of anti-HSV IgG. We further found that positive relationships between anti-HSV IgG levels and Aβ load, particularly in the anterior cingulate cortex, are moderated by the APOE4 genotype, the strongest genetic risk factor for AD. Importantly, anti-HSV IgG levels were unrelated to either subclinical cognitive deficits or to blood markers of neurodegeneration.

CONCLUSIONS

All together, these results suggest that HSV infection is selectively related to cortical Aβ deposition in normal aging, supporting the inclusion of cognitively normal older adults in prospective trials of antimicrobial therapy aimed at decreasing the AD risk in the aging population.

[1-11C]-Butanol Positron Emission Tomography reveals an impaired brain to nasal turbinates pathway in aging amyloid positive subjects

BACKGROUND

Reduced clearance of cerebrospinal fluid (CSF) has been suggested as a pathological feature of Alzheimer's disease (AD). With extensive documentation in non-human mammals and contradictory human neuroimaging data it remains unknown whether the nasal mucosa is a CSF drainage site in humans. Here, we used dynamic PET with [1-11C]-Butanol, a highly permeable radiotracer with no appreciable brain binding, to test the hypothesis that tracer drainage from the nasal pathway reflects CSF drainage from brain. As a test of the hypothesis, we examined whether brain and nasal fluid drainage times were correlated and affected by brain amyloid.

METHODS

24 cognitively normal subjects (≥ 65 years) were dynamically PET imaged for 60 min. using [1-11C]-Butanol. Imaging with either [11C]-PiB or [18F]-FBB identified 8 amyloid PET positive (Aβ+) and 16 Aβ- subjects. MRI-determined regions of interest (ROI) included: the carotid artery, the lateral orbitofrontal (LOF) brain, the cribriform plate, and an All-turbinate region comprised of the superior, middle, and inferior turbinates. The bilateral temporalis muscle and jugular veins served as control regions. Regional time-activity were used to model tracer influx, egress, and AUC.

RESULTS

LOF and All-turbinate 60 min AUC were positively associated, thus suggesting a connection between the brain and the nose. Further, the Aβ+ subgroup demonstrated impaired tracer kinetics, marked by reduced tracer influx and slower egress.

CONCLUSION

The data show that tracer kinetics for brain and nasal turbinates are related to each other and both reflect the amyloid status of the brain. As such, these data add to evidence that the nasal pathway is a potential CSF drainage site in humans. These data warrant further investigation of brain and nasal contributions to protein clearance in neurodegenerative disease.

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.

Amyloid PET Imaging: Standard Procedures and Semiquantification

Amyloid plaques are a neuropathologic hallmark of Alzheimer's disease (AD), which can be imaged through positron emission tomography (PET) technology using radiopharmaceuticals that selectively bind to the fibrillar aggregates of amyloid-β plaques (Amy-PET). Several radiotracers for amyloid PET have been validated (11C-Pittsburgh compound B and the 18F-labeled compounds such as 18F-florbetaben, 18F-florbetapir, and 18F-flutemetamol). Images can be interpreted by means of visual/qualitative, semiquantitative, and quantitative criteria. Here, we summarize the main differences between the available radiotracers for Amy-PET, the proposed interpretation criteria, and main proposed quantification methods.

DAT1 and BDNF polymorphisms interact to predict Aβ and tau pathology

Previous work has associated polymorphisms in the dopamine transporter gene (rs6347 in DAT1/SLC6A3) and brain derived neurotrophic factor gene (Val66Met in BDNF) with atrophy and memory decline. However, it is unclear whether these polymorphisms relate to atrophy and cognition through associations with Alzheimer's disease pathology. We tested for effects of DAT1 and BDNF polymorphisms on cross-sectional and longitudinal β-amyloid (Aβ) and tau pathology (measured with positron emission tomography (PET)), hippocampal volume, and cognition. We analyzed a sample of cognitively normal older adults (cross-sectional n = 321) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). DAT1 and BDNF interacted to predict Aβ-PET, tau-PET, and hippocampal atrophy. Carriers of both "non-boptimal" DAT1 C and BDNF Met alleles demonstrated greater pathology and atrophy. Our findings provide novel links between dopamine and neurotrophic factor genes and AD pathology, consistent with previous research implicating these variants in greater risk for developing AD.

Recruitment of pre-dementia participants: main enrollment barriers in a longitudinal amyloid-PET study

BACKGROUND

The mismatch between the limited availability versus the high demand of participants who are in the pre-dementia phase of Alzheimer's disease (AD) is a bottleneck for clinical studies in AD. Nevertheless, potential enrollment barriers in the pre-dementia population are relatively under-reported. In a large European longitudinal biomarker study (the AMYPAD-PNHS), we investigated main enrollment barriers in individuals with no or mild symptoms recruited from research and clinical parent cohorts (PCs) of ongoing observational studies.

METHODS

Logistic regression was used to predict study refusal based on sex, age, education, global cognition (MMSE), family history of dementia, and number of prior study visits. Study refusal rates and categorized enrollment barriers were compared between PCs using chi-squared tests.

RESULTS

535/1856 (28.8%) of the participants recruited from ongoing studies declined participation in the AMYPAD-PNHS. Only for participants recruited from clinical PCs (n = 243), a higher MMSE-score (β =  - 0.22, OR = 0.80, p < .05), more prior study visits (β =  - 0.93, OR = 0.40, p < .001), and positive family history of dementia (β = 2.08, OR = 8.02, p < .01) resulted in lower odds on study refusal. General study burden was the main enrollment barrier (36.1%), followed by amyloid-PET related burden (PCresearch = 27.4%, PCclinical = 9.0%, X2 = 10.56, p = .001), and loss of research interest (PCclinical = 46.3%, PCresearch = 16.5%, X2 = 32.34, p < .001).

CONCLUSIONS

The enrollment rate for the AMYPAD-PNHS was relatively high, suggesting an advantage of recruitment via ongoing studies. In this observational cohort, study burden reduction and tailored strategies may potentially improve participant enrollment into trial readiness cohorts such as for phase-3 early anti-amyloid intervention trials. The AMYPAD-PNHS (EudraCT: 2018-002277-22) was approved by the ethical review board of the VU Medical Center (VUmc) as the Sponsor site and in every affiliated site.

Prediction of amyloid positron emission tomography positivity using multiple regression analysis of quantitative susceptibility mapping

PURPOSE

To develop a method for predicting amyloid positron emission tomography (PET) positivity based on multiple regression analysis of quantitative susceptibility mapping (QSM).

MATERIALS AND METHODS

This prospective study included 39 patients with suspected dementia from four centers. QSM images were obtained through a 3-T, three-dimensional radiofrequency-spoiled gradient-echo sequence with multiple echoes. The cortical standard uptake value ratio (SUVR) was obtained using amyloid PET with 18F-flutemetamol, and susceptibility in the brain regions was obtained using QSM. A multiple regression model to predict cortical SUVR was constructed based on susceptibilities in multiple brain regions, with the constraint that cortical SUVR and susceptibility were positively correlated. The discrimination performance of the Aβ-positive and Aβ-negative cohorts was evaluated based on the predicted SUVR using the area under the receiver operating characteristic curve (AUC) and Mann-Whitney U test.

RESULTS

The correlation coefficients between true and predicted SUVR were increased by incorporating the constraint, and the AUC to discriminate between the Aβ-positive and Aβ-negative cohorts reached to 0.79 (p < 0.01).

CONCLUSION

These preliminary results suggest that a QSM-based multiple regression model can predict amyloid PET positivity with fair accuracy.

Amyloid and tau pathology are associated with cerebral blood flow in a mixed sample of nondemented older adults with and without vascular risk factors for Alzheimer's disease

Identification of biomarkers for the early stages of Alzheimer's disease (AD) is an imperative step in developing effective treatments. Cerebral blood flow (CBF) is a potential early biomarker for AD; generally, older adults with AD have decreased CBF compared to normally aging peers. CBF deviates as the disease process and symptoms progress. However, further characterization of the relationships between CBF and AD risk factors and pathologies is still needed. We assessed the relationships between CBF quantified by arterial spin-labeled magnetic resonance imaging, hypertension, APOEε4, and tau and amyloid positron emission tomography in 77 older adults: cognitively normal, subjective cognitive decline, and mild cognitive impairment. Tau and amyloid aggregation were related to altered CBF, and some of these relationships were dependent on hypertension or APOEε4 status. Our findings suggest a complex relationship between risk factors, AD pathologies, and CBF that warrants future studies of CBF as a potential early biomarker for AD.

Nurse-led pre-test counseling for Alzheimer's disease biomarker testing: Knowledge and skills required to meet the needs of patients and families

INTRODUCTION

Biomarker testing for Alzheimer's disease and related disorders (ADRD) brings new opportunities for nurses to foster shared decision-making by leading pre-test counseling (PTC) for patients and families.

METHODS

Audio-recordings of 18 nurse-led PTC sessions were analyzed to characterize questions posed by patient and family members dyads considering whether to pursue amyloid positron emission tomography.

RESULTS

Sessions lasted 20 to 75 minutes and generated rich discussion of the purpose and potential implications of amyloid imaging. Dyads posed questions regarding: basic neuroanatomy; the spectrum of normal cognitive aging to dementia; clinical phenotypes and pathological hallmarks of ADRD; secondary prevention of ADRD; and advance planning. In response, PTC facilitators provided disease-specific education, clarification of overt misconceptions, caregiver support, and emotion de-escalation.

CONCLUSION

Nurses conducting PTC for AD biomarker testing should be equipped to answer questions about topics both directly and indirectly related to testing, and also provide emotional support.

Passive Alzheimer's immunotherapy: A promising or uncertain option?

The US Food and Drug Administration (FDA)'s recent accelerated approval of two anti-amyloid antibodies for treatment of Alzheimer's disease (AD), aducanumab and lecanemab, has caused substantial debate. To inform this debate, we reviewed the literature on randomized clinical trials conducted with eight such antibodies focusing on clinical efficacy, cerebral amyloid removal, amyloid-related imaging abnormalities (ARIAs) and cerebral volumes to the extent such measurements have been reported. Two antibodies, donanemab and lecanemab, have demonstrated clinical efficacy, but these results remain uncertain. We further argue that the decreased amyloid PET signal in these trials is unlikely to be a one-to-one reflection of amyloid removal, but rather a reflection of increased therapy-related brain damage, as supported by the increased incidence of ARIAs and reported loss of brain volume. Due to these uncertainties of benefit and risk, we recommend that the FDA pauses existing approvals and approval of new antibodies until results of phase 4 studies with these drugs are available to inform on these risk-benefit uncertainties. We recommend that the FDA prioritize FDG PET and detection of ARIAs and accelerated brain volume loss with MRI in all trial patients, and neuropathological examination of all patients who die in these phase 4 trials.

Multimodal comparisons of QSM and PET in neurodegeneration and aging

Quantitative susceptibility mapping (QSM) has been used to study susceptibility changes that may occur based on tissue composition and mineral deposition. Iron is a primary contributor to changes in magnetic susceptibility and of particular interest in applications of QSM to neurodegeneration and aging. Iron can contribute to neurodegeneration through inflammatory processes and via interaction with aggregation of disease-related proteins. To better understand the local susceptibility changes observed on QSM, its signal has been studied in association with other imaging metrics such as positron emission tomography (PET). The associations of QSM and PET may provide insight into the pathophysiology of disease processes, such as the role of iron in aging and neurodegeneration, and help to determine the diagnostic utility of QSM as an indirect indicator of disease processes typically evaluated with PET. In this review we discuss the proposed mechanisms and summarize prior studies of the associations of QSM and amyloid PET, tau PET, TSPO PET, FDG-PET, 15O-PET, and F-DOPA PET in evaluation of neurologic diseases with a focus on aging and neurodegeneration.

Software compatibility analysis for quantitative measures of [18F]flutemetamol amyloid PET burden in mild cognitive impairment

RATIONALE

Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer's disease pathogenesis. In clinical practice, trained readers will visually categorise positron emission tomography (PET) scans as either Aβ positive or negative. However, adjunct quantitative analysis is becoming more widely available, where regulatory approved software can currently generate metrics such as standardised uptake value ratios (SUVr) and individual Z-scores. Therefore, it is of direct value to the imaging community to assess the compatibility of commercially available software packages. In this collaborative project, the compatibility of amyloid PET quantification was investigated across four regulatory approved software packages. In doing so, the intention is to increase visibility and understanding of clinically relevant quantitative methods.

METHODS

Composite SUVr using the pons as the reference region was generated from [¹⁸F]flutemetamol (GE Healthcare) PET in a retrospective cohort of 80 amnestic mild cognitive impairment (aMCI) patients (40 each male/female; mean age = 73 years, SD = 8.52). Based on previous autopsy validation work, an Aβ positivity threshold of ≥ 0.6 SUVr_pons was applied. Quantitative results from MIM Software's MIMneuro, Syntermed's NeuroQ, Hermes Medical Solutions' BRASS and GE Healthcare's CortexID were analysed using intraclass correlation coefficient (ICC), percentage agreement around the Aβ positivity threshold and kappa scores.

RESULTS

Using an Aβ positivity threshold of ≥ 0.6 SUVr_pons, 95% agreement was achieved across the four software packages. Two patients were narrowly classed as Aβ negative by one software package but positive by the others, and two patients vice versa. All kappa scores around the same Aβ positivity threshold, both combined (Fleiss') and individual software pairings (Cohen's), were ≥ 0.9 signifying "almost perfect" inter-rater reliability. Excellent reliability was found between composite SUVr measurements for all four software packages, with an average measure ICC of 0.97 and 95% confidence interval of 0.957-0.979. Correlation coefficient analysis between the two software packages reporting composite z-scores was strong (r² = 0.98).

CONCLUSION

Using an optimised cortical mask, regulatory approved software packages provided highly correlated and reliable quantification of [¹⁸F]flutemetamol amyloid PET with a ≥ 0.6 SUVr_pons positivity threshold. In particular, this work could be of interest to physicians performing routine clinical imaging rather than researchers performing more bespoke image analysis. Similar analysis is encouraged using other reference regions as well as the Centiloid scale, when it has been implemented by more software packages.

Large multi-ethnic genetic analyses of amyloid imaging identify new genes for Alzheimer disease

Amyloid PET imaging has been crucial for detecting the accumulation of amyloid beta (Aβ) deposits in the brain and to study Alzheimer's disease (AD). We performed a genome-wide association study on the largest collection of amyloid imaging data (N = 13,409) to date, across multiple ethnicities from multicenter cohorts to identify variants associated with brain amyloidosis and AD risk. We found a strong APOE signal on chr19q.13.32 (top SNP: APOE ɛ4; rs429358; β = 0.35, SE = 0.01, P = 6.2 × 10-311, MAF = 0.19), driven by APOE ɛ4, and five additional novel associations (APOE ε2/rs7412; rs73052335/rs5117, rs1081105, rs438811, and rs4420638) independent of APOE ɛ4. APOE ɛ4 and ε2 showed race specific effect with stronger association in Non-Hispanic Whites, with the lowest association in Asians. Besides the APOE, we also identified three other genome-wide loci: ABCA7 (rs12151021/chr19p.13.3; β = 0.07, SE = 0.01, P = 9.2 × 10-09, MAF = 0.32), CR1 (rs6656401/chr1q.32.2; β = 0.1, SE = 0.02, P = 2.4 × 10-10, MAF = 0.18) and FERMT2 locus (rs117834516/chr14q.22.1; β = 0.16, SE = 0.03, P = 1.1 × 10-09, MAF = 0.06) that all colocalized with AD risk. Sex-stratified analyses identified two novel female-specific signals on chr5p.14.1 (rs529007143, β = 0.79, SE = 0.14, P = 1.4 × 10-08, MAF = 0.006, sex-interaction P = 9.8 × 10-07) and chr11p.15.2 (rs192346166, β = 0.94, SE = 0.17, P = 3.7 × 10-08, MAF = 0.004, sex-interaction P = 1.3 × 10-03). We also demonstrated that the overall genetic architecture of brain amyloidosis overlaps with that of AD, Frontotemporal Dementia, stroke, and brain structure-related complex human traits. Overall, our results have important implications when estimating the individual risk to a population level, as race and sex will needed to be taken into account. This may affect participant selection for future clinical trials and therapies.

The relationship of insulin resistance and diabetes to tau PET SUVR in middle-aged to older adults

BACKGROUND

Insulin resistance (IR) and type 2 diabetes have been found to increase the risk for Alzheimer's clinical syndrome in epidemiologic studies but have not been associated with tau tangles in neuropathological research and have been inconsistently associated with cerebrospinal fluid P-tau181. IR and type 2 diabetes are well-recognized vascular risk factors. Some studies suggest that cardiovascular risk may act synergistically with cortical amyloid to increase tau measured using tau PET. Utilizing data from largely nondemented middle-aged and older adult cohorts enriched for AD risk, we investigated the association of IR and diabetes to tau PET and whether amyloid moderated those relationships.

METHODS

Participants were enrolled in either the Wisconsin Registry for Alzheimer's Prevention (WRAP) or Wisconsin Alzheimer's Disease Research Center (WI-ADRC) Clinical Core. Two partially overlapping samples were studied: a sample characterized using HOMA-IR (n=280 WRAP participants) and a sample characterized on diabetic status (n=285 WRAP and n=109 WI-ADRC). IR was measured using the homeostasis model assessment of insulin resistance (HOMA-IR). Tau PET employing the radioligand 18F-MK-6240 was used to detect AD-specific aggregated tau. Linear regression tested the relationship of IR and diabetic status to tau PET standardized uptake value ratio (SUVR) within the entorhinal cortex and whether relationships were moderated by amyloid assessed by amyloid PET distribution volume ratio (DVR) and amyloid PET positivity status.

RESULTS

Neither HOMA-IR nor diabetic status was significantly associated with tau PET SUVR. The relationship between IR and tau PET SUVR was not moderated by amyloid PET DVR or positivity status. The association between diabetic status and tau PET SUVR was not significantly moderated by amyloid PET DVR but was significantly moderated by amyloid PET positivity status. Among the amyloid PET-positive participants, the estimated marginal tau PET SUVR mean was higher in the diabetic (n=6) relative to the nondiabetic group (n=88).

CONCLUSION

Findings indicate that IR may not be related to tau in generally healthy middle-aged and older adults who are in the early stages of the AD clinicopathologic continuum but suggest the need for additional research to investigate whether a synergistic relationship between type 2 diabetes and amyloid is associated with increased tau levels.

APOE-ε4 modulates the association between regional amyloid deposition and cognitive performance in cognitively unimpaired middle-aged individuals

PURPOSE

To determine whether the APOE-ε4 allele modulates the relationship between regional β-amyloid (Aβ) accumulation and cognitive change in middle-aged cognitively unimpaired (CU) participants.

METHODS

The 352 CU participants (mean aged 61.1 [4.7] years) included completed two cognitive assessments (average interval 3.34 years), underwent [¹⁸F]flutemetamol Aβ positron emission tomography (PET), T1w magnetic resonance imaging (MRI), as well as APOE genotyping. Global and regional Aβ PET positivity was assessed across five regions-of-interest by visual reading (VR) and regional Centiloids. Linear regression models were developed to examine the interaction between regional and global Aβ PET positivity and APOE-ε4 status on longitudinal cognitive change assessed with the Preclinical Alzheimer's Cognitive Composite (PACC), episodic memory, and executive function, after controlling for age, sex, education, cognitive baseline scores, and hippocampal volume.

RESULTS

In total, 57 participants (16.2%) were VR+ of whom 41 (71.9%) were APOE-ε4 carriers. No significant APOE-ε4*global Aβ PET interactions were associated with cognitive change for any cognitive test. However, APOE-ε4 carriers who were VR+ in temporal areas (n = 19 [9.81%], p = 0.04) and in the striatum (n = 8 [4.14%], p = 0.01) exhibited a higher decline in the PACC. The temporal areas findings were replicated when regional PET positivity was determined with Centiloid values. Regionally, VR+ in the striatum was associated with higher memory decline. As for executive function, interactions between APOE-ε4 and regional VR+ were found in temporal and parietal regions, and in the striatum.

CONCLUSION

CU APOE-ε4 carriers with a positive Aβ PET VR in regions known to accumulate amyloid at later stages of the Alzheimer's disease (AD) continuum exhibited a steeper cognitive decline. This work supports the contention that regional VR of Aβ PET might convey prognostic information about future cognitive decline in individuals at higher risk of developing AD.

CLINICALTRIALS

gov Identifier: NCT02485730. Registered 20 June 2015 https://clinicaltrials.gov/ct2/show/NCT02485730 and ClinicalTrials.gov Identifier:NCT02685969. Registered 19 February 2016 https://clinicaltrials.gov/ct2/show/NCT02685969 .

Quantitative comparative analysis of amyloid PET images using three radiopharmaceuticals

OBJECTIVE

Amyloid positron emission tomography (PET) with F-18 florbetaben (FBB), F-18 flutemetamol (FMM), and F-18 florapronol (FPN) is being used clinically for the evaluation of dementia. These radiopharmaceuticals are commonly used to evaluate the accumulation of beta-amyloid plaques in the brain, but there are structural differences between them. We investigated whether there are any differences in the imaging characteristics.

METHODS

A total of 605 subjects were enrolled retrospectively in this study, including healthy subjects (HS) and patients with mild cognitive impairment or Alzheimer's disease. Participants underwent amyloid PET imaging using one of the three radiopharmaceuticals. The PET images were analyzed visually and semi-quantitatively using a standardized uptake value ratio (SUVR). In addition, we calculated and compared the cut-off SUVR of the representative regions for each radiopharmaceutical that can distinguish between positive and negative scans.

RESULTS

In the negative images of the HS group, the contrast between the white matter and the gray matter was high in the FMM PET images, while striatal uptake was relatively higher in the FPN PET images. The SUVR showed significant differences across the radiopharmaceuticals in all areas except the temporal lobe, but the range of differences was relatively small. Accuracy levels for the global cut-off SUVR to discriminate between positive and negative images were highest in FMM PET, with a value of 0.989. FBB PET also showed a high value of 0.978, while FPN PET showed a relatively low value of 0.901.

CONCLUSIONS

Negative amyloid PET images using the three radiopharmaceuticals showed visually and quantitatively similar imaging characteristics except in the striatum. Binary classification using the cut-off of the global cortex showed high accuracy overall, although there were some differences between the three PET images.

Static first-minute-frame (FMF) PET imaging after 18F-labeled amyloid tracer injection is correlated to [18F]FDG PET in patients with primary progressive aphasia

OBJECTIVE

To study the correlation between a static PET image of the first-minute-frame (FMF) acquired with ¹⁸F-labeled amyloid-binding radiotracers and brain [¹⁸F]FDG PET in patients with primary progressive aphasia (PPA).

MATERIAL AND METHODS

The study cohort includes 17 patients diagnosed with PPA with the following distribution: 9 nonfluent variant PPA, 4 logopenic variant PPA, 1 semantic variant PPA, 3 unclassifiable PPA. Regional SUVRs are extracted from FMFs and their corresponding [¹⁸F]FDG PET images and Pearson's correlation coefficients are calculated.

RESULTS

SUVRs of both images show similar patterns of regional cerebral alterations. Intrapatient correlation analyses result in a mean coefficient of r=0.94±0.06. Regional interpatient correlation coefficients of the study cohort are greater than 0.81. Radiotracer-specific and variant-specific subcohorts show no difference in the similarity between the images.

CONCLUSIONS

The static FMF could be a valid alternative to dynamic early-phase amyloid PET proposed in the literature, and a neurodegeneration biomarker for the diagnosis and classification of PPA in amyloid PET studies.

Regional Comparison of Imaging Biomarkers in the Striatum between Early- and Late-onset Alzheimer's Disease

Striatal changes in the pathogenesis of Alzheimer's disease (AD) is not fully understood yet. We compared structural and functional image differences in the striatum between patients with early onset AD (EOAD) and late onset AD (LOAD) to investigate whether EOAD harbors autosomal dominant AD like imaging findings. The clinical, neuropsychological and neuroimaging biomarkers of 77 probable AD patients and 107 elderly subjects with normal cognition (NC) from the Alzheimer's Disease Neuroimaging Initiative (ADNI)-2 dataset were analyzed. Enrolled each subject completed a 3-Tesla MRI, baseline 18F-FDG-PET, and baseline 18F-AV-45 (Florbetapir) amyloid PET studies. AD patients were divided into two groups based on the onset age of clinical symptoms (EOAD <65 yrs; LOAD ≥65 yrs). A standardized uptake value ratio of the striatum and subcortical structures was obtained from both amyloid and FDG-PET scans. Structural MR imaging analysis was conducted using a parametric boundary description protocol, SPHARM-PDM. Of the 77 AD patients, 18 were EOAD and 59 were LOAD. Except for age of symptom onset, there were no statistically significant differences between the groups in demographics and detailed neuropsychological test results. 18F-AV-45 amyloid PET showed marked β-amyloid accumulation in the bilateral caudate nucleus and left pallidum in the EOAD group. Intriguingly, the caudate nucleus and putamen showed maintained glucose metabolism in the EOAD group compared to the LOAD group. Our image findings in the striatum of EOAD patients suggest that sporadic EOAD may share some pathophysiological changes noted in autosomal dominant AD.

β-amyloid PET harmonisation across longitudinal studies: Application to AIBL, ADNI and OASIS3

INTRODUCTION

The Centiloid scale was developed to harmonise the quantification of β-amyloid (Aβ) PET images across tracers, scanners, and processing pipelines. However, several groups have reported differences across tracers and scanners even after centiloid conversion. In this study, we aim to evaluate the impact of different pre and post-processing harmonisation steps on the robustness of longitudinal Centiloid data across three large international cohort studies.

METHODS

All Aβ PET data in AIBL (N = 3315), ADNI (N = 3442) and OASIS3 (N = 1398) were quantified using the MRI-based Centiloid standard SPM pipeline and the PET-only pipeline CapAIBL. SUVR were converted into Centiloids using each tracer's respective transform. Global Aβ burden from pre-defined target cortical regions in Centiloid units were quantified for both raw PET scans and PET scans smoothed to a uniform 8 mm full width half maximum (FWHM) effective smoothness. For Florbetapir, we assessed the performance of using both the standard Whole Cerebellum (WCb) and a composite white matter (WM)+WCb reference region. Additionally, our recently proposed quantification based on Non-negative Matrix Factorisation (NMF) was applied to all spatially and SUVR normalised images. Correlation with clinical severity measured by the Mini-Mental State Examination (MMSE) and effect size, as well as tracer agreement in 11C-PiB-18F-Florbetapir pairs and longitudinal consistency were evaluated.

RESULTS

The smoothing to a uniform resolution partially reduced longitudinal variability, but did not improve inter-tracer agreement, effect size or correlation with MMSE. Using a Composite reference region for 18F-Florbetapir improved inter-tracer agreement, effect size, correlation with MMSE, and longitudinal consistency. The best results were however obtained when using the NMF method which outperformed all other quantification approaches in all metrics used.

CONCLUSIONS

FWHM smoothing has limited impact on longitudinal consistency or outliers. A Composite reference region including subcortical WM should be used for computing both cross-sectional and longitudinal Florbetapir Centiloid. NMF improves Centiloid quantification on all metrics examined.

Cerebral blood flow, tau imaging, and memory associations in cognitively unimpaired older adults

OBJECTIVE

Cerebral blood flow (CBF) has been independently linked to cognitive impairment and traditional Alzheimer's disease (AD) pathology (e.g., amyloid-beta [Aβ], tau) in older adults. However, less is known about the possible interactive effects of CBF, Aβ, and tau on memory performance. The present study examined whether CBF moderates the effect of Aβ and tau on objective and subjective memory within cognitively unimpaired (CU) older adults.

METHODS

Participants included 54 predominately white CU older adults from the Alzheimer's Disease Neuroimaging Initiative. Multiple linear regression models examined meta-temporal CBF associations with (1) meta-temporal tau PET adjusting for cortical Aβ PET and (2) and cortical Aβ PET adjusting for tau PET. The CBF and tau meta region was an average of 5 distinct temporal lobe regions. CBF interactions with Aβ or tau PET on memory performance were also examined. Covariates for all models included age, sex, education, pulse pressure, APOE-ε4 positivity, and imaging acquisition date differences.

RESULTS

CBF was significantly negatively associated with tau PET (t = -2.16, p = .04) but not Aβ PET (t = 0.98, p = .33). Results revealed a CBF by tau PET interaction such that there was a stronger effect of tau PET on objective (t = 2.51, p = .02) and subjective (t = -2.67, p = .01) memory outcomes among individuals with lower levels of CBF.

CONCLUSIONS

Cerebrovascular and tau pathologies may interact to influence cognitive performance. This study highlights the need for future vascular risk interventions, which could offer a scalable and cost-effective method for AD prevention.

Development and clinical validation of CT-based regional modified Centiloid method for amyloid PET

Background

The standard Centiloid (CL) method was proposed to harmonize and quantify global ¹⁸F-labeled amyloid beta (Aβ) PET ligands using MRI as an anatomical reference. However, there is need for harmonizing and quantifying regional Aβ uptakes between ligands using CT as an anatomical reference. In the present study, we developed and validated a CT-based regional direct comparison of ¹⁸F-florbetaben (FBB) and ¹⁸F-flutemetamol (FMM) Centiloid (rdcCL).

Methods

For development of MRI-based or CT-based rdcCLs, the cohort consisted of 63 subjects (20 young controls (YC) and 18 old controls (OC), and 25 participants with Alzheimer’s disease dementia (ADD)). We performed a direct comparison of the FMM-FBB rdcCL method using MRI and CT images to define a common target region and the six regional VOIs of frontal, temporal, parietal, posterior cingulate, occipital, and striatal regions. Global and regional rdcCL scales were compared between MRI-based and CT-based methods. For clinical validation, the cohort consisted of 2245 subjects (627 CN, 933 MCI, and 685 ADD).

Results

Both MRI-based and CT-based rdcCL scales showed that FMM and FBB were highly correlated with each other, globally and regionally (R² = 0.96~0.99). Both FMM and FBB showed that CT-based rdcCL scales were highly correlated with MRI-based rdcCL scales (R² = 0.97~0.99). Regarding the absolute difference of rdcCLs between FMM and FBB, the CT-based method was not different from the MRI-based method, globally or regionally (p value = 0.07~0.95). In our clinical validation study, the global negative group showed that the regional positive subgroup had worse neuropsychological performance than the regional negative subgroup (p < 0.05). The global positive group also showed that the striatal positive subgroup had worse neuropsychological performance than the striatal negative subgroup (p < 0.05).

Conclusions

Our findings suggest that it is feasible to convert regional FMM or FBB rdcSUVR values into rdcCL scales without additional MRI scans. This allows a more easily accessible method for researchers that can be applicable to a variety of different conditions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13195-022-01099-0.

Change in brain amyloid load and cognition in patients with amnestic mild cognitive impairment: a 3-year follow-up study

Background

Our aim was to investigate the discriminative value of ¹⁸F-Flutemetamol PET in longitudinal assessment of amyloid beta accumulation in amnestic mild cognitive impairment (aMCI) patients, in relation to longitudinal cognitive changes.

Methods

We investigated the change in ¹⁸F-Flutemetamol uptake and cognitive impairment in aMCI patients over time up to 3 years which enabled us to investigate possible association between changes in brain amyloid load and cognition over time. Thirty-four patients with aMCI (mean age 73.4 years, SD 6.6) were examined with ¹⁸F-Flutemetamol PET scan, brain MRI and cognitive tests at baseline and after 3-year follow-up or earlier if the patient had converted to Alzheimer´s disease (AD). ¹⁸F-Flutemetamol data were analyzed both with automated region-of-interest analysis and voxel-based statistical parametric mapping.

Results

¹⁸F-flutemetamol uptake increased during the follow-up, and the increase was significantly higher in patients who were amyloid positive at baseline as compared to the amyloid-negative ones. At follow-up, there was a significant association between ¹⁸F-Flutemetamol uptake and MMSE, logical memory I (immediate recall), logical memory II (delayed recall) and verbal fluency. An association was seen between the increase in ¹⁸F-Flutemetamol uptake and decline in MMSE and logical memory I scores.

Conclusions

In the early phase of aMCI, presence of amyloid pathology at baseline strongly predicted amyloid accumulation during follow-up, which was further paralleled by cognitive declines. Inversely, some of our patients remained amyloid negative also at the end of the study without significant change in ¹⁸F-Flutemetamol uptake or cognition. Future studies with longer follow-up are needed to distinguish whether the underlying pathophysiology of aMCI in such patients is other than AD.

Deep-learning prediction of amyloid deposition from early-phase amyloid positron emission tomography imaging

OBJECTIVE

While the use of biomarkers for the detection of early and preclinical Alzheimer's Disease has become essential, the need to wait for over an hour after injection to obtain sufficient image quality can be challenging for patients with suspected dementia and their caregivers. This study aimed to develop an image-based deep-learning technique to generate delayed uptake patterns of amyloid positron emission tomography (PET) images using only early-phase images obtained from 0-20 min after radiotracer injection.

METHODS

We prepared pairs of early and delayed [¹¹C]PiB dynamic images from 253 patients (cognitively normal n = 32, fronto-temporal dementia n = 39, mild cognitive impairment n = 19, Alzheimer's disease n = 163) as a training dataset. The neural network was trained with the early images as the input, and the output was the corresponding delayed image. A U-net convolutional neural network (CNN) and a conditional generative adversarial network (C-GAN) were used for the deep-learning architecture and the data augmentation methods, respectively. Then, an independent test data set consisting of early-phase amyloid PET images (n = 19) was used to generate corresponding delayed images using the trained network. Two nuclear medicine physicians interpreted the actual delayed images and predicted delayed images for amyloid positivity. In addition, the concordance of the actual delayed and predicted delayed images was assessed statistically.

RESULTS

The concordance of amyloid positivity between the actual versus AI-predicted delayed images was 79%(κ = 0.60) and 79% (κ = 0.59) for each physician, respectively. In addition, the physicians' agreement rate was at 89% (κ = 0.79) when the same image was interpreted. And, the actual versus AI-predicted delayed images were not readily distinguishable (correct answer rate, 55% and 47% for each physician, respectively). The statistical comparison of the actual versus the predicted delated images indicated that the peak signal-to-noise ratio (PSNR) was 21.8 dB ± 2.2 dB, and the structural similarity index (SSIM) was 0.45 ± 0.04.

CONCLUSION

This study demonstrates the feasibility of an image-based deep-learning framework to predict delayed patterns of Amyloid PET uptake using only the early phase images. This AI-based image generation method has the potential to reduce scan time for amyloid PET and increase the patient throughput, without sacrificing diagnostic accuracy for amyloid positivity.

Alzheimer disease neuropathology in a patient previously treated with aducanumab

Amyloid beta (Aβ) plaque is a defining pathologic feature of Alzheimer disease (AD). Aducanumab, a monoclonal IgG1 that selectively binds aggregated species of Aβ, has been shown by amyloid positron emission tomography (Amyloid PET) to reduce Aβ plaques in patients with prodromal and mild AD. This is the first autopsy report of the AD neuropathology in a patient previously treated with aducanumab. The patient was an 84-year-old woman who was randomized to the placebo arm of the PRIME Phase 1b study (221AD103). The patient progressed to moderate dementia (MMSE = 14/30), beyond the targeted early AD treatment stage, before receiving aducanumab in the long-term extension (LTE). The patient then received 32 monthly doses of aducanumab, titrated up to 6 mg/kg, for a cumulative dose of 186 mg/kg. In the LTE, Amyloid PET scans demonstrated robust Aβ plaque reduction, from a composite standard uptake value ratio (SUVR) of 1.5 at screening to < 1.1 at 56 weeks post-aducanumab dosing. MRI examinations were negative for amyloid-related imaging abnormalities (ARIA). She passed away in hospice care 4 months after her last dose of aducanumab. The postmortem neuropathologic examination confirmed AD neuropathologic changes. Aβ and IBA1 immunohistochemistry assays demonstrated sparse residual Aβ plaque engaged by amoeboid reactive microglia. Phospho-Tau (pTau) immunohistochemistry demonstrated neocortical neurofibrillary degeneration (Braak stage V, NIA/AA Stage B3). However, the density of pTau neuropathology, including neuritic plaque pTau (NP-Tau), appeared lower in the PRIME LTE Patient compared to a reference cohort of untreated Braak stage V-VI, NIA/AA Stage B3 AD cases. Taken together, this case report is the first to provide Amyloid PET and neuropathologic evidence substantiating the impact of aducanumab to reduce Aβ plaque neuropathology in a patient with AD. Furthermore, this report underscores the critical importance of autopsy neuropathology studies to augment our understanding of aducanumab's mechanism of action and impact on AD biomarkers.

A comparison of advanced semi-quantitative amyloid PET analysis methods

PURPOSE

To date, there is no consensus on how to semi-quantitatively assess brain amyloid PET. Some approaches use late acquisition alone (e.g., ELBA, based on radiomic features), others integrate the early scan (e.g., TDr, which targets the area of maximum perfusion) and structural imaging (e.g., WMR, that compares kinetic behaviour of white and grey matter, or SI based on the kinetic characteristics of the grey matter alone). In this study SUVr, ELBA, TDr, WMR, and SI were compared. The latter - the most complete one - provided the reference measure for amyloid burden allowing to assess the efficacy and feasibility in clinical setting of the other approaches.

METHODS

We used data from 85 patients (aged 44-87) who underwent dual time-point PET/MRI acquisitions. The correlations with SI were computed and the methods compared with the visual assessment. Assuming SUVr, ELBA, TDr, and WMR to be independent measures, we linearly combined them to obtain more robust indices. Finally, we investigated possible associations between each quantifier and age in amyloid-negative patients.

RESULTS

Each quantifier exhibited excellent agreement with visual assessment and strong correlation with SI (average AUC = 0.99, ρ = 0.91). Exceptions to this were observed for subcortical regions with ELBA and WMR (ρ_ELBA = 0.44, ρ_WMR = 0.70). The linear combinations showed better performances than the individual methods. Significant associations were observed between TDr, WMR, SI, and age in amyloid-negative patients (p < 0.05).

CONCLUSION

Among the other methods, TDr came closest to the reference with less implementation complexity. Moreover, this study suggests that combining independent approaches gives better results than the individual procedure, so efforts should focus on multi-classifier systems for amyloid PET. Finally, the ability of techniques integrating blood perfusion to depict age-related variations in amyloid load in amyloid-negative subjects demonstrates the goodness of the estimate.

Impact of cerebral blood flow and amyloid load on SUVR bias

Background

Despite its widespread use, the semi-quantitative standardized uptake value ratio (SUVR) may be biased compared with the distribution volume ratio (DVR). This bias may be partially explained by changes in cerebral blood flow (CBF) and is likely to be also dependent on the extent of the underlying amyloid-β (Aβ) burden. This study aimed to compare SUVR with DVR and to evaluate the effects of underlying Aβ burden and CBF on bias in SUVR in mainly cognitively unimpaired participants. Participants were scanned according to a dual-time window protocol, with either [¹⁸F]flutemetamol (N = 90) or [¹⁸F]florbetaben (N = 31). The validated basisfunction-based implementation of the two-step simplified reference tissue model was used to derive DVR and R₁ parametric images, and SUVR was calculated from 90 to 110 min post-injection, all with the cerebellar grey matter as reference tissue. First, linear regression and Bland–Altman analyses were used to compare (regional) SUVR with DVR. Then, generalized linear models were applied to evaluate whether (bias in) SUVR relative to DVR could be explained by R₁ for the global cortical average (GCA), precuneus, posterior cingulate, and orbitofrontal region.

Results

Despite high correlations (GCA: R² ≥ 0.85), large overestimation and proportional bias of SUVR relative to DVR was observed. Negative associations were observed between both SUVR or SUVR_bias and R_1, albeit non-significant.

Conclusion

The present findings demonstrate that bias in SUVR relative to DVR is strongly related to underlying Aβ burden. Furthermore, in a cohort consisting mainly of cognitively unimpaired individuals, the effect of relative CBF on bias in SUVR appears limited. EudraCT Number: 2018-002277-22, registered on: 25-06-2018.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13550-022-00898-8.

Interactive Effects of Pulse Pressure and Tau Imaging on Longitudinal Cognition

BACKGROUND

Studies have demonstrated that both tau and cardiovascular risk are associated with cognitive decline, but the possible synergistic effects of these pathologic markers remain unclear.

OBJECTIVE

To explore the interaction of AD biomarkers with a specific vascular risk marker (pulse pressure) on longitudinal cognition.

METHODS

Participants included 139 older adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Biomarkers of tau, amyloid-β (Aβ), and vascular risk (pulse pressure) were assessed. Neuropsychological assessment provided memory, language, and executive function domain composite scores at baseline and 1-year follow-up. Multiple linear regression examined interactive effects of pulse pressure with tau PET independent of Aβ PET and Aβ PET independent of tau PET on baseline and 1-year cognitive outcomes.

RESULTS

The interaction between pulse pressure and tau PET significantly predicted 1-year memory performance such that the combined effect of high pulse pressure and high tau PET levels was associated with lower memory at follow-up but not at baseline. In contrast, Aβ PET did not significantly interact with pulse pressure to predict baseline or 1-year outcomes in any cognitive domain. Main effects revealed a significant effect of tau PET on memory, and no significant effects of Aβ PET or pulse pressure on any cognitive domain.

CONCLUSION

Results indicate that tau and an indirect marker of arterial stiffening (pulse pressure) may synergistically contribute to memory decline, whereas Aβ may have a lesser role in predicting cognitive progression. Tau and vascular pathology (particularly in combination) may represent valuable targets for interventions intended to slow cognitive decline.

Boosting the diagnostic power of amyloid-β PET using a data-driven spatially informed classifier for decision support

BACKGROUND

Amyloid-β (Aβ) PET has emerged as clinically useful for more accurate diagnosis of patients with cognitive decline. Aβ deposition is a necessary cause or response to the cellular pathology of Alzheimer's disease (AD). Usual clinical and research interpretation of amyloid PET does not fully utilise all information regarding the spatial distribution of signal. We present a data-driven, spatially informed classifier to boost the diagnostic power of amyloid PET in AD.

METHODS

Voxel-wise k-means clustering of amyloid-positive voxels was performed; clusters were mapped to brain anatomy and tested for their associations by diagnostic category and disease severity with 758 amyloid PET scans from volunteers in the AD continuum from the Alzheimer's Disease Neuroimaging Initiative (ADNI). A machine learning approach based on this spatially constrained model using an optimised quadratic support vector machine was developed for automatic classification of scans for AD vs non-AD pathology.

RESULTS

This classifier boosted the accuracy of classification of AD scans to 81% using the amyloid PET alone with an area under the curve (AUC) of 0.91 compared to other spatial methods. This increased sensitivity to detect AD by 15% and the AUC by 9% compared to the use of a composite region of interest SUVr.

CONCLUSIONS

The diagnostic classification accuracy of amyloid PET was improved using an automated data-driven spatial classifier. Our classifier highlights the importance of considering the spatial variation in Aβ PET signal for optimal interpretation of scans. The algorithm now is available to be evaluated prospectively as a tool for automated clinical decision support in research settings.

In vivo staging of regional amyloid progression in healthy middle-aged to older people at risk of Alzheimer's disease

BACKGROUND

We investigated regional amyloid staging characteristics in 11C-PiB-PET data from middle-aged to older participants at elevated risk for AD enrolled in the Wisconsin Registry for Alzheimer's Prevention.

METHODS

We analyzed partial volume effect-corrected 11C-PiB-PET distribution volume ratio maps from 220 participants (mean age = 61.4 years, range 46.9-76.8 years). Regional amyloid positivity was established using region-specific thresholds. We used four stages from the frequency-based staging of amyloid positivity to characterize individual amyloid deposition. Longitudinal PET data was used to assess the temporal progression of stages and to evaluate the emergence of regional amyloid positivity in participants who were amyloid-negative at baseline. We also assessed the effect of amyloid stage on longitudinal cognitive trajectories.

RESULTS

The staging model suggested progressive accumulation of amyloid from associative to primary neocortex and gradually involving subcortical regions. Longitudinal PET measurements supported the cross-sectionally estimated amyloid progression. In mixed-effects longitudinal analysis of cognitive follow-up data obtained over an average period of 6.5 years following the baseline PET measurement, amyloid stage II showed a faster decline in executive function, and advanced amyloid stages (III and IV) showed a faster decline across multiple cognitive domains compared to stage 0.

CONCLUSIONS

Overall, the 11C-PiB-PET-based staging model was generally consistent with previously derived models from 18F-labeled amyloid PET scans and a longitudinal course of amyloid accumulation. Differences in longitudinal cognitive decline support the potential clinical utility of in vivo amyloid staging for risk stratification of the preclinical phase of AD even in middle-aged to older individuals at risk for AD.

Probing the Role of a Regional Quantitative Assessment of Amyloid PET

BACKGROUND

In clinical practice, the amy-PET is globally inspected to provide a binary outcome, but the role of a regional assessment has not been fully investigated yet.

OBJECTIVE

To deepen the role of regional amyloid burden and its implication on clinical-neuropsychological features.

MATERIALS

Amy-PET and a complete neuropsychological assessment (Trail Making Test, Rey Auditory Verbal Learning Test, semantic verbal fluency, Symbol Digit, Stroop, visuoconstruction) were available in 109 patients with clinical suspicion of Alzheimer's disease. By averaging the standardized uptake value ratio and ELBA, a regional quantification was calculated for each scan. Patients were grouped according to their overall amyloid load: correlation maps, based on regional quantification, were calculated and compared. A regression analysis between neuropsychological assessment and the regional amyloid-β (Aβ) load was carried out.

RESULTS

Significant differences were observed between the correlation maps of patients at increasing levels of Aβ and the overall dataset. The Aβ uptake of the subcortical gray matter resulted not related to other brain regions independently of the global Aβ level. A significant association of semantic verbal fluency was observed with ratios of cortical and subcortical distribution of Aβ which represent a coarse measure of differences in regional distribution of Aβ.

CONCLUSION

Our observations confirmed the different susceptibility to Aβ accumulation among brain regions. The association between cognition and Aβ distribution deserves further investigations: it is possibly due to a direct local effect or it represents a proxy marker of a more aggressive disease subtype. Regional Aβ assessment represents an available resource on amy-PET scan with possibly clinical and prognostic implications.

True ultra-low-dose amyloid PET/MRI enhanced with deep learning for clinical interpretation

PURPOSE

While sampled or short-frame realizations have shown the potential power of deep learning to reduce radiation dose for PET images, evidence in true injected ultra-low-dose cases is lacking. Therefore, we evaluated deep learning enhancement using a significantly reduced injected radiotracer protocol for amyloid PET/MRI.

METHODS

Eighteen participants underwent two separate ¹⁸F-florbetaben PET/MRI studies in which an ultra-low-dose (6.64 ± 3.57 MBq, 2.2 ± 1.3% of standard) or a standard-dose (300 ± 14 MBq) was injected. The PET counts from the standard-dose list-mode data were also undersampled to approximate an ultra-low-dose session. A pre-trained convolutional neural network was fine-tuned using MR images and either the injected or sampled ultra-low-dose PET as inputs. Image quality of the enhanced images was evaluated using three metrics (peak signal-to-noise ratio, structural similarity, and root mean square error), as well as the coefficient of variation (CV) for regional standard uptake value ratios (SUVRs). Mean cerebral uptake was correlated across image types to assess the validity of the sampled realizations. To judge clinical performance, four trained readers scored image quality on a five-point scale (using 15% non-inferiority limits for proportion of studies rated 3 or better) and classified cases into amyloid-positive and negative studies.

RESULTS

The deep learning-enhanced PET images showed marked improvement on all quality metrics compared with the low-dose images as well as having generally similar regional CVs as the standard-dose. All enhanced images were non-inferior to their standard-dose counterparts. Accuracy for amyloid status was high (97.2% and 91.7% for images enhanced from injected and sampled ultra-low-dose data, respectively) which was similar to intra-reader reproducibility of standard-dose images (98.6%).

CONCLUSION

Deep learning methods can synthesize diagnostic-quality PET images from ultra-low injected dose simultaneous PET/MRI data, demonstrating the general validity of sampled realizations and the potential to reduce dose significantly for amyloid imaging.

The role of amyloid PET in patient selection for extra-ventricular shunt insertion for the treatment of idiopathic normal pressure hydrocephalus: A pooled analysis

BACKGROUND

Idiopathic Normal Pressure Hydrocephalus (iNPH) can be effectively treated through shunt insertion. However, most shunted patients experience little or no clinical benefit, which suggests suboptimal patient selection. While contentious, multiple studies have reported poorer shunt outcomes associated with concomitant Alzheimer's disease. Prompted by this observation, multiple studies have assessed the role of amyloid PET, a specific test for Alzheimer's disease, in patient selection for shunting.

METHODS

A comprehensive literature search was performed to identify studies that assessed the association between amyloid PET result and the clinical response to shunting in patients with suspected iNPH. Pooled diagnostic statistics were calculated.

RESULTS

Across three relevant studies, a total of 38 patients with suspected iNPH underwent amyloid PET imaging and shunt insertion. Twenty-three patients had a positive clinical response to shunting. 18/28 (64.3%) of patients with a negative amyloid PET and 5/10 (50%) with a positive amyloid PET had a positive response to shunting. The pooled sensitivity, specificity and accuracy was 33.3%, 76.2% and 58.3%. None of these statistics reached statistical significance.

CONCLUSION

The results of this pooled analysis do not support the selection of patients with suspected iNPH for shunting on the basis of amyloid PET alone. However, due to small cohort sizes and weakness in study design, further high-quality studies are required to properly determine the role of amyloid PET in assessing this complex patient group.

PET/MRI Delivers Multimodal Brain Signature in Alzheimer's Disease with De Novo PSEN1 Mutation

BACKGROUND

Little is known so far about the brain phenotype and the spatial interplay of different Alzheimer's disease (AD) biomarkers with structural and functional brain connectivity in the early phase of autosomal-dominant AD (ADAD). Multimodal PET/MRI might be suitable to fill this gap.

MATERIAL AND METHODS

We presented a 31-year-old male patient without a family history of dementia with progressive worsening of memory and motor function. Two separate sessions of 3T PET/MRI acquisitions were arranged with the ß-amyloid tracer [¹⁸F]Florbetaben and the secondgeneration tau tracer [¹⁸F]PI-2620. Simultaneously acquired MRI consisted of high-resolution 3D T1, diffusion-tensor imaging (DTI), and resting-state fMRI. PET/MRI data were compared with ten age-matched healthy controls.

RESULTS

Widespread β-amyloid depositions were found in cortical regions, and striatum (Thal stage III) along with tau pathology restricted to the mesial-temporal structures (Braak stage III/IV). Volumetric/shape analysis of subcortical structures revealed atrophy of the hippocampal-amygdala complex. In addition, cortical thinning was detected in the right middle temporal pole. Alterations of multiple DTI indices were noted in the major white matter fiber bundles, together with disruption of default mode and sensory-motor network functional connectivity. Molecular genetic analysis by next-generation sequencing revealed a heterozygote missense pathogenic variant of the PSEN1 (Met233Val).

CONCLUSION

Multimodal PET/MR imaging is able to deliver, in a one-stop-shop approach, an array of molecular, structural and functional brain information in AD due to de novo pathogenic variant, which can be studied for spatial interplay and might provide a rationale for initiating anti- amyloid/tau therapeutic approaches.

Relationship between F-18 florbetapir uptake in occipital lobe and neurocognitive performance in Alzheimer's disease

PURPOSE

To determine the association between occipital amyloid-PET uptake and neurocognitive performance in Alzheimer's disease (AD).

MATERIALS AND METHODS

Fifty-eight participants with normal aged, mild cognitive impairment (MCI) due to AD and AD subjects who underwent F-18 florbetapir brain PET/CT scans were divided into four groups (A, normal; B, MCI; C, mild AD; and D, moderate/severe AD). Semiquantitative analyses of SUVR images were performed. The differences between groups and the correlations between florbetapir uptake and Thai Mental State Examination (TMSE) scores were determined. Significant differences were defined using a P < 0.001, uncorrected, or a P < 0.05, FWE for the voxel-based analyses with Statistical Parametric Mapping (SPM).

RESULTS

There was a slightly higher florbetapir uptake in the precuneus, parietal, and occipital association cortices in Group B > A. The occipital florbetapir uptake in Groups C and D was significantly higher than in Group A, in addition to the precuneus, anterior cingulate, posterior cingulate, temporoparietal, and frontal cortices. There was a strong negative correlation between TMSE scores and florbetapir uptake in the occipital lobe.

CONCLUSIONS

Occipital amyloid uptake is associated with clinically advanced AD, and is inversely correlated with neurocognitive performance and may be useful for evaluating AD severity.

Regional Amyloid Accumulation and White Matter Integrity in Cognitively Normal Individuals

BACKGROUND

Recent studies have shown that amyloid-β (Aβ) burden influenced white matter (WM) integrity before the onset of dementia.

OBJECTIVE

To assess whether the effects of Aβ burden on WM integrity in cognitively normal (CN) individuals were regionally specific.

METHODS

Our cohort consisted of 71 CNs from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database who underwent both AV45 amyloid-PET and diffusion tensor imaging. Standardized uptake value ratio (SUVR) was computed across four bilateral regions of interest (ROIs) corresponding to four stages of in vivo amyloid staging model (Amyloid stages I-IV). Linear regression models were conducted in entire CN group and between APOEɛ4 carriers and non-carriers.

RESULTS

Our results indicated that higher global Aβ-SUVR was associated with higher mean diffusivity (MD) in the entire CN group (p = 0.023), and with both higher MD (p = 0.015) and lower fractional anisotropy (FA) (p = 0.026) in APOEɛ4 carriers. Subregion analysis showed that higher Amyloid stage I-II Aβ-SUVRs were associated with higher MD (Stage-1: p = 0.030; Stage-2: p = 0.016) in the entire CN group, and with both higher MD (Stage-1: p = 0.004; Stage-2: p = 0.010) and lower FA (Stage-1: p = 0.022; Stage-2: p = 0.014) in APOEɛ4 carriers. No associations were found in APOEɛ4 non-carriers and in Amyloid stage III-IV ROIs.

CONCLUSIONS

Our results indicated that the effects of Aβ burden on WM integrity in CNs might be regionally specific, particularly in Amyloid stage I-II ROIs, and modulated by APOEɛ4 status.

A randomized, double-blind, phase 2b proof-of-concept clinical trial in early Alzheimer's disease with lecanemab, an anti-Aβ protofibril antibody

BACKGROUND

Lecanemab (BAN2401), an IgG1 monoclonal antibody, preferentially targets soluble aggregated amyloid beta (Aβ), with activity across oligomers, protofibrils, and insoluble fibrils. BAN2401-G000-201, a randomized double-blind clinical trial, utilized a Bayesian design with response-adaptive randomization to assess 3 doses across 2 regimens of lecanemab versus placebo in early Alzheimer's disease, mild cognitive impairment due to Alzheimer's disease (AD) and mild AD dementia.

METHODS

BAN2401-G000-201 aimed to establish the effective dose 90% (ED90), defined as the simplest dose that achieves ≥90% of the maximum treatment effect. The primary endpoint was Bayesian analysis of 12-month clinical change on the Alzheimer's Disease Composite Score (ADCOMS) for the ED90 dose, which required an 80% probability of ≥25% clinical reduction in decline versus placebo. Key secondary endpoints included 18-month Bayesian and frequentist analyses of brain amyloid reduction using positron emission tomography; clinical decline on ADCOMS, Clinical Dementia Rating-Sum-of-Boxes (CDR-SB), and Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog14); changes in CSF core biomarkers; and total hippocampal volume (HV) using volumetric magnetic resonance imaging.

RESULTS

A total of 854 randomized subjects were treated (lecanemab, 609; placebo, 245). At 12 months, the 10-mg/kg biweekly ED90 dose showed a 64% probability to be better than placebo by 25% on ADCOMS, which missed the 80% threshold for the primary outcome. At 18 months, 10-mg/kg biweekly lecanemab reduced brain amyloid (-0.306 SUVr units) while showing a drug-placebo difference in favor of active treatment by 27% and 30% on ADCOMS, 56% and 47% on ADAS-Cog14, and 33% and 26% on CDR-SB versus placebo according to Bayesian and frequentist analyses, respectively. CSF biomarkers were supportive of a treatment effect. Lecanemab was well-tolerated with 9.9% incidence of amyloid-related imaging abnormalities-edema/effusion at 10 mg/kg biweekly.

CONCLUSIONS

BAN2401-G000-201 did not meet the 12-month primary endpoint. However, prespecified 18-month Bayesian and frequentist analyses demonstrated reduction in brain amyloid accompanied by a consistent reduction of clinical decline across several clinical and biomarker endpoints. A phase 3 study (Clarity AD) in early Alzheimer's disease is underway.

TRIAL REGISTRATION

Clinical Trials.gov NCT01767311 .

A multisite analysis of the concordance between visual image interpretation and quantitative analysis of [18F]flutemetamol amyloid PET images

BACKGROUND

[¹⁸F]flutemetamol PET scanning provides information on brain amyloid load and has been approved for routine clinical use based upon visual interpretation as either negative (equating to none or sparse amyloid plaques) or amyloid positive (equating to moderate or frequent plaques). Quantitation is however fundamental to the practice of nuclear medicine and hence can be used to supplement amyloid reading methodology especially in unclear cases.

METHODS

A total of 2770 [¹⁸F]flutemetamol images were collected from 3 clinical studies and 6 research cohorts with available visual reading of [¹⁸F]flutemetamol and quantitative analysis of images. These were assessed further to examine both the discordance and concordance between visual and quantitative imaging primarily using thresholds robustly established using pathology as the standard of truth. Scans covered a wide range of cases (i.e. from cognitively unimpaired subjects to patients attending the memory clinics). Methods of quantifying amyloid ranged from using CE/510K cleared marked software (e.g. CortexID, Brass), to other research-based methods (e.g. PMOD, CapAIBL). Additionally, the clinical follow-up of two types of discordance between visual and quantitation (V+Q- and V-Q+) was examined with competing risk regression analysis to assess possible differences in prediction for progression to Alzheimer's disease (AD) and other diagnoses (OD).

RESULTS

Weighted mean concordance between visual and quantitation using the autopsy-derived threshold was 94% using pons as the reference region. Concordance from a sensitivity analysis which assessed the maximum agreement for each cohort using a range of cut-off values was also estimated at approximately 96% (weighted mean). Agreement was generally higher in clinical cases compared to research cases. V-Q+ discordant cases were 11% more likely to progress to AD than V+Q- for the SUVr with pons as reference region.

CONCLUSIONS

Quantitation of amyloid PET shows a high agreement vs binary visual reading and also allows for a continuous measure that, in conjunction with possible discordant analysis, could be used in the future to identify possible earlier pathological deposition as well as monitor disease progression and treatment effectiveness.

Parametric imaging of dual-time window [18F]flutemetamol and [18F]florbetaben studies

Optimal pharmacokinetic models for quantifying amyloid beta (Aβ) burden using both [¹⁸F]flutemetamol and [¹⁸F]florbetaben scans have previously been identified at a region of interest (ROI) level. The purpose of this study was to determine optimal quantitative methods for parametric analyses of [¹⁸F]flutemetamol and [¹⁸F]florbetaben scans. Forty-six participants were scanned on a PET/MR scanner using a dual-time window protocol and either [¹⁸F]flutemetamol (N=24) or [¹⁸F]florbetaben (N=22). The following parametric approaches were used to derive DVR estimates: reference Logan (RLogan), receptor parametric mapping (RPM), two-step simplified reference tissue model (SRTM2) and multilinear reference tissue models (MRTM0, MRTM1, MRTM2), all with cerebellar grey matter as reference tissue. In addition, a standardized uptake value ratio (SUVR) was calculated for the 90-110 min post injection interval. All parametric images were assessed visually. Regional outcome measures were compared with those from a validated ROI method, i.e. DVR derived using RLogan. Visually, RPM, and SRTM2 performed best across tracers and, in addition to SUVR, provided highest AUC values for differentiating between Aβ-positive vs Aβ-negative scans ([¹⁸F]flutemetamol: range AUC=0.96-0.97 [¹⁸F]florbetaben: range AUC=0.83-0.85). Outcome parameters of most methods were highly correlated with the reference method (R²≥0.87), while lowest correlation were observed for MRTM2 (R²=0.71-0.80). Furthermore, bias was low (≤5%) and independent of underlying amyloid burden for MRTM0 and MRTM1. The optimal parametric method differed per evaluated aspect; however, the best compromise across aspects was found for MRTM0 followed by SRTM2, for both tracers. SRTM2 is the preferred method for parametric imaging because, in addition to its good performance, it has the advantage of providing a measure of relative perfusion (R₁), which is useful for measuring disease progression.

The Role of Amyloid PET in Diagnosing Possible Transmissible Cerebral Amyloid Angiopathy in Young Adults with a History of Neurosurgery: A Case Series

BACKGROUND

Cerebral amyloid angiopathy (CAA) is a common cause of cerebrovascular disease in the elderly. There is accumulating evidence suggestive of transmissibility of β-amyloid resulting in amyloid pathology at younger age. According to the Boston criteria, defining CAA in patients <55 years requires histological evidence which may hamper diagnosis. We explored the role of amyloid PET in the diagnosis of possible transmissible CAA in young adults.

CASES

We report 4 young adults (<55 years) presenting with clinical and neuroimaging features suggestive of CAA but without genetic evidence of hereditary CAA explaining the young onset. A common factor in all cases was a medical history of neurosurgery during childhood. All patients underwent amyloid PET to support the diagnosis of an amyloid-related pathology and the result was positive in all 4.

CONCLUSION

Combining the clinical presentation and imaging findings of the 4 cases, we postulate transmissible CAA as the possible diagnosis. Further epidemiological studies are required to gain more insight in the prevalence of this novel entity. Amyloid PET may be a useful, non-invasive tool in these analyses especially since pathological evidence will be lacking in most of these studies.

Repeatability of parametric methods for [18F]florbetapir imaging in Alzheimer's disease and healthy controls: A test-retest study

Accumulation of amyloid beta (Aβ) is one of the pathological hallmarks of Alzheimer's disease (AD), which can be visualized using [¹⁸F]florbetapir positron emission tomography (PET). The aim of this study was to evaluate various parametric methods and to assess their test-retest (TRT) reliability. Two 90 min dynamic [¹⁸F]florbetapir PET scans, including arterial sampling, were acquired (n = 8 AD patient, n = 8 controls). The following parametric methods were used; (reference:cerebellum); Logan and spectral analysis (SA), receptor parametric mapping (RPM), simplified reference tissue model2 (SRTM2), reference Logan (rLogan) and standardized uptake value ratios (SUV_r(50-70)). BP_ND+1, DVR, V_T and SUVr were compared with corresponding estimates (V_T or DVR) from the plasma input reversible two tissue compartmental (2T4k_V_B) model with corresponding TRT values for 90-scan duration. RPM (r² = 0.92; slope = 0.91), Logan (r² = 0.95; slope = 0.84) and rLogan (r² = 0.94; slope = 0.88), and SRTM2 (r² = 0.91; slope = 0.83), SA (r² = 0.91; slope = 0.88), SUVr (r² = 0.84; slope = 1.16) correlated well with their 2T4k_V_B counterparts. RPM (controls: 1%, AD: 3%), rLogan (controls: 1%, AD: 3%) and SUV_r(50-70) (controls: 3%, AD: 8%) showed an excellent TRT reliability. In conclusion, most parametric methods showed excellent performance for [¹⁸F]florbetapir, but RPM and rLogan seem the methods of choice, combining the highest accuracy and best TRT reliability.

Visual assessment of [18F]flutemetamol PET images can detect early amyloid pathology and grade its extent

Purpose

To investigate the sensitivity of visual read (VR) to detect early amyloid pathology and the overall utility of regional VR.

Methods

[¹⁸F]Flutemetamol PET images of 497 subjects (ALFA+ N = 352; ADC N = 145) were included. Scans were visually assessed according to product guidelines, recording the number of positive regions (0–5) and a final negative/positive classification. Scans were quantified using the standard and regional Centiloid (CL) method. The agreement between VR-based classification and published CL-based cut-offs for early (CL = 12) and established (CL = 30) pathology was determined. An optimal CL cut-off maximizing Youden’s index was derived. Global and regional CL quantification was compared to VR. Finally, 28 post-mortem cases from the [¹⁸F]flutemetamol phase III trial were included to assess the percentage agreement between VR and neuropathological classification of neuritic plaque density.

Results

VR showed excellent agreement against CL = 12 (κ = .89, 95.2%) and CL = 30 (κ = .88, 95.4%) cut-offs. ROC analysis resulted in an optimal CL = 17 cut-off against VR (sensitivity = 97.9%, specificity = 97.8%). Each additional positive VR region corresponded to a clear increase in global CL. Regional VR was also associated with regional CL quantification. Compared to mCERAD_SOT-based classification (i.e., any region mCERAD_SOT > 1.5), VR was in agreement in 89.3% of cases, with 13 true negatives, 12 true positives, and 3 false positives (FP). Regional sparse-to-moderate neuritic and substantial diffuse Aβ plaque was observed in all FP cases. Regional VR was also associated with regional plaque density.

Conclusion

VR is an appropriate method for assessing early amyloid pathology and that grading the extent of visual amyloid positivity could present clinical value.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-020-05174-2.

PET measurement of longitudinal amyloid load identifies the earliest stages of amyloid-beta accumulation during Alzheimer's disease progression in Down syndrome

Introduction:

Adults with Down syndrome (DS) are predisposed to Alzheimer’s disease (AD) and reveal early amyloid beta (Aβ) pathology in the brain. Positron emission tomography (PET) provides an in vivo measure of Aβ throughout the AD continuum. Due to the high prevalence of AD in DS, there is need for longitudinal imaging studies of Aβ to better characterize the natural history of Aβ accumulation, which will aid in the staging of this population for clinical trials aimed at AD treatment and prevention.

Methods:

Adults with DS (N = 79; Mean age (SD) = 42.7 (7.28) years) underwent longitudinal [C-11]Pittsburgh compound B (PiB) PET. Global Aβ burden was quantified using the amyloid load metric (Aβ_L). Modeled PiB images were generated from the longitudinal Aβ_L data to visualize which regions are most susceptible to Aβ accumulation in DS. Aβ_L change was evaluated across Aβ(−), Aβ-converter, and Aβ(+) groups to assess longitudinal Aβ trajectories during different stages of AD-pathology progression. Aβ_L change values were used to identify Aβ-accumulators within the Aβ(−) group prior to reaching the Aβ(+) threshold (previously reported as 20 Aβ_L) which would have resulted in an Aβ-converter classification. With knowledge of trajectories of Aβ(−) accumulators, a new cutoff of Aβ(+) was derived to better identify subthreshold Aβ accumulation in DS. Estimated sample sizes necessary to detect a 25% reduction in annual Aβ change with 80% power (alpha 0.01) were determined for different groups of Aβ-status.

Results:

Modeled PiB images revealed the striatum, parietal cortex and precuneus as the regions with earliest detected Aβ accumulation in DS. The Aβ(−) group had a mean Aβ_L change of 0.38 (0.58) Aβ_L/year, while the Aβ-converter and Aβ(+) groups had change of 2.26 (0.66) and 3.16 (1.34) Aβ_L/year, respectively. Within the Aβ(−) group, Aβ-accumulators showed no significant difference in Aβ_L change values when compared to Aβ-converter and Aβ(+) groups. An Aβ(+) cutoff for subthreshold Aβ accumulation was derived as 13.3 Aβ_L. The estimated sample size necessary to detect a 25% reduction in Aβ was 79 for Aβ(−) accumulators and 59 for the Aβ-converter/Aβ(+) group in DS.

Conclusion:

Longitudinal Aβ_L changes were capable of distinguishing Aβ accumulators from non-accumulators in DS. Longitudinal imaging allowed for identification of subthreshold Aβ accumulation in DS during the earliest stages of AD-pathology progression. Detection of active Aβ deposition evidenced by subthreshold accumulation with longitudinal imaging can identify DS individuals at risk for AD development at an earlier stage.

Lack of association between acute stroke, post-stroke dementia, race, and β-amyloid status

INTRODUCTION

Stroke and Alzheimer disease share risk factors and often co-occur, and both have been reported to have a higher prevalence in African Americans as compared to non-Hispanic whites. However, their interaction has not been established. The objective of this study was to determine if preclinical Alzheimer disease is a risk factor for stroke and post-stroke dementia and whether racial differences moderate this relationship.

METHODS

This case-control study was analyzed in 2019 using retrospective data from 2007 to 2013. Participants were adults age 65 and older with and without acute ischemic stroke. Recruitment included word of mouth and referrals in Saint Louis, MO, with stroke participants recruited from acutely hospitalized patients and non-stroke participants from community living older adults who were research volunteers. Our assessment included radiologic reads of infarcts, microbleeds, and white matter hyperintensitites (WMH); a Pittsburgh Compound B PET measure of cortical β-amyloid binding; quantitative measures of hippocampal and WMH volume; longitudinal Mini Mental State Examination (MMSE) scores; and Clinical Dementia Rating (CDR) 1 year post-stroke.

RESULTS

A total of 243 participants were enrolled, 81 of which had a recent ischemic stroke. Participants had a mean age of 75, 57% were women, and 52% were African American. Cortical amyloid did not differ significantly by race, stroke status, or CDR post-stroke. There were racial differences in MMSE scores at baseline (mean 26.8 for African Americans, 27.9 for non-Hispanic whites, p = 0.03), but not longitudinally. African Americans were more likely to have microbleeds (32.8% vs 22.6%, p = 0.04), and within the acute stroke group, African Americans were more likely to have small infarcts (75.6% vs 56.8%, p = 0.049).

CONCLUSION

Preclinical Alzheimer disease did not show evidence of being a risk factor for stroke nor predictive of post-stroke dementia. We did not observe racial differences in β-amyloid levels. However, even after controlling for several vascular risk factors, African Americans with clinical stroke presentations had greater levels of vascular pathology on MRI.

Generalization of deep learning models for ultra-low-count amyloid PET/MRI using transfer learning

PURPOSE

We aimed to evaluate the performance of deep learning-based generalization of ultra-low-count amyloid PET/MRI enhancement when applied to studies acquired with different scanning hardware and protocols.

METHODS

Eighty simultaneous [18F]florbetaben PET/MRI studies were acquired, split equally between two sites (site 1: Signa PET/MRI, GE Healthcare, 39 participants, 67 ± 8 years, 23 females; site 2: mMR, Siemens Healthineers, 64 ± 11 years, 23 females) with different MRI protocols. Twenty minutes of list-mode PET data (90-110 min post-injection) were reconstructed as ground-truth. Ultra-low-count data obtained from undersampling by a factor of 100 (site 1) or the first minute of PET acquisition (site 2) were reconstructed for ultra-low-dose/ultra-short-time (1% dose and 5% time, respectively) PET images. A deep convolution neural network was pre-trained with site 1 data and either (A) directly applied or (B) trained further on site 2 data using transfer learning. Networks were also trained from scratch based on (C) site 2 data or (D) all data. Certified physicians determined amyloid uptake (+/-) status for accuracy and scored the image quality. The peak signal-to-noise ratio, structural similarity, and root-mean-squared error were calculated between images and their ground-truth counterparts. Mean regional standardized uptake value ratios (SUVR, reference region: cerebellar cortex) from 37 successful site 2 FreeSurfer segmentations were analyzed.

RESULTS

All network-synthesized images had reduced noise than their ultra-low-count reconstructions. Quantitatively, image metrics improved the most using method B, where SUVRs had the least variability from the ground-truth and the highest effect size to differentiate between positive and negative images. Method A images had lower accuracy and image quality than other methods; images synthesized from methods B-D scored similarly or better than the ground-truth images.

CONCLUSIONS

Deep learning can successfully produce diagnostic amyloid PET images from short frame reconstructions. Data bias should be considered when applying pre-trained deep ultra-low-count amyloid PET/MRI networks for generalization.

[11C]PIB amyloid quantification: effect of reference region selection

Background

The standard reference region (RR) for amyloid-beta (Aβ) PET studies is the cerebellar grey matter (GMCB), while alternative RRs have mostly been utilized without prior validation against the gold standard. This study compared five commonly used RRs to gold standard plasma input-based quantification using the GMCB.

Methods

Thirteen subjects from a test–retest (TRT) study and 30 from a longitudinal study were retrospectively included (total: 17 Alzheimer’s disease, 13 mild cognitive impairment, 13 controls). Dynamic [¹¹C]PiB PET (90 min) and T1-weighted MR scans were co-registered and time–activity curves were extracted for cortical target regions and the following RRs: GMCB, whole cerebellum (WCB), white matter brainstem/pons (WMBS), whole brainstem (WBS) and eroded subcortical white matter (WMES). A two-tissue reversible plasma input model (2T4k_V_b) with GMCB as RR, reference Logan and the simplified reference tissue model were used to derive distribution volume ratios (DVRs), and standardized uptake value (SUV) ratios were calculated for 40–60 min and 60–90 min intervals. Parameter variability was evaluated using TRT scans, and correlations and agreements with the gold standard (DVR from 2T4k_V_b with GMCB RR) were also assessed. Next, longitudinal changes in SUVs (both intervals) were assessed for each RR. Finally, the ability to discriminate between visually Aβ positive and Aβ negative scans was assessed.

Results

All RRs yielded stable TRT performance (max 5.1% variability), with WCB consistently showing lower variability. All approaches were able to discriminate between Aβ positive and Aβ negative scans, with highest effect sizes obtained for GMCB (range − 0.9 to − 0.7), followed by WCB (range − 0.8 to − 0.6). Furthermore, all approaches provided good correlations with the gold standard (r ≥ 0.78), while the highest bias (as assessed by the regression slope) was observed using WMES (range slope 0.52–0.67), followed by WBS (range slope 0.58–0.92) and WMBS (range slope 0.62–0.91). Finally, RR SUVs were stable across a period of 2.6 years for all except WBS and WMBS RRs (60–90 min interval).

Conclusions

GMCB and WCB are considered the best RRs for quantifying amyloid burden using [¹¹C]PiB PET.

Development and evaluation of an automated quantification tool for amyloid PET images

BACKGROUND

Quantitative evaluation of amyloid positron emission tomography (PET) with standardized uptake value ratio (SUVR) plays a key role in clinical studies of Alzheimer's disease (AD). We have proposed a PET-only (MR-free) amyloid quantification method, although some commercial software packages are required. The aim of this study was to develop an automated quantification tool for amyloid PET without using commercial software.

METHODS

The quantification tool was created by combining four components: (1) anatomical standardization to positive and negative templates using NEUROSTAT stereo.exe; (2) similarity calculation between standardized images and respective templates based on normalized cross-correlation (selection of the image for SUVR measurement); (3) voxel value normalization by the mean value of reference regions (making an SUVR-scaled image); and (4) SUVR calculation based on pre-defined regions of interest (ROIs). We examined 166 subjects who underwent a [¹¹C] Pittsburgh compound-B PET scan through the Japanese Alzheimer's Disease Neuroimaging Initiative (J-ADNI) study. SUVRs in five ROIs (frontal lobe, temporal lobe, parietal lobe, occipital lobe, and posterior cingulate cortex and precuneus) were calculated with the cerebellar cortex as the reference region. The SUVRs obtained by our tool were compared with manual step-by-step processing and the conventional PMOD-based method (PMOD Technologies, Switzerland).

RESULTS

Compared with manual step-by-step processing, our developed automated quantification tool reduced processing time by 85%. The SUVRs obtained by the developed quantification tool were consistent with those obtained by manual processing. Compared with the conventional PMOD-based method, the developed quantification tool provided 1.5% lower SUVR values, on average. We determined that this bias is likely due to the difference in anatomical standardization methods.

CONCLUSIONS

We developed an automated quantification tool for amyloid PET images. Using this tool, SUVR values can be quickly measured without individual MRI and without commercial software. This quantification tool may be useful for clinical studies of AD.

Defining a Centiloid scale threshold predicting long-term progression to dementia in patients attending the memory clinic: an [18F] flutemetamol amyloid PET study

PURPOSE

To evaluate cerebral amyloid-β(Aβ) pathology in older adults with cognitive complaints, visual assessment of PET images is approved as the routine method for image interpretation. In research studies however, Aβ-PET semi-quantitative measures are associated with greater risk of progression to dementia; but until recently, these measures lacked standardization. Therefore, the Centiloid scale, providing standardized Aβ-PET semi-quantitation, was recently validated. We aimed to determine the predictive values of visual assessments and Centiloids in non-demented patients, using long-term progression to dementia as our standard of truth.

METHODS

One hundred sixty non-demented participants (age, 54-86) were enrolled in a monocentric [¹⁸F] flutemetamol Aβ-PET study. Flutemetamol images were interpreted visually following the manufacturers recommendations. SUVr values were converted to the Centiloid scale using the GAAIN guidelines. Ninety-eight persons were followed until dementia diagnosis or were clinically stable for a median of 6 years (min = 4.0; max = 8.0). Twenty-five patients with short follow-up (median = 2.0 years; min = 0.8; max = 3.9) and 37 patients with no follow-up were excluded. We computed ROC curves predicting subsequent dementia using baseline PET data and calculated negative (NPV) and positive (PPV) predictive values.

RESULTS

In the 98 participants with long follow-up, Centiloid = 26 provided the highest overall predictive value = 87% (NPV = 85%, PPV = 88%). Visual assessment corresponded to Centiloid = 40, which predicted dementia with an overall predictive value = 86% (NPV = 81%, PPV = 92%). Inclusion of the 25 patients who only had a 2-year follow-up decreased the PPV = 67% (NPV = 88%), reflecting the many positive cases that did not progress to dementia after short follow-ups.

CONCLUSION

A Centiloid threshold = 26 optimally predicts progression to dementia 6 years after PET. Visual assessment provides similar predictive value, with higher specificity and lower sensitivity.

TRIAL REGISTRATION

Eudra-CT number: 2011-001756-12.

Feasibility study of a PET-only amyloid quantification method: a comparison with visual interpretation

OBJECTIVE

Visual evaluation is the standard for amyloid positron emission tomography (PET) examination, though the result depends upon the physician's subjective review of the images. Therefore, it is expected that objective quantitative evaluation is useful for image interpretation. In this study, we examined the usefulness of the quantitative evaluation of amyloid PET using a PET-only quantification method in comparison with visual evaluation.

METHODS

In this study we retrospectively investigated a total of 166 individuals, including 58 cognitively normal controls, 62 individuals with mild cognitive impairment, and 46 individuals with early Alzheimer's disease. They underwent ¹¹C-Pittsburgh compound-B (PiB) PET examination through the Japanese Alzheimer's Disease Neuroimaging Initiative (J-ADNI). Amyloid accumulation in cerebral cortices was assessed using visual and quantitative methods. The quantitative evaluation was performed using the adaptive template method and empirically PiB-prone region of interest, and the standardized uptake value ratio (SUVR) in each area was obtained.

RESULTS

Visual evaluation and SUVR were significantly correlated in the cerebral cortices (ρ = 0.85-0.87; p < 0.05). In visual evaluation, sensitivity, specificity, and accuracy were 78%, 76%, and 77%, respectively. Meanwhile, for quantitative evaluation, sensitivity, specificity, and accuracy were 77%, 79%, and 78% in mean cortical SUVR (mcSUVR) and 79%, 79%, and 79% in maximum SUVR (maxSUVR), respectively.

CONCLUSION

The PET-only quantification method provided a concordant result with visual evaluation and was considered useful for amyloid PET.

Comparison of Amyloid Positivity Rate and Accumulation Pattern between Amnestic and Non-Amnestic Type Mild Cognitive Impairment

OBJECTIVE

We aimed to compare cerebral beta-amyloid protein (Aβ) positivity rate and amyloid accumulation pattern on amyloid positron emission tomography (PET) between mild cognitive impairment (MCI) subtypes, i.e. amnestic mild cognitive impairment (aMCI) and non-amnestic mild cognitive impairment (naMCI).

METHODS

The study participants were 34 naMCI patients and age-, sex- and education-matched 68 aMCI patients (1:2 ratio) who visited the Dementia and Age-Associated Cognitive Decline Clinic of the Seoul National University Hospital. All participants received comprehensive clinical and neuropsychological assessments and [¹⁸F] florbetaben PET.

RESULTS

Aβ positivity rate of naMCI group (26.5%) was significantly lower than that of aMCI group (64.7%). Among Aβ positive individuals, there was no difference in Aβ accumulation pattern between naMCI and aMCI.

CONCLUSION

The findings suggest that MCI subtypes based on impaired cognitive domains have a differential association with brain Aβ deposition, a core pathology of AD. Amnestic subtype of MCI are more closely associated with cerebral Aβ deposition compared to nonamnestic subtype. In contrast, the pattern of amyloid deposition does not appear to have any difference between the subtypes.