Semi-quantification and grading of amyloid PET: A project of the European Alzheimer's Disease Consortium (EADC)

Global experience in brain amyloid imaging

Brain amyloid imaging has become a crucial tool in diagnosing and understanding Alzheimer's disease (AD) and related neurodegenerative disorders. The introduction of amyloid positron emission tomography (PET) with [¹¹C]Pittsburgh Compound-B ([¹¹C]PiB) in the early 2000s marked a breakthrough in visualizing amyloid-β (Aβ) deposition in vivo. Subsequent development of ¹⁸F-labeled tracers, such as [¹⁸F]florbetapir, [¹⁸F]flutemetamol, and [¹⁸F]florbetaben, improved accessibility and extended imaging capabilities. However, global adoption remains uneven due to disparities in healthcare infrastructure, costs, and regulatory frameworks. In high-income countries, amyloid PET is increasingly used in clinical workflows, particularly for differentiating atypical dementia cases and selecting patients for anti-amyloid therapies like aducanumab and lecanemab. Despite its high sensitivity and specificity, challenges persist regarding its clinical utility, particularly in cognitively normal individuals with amyloid accumulation. Research is focusing on integrating amyloid PET with other biomarkers-tau PET, cerebrospinal fluid analysis, and plasma assays-to improve diagnostic accuracy. Geographical variations in amyloid PET research and implementation reveal North America and Europe as leaders, while access remains limited in low- and middle-income countries. Efforts such as the Worldwide Alzheimer's Disease Neuroimaging Initiative aim to enhance global standardization and accessibility. Emerging trends in artificial intelligence (AI)-assisted imaging analysis and next-generation tracers promise further improvements. Addressing ethical concerns related to preclinical screening and ensuring equitable access to amyloid PET are critical for optimizing its role in neurology and nuclear medicine worldwide.

Visual assessments of 11 C-Pittsburgh compound-B PET vs. 18 F-flutemetamol PET across the age spectrum

OBJECTIVE

Visual assessments of amyloid-β PET, used for Alzheimer's disease (AD) diagnosis and treatment evaluation, require a careful approach when different PET ligands are utilized. Because the gray matter (GM) and white matter (WM) ligand bindings vary with age, the objective was to investigate the agreement between visual reads of 11 C- and 18 F-PET scans.

METHODS

Cognitively unimpaired (CU) younger adults ( N  =   30; 39.5   ±   6.0   years), CU older adults ( N  =   30; 68.6   ±   5.9   years), and adults with AD ( N  =   22; 67.0   ±   8.5   years) underwent brain MRI, 11 C-Pittsburgh compound-B (PiB)-PET, and 18 F-flutemetamol-PET. Amyloid-β deposition was assessed visually by two nuclear medicine specialists on 11 C-PiB-PET and 18 F-flutemetamol-PET, and quantitatively by PET centiloids.

RESULTS

Seventy-two 11 C-PiB-PET and 18 F-flutemetamol-PET visual reads were concordant. However, 1 18 F-flutemetamol-PET and 9 11 C-PiB-PET were discordant with quantitative values. In four additional cases, while 11 C-PiB-PET and 18 F-flutemetamol-PET visual reads were concordant, they were discordant with quantitative values. Disagreements in CU younger adults were only with 11 C-PiB-PET visual reads. The remaining disagreements were with CU older adults.

CONCLUSION

Age, GM/WM binding, amyloid-β load, and disease severity may affect visual assessments of PET ligands. Increase in WM binding with age causes a loss of contrast between GM and WM on 11 C-PiB-PET, particularly in CU younger adults, leading to false positivity. In CU older adults, increased WM signal may bleed more into cortical regions, hiding subtle cortical uptake, especially with 18 F-flutemetamol, whereas 11 C-PiB can detect true regional positivity. Understanding these differences will improve patient care and treatment evaluation in clinic and clinical trials.

Novel β-amyloid PET Imaging Study of [18F]92 in Patients with Cognitive Decline

[18F]-4-((E)-(((E)-4-(2-(2-(2-Fluoroethoxy)ethoxy)ethoxy)benzylidene)-hydrazono)methyl)-N-methylaniline ([18F]92) is a novel positron emission tomography (PET) tracer previously reported to exhibit high binding affinity to aggregated β-amyloid (Aβ). This study aims to report a fully automated radiosynthesis procedure for [18F]92, explore its radioactive distribution in the brains of healthy subjects, and investigate its potential application value in the early diagnosis of Alzheimer's disease (AD). The fully automated radiosynthesis of [18F]92 was performed on the AllinOne module. Thirty one participants were recruited for this study. Dynamic [18F]92 PET imaging was conducted over 0-90 min period to assess time-activity curves (TAC) and standardized uptake value ratio (SUVR) curves in cognitively normal (CN) subjects. All participants were visually classified as either positive (+) or negative (-). Semiquantitative analyses of [18F]92 were performed by calculating SUVRs in different regions of interest. Furthermore, the study analyzed the relationships between global SUVR and plasma AD biomarkers, including Aβ42, Aβ40, P-tau181, and T-tau. The automated radiosynthesis of [18F]92 was completed within 50 min, yielding a radiochemical purity of greater than 95% and a radiochemical yield of 36 ± 3% (nondecay-corrected). Among the participants, 15 were estimated as Aβ (-) and 16 as Aβ (+). TACs indicated that [18F]92 rapidly crossed the blood-brain barrier within 10 min, followed by a rapid decrease, which then slowed down in the last 50-90 min. SUVR curves revealed that SUVR values stabilized around 60-70 min after injection and reached an equilibrium between 70 and 90 min, primarily in the cerebral cortex. SUVRs of Aβ (+) participants were significantly higher than those of Aβ (-) individuals within the cerebral cortex. In addition, Aβ42 and the Aβ42/Aβ40 ratio exhibited negative correlations with global SUVR, while plasma P-tau181 and the P-tau181/T-tau ratio displayed positive correlations with global SUVR. [18F]92 exhibits excellent pharmacokinetic properties in the human brain and can be synthesized automatically on a large scale. [18F]92 is a promising and reliable radiotracer for estimating Aβ pathology accumulation, providing valuable assistance in AD diagnosis and guiding clinical trials of therapeutic drugs.

New horizons in the diagnosis and management of Alzheimer's Disease in older adults

Alzheimer's Disease (ad) is the most common cause of dementia, and in addition to cognitive decline, it directly contributes to physical frailty, falls, incontinence, institutionalisation and polypharmacy in older adults. Increasing availability of clinically validated biomarkers including cerebrospinal fluid and positron emission tomography to assess both amyloid and tau pathology has led to a reconceptualisation of ad as a clinical-biological diagnosis, rather than one based purely on clinical phenotype. However, co-pathology is frequent in older adults which influence the accuracy of biomarker interpretation. Importantly, some older adults with positive amyloid or tau pathological biomarkers may never experience cognitive impairment or dementia. These strides towards achieving an accurate clinical-biological diagnosis are occurring alongside recent positive phase 3 trial results reporting statistically significant effects of anti-amyloid Disease-Modifying Therapies (DMTs) on disease severity in early ad. However, the real-world clinical benefit of these DMTs is not clear and concerns remain regarding how trial results will translate to real-world clinical populations, potential adverse effects (including amyloid-related imaging abnormalities), which can be severe and healthcare systems readiness to afford and deliver potential DMTs to appropriate populations. Here, we review recent advances in both clinical-biological diagnostic classification and future treatment in older adults living with ad. Advocating for access to both more accurate clinical-biological diagnosis and potential DMTs must be done so in a holistic and gerontologically attuned fashion, with geriatricians advocating for enhanced multi-component and multi-disciplinary care for all older adults with ad. This includes those across the ad severity spectrum including older adults potentially ineligible for emerging DMTs.

Feasibility evaluation of middle-phase 18F-florbetaben positron emission tomography imaging using centiloid quantification and visual assessment

Background

18F-florbetaben (FBB) positron emission tomography (PET) scan has been widely used in research and routine clinical practice. Most studies used late-phase (scanning from 90 to 110 min after injection) FBB scans to generate beta-amyloid accumulation data. The feasibility of middle-phase scan is seldom discussed. Using the middle-phase data can shorten the patients' waiting between the injection and scan, and hospital can acquire more flexible schedule of routine scan.

Methods

Paired middle-phase (60-80 min) FBB scans and standard (90-110 min) FBB scans were obtained from 27 subjects (12 neurodegenerative dementia, 8 mild cognitive impairment, 3 normal control, and 4 patients not suffering from neurodegenerative dementia). Standardized uptake value ratios (SUVRs) were calculated and converted to centiloid (CL) scale to investigate the impact on image quantification. CL pipeline validation were performed to build an equation converting the middle-phase data into equivalent standard scans. Cohen's kappa of binary interpretation and brain amyloid plaque load (BAPL) score were also used to evaluate the intrareader agreement of the FBB image from the two protocols.

Results

The middle-phase FBB SUVR showed an excellent correlation, which provided a linear regression equation of SUVRFBB60-80 = 0.88 × SUVRFBB90-110 + 0.07, with R2=0.98. The slope of the equation indicated that there was bias between the middle and standard acquisition. This can be converted into the CL scale using CL = 174.68 × SUVR - 166.39. Cohen's kappa of binary interpretation and BAPL score were 1.0 (P<0.0001).

Conclusions

Our findings indicate that the middle-phase FBB protocol is feasible in clinical applications for scans that are at either end of beta-amyloid spectrum, which provides comparable semiquantitative results to standard scan. Patient's waiting time between the injection and scan can be shortened.

A multicenter evaluation of a deep learning software (LungQuant) for lung parenchyma characterization in COVID-19 pneumonia

BACKGROUND

The role of computed tomography (CT) in the diagnosis and characterization of coronavirus disease 2019 (COVID-19) pneumonia has been widely recognized. We evaluated the performance of a software for quantitative analysis of chest CT, the LungQuant system, by comparing its results with independent visual evaluations by a group of 14 clinical experts. The aim of this work is to evaluate the ability of the automated tool to extract quantitative information from lung CT, relevant for the design of a diagnosis support model.

METHODS

LungQuant segments both the lungs and lesions associated with COVID-19 pneumonia (ground-glass opacities and consolidations) and computes derived quantities corresponding to qualitative characteristics used to clinically assess COVID-19 lesions. The comparison was carried out on 120 publicly available CT scans of patients affected by COVID-19 pneumonia. Scans were scored for four qualitative metrics: percentage of lung involvement, type of lesion, and two disease distribution scores. We evaluated the agreement between the LungQuant output and the visual assessments through receiver operating characteristics area under the curve (AUC) analysis and by fitting a nonlinear regression model.

RESULTS

Despite the rather large heterogeneity in the qualitative labels assigned by the clinical experts for each metric, we found good agreement on the metrics compared to the LungQuant output. The AUC values obtained for the four qualitative metrics were 0.98, 0.85, 0.90, and 0.81.

CONCLUSIONS

Visual clinical evaluation could be complemented and supported by computer-aided quantification, whose values match the average evaluation of several independent clinical experts.

KEY POINTS

We conducted a multicenter evaluation of the deep learning-based LungQuant automated software. We translated qualitative assessments into quantifiable metrics to characterize coronavirus disease 2019 (COVID-19) pneumonia lesions. Comparing the software output to the clinical evaluations, results were satisfactory despite heterogeneity of the clinical evaluations. An automatic quantification tool may contribute to improve the clinical workflow of COVID-19 pneumonia.

Quantification of amyloid PET for future clinical use: a state-of-the-art review

Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer's disease (AD) pathogenesis. The overall load and spatial distribution of brain Aβ can be determined in vivo using positron emission tomography (PET), for which three fluorine-18 labelled radiotracers have been approved for clinical use. In clinical practice, trained readers will categorise scans as either Aβ positive or negative, based on visual inspection. Diagnostic decisions are often based on these reads and patient selection for clinical trials is increasingly guided by amyloid status. However, tracer deposition in the grey matter as a function of amyloid load is an inherently continuous process, which is not sufficiently appreciated through binary cut-offs alone. State-of-the-art methods for amyloid PET quantification can generate tracer-independent measures of Aβ burden. Recent research has shown the ability of these quantitative measures to highlight pathological changes at the earliest stages of the AD continuum and generate more sensitive thresholds, as well as improving diagnostic confidence around established binary cut-offs. With the recent FDA approval of aducanumab and more candidate drugs on the horizon, early identification of amyloid burden using quantitative measures is critical for enrolling appropriate subjects to help establish the optimal window for therapeutic intervention and secondary prevention. In addition, quantitative amyloid measurements are used for treatment response monitoring in clinical trials. In clinical settings, large multi-centre studies have shown that amyloid PET results change both diagnosis and patient management and that quantification can accurately predict rates of cognitive decline. Whether these changes in management reflect an improvement in clinical outcomes is yet to be determined and further validation work is required to establish the utility of quantification for supporting treatment endpoint decisions. In this state-of-the-art review, several tools and measures available for amyloid PET quantification are summarised and discussed. Use of these methods is growing both clinically and in the research domain. Concurrently, there is a duty of care to the wider dementia community to increase visibility and understanding of these methods.

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.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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.

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.

The search for a convenient procedure to detect one of the earliest signs of Alzheimer's disease: A systematic review of the prediction of brain amyloid status

INTRODUCTION

Convenient, cost-effective tests for amyloid beta (Aβ) are needed to identify those at higher risk for developing Alzheimer's disease (AD). This systematic review evaluates recent models that predict dichotomous Aβ. (PROSPERO: CRD42020144734).

METHODS

We searched Embase and identified 73 studies from 29,581 for review. We assessed study quality using established tools, extracted information, and reported results narratively.

RESULTS

We identified few high-quality studies due to concerns about Aβ determination and analytical issues. The most promising convenient, inexpensive classifiers consist of age, apolipoprotein E genotype, cognitive measures, and/or plasma Aβ. Plasma Aβ may be sufficient if pre-analytical variables are standardized and scalable assays developed. Some models lowered costs associated with clinical trial recruitment or clinical screening.

DISCUSSION

Conclusions about models are difficult due to study heterogeneity and quality. Promising prediction models used demographic, cognitive/neuropsychological, imaging, and plasma Aβ measures. Further studies using standardized Aβ determination, and improved model validation are required.

Evaluation of a visual interpretation method for tau-PET with 18F-flortaucipir

INTRODUCTION

Positron emission tomography targeting tau (tau-PET) is a promising diagnostic tool for the identification of Alzheimer's disease (AD). Currently available data rely on quantitative measures, and a visual interpretation method, critical for clinical translation, is needed.

METHODS

We developed a visual interpretation method for 18F-flortaucipir tau-PET and tested it on 274 individuals (cognitively normal controls, patients with mild cognitive impairment [MCI], AD dementia, and non-AD diagnoses). Two readers interpreted 18F-flortaucipir PET using two complementary indices: a global visual score and a visual distribution pattern.

RESULTS

Global visual scores were reliable, correlated with global cortical 18F-flortaucipir standardized uptake value ratio (SUVR) and were associated with clinical diagnosis and amyloid status. The AD-like 18F-flortaucipir pattern had good sensitivity and specificity to identify amyloid-positive patients with AD dementia or MCI.

DISCUSSION

This 18F-flortaucipir visual rating scheme is associated with SUVR quantification, clinical diagnosis, and amyloid status, and constitutes a promising approach to tau measurement in clinical settings.

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

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

No evidence for amyloid pathology as a key mediator of neurodegeneration post-stroke - a seven-year follow-up study

Background

Cognitive impairment (CI) with mixed vascular and neurodegenerative pathologies after stroke is common. The role of amyloid pathology in post-stroke CI is unclear. We hypothesize that amyloid deposition, measured with Flutemetamol (¹⁸F-Flut) positron emission tomography (PET), is common in seven-year stroke survivors diagnosed with CI and, further, that quantitatively assessed ¹⁸F-Flut-PET uptake after 7 years correlates with amyloid-β peptide (Aβ₄₂) levels in cerebrospinal fluid (CSF) at 1 year, and with measures of neurodegeneration and cognition at 7 years post-stroke.

Methods

208 patients with first-ever stroke or transient Ischemic Attack (TIA) without pre-existing CI were included during 2007 and 2008. At one- and seven-years post-stroke, cognitive status was assessed, and categorized into dementia, mild cognitive impairment or normal. Etiologic sub-classification was based on magnetic resonance imaging (MRI) findings, CSF biomarkers and clinical cognitive profile. At 7 years, patients were offered ¹⁸F-Flut-PET, and amyloid-positivity was assessed visually and semi-quantitatively. The associations between ¹⁸F-Flut-PET standardized uptake value ratios (SUVr) and measures of neurodegeneration (medial temporal lobe atrophy (MTLA), global cortical atrophy (GCA)) and cognition (Mini-Mental State Exam (MMSE), Trail-making test A (TMT-A)) and CSF Aβ₄₂ levels were assessed using linear regression.

Results

In total, 111 patients completed 7-year follow-up, and 26 patients agreed to PET imaging, of whom 13 had CSF biomarkers from 1 year. Thirteen out of 26 patients were diagnosed with CI 7 years post-stroke, but only one had visually assessed amyloid positivity. CSF Aβ₄₂ levels at 1 year, MTA grade, GCA scale, MMSE score or TMT-A at 7 years did not correlate with ¹⁸F-Flut-PET SUVr in this cohort.

Conclusions

Amyloid binding was not common in 7-year stroke survivors diagnosed with CI. Quantitatively assessed, cortical amyloid deposition did not correlate with other measures related to neurodegeneration or cognition. Therefore, amyloid pathology may not be a key mediator of neurodegeneration 7 years post-stroke.

Trial registration

Clinicaltrials.gov (NCT00506818). July 23, 2007. Inclusion from February 2007, randomization and intervention from May 2007 and trial registration in July 2007.

Improved Risk Stratification for Progression from Mild Cognitive Impairment to Alzheimer's Disease with a Multi-Analytical Evaluation of Amyloid-β Positron Emission Tomography

BACKGROUND

Amyloid-β (Aβ) accumulation in brain of patients with suspected Alzheimer's disease (AD) can be assessed by positron emission tomography (PET) in vivo. While visual classification prevails in the clinical routine, semiquantitative PET analyses may enable more reliable evaluation of cases with a visually uncertain, borderline Aβ accumulation.

OBJECTIVE

We evaluated different analysis approaches (visual/semiquantitative) to find the most accurate and sensitive interpretation of Aβ-PET for predicting risk of progression from mild cognitive impairment (MCI) to AD.

METHODS

Based on standard uptake value (SUV) ratios of a cortical-composite volume of interest of 18F-AV45-PET from MCI subjects (n = 396, ADNI database), we compared three different reference region (cerebellar grey matter, CBL; brainstem, BST; white matter, WM) normalizations and the visual read by receiver operator characteristics for calculating a hazard ratio (HR) for progression to Alzheimer's disease dementia (ADD).

RESULTS

During a mean follow-up time of 45.6±13.0 months, 28% of the MCI cases (110/396) converted to ADD. Among the tested methods, the WM reference showed best discriminatory power and progression-risk stratification (HRWM of 4.4 [2.6-7.6]), but the combined results of the visual and semiquantitative analysis with all three reference regions showed an even higher discriminatory power.

CONCLUSION

A multi-analytical composite of visual and semiquantitative reference tissue analyses of 18F-AV45-PET gave improved risk stratification for progression from MCI to ADD relative to performance of single read-outs. This optimized approach is of special interest for prospective treatment trials, which demand a high accuracy.

A kinetics-based approach to amyloid PET semi-quantification

PURPOSE

To develop and validate a semi-quantification method (time-delayed ratio, TDr) applied to amyloid PET scans, based on tracer kinetics information.

METHODS

The TDr method requires two static scans per subject: one early (~ 0-10 min after the injection) and one late (typically 50-70 min or 90-100 min after the injection, depending on the tracer). High perfusion regions are delineated on the early scan and applied onto the late scan. A SUVr-like ratio is calculated between the average intensities in the high perfusion regions and the late scan hotspot. TDr was applied to a naturalistic multicenter dataset of 143 subjects acquired with [¹⁸F]florbetapir. TDr values are compared to visual evaluation, cortical-cerebellar SUVr, and to the geometrical semi-quantification method ELBA. All three methods are gauged versus the heterogeneity of the dataset.

RESULTS

TDr shows excellent agreement with respect to the binary visual assessment (AUC = 0.99) and significantly correlates with both validated semi-quantification methods, reaching a Pearson correlation coefficient of 0.86 with respect to ELBA.

CONCLUSIONS

TDr is an alternative approach to previously validated ones (SUVr and ELBA). It requires minimal image processing; it is independent on predefined regions of interest and does not require MR registration. Besides, it takes advantage on the availability of early scans which are becoming common practice while imposing a negligible added patient discomfort.