Reference tissue normalization in longitudinal (18)F-florbetapir positron emission tomography of late mild cognitive impairment

The associations between synaptic density and "A/T/N" biomarkers in Alzheimer's disease: An 18F-SynVesT-1 PET/MR study

A newly developed SV2A radiotracer, 18F-SynVesT-1, was used in this study to investigate synaptic density and its association with Alzheimer's disease (AD) "A/T/N" biomarkers. The study included a cohort of 97 subjects, consisting of 64 patients with cognitive impairment (CI) and 33 individuals with normal cognition (CU). All subjects underwent 18F-SynVesT-1 PET/MR and 18F-florbetapir PET/CT scans. Additionally, a subgroup of individuals also underwent 18F-MK-6240, 18F-FDG PET/CT, plasma Aβ42/Aβ40 and p-tau181 tests. The differences in synaptic density between the groups and the correlations between synaptic density and AD "A/T/N" biomarkers were analyzed. The results showed that compared to the CU group, the CI with Aβ+ (CI+) group exhibited the most pronounced synapse loss in the hippocampus, with some loss also observed in the neocortex. Furthermore, synaptic density in the hippocampus and parahippocampal gyrus showed associations with AD biomarkers detected by both imaging and plasma tests in the CI group. The associations between synaptic density and FDG uptake and hippocampal volume were also observed in the CI+ group. In conclusion, the study demonstrated significant synaptic density loss, as measured by the promising tracer 18F-SynVesT-1, and its close correlation with "A/T/N" biomarkers in patients with both Alzheimer's clinical syndrome and pathological changes.

Multi-domain cognition dysfunction accompanies frontoparietal and temporal amyloid accumulation in the elderly

It is helpful to understand the pathology of Alzheimer's disease by exploring the relationship between amyloid-β accumulation and cognition. The study explored the relationship between regional amyloid-β accumulation and multiple cognitions and study their application value in the Alzheimer's disease diagnosis. 135 participants completed 18F-florbetapir Positron Emission Tomography (PET), structural MRI, and a cognitive battery. Partial correlation was used to examine the relationship between global and regional amyloid-β accumulation and cognitions. Then, a support vector machine was applied to determine whether cognition-related accumulation regions can adequately distinguish the cognitively normal controls (76 participants) and mild cognitive impairment (30 participants) groups or mild cognitive impairment and Alzheimer's disease (29 participants) groups. The result showed that amyloid-β accumulation regions were mainly located in the frontoparietal cortex, calcarine fissure, and surrounding cortex and temporal pole regions. Episodic memory-related regions included the frontoparietal cortices; executive function-related regions included the frontoparietal, temporal, and occipital cortices; and processing speed-related regions included the frontal and occipital cortices. Support vector machine analysis showed that only episodic memory-related amyloid-β accumulation regions had better classification performance during the progression of Alzheimer's disease. Assessing regional changes in amyloid, particularly in frontoparietal regions, can aid in the early detection of amyloid-related decline in cognitive function.

Quantitative Mass Spectrometry Analysis of Cerebrospinal Fluid Protein Biomarkers in Alzheimer's Disease

Alzheimer's disease (AD) is the most common form of dementia, with cerebrospinal fluid (CSF) β-amyloid (Aβ), total Tau, and phosphorylated Tau (pTau) providing the most sensitive and specific biomarkers for diagnosis. However, these diagnostic biomarkers do not reflect the complex changes in AD brain beyond amyloid (A) and Tau (T) pathologies. Here, we report a selected reaction monitoring mass spectrometry (SRM-MS) method with isotopically labeled standards for relative protein quantification in CSF. Biomarker positive (AT+) and negative (AT-) CSF pools were used as quality controls (QCs) to assess assay precision. We detected 62 peptides (51 proteins) with an average coefficient of variation (CV) of ~13% across 30 QCs and 133 controls (cognitively normal, AT-), 127 asymptomatic (cognitively normal, AT+) and 130 symptomatic AD (cognitively impaired, AT+). Proteins that could distinguish AT+ from AT- individuals included SMOC1, GDA, 14-3-3 proteins, and those involved in glycolysis. Proteins that could distinguish cognitive impairment were mainly neuronal proteins (VGF, NPTX2, NPTXR, and SCG2). This demonstrates the utility of SRM-MS to quantify CSF protein biomarkers across stages of AD.

The RSNA QIBA Profile for Amyloid PET as an Imaging Biomarker for Cerebral Amyloid Quantification

A standardized approach to acquiring amyloid PET images increases their value as disease and drug response biomarkers. Most 18F PET amyloid brain scans often are assessed only visually (per regulatory labels), with a binary decision indicating the presence or absence of Alzheimer disease amyloid pathology. Minimizing technical variance allows precise, quantitative SUV ratios (SUVRs) for early detection of β-amyloid plaques and allows the effectiveness of antiamyloid treatments to be assessed with serial studies. Methods: The Quantitative Imaging Biomarkers Alliance amyloid PET biomarker committee developed and validated a profile to characterize and reduce the variability of SUVRs, increasing statistical power for these assessments. Results: On achieving conformance, sites can justify a claim that brain amyloid burden reflected by the SUVR is measurable to a within-subject coefficient of variation of no more than 1.94% when the same radiopharmaceutical, scanner, acquisition, and analysis protocols are used. Conclusion: This overview explains the claim, requirements, barriers, and potential future developments of the profile to achieve precision in clinical and research amyloid PET imaging.

Comparison of 11C-Pittsburgh Compound B and 18F-Flutemetamol White Matter Binding in PET

PET imaging with β-amyloid ligands is emerging as a molecular imaging technique targeting white matter integrity and demyelination. β-amyloid PET ligands such as 11C-Pittsburgh compound B (11C-PiB) have been considered for quantitative measurement of myelin content changes in multiple sclerosis, but 11C-PiB is not commercially available given its short half-life. A 18F PET ligand such as flutemetamol with a longer half-life may be an alternative, but its ability to differentiate white matter hyperintensities (WMH) from normal-appearing white matter (NAWM) and its relationship with age remains to be investigated. Methods: Cognitively unimpaired (CU) older and younger adults (n = 61) were recruited from the community responding to a study advertisement for β-amyloid PET. Participants prospectively underwent MRI, 11C-PiB, and 18F-flutemetamol PET scans. MRI fluid-attenuated inversion recovery images were segmented into WMH and NAWM and registered to the T1-weighted MRI. 11C-PiB and 18F-flutemetamol PET images were also registered to the T1-weighted MRI. 11C-PiB and 18F-flutemetamol SUV ratios (SUVrs) from the WMH and NAWM were calculated using cerebellar crus uptake as a reference for both 11C-PiB and 18F-flutemetamol. Results: The median age was 38 y (range, 30-48 y) in younger adults and 67 y (range, 61-83 y) in older adults. WMH and NAWM SUVrs were higher with 18F-flutemetamol than with 11C-PiB in both older (P < 0.001) and younger (P < 0.001) CU adults. 11C-PiB and 18F-flutemetamol SUVrs were higher in older than in younger CU adults in both WMH (P < 0.001) and NAWM (P < 0.001). 11C-PiB and 18F-flutemetamol SUVrs were higher in NAWM than WMH in both older (P < 0.001) and younger (P < 0.001) CU adults. There was no apparent difference between 11C-PiB and 18F-flutemetamol SUVrs in differentiating WMH from NAWM in older and in younger adults. Conclusion:11C-PiB and 18F-flutemetamol show a similar topographic pattern of uptake in white matter with a similar association with age in WMH and NAWM. 11C-PiB and 18F-flutemetamol can also effectively distinguish between WMH and NAWM. However, given its longer half-life, commercial availability, and higher binding potential, 18F-flutemetamol can be an alternative to 11C-PiB in molecular imaging studies specifically targeting multiple sclerosis to evaluate white matter integrity.

Tracer-specific reference tissues selection improves detection of 18 F-FDG, 18 F-florbetapir, and 18 F-flortaucipir PET SUVR changes in Alzheimer's disease

This study sought to identify a reference tissue‐based quantification approach for improving the statistical power in detecting changes in brain glucose metabolism, amyloid, and tau deposition in Alzheimer's disease studies. A total of 794, 906, and 903 scans were included for ¹⁸F‐FDG, ¹⁸F‐florbetapir, and ¹⁸F‐flortaucipir, respectively. Positron emission tomography (PET) and T1‐weighted images of participants were collected from the Alzheimer's disease Neuroimaging Initiative database, followed by partial volume correction. The standardized uptake value ratios (SUVRs) calculated from the cerebellum gray matter, centrum semiovale, and pons were evaluated at both region of interest (ROI) and voxelwise levels. The statistical power of reference tissues in detecting longitudinal SUVR changes was assessed via paired t‐test. In cross‐sectional analysis, the impact of reference tissue‐based SUVR differences between cognitively normal and cognitively impaired groups was evaluated by effect sizes Cohen's d and two sample t‐test adjusted by age, sex, and education levels. The average ROI t values of pons were 86.62 and 38.40% higher than that of centrum semiovale and cerebellum gray matter in detecting glucose metabolism decreases, while the centrum semiovale reference tissue‐based SUVR provided higher t values for the detection of amyloid and tau deposition increases. The three reference tissues generated comparable d images for ¹⁸F‐FDG, ¹⁸F‐florbetapir, and ¹⁸F‐flortaucipir and comparable t maps for ¹⁸F‐florbetapir and ¹⁸F‐flortaucipir, but pons‐based t map showed superior performance in ¹⁸F‐FDG. In conclusion, the tracer‐specific reference tissue improved the detection of ¹⁸F‐FDG, ¹⁸F‐florbetapir, and ¹⁸F‐flortaucipir PET SUVR changes, which helps the early diagnosis, monitoring of disease progression, and therapeutic response in Alzheimer's disease.

Self-normalized Classification of Parkinson's Disease DaTscan Images

Classifying SPECT images requires a preprocessing step which normalizes the images using a normalization region. The choice of the normalization region is not standard, and using different normalization regions introduces normalization region-dependent variability. This paper mathematically analyzes the effect of the normalization region to show that normalized-classification is exactly equivalent to a subspace separation of the half rays of the images under multiplicative equivalence. Using this geometry, a new self-normalized classification strategy is proposed. This strategy eliminates the normalizing region altogether. The theory is used to classify DaTscan images of 365 Parkinson's disease (PD) subjects and 208 healthy control (HC) subjects from the Parkinson's Progression Marker Initiative (PPMI). The theory is also used to understand PD progression from baseline to year 4.

Spatially constrained kinetic modeling with dual reference tissues improves 18F-flortaucipir PET in studies of Alzheimer disease

PURPOSE

Recent studies have shown that standard compartmental models using plasma input or the cerebellum reference tissue input are generally not reliable for quantifying tau burden in dynamic 18F-flortaucipir PET studies of Alzheimer disease. So far, the optimal reference region for estimating 18F-flortaucipir delivery and specific tau binding has yet to be determined. The objective of the study is to improve 18F-flortaucipir brain tau PET quantification using a spatially constrained kinetic model with dual reference tissues.

METHODS

Participants were classified as either cognitively normal (CN) or cognitively impaired (CI) based on clinical assessment. T1-weighted structural MRI and 105-min dynamic 18F-flortaucipir PET scans were acquired for each participant. Using both a simplified reference tissue model (SRTM2) and Logan plot with either cerebellum gray matter or centrum semiovale (CS) white matter as the reference tissue, we estimated distribution volume ratios (DVRs) and the relative transport rate constant R1 for region of interest-based (ROI) and voxelwise-based analyses. Conventional linear regression (LR) and LR with spatially constrained (LRSC) parametric imaging algorithms were then evaluated. Noise-induced bias in the parametric images was compared to estimates from ROI time activity curve-based kinetic modeling. We finally evaluated standardized uptake value ratios at early phase (SUVREP, 0.7-2.9 min) and late phase (SUVRLP, 80-105 min) to approximate R1 and DVR, respectively.

RESULTS

The percent coefficients of variation of R1 and DVR estimates from SRTM2 with spatially constrained modeling were comparable to those from the Logan plot and SUVRs. The SRTM2 using CS reference tissue with LRSC reduced noise-induced underestimation in the LR generated DVR images to negligible levels (< 1%). Inconsistent overestimation of DVR in the SUVRLP only occurred using the cerebellum reference tissue-based measurements. The CS reference tissue-based DVR and SUVRLP, and cerebellum-based SUVREP and R1 provided higher Cohen's effect size d to detect increased tau deposition and reduced relative tracer transport rate in CI individuals.

CONCLUSION

Using a spatially constrained kinetic model with dual reference tissues significantly improved quantification of relative perfusion and tau binding. Cerebellum and CS are the suggested reference tissues to estimate R1 and DVR, respectively, for dynamic 18F-flortaucipir PET studies. Cerebellum-based SUVREP and CS-based SUVRLP may be used to simplify 18F-flortaucipir PET study.

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.

Evaluation of the early-phase [18F]AV45 PET as an optimal surrogate of [18F]FDG PET in ageing and Alzheimer's clinical syndrome

Dual-phase [18F]AV45 positron emission tomography (PET) is highly promising in the assessment of neurodegenerative diseases, allowing to obtain information on both neurodegeneration (early-phase; eAV45) and amyloid deposition (late-phase; lAV45) which are highly complementary; yet eAV45 needs further evaluation. This study aims at validating eAV45 as an optimal proxy of [18F]FDG PET in a large mixed-population of healthy ageing and Alzheimer's clinical syndrome participants (n = 191) who had [18F]FDG PET, eAV45 and lAV45 scans. We found early time frame 0-4 min to give maximal correlation with [18F]FDG PET and minimal correlation with lAV45. Moreover, maximal overlap of [18F]FDG PET versus eAV45 associations with clinical diagnosis and cognition was obtained with pons scaling. Across reference regions, classification performance between clinical subgroups was similar for both eAV45 and [18F]FDG PET. These findings highlight the optimal use of eAV45 to assess neurodegeneration as a validated proxy of [18F]FDG PET. On top of this purpose, this study showed that combined [18F]AV45 PET dual-biomarker even outperformed [18F]FDG PET or lAV45 alone.

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.

Imaging Techniques in Alzheimer's Disease: A Review of Applications in Early Diagnosis and Longitudinal Monitoring

BACKGROUND

Alzheimer's disease (AD) is a progressive neurodegenerative disorder affecting many individuals worldwide with no effective treatment to date. AD is characterized by the formation of senile plaques and neurofibrillary tangles, followed by neurodegeneration, which leads to cognitive decline and eventually death.

INTRODUCTION

In AD, pathological changes occur many years before disease onset. Since disease-modifying therapies may be the most beneficial in the early stages of AD, biomarkers for the early diagnosis and longitudinal monitoring of disease progression are essential. Multiple imaging techniques with associated biomarkers are used to identify and monitor AD.

AIM

In this review, we discuss the contemporary early diagnosis and longitudinal monitoring of AD with imaging techniques regarding their diagnostic utility, benefits and limitations. Additionally, novel techniques, applications and biomarkers for AD research are assessed.

FINDINGS

Reduced hippocampal volume is a biomarker for neurodegeneration, but atrophy is not an AD-specific measure. Hypometabolism in temporoparietal regions is seen as a biomarker for AD. However, glucose uptake reflects astrocyte function rather than neuronal function. Amyloid-β (Aβ) is the earliest hallmark of AD and can be measured with positron emission tomography (PET), but Aβ accumulation stagnates as disease progresses. Therefore, Aβ may not be a suitable biomarker for monitoring disease progression. The measurement of tau accumulation with PET radiotracers exhibited promising results in both early diagnosis and longitudinal monitoring, but large-scale validation of these radiotracers is required. The implementation of new processing techniques, applications of other imaging techniques and novel biomarkers can contribute to understanding AD and finding a cure.

CONCLUSIONS

Several biomarkers are proposed for the early diagnosis and longitudinal monitoring of AD with imaging techniques, but all these biomarkers have their limitations regarding specificity, reliability and sensitivity. Future perspectives. Future research should focus on expanding the employment of imaging techniques and identifying novel biomarkers that reflect AD pathology in the earliest stages.

Parametric estimation of reference signal intensity in the quantification of amyloid-beta deposition: an 18F-AV-45 study

BACKGROUND

Positron emission tomography (PET) with the radiotracer florbetapir (18F-AV-45) allows the pathophysiology of Alzheimer's disease (AD) to be tracked in vivo. The semi-quantification of amyloid-beta (Aβ) has been extensively evaluated with the standardized uptake value ratio (SUVR) but is susceptible to disturbance from the candidate reference region and the partial volume effect (PVE). In the present study, we applied the parametric estimation of reference signal intensity (PERSI) method to 18F-AV-45 PET images for intensity normalization.

METHODS

We enrolled 479 people with 18F-AV-45 images from the Alzheimer's Disease Neuroimaging Initiative database: 261 healthy controls (HCs), 102 patients with mild cognitive impairment (MCI), and 116 AD patients. We used white matter post-processed by PERSI (PERSI-WM) as the reference region and compared our proposed method with the traditional method for semi-quantification. SUVRs were calculated for eight regions of interest: the frontal lobe, the parietal lobe, the temporal lobe, the occipital lobe, the anterior cingulate cortex, the posterior cingulate cortex, the precuneus, and the global cortex. The SUVRs derived from PERSI-WM and other reference regions were evaluated by effect size and receiver-operator characteristic curve analyses.

RESULTS

The SUVRs derived from PERSI-WM showed significantly higher trace retention in the frontal, parietal, temporal, and occipital lobes, as well as in the anterior cingulate, posterior cingulate, precuneus, and global cortex in the AD Aβ-positive (+) group (mean: +43.3%±5.4%, P<0.01) and MCI Aβ+ group (mean: +29.6%±5.3%, P<0.01). For the global cortex, PERSI-WM had the greatest Cohen's d effect size compared with the HC Aβ-negative (-) group (AD Aβ+ and MCI Aβ+: 3.02, AD Aβ+: 3.56, MCI Aβ+: 2.34), and the highest area under the curve (AUC) between the HC Aβ- and AD Aβ+ groups (AUC: 0.983, 95% confidence interval: 0.978-0.998).

CONCLUSIONS

PERSI-WM could mitigate the influence of PVE and improve the semi-quantification of 18F-AV-45 images; therefore, it could be used for large-scale clinical application in the nuclear medicine domain.

Blinded Clinical Evaluation for Dementia of Alzheimer's Type Classification Using FDG-PET: A Comparison Between Feature-Engineered and Non-Feature-Engineered Machine Learning Methods

BACKGROUND

Advanced machine learning methods can aid in the identification of dementia risk using neuroimaging-derived features including FDG-PET. However, to enable the translation of these methods and test their usefulness in clinical practice, it is crucial to conduct independent validation on real clinical samples, which has yet to be properly delineated in the current literature.

OBJECTIVE

In this paper, we present our efforts to enable such clinical translational through the evaluation and comparison of two machine-learning methods for discrimination between dementia of Alzheimer's type (DAT) and Non-DAT controls.

METHODS

FDG-PET-based dementia scores were generated on an independent clinical sample whose clinical diagnosis was blinded to the algorithm designers. A feature-engineered approach (multi-kernel probability classifier) and a non-feature-engineered approach (3D convolutional neural network) were analyzed. Both classifiers were pre-trained on cognitively normal subjects as well as subjects with DAT. These two methods provided a probabilistic dementia score for this previously unseen clinical data. Performance of the algorithms were compared against ground-truth dementia rating assessed by experienced nuclear physicians.

RESULTS

Blinded clinical evaluation on both classifiers showed good separation between the cognitively normal subjects and the patients diagnosed with DAT. The non-feature-engineered dementia score showed higher sensitivity among subjects whose diagnosis was in agreement between the machine-learning models, while the feature-engineered approach showed higher specificity in non-consensus cases.

CONCLUSION

In this study, we demonstrated blinded evaluation using data from an independent clinical sample for assessing the performance in DAT classification models in a clinical setting. Our results showed good generalizability for two machine-learning approaches, marking an important step for the translation of pre-trained machine-learning models into clinical practice.

(18F)-Fluorodeoxyglucose positron emission tomography/magnetic resonance imaging assessment of hypometabolism patterns in clinical phenotypes of suspected corticobasal degeneration

Corticobasal degeneration (CBD) is a rare neurodegenerative disorder presenting with atypical parkinsonian symptoms that characteristically involves the frontoparietal region including the primary sensorimotor cortex, ipsilateral basal ganglia, and thalamus, typically in an asymmetric pattern. We aim to evaluate the metabolic and volumetric abnormalities in patients with clinically suspected CBD phenotypes utilizing hybrid ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography–magnetic resonance (PET/ MR) brain imaging. A retrospective analysis was performed on 75 patients (mean age 74 years, 31 males and 44 females) who underwent ¹⁸F-FDG PET/MR imaging (MRI) as part of their clinical dementia workup. Images were obtained using an integrated Siemens mMR 3T PET/MRI scanner. Two board-certified neuroradiologists and a nuclear medicine physician evaluated the metabolic and volumetric data of each hemisphere to assess for symmetric or asymmetric involvement of regions of interest in the subset of patients with suspected CBD. Of the 75 patients, 12 were diagnosed with suspected CBD based on a combination of clinical symptoms, neurocognitive testing, and hybrid neuroimaging findings. Ten of 12 patients (87%) demonstrated asymmetrically decreased FDG uptake involving a single cerebral hemisphere and ipsilateral subcortical structures, whereas two of 12 patients (13%) demonstrated striking hypometabolism of the bilateral sensorimotor cortices. Our study highlights two characteristic patterns of hypometabolism in patients with clinical and neuroimaging findings suggestive of the underlying CBD. The first pattern is asymmetric hypometabolism and volume loss, particularly within the frontoparietal and occipital cortices with involvement of ipsilateral subcortical structures, including the basal ganglia and thalamus. The second, more atypical pattern, is symmetric hypometabolism with striking involvement of the bilateral sensorimotor cortices.

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.

Quantification of [18F]florbetapir: A test-retest tracer kinetic modelling study

Accumulation of amyloid beta can be visualized using [¹⁸F]florbetapir positron emission tomography. The aim of this study was to identify the optimal model for quantifying [¹⁸F]florbetapir uptake and to assess test-retest reliability of corresponding outcome measures. Eight Alzheimer's disease patients (age: 67 ± 6 years, Mini-Mental State Examination (MMSE): 23 ± 3) and eight controls (age: 63 ± 4 years, MMSE: 30 ± 0) were included. Ninety-minute dynamic positron emission tomography scans, together with arterial blood sampling, were acquired immediately following a bolus injection of 294 ± 32 MBq [¹⁸F]florbetapir. Several plasma input models and the simplified reference tissue model (SRTM) were evaluated. The Akaike information criterion was used to identify the preferred kinetic model. Compared to controls, Alzheimer's disease patients had lower MMSE scores and evidence for cortical Aβ pathology. A reversible two-tissue compartment model with fitted blood volume fraction (2T4k_V_B) was the preferred model for describing [¹⁸F]florbetapir kinetics. SRTM-derived non-displaceable binding potential (BP_ND) correlated well (r²= 0.83, slope = 0.86) with plasma input-derived distribution volume ratio. Test-retest reliability for plasma input-derived distribution volume ratio, SRTM-derived BP_ND and SUVr_(50-70) were r = 0.88, r = 0.91 and r = 0.86, respectively. In vivo kinetics of [¹⁸F]florbetapir could best be described by a reversible two-tissue compartmental model and [¹⁸F]florbetapir BP_ND can be reliably estimated using an SRTM.

AD molecular: PET amyloid imaging across the Alzheimer's disease spectrum: From disease mechanisms to prevention

The advent of amyloid-beta (Aβ) positron emission tomography (PET) imaging has transformed the field of Alzheimer's disease (AD) by enabling the quantification of cortical Aβ accumulation and propagation in vivo. This revolutionary tool has made it possible to measure direct associations between Aβ and other AD biomarkers, to identify factors that influence Aβ accumulation and to redefine entry criteria into clinical trials as well as measure drug target engagement. This chapter summarizes the main findings on the associations of Aβ with other biomarkers of disease progression across the AD spectrum. It discusses investigations of the timing at which Aβ pathology starts to accumulate, demonstrates the clinical utility of Aβ PET imaging and discusses some ethical implications. Finally, it presents genetic and potentially modifiable lifestyle factors that might influence Aβ accumulation and therefore be targets for AD prevention.

Investigation of white matter PiB uptake as a marker of white matter integrity

OBJECTIVE

To investigate the associations of Pittsburgh compound-B (PiB) uptake in white matter hyperintensities (WMH) and normal appearing white matter (NAWM) with white matter (WM) integrity measured with DTI and cognitive function in cognitively unimpaired older adults.

METHODS

Cognitively unimpaired older adults from the population-based Mayo Clinic Study of Aging (n = 537, age 65-95) who underwent both PiB PET and DTI were included. The associations of WM PiB standard uptake value ratio (SUVr) with fractional anisotropy (FA) and mean diffusivity (MD) in the WMH and NAWM were tested after adjusting for age. The associations of PiB SUVr with cognitive function z-scores were tested after adjusting for age and global cortical PiB SUVr.

RESULTS

The WMH PiB SUVr was lower than NAWM PiB SUVr (P < 0.001). In the WMH, lower PiB SUVr correlated with lower FA (r = 0.21, P < 0.001), and higher MD (r = -0.31, P < 0.001). In the NAWM, lower PiB SUVr only correlated with higher MD (r = -0.10, P = 0.02). Both in the WMH and NAWM, lower PiB SUVr was associated with lower memory, language, and global cognitive function z-scores after adjusting for age and global cortical PiB SUVr.

INTERPRETATION

Reduced PiB uptake in the WMH is associated with a loss of WM integrity and cognitive function after accounting for the global cortical PiB uptake, suggesting that WM PiB uptake may be an early biomarker of WM integrity that precedes cognitive impairment in older adults. When using WM as a reference region in cross-sectional analysis of PiB SUVr, individual variability in WMH volume as well as age should be considered.

Association of short-term cognitive decline and MCI-to-AD dementia conversion with CSF, MRI, amyloid- and 18F-FDG-PET imaging

Disease-modifying treatment trials are increasingly advanced to the prodromal or preclinical phase of Alzheimer's disease (AD), and inclusion criteria are based on biomarkers rather than clinical symptoms. Therefore, it is of great interest to determine which biomarkers should be combined to accurately predict conversion from mild cognitive impairment (MCI) to AD dementia. However, up to date, only few studies performed a complete A/T/N subject characterization using each of the CSF and imaging markers, or they only investigated long-term (≥ 2 years) prognosis. This study aimed to investigate the association between cerebrospinal fluid (CSF), magnetic resonance imaging (MRI), amyloid- and ¹⁸F-FDG positron emission tomography (PET) measures at baseline, in relation to cognitive changes and conversion to AD dementia over a short-term (12-month) period. We included 13 healthy controls, 49 MCI and 16 AD dementia patients with a clinical-based diagnosis and a complete A/T/N characterization at baseline. Global cortical amyloid-β (Aβ) burden was quantified using the ¹⁸F-AV45 standardized uptake value ratio (SUVR) with two different reference regions (cerebellar grey and subcortical white matter), whereas metabolism was assessed based on ¹⁸F-FDG SUVR. CSF measures included Aβ_1–42, Aβ_1–40, T-tau, P-tau₁₈₁, and their ratios, and MRI markers included hippocampal volumes (HV), white matter hyperintensities, and cortical grey matter volumes. Cognitive functioning was measured by MMSE and RBANS index scores. All statistical analyses were corrected for age, sex, education, and APOE ε4 genotype. As a result, faster cognitive decline was most strongly associated with hypometabolism (posterior cingulate) and smaller hippocampal volume (e.g., Δstory recall: β = +0.43 [p < 0.001] and + 0.37 [p = 0.005], resp.) at baseline. In addition, faster cognitive decline was significantly associated with higher baseline Aβ burden only if SUVR was referenced to the subcortical white matter (e.g., Δstory recall: β = −0.28 [p = 0.020]). Patients with MCI converted to AD dementia at an annual rate of 31%, which could be best predicted by combining neuropsychological testing (visuospatial construction skills) with either MRI-based HV or ¹⁸F-FDG-PET. Combining all three markers resulted in 96% specificity and 92% sensitivity. Neither amyloid-PET nor CSF biomarkers could discriminate short-term converters from non-converters.

•

FDG-PET and MRI HV are the strongest predictors of cognitive decline and conversion to AD.

•

Combination of visuospatial construction testing with FDG-PET or MRI HV present high predicting power of conversion.

•

CSF and amyloid-PET seem less suitable markers of disease progression.

•

Increased AV45-PET predicts short-term cognitive decline if SUVR is referenced to WM instead of CB.

White Matter Reference Region in PET Studies of 11C-Pittsburgh Compound B Uptake: Effects of Age and Amyloid-β Deposition

Amyloid-β (Aβ) deposition as seen on PET using an Aβ-binding agent is a critical diagnostic biomarker for Alzheimer disease (AD). Some reports suggest using white matter (WM) as a reference region for quantification of serial Aβ PET studies; however, nonspecific WM retention in Aβ PET in people with dementia or cognitively unimpaired (CU) has been widely reported and is poorly understood. Methods: To investigate the suitability of WM as a reference region and the factors affecting WM 11C-Pittsburgh compound B (11C-PiB) uptake variability, we conducted a retrospective study on 2 large datasets: a longitudinal study of participants (n = 577) who were CU, had mild cognitive impairment, or had dementia likely due to AD; and a cross-sectional study of single-scan PET imaging in CU subjects (n = 1,349). In the longitudinal study, annual changes in WM 11C-PiB uptake were assessed, and in the cross-sectional study, WM 11C-PiB uptake was assessed relative to subject age. Results: Overall, we found that WM 11C-PiB uptake showed age-related increases, which varied with the WM regions selected. Further, variable annual WM 11C-PiB uptake changes were seen with different gray matter (GM) 11C-PiB baseline uptake levels. Conclusion: WM binding increases with age and varies with GM 11C-PiB. These correlations should be considered when using WM for normalization in 11C-PiB PET studies. The cerebellar crus1+crus2 showed no increase with age and cerebellar GM+WM showed minimal increase, supporting their use as reference regions for cross-sectional studies comparing wide age spans. In longitudinal studies, the increase in WM uptake may be minimal in the short-term and thus using WM as a reference region in these studies seems reasonable. However, as participants age, the findings may be affected by changes in WM uptake. Changes in WM 11C-PiB uptake may relate to disease progression, warranting examination of the causes of WM 11C-PiB uptake.

Non-beta-amyloid/tau cerebrospinal fluid markers inform staging and progression in Alzheimer's disease

Background

Alzheimer’s disease (AD) is a complex neurodegenerative disorder characterized by neuropathologic changes involving beta-amyloid (Aβ), tau, neuronal loss, and other associated biological events. While levels of cerebrospinal fluid (CSF) Aβ and tau peptides have enhanced the antemortem detection of AD-specific changes, these two markers poorly reflect the severity of cognitive and functional deficits in people with altered Aβ and tau levels. While multiple previous studies identified non-Aβ, non-tau proteins as candidate neurodegenerative markers to inform the A/T/N biomarker scheme of AD, few have advanced beyond association with clinical AD diagnosis. Here we analyzed nine promising neurodegenerative markers in a three-centered cohort using independent assays to identify candidates most likely to complement Aβ and tau in the A/T/N framework.

Methods

CSF samples from 125 subjects recruited at the three centers were exchanged such that each of the nine previously identified biomarkers can be measured at one of the three centers. Subjects were classified according to cognitive status and CSF AD biomarker profiles as having normal cognition and normal CSF (n = 31), normal cognition and CSF consistent with AD (n = 13), mild cognitive impairment and normal CSF (n = 13), mild cognitive impairment with CSF consistent with AD (n = 23), AD dementia (n = 32; CSF consistent with AD), and other non-AD dementia (n = 13; CSF not consistent with AD).

Results

Three biomarkers were identified to differ among the AD stages, including neurofilament light chain (NfL; p < 0.001), fatty acid binding protein 3 (Fabp3; p < 0.001), and interleukin (IL)-10 (p = 0.033). Increased NfL levels were most strongly associated with the dementia stage of AD, but increased Fabp3 levels were more sensitive to milder AD stages and correlated with both CSF tau markers. IL-10 levels did not correlate with tau biomarkers, but were associated with rates of longitudinal cognitive decline in mild cognitive impairment due to AD (p = 0.006). Prefreezing centrifugation did not influence measured CSF biomarker levels.

Conclusion

CSF proteins associated with AD clinical stages and progression can complement Aβ and tau markers to inform neurodegeneration. A validated panel inclusive of multiple biomarker features (etiology, stage, progression) can improve AD phenotyping along the A/T/N framework.

Amyloid positron emission tomography and cerebrospinal fluid results from a crenezumab anti-amyloid-beta antibody double-blind, placebo-controlled, randomized phase II study in mild-to-moderate Alzheimer's disease (BLAZE)

BACKGROUND

We investigated the effect of crenezumab, a humanized anti-amyloid-beta (Aβ) immunoglobulin (Ig)G4 monoclonal antibody, on biomarkers of amyloid pathology, neurodegeneration, and disease progression in patients with mild-to-moderate Alzheimer's disease (AD).

METHODS

This double-blind, placebo-controlled, randomized phase II study enrolled patients with mild-to-moderate AD and a Mini-Mental State Examination (MMSE) score of 18-26. In part 1 of the study, patients were 2:1 randomized to receive low-dose subcutaneous (SC) 300 mg crenezumab every 2 weeks (q2w) or placebo for 68 weeks; in part 2, patients were 2:1 randomized to receive high-dose intravenous (IV) 15 mg/kg crenezumab every 4 weeks (q4w) or placebo for 68 weeks. The primary endpoint was change in amyloid burden from baseline to week 69 assessed by florbetapir positron emission tomography (PET) in the modified intent-to-treat population. Secondary endpoints were change from baseline to week 69 in cerebrospinal fluid (CSF) biomarkers and fluorodeoxyglucose PET, and change from baseline to week 73 in 12-point Alzheimer's Disease Assessment Scale cognitive subscale (ADAS-Cog12) and Clinical Dementia Rating Sum of Boxes (CDR-SB). Safety was assessed in patients who received at least one dose of study treatment.

RESULTS

From August 2011 to September 2012, 91 patients were enrolled and randomized (low-dose SC cohort: crenezumab (n = 26) or placebo (n = 13); high-dose IV cohort: crenezumab (n = 36) or placebo (n = 16)). The primary endpoint was not met using a prespecified cerebellar reference region to calculate standard uptake value ratios (SUVRs) from florbetapir PET. Exploratory analyses using subcortical white matter reference regions showed nonsignificant trends toward slower accumulation of plaque amyloid in the high-dose IV cohort. In both cohorts, a significant mean increase from baseline in CSF Aβ(1-42) levels versus placebo was observed. Nonsignificant trends toward ADAS-Cog12 and CDR-SB benefits were identified in a mild (MMSE 20-26) subset of the high-dose IV cohort. No amyloid-related imaging abnormalities due to edema/effusion were observed.

CONCLUSION

The primary endpoint was not met. Exploratory findings suggest potential Aβ target engagement with crenezumab and possible slower accumulation of plaque amyloid. Studies investigating the effects of higher doses of crenezumab on amyloid load and disease progression are ongoing.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT01397578 . Registered on 18 July 2011.

Using CT Data to Improve the Quantitative Analysis of 18F-FBB PET Neuroimages

¹⁸F-FBB PET is a neuroimaging modality that is been increasingly used to assess brain amyloid deposits in potential patients with Alzheimer's disease (AD). In this work, we analyze the usefulness of these data to distinguish between AD and non-AD patients. A dataset with ¹⁸F-FBB PET brain images from 94 subjects diagnosed with AD and other disorders was evaluated by means of multiple analyses based on t-test, ANOVA, Fisher Discriminant Analysis and Support Vector Machine (SVM) classification. In addition, we propose to calculate amyloid standardized uptake values (SUVs) using only gray-matter voxels, which can be estimated using Computed Tomography (CT) images. This approach allows assessing potential brain amyloid deposits along with the gray matter loss and takes advantage of the structural information provided by most of the scanners used for PET examination, which allow simultaneous PET and CT data acquisition. The results obtained in this work suggest that SUVs calculated according to the proposed method allow AD and non-AD subjects to be more accurately differentiated than using SUVs calculated with standard approaches.

The Cerebrospinal Fluid Aβ1-42/Aβ1-40 Ratio Improves Concordance with Amyloid-PET for Diagnosing Alzheimer's Disease in a Clinical Setting

Background:

Evidence suggests that the concordance between amyloid-PET and cerebrospinal fluid (CSF) amyloid-β (Aβ) increases when the CSF Aβ_1–42/Aβ_1–40 ratio is used as compared to CSF Aβ_1–42 levels alone.

Objective:

In order to test this hypothesis, we set up a prospective longitudinal study comparing the concordance between different amyloid biomarkers for Alzheimer’s disease (AD) in a clinical setting.

Methods:

Seventy-eight subjects (AD dementia (n = 17), mild cognitive impairment (MCI, n = 48), and cognitively healthy controls (n = 13)) underwent a [¹⁸F]Florbetapir ([¹⁸F]AV45) PET scan, [¹⁸F]FDG PET scan, MRI scan, and an extensive neuropsychological examination. In a large subset (n = 67), a lumbar puncture was performed and AD biomarkers were analyzed (Aβ_1–42, Aβ_1–40, T-tau, P-tau₁₈₁).

Results:

We detected an increased concordance in the visual and quantitative (standardized uptake value ratio (SUVR) and total volume of distribution (V_T)) [¹⁸F]AV45 PET measures when the CSF Aβ_1–42/Aβ_1–40 was applied compared to Aβ_1–42 alone. CSF biomarkers were stronger associated to [¹⁸F]AV45 PET for SUVR values when considering the total brain white matter as reference region instead of cerebellar grey matter

Conclusions:

The concordance between CSF Aβ and [¹⁸F]AV45 PET increases when the CSF Aβ_1–42/Aβ_1–40 ratio is applied. This finding is of most importance for the biomarker-based diagnosis of AD as well as for selection of subjects for clinical trials with potential disease-modifying therapies for AD.

Diagnostic and prognostic value of amyloid PET textural and shape features: comparison with classical semi-quantitative rating in 760 patients from the ADNI-2 database

We evaluated the performance of amyloid PET textural and shape features in discriminating normal and Alzheimer's disease (AD) subjects, and in predicting conversion to AD in subjects with mild cognitive impairment (MCI) or significant memory concern (SMC). Subjects from the Alzheimer's Disease Neuroimaging Initiative with available baseline ¹⁸F-florbetapir and T1-MRI scans were included. The cross-sectional cohort consisted of 181 controls and 148 AD subjects. The longitudinal cohort consisted of 431 SMC/MCI subjects, 85 of whom converted to AD during follow-up. PET images were normalized to MNI space and post-processed using in-house software. Relative retention indices (SUVr) were computed with respect to pontine, cerebellar, and composite reference regions. Several textural and shape features were extracted then combined using a support vector machine (SVM) to build a predictive model of AD conversion. Diagnostic and prognostic performance was evaluated using ROC analysis and survival analysis with the Cox proportional hazard model. The three SUVr and all the tested features effectively discriminated AD subjects in cross-sectional analysis (all p < 0.001). In longitudinal analysis, the variables with the highest prognostic value were composite SUVr (AUC 0.86; accuracy 81%), skewness (0.87; 83%), local minima (0.85; 79%), Geary's index (0.86; 81%), gradient norm maximal argument (0.83; 82%), and the SVM model (0.91; 86%). The adjusted hazard ratio for AD conversion was 5.5 for the SVM model, compared with 4.0, 2.6, and 3.8 for cerebellar, pontine and composite SUVr (all p < 0.001), indicating that appropriate amyloid textural and shape features predict conversion to AD with at least as good accuracy as classical SUVr.

Longitudinal Positron Emission Tomography in Preventive Alzheimer's Disease Drug Trials, Critical Barriers from Imaging Science Perspective

Recent Alzheimer's trials have recruited cognitively normal people at risk for Alzheimer's dementia. Due to the lack of clinical symptoms in normal population, conventional clinical outcome measures are not suitable for these early trials. While several groups are developing new composite cognitive tests that could serve as potential outcome measures by detecting subtle cognitive changes in normal people, there is a need for longitudinal brain imaging techniques that can correlate with temporal changes in these new tests and provide additional objective measures of neuropathological changes in brain. Positron emission tomography (PET) is a nuclear medicine imaging procedure based on the measurement of annihilation photons after positron emission from radiolabeled molecules that allow tracking of biological processes in body, including the brain. PET is a well-established in vivo imaging modality in Alzheimer's disease diagnosis and research due to its capability of detecting abnormalities in three major hallmarks of this disease. These include (1) amyloid beta plaques; (2) neurofibrillary tau tangles and (3) decrease in neuronal activity due to loss of nerve cell connection and death. While semiquantitative PET imaging techniques are commonly used to set discrete cut-points to stratify abnormal levels of amyloid accumulation and neurodegeneration, they are suboptimal for detecting subtle longitudinal changes. In this study, we have identified and discussed four critical barriers in conventional longitudinal PET imaging that may be particularly relevant for early Alzheimer's disease studies. These include within and across subject heterogeneity of AD-affected brain regions, PET intensity normalization, neuronal compensations in early disease stages and cerebrovascular amyloid deposition.

Application of Haralick texture features in brain [18F]-florbetapir positron emission tomography without reference region normalization

Objectives

Semi-quantitative image analysis methods in Alzheimer’s Disease (AD) require normalization of positron emission tomography (PET) images. However, recent studies have found variabilities associated with reference region selection of amyloid PET images. Haralick features (HFs) generated from the Gray Level Co-occurrence Matrix (GLCM) quantify spatial characteristics of amyloid PET radiotracer uptake without the need for intensity normalization. The objective of this study is to calculate several HFs in different diagnostic groups and determine the group differences.

Methods

All image and metadata were acquired through the Alzheimer’s Disease Neuroimaging Initiative database. Subjects were grouped in three ways: by clinical diagnosis, by APOE e4 allele, and by Alzheimer’s Disease Assessment Scale-cognitive subscale (ADAS-Cog) score. Several GLCM matrices were calculated for different direction and distances (1–4 mm) from multiple regions on PET images. The HFs, contrast, correlation, dissimilarity, energy, entropy, and homogeneity, were calculated from these GLCMs. Wilcoxon tests and Student t-tests were performed on Haralick features and standardized uptake value ratio (SUVR) values, respectively, to determine group differences. In addition to statistical testing, receiver operating characteristic (ROC) curves were generated to determine the discrimination performance of the selected regional HFs and the SUVR values.

Results

Preliminary results from statistical testing indicate that HFs were capable of distinguishing groups at baseline and follow-up (false discovery rate corrected p<0.05) in particular regions at much higher occurrences than SUVR (81 of 252). Conversely, we observed nearly no significant differences between all groups within ROIs at baseline or follow-up utilizing SUVR. From the ROC analysis, we found that the Energy and Entropy offered the best performance to distinguish Normal versus mild cognitive impairment and ADAS-Cog negative versus ADAS-Cog positive groups.

Conclusion

These results suggest that this technique could improve subject stratification in AD drug trials and help to evaluate the disease progression and treatment effects longitudinally without the disadvantages associated with intensity normalization.

A simulation study on the impact of the blood flow-dependent component in [18F]AV45 SUVR in Alzheimer's disease

Background

Increased brain uptake on [¹⁸F]AV45 PET is a biomarker for Alzheimer’s disease (AD). The standardised uptake value ratio (SUVR) is widely used for quantification but is subject to variability. Here we evaluate how SUVR of a cortical target region is affected by blood flow changes in the target and two frequently used reference regions.

Methods

Regional baseline time-activity curves (TACs) were simulated based on metabolite-corrected plasma input functions and pharmacokinetic parameters obtained from our previously acquired data in healthy control (HC; n = 10), amnestic mild cognitive impairment (aMCI; n = 15) and AD cohorts (n = 9). Blood flow changes were simulated by altering the regional tracer delivery rate K1 (and clearance rate k2) between -40% and +40% from its regional baseline value in the target region and/or cerebellar grey (CB) or subcortical white matter (WM) reference regions. The corresponding change in SUVR was calculated at 50–60 min post-injection.

Results

A -40% blood flow reduction in the target resulted in an increased SUVR^target (e.g. SUVR^precuneus: +10.0±5% in HC, +2.5±2% in AD), irrespective of the used reference region. A -40% blood flow reduction in the WM reference region increased SUVR_WM (+11.5±4% in HC, +13.5±3% in AD) while a blood flow reduction in CB decreased SUVR_CB (-9.5±6% in HC, -5.5±2% in AD), irrespective of the used target region. A -40% flow reduction in both the precuneus and reference WM (i.e., global flow change) induced an increased SUVR (+22.5±8% in HC, +16.0±4% in AD). When considering reference CB instead, SUVR was decreased by less than -5% (both in HC and AD).

Conclusion

Blood flow changes introduce alterations in [¹⁸F]AV45 PET SUVR. Flow reductions in the CB and WM reference regions resulted in a decreased and increased SUVR of the target, respectively. SUVR was more affected by global blood flow changes when considering WM instead of CB normalization.

18F PET with florbetapir for the early diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI)

BACKGROUND

¹⁸F-florbetapir uptake by brain tissue measured by positron emission tomography (PET) is accepted by regulatory agencies like the Food and Drug Administration (FDA) and the European Medicine Agencies (EMA) for assessing amyloid load in people with dementia. Its added value is mainly demonstrated by excluding Alzheimer's pathology in an established dementia diagnosis. However, the National Institute on Aging and Alzheimer's Association (NIA-AA) revised the diagnostic criteria for Alzheimer's disease and confidence in the diagnosis of mild cognitive impairment (MCI) due to Alzheimer's disease may be increased when using amyloid biomarkers tests like ¹⁸F-florbetapir. These tests, added to the MCI core clinical criteria, might increase the diagnostic test accuracy (DTA) of a testing strategy. However, the DTA of ¹⁸F-florbetapir to predict the progression from MCI to Alzheimer's disease dementia (ADD) or other dementias has not yet been systematically evaluated.

OBJECTIVES

To determine the DTA of the ¹⁸F-florbetapir PET scan for detecting people with MCI at time of performing the test who will clinically progress to ADD, other forms of dementia (non-ADD), or any form of dementia at follow-up.

SEARCH METHODS

This review is current to May 2017. We searched MEDLINE (OvidSP), Embase (OvidSP), PsycINFO (OvidSP), BIOSIS Citation Index (Thomson Reuters Web of Science), Web of Science Core Collection, including the Science Citation Index (Thomson Reuters Web of Science) and the Conference Proceedings Citation Index (Thomson Reuters Web of Science), LILACS (BIREME), CINAHL (EBSCOhost), ClinicalTrials.gov (https://clinicaltrials.gov), and the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP) (http://www.who.int/ictrp/search/en/). We also searched ALOIS, the Cochrane Dementia & Cognitive Improvement Group's specialised register of dementia studies (http://www.medicine.ox.ac.uk/alois/). We checked the reference lists of any relevant studies and systematic reviews, and performed citation tracking using the Science Citation Index to identify any additional relevant studies. No language or date restrictions were applied to the electronic searches.

SELECTION CRITERIA

We included studies that had prospectively defined cohorts with any accepted definition of MCI at time of performing the test and the use of ¹⁸F-florbetapir scan to evaluate the DTA of the progression from MCI to ADD or other forms of dementia. In addition, we only selected studies that applied a reference standard for Alzheimer's dementia diagnosis, for example, National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) or Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV) criteria.

DATA COLLECTION AND ANALYSIS

We screened all titles and abstracts identified in electronic-database searches. Two review authors independently selected studies for inclusion and extracted data to create two-by-two tables, showing the binary test results cross-classified with the binary reference standard. We used these data to calculate sensitivities, specificities, and their 95% confidence intervals. Two independent assessors performed quality assessment using the QUADAS-2 tool plus some additional items to assess the methodological quality of the included studies.

MAIN RESULTS

We included three studies, two of which evaluated the progression from MCI to ADD, and one evaluated the progression from MCI to any form of dementia.Progression from MCI to ADD was evaluated in 448 participants. The studies reported data on 401 participants with 1.6 years of follow-up and in 47 participants with three years of follow-up. Sixty-one (15.2%) participants converted at 1.6 years follow-up; nine (19.1%) participants converted at three years of follow-up.Progression from MCI to any form of dementia was evaluated in five participants with 1.5 years of follow-up, with three (60%) participants converting to any form of dementia.There were concerns regarding applicability in the reference standard in all three studies. Regarding the domain of flow and timing, two studies were considered at high risk of bias. MCI to ADD;Progression from MCI to ADD in those with a follow-up between two to less than four years had a sensitivity of 67% (95% CI 30 to 93) and a specificity of 71% (95% CI 54 to 85) by visual assessment (n = 47, 1 study).Progression from MCI to ADD in those with a follow-up between one to less than two years had a sensitivity of 89% (95% CI 78 to 95) and a specificity of 58% (95% CI 53 to 64) by visual assessment, and a sensitivity of 87% (95% CI 76 to 94) and a specificity of 51% (95% CI 45 to 56) by quantitative assessment by the standardised uptake value ratio (SUVR)(n = 401, 1 study). MCI to any form of dementia;Progression from MCI to any form of dementia in those with a follow-up between one to less than two years had a sensitivity of 67% (95% CI 9 to 99) and a specificity of 50% (95% CI 1 to 99) by visual assessment (n = 5, 1 study). MCI to any other forms of dementia (non-ADD);There was no information regarding the progression from MCI to any other form of dementia (non-ADD).

AUTHORS' CONCLUSIONS

Although sensitivity was good in one included study, considering the poor specificity and the limited data available in the literature, we cannot recommend routine use of ¹⁸F-florbetapir PET in clinical practice to predict the progression from MCI to ADD.Because of the poor sensitivity and specificity, limited number of included participants, and the limited data available in the literature, we cannot recommend its routine use in clinical practice to predict the progression from MCI to any form of dementia.Because of the high financial costs of ¹⁸F-florbetapir, clearly demonstrating the DTA and standardising the process of this modality are important prior to its wider use.

Comparison of CSF markers and semi-quantitative amyloid PET in Alzheimer's disease diagnosis and in cognitive impairment prognosis using the ADNI-2 database

BACKGROUND

The relative performance of semi-quantitative amyloid positron emission tomography (PET) and cerebrospinal fluid (CSF) markers in diagnosing Alzheimer's disease (AD) and predicting the cognitive evolution of patients with mild cognitive impairment (MCI) is still debated.

METHODS

Subjects from the Alzheimer's Disease Neuroimaging Initiative 2 with complete baseline cognitive assessment (Mini Mental State Examination, Clinical Dementia Rating [CDR] and Alzheimer's Disease Assessment Scale-Cognitive Subscale [ADAS-cog] scores), CSF collection (amyloid-β1-42 [Aβ], tau and phosphorylated tau) and 18F-florbetapir scans were included in our cross-sectional cohort. Among these, patients with MCI or substantial memory complaints constituted our longitudinal cohort and were followed for 30 ± 16 months. PET amyloid deposition was quantified using relative retention indices (standardised uptake value ratio [SUVr]) with respect to pontine, cerebellar and composite reference regions. Diagnostic and prognostic performance based on PET and CSF was evaluated using ROC analysis, multivariate linear regression and survival analysis with the Cox proportional hazards model.

RESULTS

The cross-sectional study included 677 participants and revealed that pontine and composite SUVr values were better classifiers (AUC 0.88, diagnostic accuracy 85%) than CSF markers (AUC 0.83 and 0.85, accuracy 80% and 75%, for Aβ and tau, respectively). SUVr was a strong independent determinant of cognition in multivariate regression, whereas Aβ was not; tau was also a determinant, but to a lesser degree. Among the 396 patients from the longitudinal study, 82 (21%) converted to AD within 22 ± 13 months. Optimal SUVr thresholds to differentiate AD converters were quite similar to those of the cross-sectional study. Composite SUVr was the best AD classifier (AUC 0.86, sensitivity 88%, specificity 81%). In multivariate regression, baseline cognition (CDR and ADAS-cog) was the main predictor of subsequent cognitive decline. Pontine and composite SUVr were moderate but independent predictors of final status and CDR/ADAS-cog progression rate, whereas baseline CSF markers had a marginal influence. The adjusted HRs for AD conversion were 3.8 (p = 0.01) for PET profile, 1.2 (p = ns) for Aβ profile and 1.8 (p = 0.03) for tau profile.

CONCLUSIONS

Semi-quantitative amyloid PET appears more powerful than CSF markers for AD grading and MCI prognosis in terms of cognitive decline and AD conversion.

Validation of the Semiquantitative Static SUVR Method for 18F-AV45 PET by Pharmacokinetic Modeling with an Arterial Input Function

Increased brain uptake of ¹⁸F-AV45 visualized by PET is a key biomarker for Alzheimer disease (AD). The SUV ratio (SUVR) is widely used for quantification, but is subject to variability based on choice of reference region and changes in cerebral blood flow. Here we validate the SUVR method against the gold standard volume of distribution (V_T) to assess cross-sectional differences in plaque load. Methods: Dynamic 60-min ¹⁸F-AV45 (291 ± 67 MBq) and 1-min ¹⁵O-H₂O (370 MBq) scans were obtained in 35 age-matched elderly subjects, including 10 probable AD, 15 amnestic mild cognitive impairment (aMCI), and 10 cognitively healthy controls (HCs). ¹⁸F-AV45 V_T was determined from 2-tissue-compartment modeling using a metabolite-corrected plasma input function. Static SUVR was calculated at 50-60 min after injection, using either cerebellar gray matter (SUVR_CB) or whole subcortical white matter (SUVR_WM) as the reference. Additionally, whole cerebellum, pons, centrum semiovale, and a composite region were examined as alternative references. Blood flow was quantified by ¹⁵O-H₂O SUV. Data are presented as mean ± SEM. Results: There was rapid metabolization of ¹⁸F-AV45, with only 35% of unchanged parent remaining at 10 min. Compared with V_T, differences in cortical Aβ load between aMCI and AD were overestimated by SUVR_WM (+4% ± 2%) and underestimated by SUVR_CB (-10% ± 2%). V_T correlated better with SUVR_WM (Pearson r: from 0.63 for posterior cingulate to 0.89 for precuneus, P < 0.0001) than with SUVR_CB (Pearson r: from 0.51 for temporal lobe [P = 0.002] to 0.82 for precuneus [P < 0.0001]) in all tested regions. Correlation results for the alternative references were in between those for CB and WM. ¹⁵O-H₂O data showed that blood flow was decreased in AD compared with aMCI in cortical regions (-5% ± 1%) and in the reference regions (CB, -9% ± 8%; WM, -8% ± 8%). Conclusion: Increased brain uptake of ¹⁸F-AV45 assessed by the simplified static SUVR protocol does not truly reflect Aβ load. However, SUVR_WM is better correlated with V_T and more closely reflects V_T differences between aMCI and AD than SUVR_CB.