Head-to-Head Comparison of 18F-Florbetaben and 18F-Flutemetamol in the Cortical and Striatal Regions

Imaging of Tauopathies with PET Ligands: State of the Art and Future Outlook

(1) Background: Tauopathies are a group of diseases characterized by the deposition of abnormal tau protein. They are distinguished into 3R, 4R, and 3R/4R tauopathies and also include Alzheimer's disease (AD) and chronic traumatic encephalopathy (CTE). Positron emission tomography (PET) imaging represents a pivotal instrument to guide clinicians. This systematic review aims to summarize the current and novel PET tracers. (2) Methods: Literature research was conducted on Pubmed, Scopus, Medline, Central, and the Web of Science using the query "pet ligands" and "tauopathies". Articles published from January 2018 to 9 February, 2023, were searched. Only studies on the development of novel PET radiotracers for imaging in tauopathies or comparative studies between existing PET tracers were included. (3) Results: A total of 126 articles were found, as follows: 96 were identified from PubMed, 27 from Scopus, one on Central, two on Medline, and zero on the Web of Science. Twenty-four duplicated works were excluded, and 63 articles did not satisfy the inclusion criteria. The remaining 40 articles were included for quality assessment. (4) Conclusions: PET imaging represents a valid instrument capable of helping clinicians in diagnosis, but it is not always perfect in differential diagnosis, even if further investigations on humans for novel promising ligands are needed.

Effect of reduction in brain amyloid levels on change in cognitive and functional decline in randomized clinical trials: An instrumental variable meta-analysis

INTRODUCTION

Whether the reduction in brain amyloid beta (Aβ) plaque alone may substantially slow cognitive and functional decline in patients with dementia or mild cognitive impairment due to Alzheimer's disease (AD) remains debated.

METHODS

An instrumental variable meta-analysis was performed to infer the effect of change in positron emission tomography (PET)-measured Aβ standardized uptake value ratio (SUVR) on cognitive and functional decline.

RESULTS

Pooling data from 16 randomized trials demonstrates that each 0.1-unit decrease in PET Aβ SUVR is associated with a reduction (95% confidence interval) by 0.09 (0.034-0.15), 0.33 (0.12-0.55), and 0.13 (0.017-0.24) point in the average change of the Clinical Dementia Rating-Sum of Boxes, the Alzheimer's Disease Assessment Scale-Cognitive Subscale, and the Mini-Mental State Examination, respectively.

DISCUSSION

This meta-analysis provides statistically significant evidence of a likely causal relationship between a reduction in Aβ plaque and a reduction in cognitive and functional decline in patients with AD.

HIGHLIGHTS

A widely cited meta-analysis article concluded amyloid beta reduction does not substantially improve cognition. We identified data inconsistencies in the initial publication and found new trial data. We repeated the meta-analysis after correcting data inconsistencies and adding new trial data. Updated results suggested statistically significant clinical benefit of amyloid beta reduction. Amyloid beta is a viable biological target for the treatment and prevention of AD.

Longitudinal changes in 18F-Flutemetamol amyloid load in cognitively intact APOE4 carriers versus noncarriers: Methodological considerations

PURPOSE

Measuring longitudinal changes in amyloid load in the asymptomatic stage of Alzheimer's disease is of high relevance for clinical research and progress towards more efficacious, timely treatments. Apolipoprotein E ε4 (APOE4) has a well-established effect on the rate of amyloid accumulation. Here we investigated which region of interest and which reference region perform best at detecting the effect of APOE4 on longitudinal amyloid load in individuals participating in the Flemish Prevent Alzheimer's Disease Cohort KU Leuven (F-PACK).

METHODS

Ninety cognitively intact F-PACK participants (baseline age: 68 (52-80) years, 46 males, 42 APOE4 carriers) received structural MRI and ¹⁸F-Flutemetamol PET scans at baseline and follow-up (6.2 (3.4-10.9) year interval). Standardised uptake value ratios (SUVRs) and Centiloids (CLs) were calculated in a composite cortical volume of interest (SUVR_comp/CL) and in the precuneus (SUVR_prec), and amyloid rate of change derived: (follow-up amyloid load - baseline amyloid load) / time interval (years). Four reference regions were used to derive amyloid load: whole cerebellum, cerebellar grey matter, eroded subcortical white matter, and pons.

RESULTS

When using whole cerebellum or cerebellar grey matter as reference region, APOE4 carriers had a significantly higher SUVR_comp amyloid rate of change than non-carriers (p_corr = 0.004, t = 3.40 (CI 0.005-0.018); p_corr = 0.036, t = 2.66 (CI 0.003-0.018), respectively). Significance was not observed for eroded subcortical white matter or pons (p_corr = 0.144, t = 2.13 (CI 0.0003-0.008); p_corr = 0.116, t = 2.22 (CI 0.005-0.010), respectively). When using CLs as the amyloid measurement, and whole cerebellum, APOE4 carriers had a higher amyloid rate of change than non-carriers (p_corr = 0.012, t = 3.05 (CI 0.499-2.359)). Significance was not observed for the other reference regions. No significance was observed with any of the reference regions and amyloid rate of change in the precuneus (SUVR_prec).

CONCLUSION

In this cognitively intact cohort, a composite neocortical volume of interest together with whole cerebellum or cerebellar grey matter as reference region are the methods of choice for detecting APOE4-dependent differences in amyloid rate of change.

Clinical outcomes of increased focal amyloid uptake in individuals with subthreshold global amyloid levels

Background

Although the standardized uptake value ratio (SUVR) method is objective and simple, cut-off optimization using global SUVR values may not reflect focal increased uptake in the cerebrum. The present study investigated clinical and neuroimaging characteristics according to focally increased β-amyloid (Aβ) uptake and global Aβ status.

Methods

We recruited 968 participants with cognitive continuum. All participants underwent neuropsychological tests and 498 ¹⁸F-florbetaben (FBB) amyloid positron emission tomography (PET) and 470 ¹⁸F-flutemetamol (FMM) PET. Each PET scan was assessed in 10 regions (left and right frontal, lateral temporal, parietal, cingulate, and striatum) with focal-quantitative SUVR-based cutoff values for each region by using an iterative outlier approach.

Results

A total of 62 (6.4%) subjects showed increased focal Aβ uptake with subthreshold global Aβ status [global (-) and focal (+) Aβ group, G(-)F(+) group]. The G(-)F(+) group showed worse performance in memory impairment (p < 0.001), global cognition (p = 0.009), greater hippocampal atrophy (p = 0.045), compared to those in the G(-)F(-). Participants with widespread Aβ involvement in the whole region [G(+)] showed worse neuropsychological (p < 0.001) and neuroimaging features (p < 0.001) than those with focal Aβ involvement G(-)F(+).

Conclusion

Our findings suggest that individuals show distinctive clinical outcomes according to focally increased Aβ uptake and global Aβ status. Thus, researchers and clinicians should pay more attention to focal increased Aβ uptake in addition to global Aβ status.

Amyloid and Tau Positron Emission Tomography Imaging in Alzheimer’s Disease and Other Tauopathies

The detection and staging of Alzheimer’s disease (AD) using non-invasive imaging biomarkers is of substantial clinical importance. Positron emission tomography (PET) provides readouts to uncover molecular alterations in the brains of AD patients with high sensitivity and specificity. A variety of amyloid-β (Aβ) and tau PET tracers are already available for the clinical diagnosis of AD, but there is still a lack of imaging biomarkers with high affinity and selectivity for tau inclusions in primary tauopathies, such as progressive supranuclear palsy (PSP), corticobasal degeneration (CBD) and Pick’s disease (PiD). This review aims to provide an overview of the existing Aβ and tau PET imaging biomarkers and their binding properties from in silico, in vitro, and in vivo assessment. Imaging biomarkers for pathologic proteins are vital for clinical diagnosis, disease staging and monitoring of the potential therapeutic approaches of AD. Off-target binding of radiolabeled tracers to white matter or other neural structures is one confounding factor when interpreting images. To improve binding properties such as binding affinity and to eliminate off-target binding, second generation of tau PET tracers have been developed. To conclude, we further provide an outlook for imaging tauopathies and other pathological features of AD and primary tauopathies.

Development of Amyloid PET Analysis Pipeline Using Deep Learning-Based Brain MRI Segmentation—A Comparative Validation Study

Amyloid positron emission tomography (PET) scan is clinically essential for the non-invasive assessment of the presence and spatial distribution of amyloid-beta deposition in subjects with cognitive impairment suspected to have been a result of Alzheimer’s disease. Quantitative assessment can enhance the interpretation reliability of PET scan; however, its clinical application has been limited due to the complexity of preprocessing. This study introduces a novel deep-learning-based approach for SUVR quantification that simplifies the preprocessing step and significantly reduces the analysis time. Using two heterogeneous amyloid ligands, our proposed method successfully distinguished standardized uptake value ratio (SUVR) between amyloidosis-positive and negative groups. The proposed method’s intra-class correlation coefficients were 0.97 and 0.99 against PETSurfer and PMOD, respectively. The difference of global SUVRs between the proposed method and PETSurfer or PMOD were 0.04 and −0.02, which are clinically acceptable. The AUC-ROC exceeded 0.95 for three tools in the amyloid positive assessment. Moreover, the proposed method had the fastest processing time and had a low registration failure rate (1%). In conclusion, our proposed method calculates SUVR that is consistent with PETSurfer and PMOD, and has advantages of fast processing time and low registration failure rate. Therefore, PET quantification provided by our proposed method can be used in clinical practice.

18F-THK5351 PET Positivity and Longitudinal Changes in Cognitive Function in β-Amyloid-Negative Amnestic Mild Cognitive Impairment

PURPOSE

Neuroinflammation is considered an important pathway associated with several diseases that result in cognitive decline. ¹⁸F-THK5351 positron emission tomography (PET) signals might indicate the presence of neuroinflammation, as well as Alzheimer's disease-type tau aggregates. β-amyloid (Aβ)-negative (Aβ-) amnestic mild cognitive impairment (aMCI) may be associated with non-Alzheimer's disease pathophysiology. Accordingly, we investigated associations between ¹⁸F-THK5351 PET positivity and cognitive decline among Aβ- aMCI patients.

MATERIALS AND METHODS

The present study included 25 amyloid PET negative aMCI patients who underwent a minimum of two follow-up neuropsychological evaluations, including clinical dementia rating-sum of boxes (CDR-SOB). The patients were classified into two groups: ¹⁸F-THK5351-positive and -negative groups. The present study used a linear mixed effects model to estimate the effects of ¹⁸F-THK5351 PET positivity on cognitive prognosis among Aβ- aMCI patients.

RESULTS

Among the 25 Aβ- aMCI patients, 10 (40.0%) were ¹⁸F-THK5351 positive. The patients in the ¹⁸F-THK5351-positive group were older than those in the ¹⁸F-THK5351-negative group (77.4±2.2 years vs. 70.0±5.5 years; p<0.001). There was no difference between the two groups with regard to the proportion of apolipoprotein E ε4 carriers. Interestingly, however, the CDR-SOB scores of the ¹⁸F-THK5351-positive group deteriorated at a faster rate than those of the ¹⁸F-THK5351-negative group (B=0.003, p=0.033).

CONCLUSION

The results of the present study suggest that increased ¹⁸F-THK5351 uptake might be a useful predictor of poor prognosis among Aβ- aMCI patients, which might be associated with increased neuroinflammation (ClinicalTrials.gov NCT02656498).

Harmonisation of PET imaging features with different amyloid ligands using machine learning-based classifier

PURPOSE

In this study, we used machine learning to develop a new method derived from a ligand-independent amyloid (Aβ) positron emission tomography (PET) classifier to harmonise different Aβ ligands.

METHODS

We obtained 107 paired 18F-florbetaben (FBB) and 18F-flutemetamol (FMM) PET images at the Samsung Medical Centre. To apply the method to FMM ligand, we transferred the previously developed FBB PET classifier to test similar features from the FMM PET images for application to FMM, which in turn developed a ligand-independent Aβ PET classifier. We explored the concordance rates of our classifier in detecting cortical and striatal Aβ positivity. We investigated the correlation of machine learning-based cortical tracer uptake (ML-CTU) values quantified by the classifier between FBB and FMM.

RESULTS

This classifier achieved high classification accuracy (area under the curve = 0.958) even with different Aβ PET ligands. In addition, the concordance rate of FBB and FMM using the classifier (87.5%) was good to excellent, which seemed to be higher than that in visual assessment (82.7%) and lower than that in standardised uptake value ratio cut-off categorisation (93.3%). FBB and FMM ML-CTU values were highly correlated with each other (R = 0.903).

CONCLUSION

Our findings suggested that our novel classifier may harmonise FBB and FMM ligands in the clinical setting which in turn facilitate the biomarker-guided diagnosis and trials of anti-Aβ treatment in the research field.

AMYQ: An index to standardize quantitative amyloid load across PET tracers

INTRODUCTION

Positron emission tomography (PET) amyloid quantification methods require magnetic resonance imaging (MRI) for spatial registration and a priori reference region to scale the images. Furthermore, different tracers have distinct thresholds for positivity. We propose the AMYQ index, a new measure of amyloid burden, to overcome these limitations.

METHODS

We selected 18F-amyloid scans from ADNI and Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL) with the corresponding T1-MRI. A subset also had neuropathological data. PET images were normalized, and the AMYQ was calculated based on an adaptive template. We compared AMYQ with the Centiloid scale on clinical and neuropathological diagnostic performance.

RESULTS

AMYQ was related with amyloid neuropathological burden and had excellent diagnostic performance to discriminate controls from patients with Alzheimer's disease (AD) (area under the curve [AUC] = 0.86). AMYQ had a high agreement with the Centiloid scale (intraclass correlation coefficient [ICC] = 0.88) and AUC between 0.94 and 0.99 to discriminate PET positivity when using different Centiloid cutoffs.

DISCUSSION

AMYQ is a new MRI-independent index for standardizing and quantifying amyloid load across tracers.

A Comparative Study on the Predictive Value of Different Resting-State Functional Magnetic Resonance Imaging Parameters in Preclinical Alzheimer's Disease

Objective: Diverse resting-state functional magnetic resonance imaging (rs-fMRI) studies showed that rs-fMRI might be able to reflect the earliest detrimental effect of cerebral beta-amyloid (Aβ) pathology. However, no previous studies specifically compared the predictive value of different rs-fMRI parameters in preclinical AD. Methods: A total of 106 cognitively normal adults (Aβ+ group = 66 and Aβ- group = 40) were included. Three different rs-fMRI parameter maps including functional connectivity (FC), fractional amplitude of low-frequency fluctuations (fALFF), and regional homogeneity (ReHo) were calculated. Receiver operating characteristic (ROC) curve analyses were utilized to compare classification performance of the three rs-fMRI parameters. Results: FC maps showed the best classifying performance in ROC curve analysis (AUC, 0.915, p < 0.001). Good but weaker performance was achieved by using ReHo maps (AUC, 0.836, p < 0.001) and fALFF maps (AUC, 0.804, p < 0.001). The brain regions showing the greatest discriminative power included the left angular gyrus for FC, left anterior cingulate for ReHo, and left middle frontal gyrus for fALFF. However, among the three measurements, ROI-based FC was the only measure showing group difference in voxel-wise analysis. Conclusion: Our results strengthen the idea that rs-fMRI might be sensitive to earlier changes in spontaneous brain activity and FC in response to cerebral Aβ retention. However, further longitudinal studies with larger sample sizes are needed to confirm their utility in predicting the risk of AD.

Cerebrospinal Fluid Biomarkers for the Diagnosis and Classification of Alzheimer's Disease Spectrum

BACKGROUND

Cerebrospinal fluid (CSF) biomarkers are increasingly used in clinical practice for the diagnosis of Alzheimer's disease (AD). We aimed to 1) determine cutoff values of CSF biomarkers for AD, 2) investigate their clinical utility by estimating a concordance with amyloid positron emission tomography (PET), and 3) apply ATN (amyloid/tau/neurodegeneration) classification based on CSF results.

METHODS

We performed CSF analysis in 51 normal controls (NC), 23 mild cognitive impairment (MCI) and 65 AD dementia (ADD) patients at the Samsung Medical Center in Korea. We attempted to develop cutoff of CSF biomarkers for differentiating ADD from NC using receiver operating characteristic analysis. We also investigated a concordance between CSF and amyloid PET results and applied ATN classification scheme based on CSF biomarker abnormalities to characterize our participants.

RESULTS

CSF Aβ42, total tau (t-tau) and phosphorylated tau (p-tau) significantly differed across the three groups. The area under curve for the differentiation between NC and ADD was highest in t-tau/Aβ42 (0.994) followed by p-tau/Aβ42 (0.963), Aβ42 (0.960), t-tau (0.918), and p-tau (0.684). The concordance rate between CSF Aβ42 and amyloid PET results was 92%. Finally, ATN classification based on CSF biomarker abnormalities led to a majority of NC categorized into A-T-N-(73%), MCI as A+T-N-(30%)/A+T+N+(26%), and ADD as A+T+N+(57%).

CONCLUSION

CSF biomarkers had high sensitivity and specificity in differentiating ADD from NC and were as accurate as amyloid PET. The ATN subtypes based on CSF biomarkers may further serve to predict the prognosis.

Prediction of amyloid β PET positivity using machine learning in patients with suspected cerebral amyloid angiopathy markers

Amyloid-β(Aβ) PET positivity in patients with suspected cerebral amyloid angiopathy (CAA) MRI markers is predictive of a worse cognitive trajectory, and it provides insights into the underlying vascular pathology (CAA vs. hypertensive angiopathy) to facilitate prognostic prediction and appropriate treatment decisions. In this study, we applied two interpretable machine learning algorithms, gradient boosting machine (GBM) and random forest (RF), to predict Aβ PET positivity in patients with CAA MRI markers. In the GBM algorithm, the number of lobar cerebral microbleeds (CMBs), deep CMBs, lacunes, CMBs in dentate nuclei, and age were ranked as the most influential to predict Aβ positivity. In the RF algorithm, the absence of diabetes was additionally chosen. Cut-off values of the above variables predictive of Aβ positivity were as follows: (1) the number of lobar CMBs > 16.4(GBM)/14.3(RF), (2) no deep CMBs(GBM/RF), (3) the number of lacunes > 7.4(GBM/RF), (4) age > 74.3(GBM)/64(RF), (5) no CMBs in dentate nucleus(GBM/RF). The classification performances based on the area under the receiver operating characteristic curve were 0.83 in GBM and 0.80 in RF. Our study demonstrates the utility of interpretable machine learning in the clinical setting by quantifying the relative importance and cutoff values of predictive variables for Aβ positivity in patients with suspected CAA markers.

Association of impaired fasting glucose and Type 2 Diabetes Mellitus with brain volume changes in Alzheimer's Disease patients analyzed by MRI: a retrospective study

Objectives

Alzheimer’s disease (AD), impaired fasting glucose (IFG), and Type 2 diabetes mellitus (T2DM) were reported associated with smaller brain volumes. Nevertheless, the association of hyperglycemia with brain volume changes in AD patients remains unclear. To investigate this issue, structural magnetic resonance imaging was used to compare brain volumes among AD patients with different fasting glucose levels.

Methods

Eighty-five AD patients were divided into three groups based on their fasting glucose level as suggested by the American Diabetes Association: normal fasting glucose group (AD_NFG, n = 45), AD_IFG group (n = 15), and AD_T2DM group (n = 25). Sagittal 3D T1-weighted images were obtained to calculate the brain volume. Brain parenchyma and 33 brain structures were automatically segmented. Each regional volume was analyzed among groups. For regions with statistical significance, partial correlation analysis was used to evaluate their relationships with fasting glucose level, corrected for Mini-Mental State Examination score, age, education level, cholesterol, triglyceride, and blood pressure.

Results

Compared with the AD_IFG and AD_NFG groups, the volume of pons in AD_T2DM group was significantly smaller. Fasting glucose was negatively correlated with pontine volume.

Conclusions

T2DM may exacerbate pontine atrophy in AD patients, and fasting glucose level is associated with pontine volume.