Partial-Volume Effect Correction Improves Quantitative Analysis of 18F-Florbetaben β-Amyloid PET Scans

Traumatic brain injury and Alzheimer's Disease biomarkers: A systematic review of findings from amyloid and tau positron emission tomography (PET)

Traumatic brain injury (TBI) has been discussed as a risk factor for Alzheimer's disease (AD) due to its association with dementia risk and earlier cognitive symptom onset. However, the mechanisms behind this relationship are unclear. Some studies have suggested TBI may increase pathological protein deposition in an AD-like pattern; others have failed to find such associations. This review covers literature that uses positron emission tomography (PET) of amyloid-β and/or tau to examine subjects with history of TBI who are at risk for AD due to advanced age. A comprehensive literature search was conducted on January 9, 2023, and 24 resulting citations met inclusion criteria. Common methodological concerns included small samples, limited clinical detail about subjects' TBI, recall bias due to reliance on self-reported TBI, and an inability to establish causation. For both amyloid and tau, results were widespread but inconsistent. The regions which showed the most compelling evidence for increased amyloid deposition were the cingulate gyrus, cuneus/precuneus, and parietal lobe. Evidence for increased tau was strongest in the medial temporal lobe, entorhinal cortex, precuneus, and frontal, temporal, parietal, and occipital lobes. However, conflicting findings across most regions of interest in both amyloid- and tau-PET studies indicate the critical need for future work in expanded samples and with greater clinical detail to offer a clearer picture of the relationship between TBI and protein deposition in older subjects at risk for AD.

Challenges and innovations in brain PET analysis of neurodegenerative disorders: a mini-review on partial volume effects, small brain region studies, and reference region selection

Positron Emission Tomography (PET) brain imaging is increasingly utilized in clinical and research settings due to its unique ability to study biological processes and subtle changes in living subjects. However, PET imaging is not without its limitations. Currently, bias introduced by partial volume effect (PVE) and poor signal-to-noise ratios of some radiotracers can hamper accurate quantification. Technological advancements like ultra-high-resolution scanners and improvements in radiochemistry are on the horizon to address these challenges. This will enable the study of smaller brain regions and may require more sophisticated methods (e.g., data-driven approaches like unsupervised clustering) for reference region selection and to improve quantification accuracy. This review delves into some of these critical aspects of PET molecular imaging and offers suggested strategies for improvement. This will be illustrated by showing examples for dopaminergic and cholinergic nerve terminal ligands.

Prediction of Conversion from Mild Cognitive Impairment to Alzheimer's Disease Using Amyloid PET and Brain MR Imaging Data: A 48-Month Follow-Up Analysis of the Alzheimer's Disease Neuroimaging Initiative Cohort

We developed a novel quantification method named "shape feature" by combining the features of amyloid positron emission tomography (PET) and brain magnetic resonance imaging (MRI) and evaluated its significance in predicting the conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. From the ADNI database, 334 patients with MCI were included. The brain amyloid smoothing score (AV45_BASS) and brain atrophy index (MR_BAI) were calculated using the surface area and volume of the region of interest in AV45 PET and MRI. During the 48-month follow-up period, 108 (32.3%) patients converted from MCI to AD. Age, Mini-Mental State Examination (MMSE), cognitive subscale of the Alzheimer's Disease Assessment Scale (ADAS-cog), apolipoprotein E (APOE), standardized uptake value ratio (SUVR), AV45_BASS, MR_BAI, and shape feature were significantly different between converters and non-converters. Univariate analysis showed that age, MMSE, ADAS-cog, APOE, SUVR, AV45_BASS, MR_BAI, and shape feature were correlated with the conversion to AD. In multivariate analyses, high shape feature, SUVR, and ADAS-cog values were associated with an increased risk of conversion to AD. In patients with MCI in the ADNI cohort, our quantification method was the strongest prognostic factor for predicting their conversion to AD.

Longitudinal amyloid and tau PET imaging in Alzheimer's disease: A systematic review of methodologies and factors affecting quantification

Deposition of amyloid and tau pathology can be quantified in vivo using positron emission tomography (PET). Accurate longitudinal measurements of accumulation from these images are critical for characterizing the start and spread of the disease. However, these measurements are challenging; precision and accuracy can be affected substantially by various sources of errors and variability. This review, supported by a systematic search of the literature, summarizes the current design and methodologies of longitudinal PET studies. Intrinsic, biological causes of variability of the Alzheimer's disease (AD) protein load over time are then detailed. Technical factors contributing to longitudinal PET measurement uncertainty are highlighted, followed by suggestions for mitigating these factors, including possible techniques that leverage shared information between serial scans. Controlling for intrinsic variability and reducing measurement uncertainty in longitudinal PET pipelines will provide more accurate and precise markers of disease evolution, improve clinical trial design, and aid therapy response monitoring.

International Nuclear Medicine Consensus on the Clinical Use of Amyloid Positron Emission Tomography in Alzheimer's Disease

Alzheimer's disease (AD) is the main cause of dementia, with its diagnosis and management remaining challenging. Amyloid positron emission tomography (PET) has become increasingly important in medical practice for patients with AD. To integrate and update previous guidelines in the field, a task group of experts of several disciplines from multiple countries was assembled, and they revised and approved the content related to the application of amyloid PET in the medical settings of cognitively impaired individuals, focusing on clinical scenarios, patient preparation, administered activities, as well as image acquisition, processing, interpretation and reporting. In addition, expert opinions, practices, and protocols of prominent research institutions performing research on amyloid PET of dementia are integrated. With the increasing availability of amyloid PET imaging, a complete and standard pipeline for the entire examination process is essential for clinical practice. This international consensus and practice guideline will help to promote proper clinical use of amyloid PET imaging in patients with AD.

A cycle-consistent adversarial network for brain PET partial volume correction without prior anatomical information

PURPOSE

Partial volume effect (PVE) is a consequence of the limited spatial resolution of PET scanners. PVE can cause the intensity values of a particular voxel to be underestimated or overestimated due to the effect of surrounding tracer uptake. We propose a novel partial volume correction (PVC) technique to overcome the adverse effects of PVE on PET images.

METHODS

Two hundred and twelve clinical brain PET scans, including 50 18F-Fluorodeoxyglucose (18F-FDG), 50 18F-Flortaucipir, 36 18F-Flutemetamol, and 76 18F-FluoroDOPA, and their corresponding T1-weighted MR images were enrolled in this study. The Iterative Yang technique was used for PVC as a reference or surrogate of the ground truth for evaluation. A cycle-consistent adversarial network (CycleGAN) was trained to directly map non-PVC PET images to PVC PET images. Quantitative analysis using various metrics, including structural similarity index (SSIM), root mean squared error (RMSE), and peak signal-to-noise ratio (PSNR), was performed. Furthermore, voxel-wise and region-wise-based correlations of activity concentration between the predicted and reference images were evaluated through joint histogram and Bland and Altman analysis. In addition, radiomic analysis was performed by calculating 20 radiomic features within 83 brain regions. Finally, a voxel-wise two-sample t-test was used to compare the predicted PVC PET images with reference PVC images for each radiotracer.

RESULTS

The Bland and Altman analysis showed the largest and smallest variance for 18F-FDG (95% CI: - 0.29, + 0.33 SUV, mean = 0.02 SUV) and 18F-Flutemetamol (95% CI: - 0.26, + 0.24 SUV, mean =  - 0.01 SUV), respectively. The PSNR was lowest (29.64 ± 1.13 dB) for 18F-FDG and highest (36.01 ± 3.26 dB) for 18F-Flutemetamol. The smallest and largest SSIM were achieved for 18F-FDG (0.93 ± 0.01) and 18F-Flutemetamol (0.97 ± 0.01), respectively. The average relative error for the kurtosis radiomic feature was 3.32%, 9.39%, 4.17%, and 4.55%, while it was 4.74%, 8.80%, 7.27%, and 6.81% for NGLDM_contrast feature for 18F-Flutemetamol, 18F-FluoroDOPA, 18F-FDG, and 18F-Flortaucipir, respectively.

CONCLUSION

An end-to-end CycleGAN PVC method was developed and evaluated. Our model generates PVC images from the original non-PVC PET images without requiring additional anatomical information, such as MRI or CT. Our model eliminates the need for accurate registration or segmentation or PET scanner system response characterization. In addition, no assumptions regarding anatomical structure size, homogeneity, boundary, or background level are required.

Symptomatology in 4-repeat tauopathies is associated with data-driven topology of [18F]-PI-2620 tau-PET signal

In recent years in vivo visualization of tau deposits has become possible with various PET radiotracers. The tau tracer [18F]PI-2620 proved high affinity both to 3-repeat/4-repeat tau in Alzheimer's disease as well as to 4-repeat tau in progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS). However, to be clinically relevant, biomarkers should not only correlate with pathological changes but also with disease stage and progression. Therefore, we aimed to investigate the correlation between topology of [18F]PI-2620 uptake and symptomatology in 4-repeat tauopathies. 72 patients with possible or probable 4-repeat tauopathy, i.e. 31 patients with PSP-Richardson's syndrome (PSP-RS), 30 with amyloid-negative CBS and 11 with PSP-non-RS/CBS, underwent [18F]PI-2620-PET. Principal component analysis was performed to identify groups of similar brain regions based on 20-40 min p.i. regional standardized uptake value ratio z-scores. Correlations between component scores and the items of the PSP Rating Scale were explored. Motor signs like gait, arising from chair and postural instability showed a positive correlation with tracer uptake in mesial frontoparietal lobes and the medial superior frontal gyrus and adjacent anterior cingulate cortex. While the signs disorientation and bradyphrenia showed a positive correlation with tracer uptake in the parietooccipital junction, the signs disorientation and arising from chair were negatively correlated with tau-PET signal in the caudate nucleus and thalamus. Total PSP Rating Scale Score showed a trend towards a positive correlation with mesial frontoparietal lobes and a negative correlation with caudate nucleus and thalamus. While in CBS patients, the main finding was a negative correlation of tracer binding in the caudate nucleus and thalamus and a positive correlation of tracer binding in medial frontal cortex with gait and motor signs, in PSP-RS patients various correlations of clinical signs with tracer binding in specific cerebral regions could be detected. Our data reveal [18F]PI-2620 tau-PET topology to correlate with symptomatology in 4-repeat tauopathies. Longitudinal studies will be needed to address whether a deterioration of signs and symptoms over time can be monitored by [18F]PI-2620 in 4-repeat tauopathies and whether [18F]PI-2620 may serve as a marker of disease progression in future therapeutic trials. The detected negative correlation of tracer binding in the caudate nucleus and thalamus with the signs disorientation and arising from chair may be due to an increasing atrophy in these regions leading to partial volume effects and a relative decrease of tracer uptake in the disease course. As cerebral regions correlating with symptomatology differ depending on the clinical phenotype, a precise knowledge of clinical signs and symptoms is necessary when interpreting [18F]PI-2620 PET results.

A PET-CT study on neuroinflammation in Huntington's disease patients participating in a randomized trial with laquinimod

Microglia activation, an indicator of central nervous system inflammation, is believed to contribute to the pathology of Huntington's disease. Laquinimod is capable of regulating microglia. By targeting the translocator protein, 11C-PBR28 PET-CT imaging can be used to assess the state of regional gliosis in vivo and explore the effects of laquinimod treatment. This study relates to the LEGATO-HD, multi-centre, double-blinded, Phase 2 clinical trial with laquinimod (US National Registration: NCT02215616). Fifteen patients of the UK LEGATO-HD cohort (mean age: 45.2 ± 7.4 years; disease duration: 5.6 ± 3.0 years) were treated with laquinimod (0.5 mg, N = 4; 1.0 mg, N = 6) or placebo (N = 5) daily. All participants had one 11C-PBR28 PET-CT and one brain MRI scan before laquinimod (or placebo) and at the end of treatment (12 months apart). PET imaging data were quantified to produce 11C-PBR28 distribution volume ratios. These ratios were calculated for the caudate and putamen using the reference Logan plot with the corpus callosum as the reference region. Partial volume effect corrections (Müller-Gartner algorithm) were applied. Differences were sought in Unified Huntington's Disease Rating Scale scores and regional distribution volume ratios between baseline and follow-up and between the two treatment groups (laquinimod versus placebo). No significant change in 11C-PBR28 distribution volume ratios was found post treatment in the caudate and putamen for both those treated with laquinimod (N = 10) and those treated with placebo (N = 5). Over time, the patients treated with laquinimod did not show a significant clinical improvement. Data from the 11C-PBR28 PET-CT study indicate that laquinimod may not have affected regional translocator protein expression and clinical performance over the studied period.

Semiquantitative Approach to Amyloid Positron Emission Tomography Interpretation in Clinical Practice

Objective  Amyloid positron emission tomography (PET) plays a vital role in the in vivo detection of β-amyloid accumulation in Alzheimer's disease. Increasingly, trainees and infrequent readers are relying on semiquantitative analyses to support clinical diagnostic efforts. Our objective was to determine if the visual assessment of amyloid PET may be facilitated by relying on semiquantitative analysis. Methods  We conducted a retrospective review of [ ¹⁸ F]-florbetaben PET/computed tomographies (CTs) from 2016 to 2018. Visual interpretation to determine Aβ+ status was conducted by two readers blinded to each other's interpretation. Scans were then post-processed utilizing the MIMneuro software, which generated regional-based semiquantitative Z-scores indicating cortical Aβ-burden. Results  Of 167 [ ¹⁸ F]-florbetaben PET/CTs, 92/167 (reader-1) and 101/167 (reader-2) were positive for amyloid deposition (agreement = 92.2%, κ = 0.84). Additional nine scans were identified as possible Aβ-positive based solely on semiquantitative analyses. Largest semiquantitative differences were identified in the left frontal lobe (Z = 7.74 in Aβ + ; 0.50 in Aβ - ). All unilateral regions showed large statistically significant differences in Aβ-burden ( P ≤ 2.08E-28). Semiquantitative scores were highly sensitive to Aβ+ status and accurate in their ability to identify amyloid positivity, defined as a positive scan by both readers (AUC ≥ 0.90 [0.79-1.00]). Spread analyses suggested that amyloid deposition was most severe in the left posterior cingulate gyrus. The largest differences between Aβ +/Aβ- were in the left frontal lobe. Analyses using region-specific cutoffs indicated that the presence of amyloid in the temporal and anterior cingulate cortex, while exhibiting relatively low Z-scores, was most common. Conclusion  Visual assessment and semiquantitative analysis provide highly congruent results, thereby enhancing reader confidence and improving scan interpretation. This is particularly relevant, given recent advances in amyloid-targeting disease-modifying therapeutics.

High-resolution and high-sensitivity PET for quantitative molecular imaging of the monoaminergic nuclei: A GATE simulation study

PURPOSE

Quantitative in vivo molecular imaging of fine brain structures requires high-spatial resolution and high-sensitivity. Positron emission tomography (PET) is an attractive candidate to introduce molecular imaging into standard clinical care due to its highly targeted and versatile imaging capabilities based on the radiotracer being used. However, PET suffers from relatively poor spatial resolution compared to other clinical imaging modalities, which limits its ability to accurately quantify radiotracer uptake in brain regions and nuclei smaller than 3 mm in diameter. Here we introduce a new practical and cost-effective high-resolution and high-sensitivity brain-dedicated PET scanner, using our depth-encoding Prism-PET detector modules arranged in a conformal decagon geometry, to substantially reduce the partial volume effect and enable accurate radiotracer uptake quantification in small subcortical nuclei.

METHODS

Two Prism-PET brain scanner setups were proposed based on our 4-to-1 and 9-to-1 coupling of scintillators to readout pixels using1.5 × 1.5 × 20 $1.5 \times 1.5 \times 20$  mm3 and0.987 × 0.987 × 20 $0.987 \times 0.987 \times 20$  mm3 crystal columns, respectively. Monte Carlo simulations of our Prism-PET scanners, Siemens Biograph Vision, and United Imaging EXPLORER were performed using Geant4 application for tomographic emission (GATE). National Electrical Manufacturers Association (NEMA) standard was followed for the evaluation of spatial resolution, sensitivity, and count-rate performance. An ultra-micro hot spot phantom was simulated for assessing image quality. A modified Zubal brain phantom was utilized for radiotracer imaging simulations of 5-HT1A receptors, which are abundant in the raphe nuclei (RN), and norepinephrine transporters, which are highly concentrated in the bilateral locus coeruleus (LC).

RESULTS

The Prism-PET brain scanner with 1.5 mm crystals is superior to that with 1 mm crystals as the former offers better depth-of-interaction (DOI) resolution, which is key to realizing compact and conformal PET scanner geometries. We achieved uniform 1.3 mm full-width-at-half-maximum (FWHM) spatial resolutions across the entire transaxial field-of-view (FOV), a NEMA sensitivity of 52.1 kcps/MBq, and a peak noise equivalent count rate (NECR) of 957.8 kcps at 25.2 kBq/mL using 450-650 keV energy window. Hot spot phantom results demonstrate that our scanner can resolve regions as small as 1.35 mm in diameter at both center and 10 cm away from the center of the transaixal FOV. Both 5-HT1A receptor and norepinephrine transporter brain simulations prove that our Prism-PET scanner enables accurate quantification of radiotracer uptake in small brain regions, with a 1.8-fold and 2.6-fold improvement in the dorsal RN as well as a 3.2-fold and 4.4-fold improvement in the bilateral LC compared to the Biograph Vision and EXPLORER, respectively.

CONCLUSIONS

Based on our simulation results, the proposed high-resolution and high-sensitivity Prism-PET brain scanner is a promising cost-effective candidate to achieve quantitative molecular neuroimaging of small but important brain regions with PET clinically viable.

Impact of Partial Volume Correction on [18F]GE-180 PET Quantification in Subcortical Brain Regions of Patients with Corticobasal Syndrome

Corticobasal syndrome (CBS) is a rare neurodegenerative condition characterized by four-repeat tau aggregation in the cortical and subcortical brain regions and accompanied by severe atrophy. The aim of this study was to evaluate partial volume effect correction (PVEC) in patients with CBS compared to a control cohort imaged with the 18-kDa translocator protein (TSPO) positron emission tomography (PET) tracer [¹⁸F]GE-180. Eighteen patients with CBS and 12 age- and sex-matched healthy controls underwent [¹⁸F]GE-180 PET. The cortical and subcortical regions were delineated by deep nuclei parcellation (DNP) of a 3D-T1 MRI. Region-specific subcortical volumes and standardized uptake values and ratios (SUV and SUVr) were extracted before and after region-based voxel-wise PVEC. Regional volumes were compared between patients with CBS and controls. The % group differences and effect sizes (CBS vs. controls) of uncorrected and PVE-corrected SUVr data were compared. Single-region positivity in patients with CBS was assessed by a >2 SD threshold vs. controls and compared between uncorrected and PVE-corrected data. Smaller regional volumes were detected in patients with CBS compared to controls in the right ventral striatum (p = 0.041), the left putamen (p = 0.005), the right putamen (p = 0.038) and the left pallidum (p = 0.015). After applying PVEC, the % group differences were distinctly higher, but the effect sizes of TSPO uptake were only slightly stronger due to the higher variance after PVEC. The single-region positivity of TSPO PET increased in patients with CBS after PVEC (100 vs. 83 regions). PVEC in the cortical and subcortical regions is valuable for TSPO imaging of patients with CBS, leading to the improved detection of elevated [¹⁸F]GE-180 uptake, although the effect sizes in the comparison against the controls did not improve strongly.

Partial Volume Correction Increases the Sensitivity of 18F-Florbetapir-Positron Emission Tomography for the Detection of Early Stage Amyloidosis

Purpose: To test whether correcting for unspecific signal from the cerebral white matter increases the sensitivity of amyloid-PET for early stages of cerebral amyloidosis.

Methods: We analyzed 18F-Florbetapir-PET and cerebrospinal fluid (CSF) Aβ42 data from 600 older individuals enrolled in the Alzheimer’s Disease Neuroimaging Initiative (ADNI), including people with normal cognition, mild cognitive impairment (MCI), and Alzheimer’s disease (AD) dementia. We determined whether three compartmental partial volume correction (PVC-3), explicitly modeling signal spill-in from white matter, significantly improved the association of CSF Aβ42 levels with global 18F-Florbetapir-PET values compared with standard processing without PVC (non-PVC) and a widely used two-compartmental PVC method (PVC-2). In additional voxel-wise analyses, we determined the sensitivity of PVC-3 compared with non-PVC and PVC-2 for detecting early regional amyloid build-up as modeled by decreasing CSF Aβ42 levels. For replication, we included an independent sample of 43 older individuals with subjective memory complaints from the INveStIGation of AlzHeimer’s PredicTors cohort (INSIGHT-preAD study).

Results: In the ADNI sample, PVC-3 18F-Florbetapir-PET values normalized to whole cerebellum signal showed significantly stronger associations with CSF Aβ42 levels than non-PVC or PVC-2, particularly in the lower range of amyloid levels. These effects were replicated in the INSIGHT-preAD sample. PVC-3 18F-Florbetapir-PET data detected regional amyloid build-up already at higher (less abnormal) CSF Aβ42 levels than non-PVC or PVC-2 data.

Conclusion: A PVC approach that explicitly models unspecific white matter binding improves the sensitivity of amyloid-PET for identifying the earliest stages of cerebral amyloid pathology which has implications for future primary prevention trials.

Simple Quantification of Surface Uptake in F-18 Florapronol PET/CT Imaging for the Validation of Alzheimer’s Disease

We developed a novel quantification method named shape feature using F-18 florapronol positron emission tomography–computed tomography (PET/CT) and evaluated its sensitivity and specificity for discriminating between patients with Alzheimer’s disease (AD) and patients with mild cognitive impairment or other precursors dementia (non-AD). We calculated the cerebral amyloid smoothing score (CASS) and brain atrophy index (BAI) using the surface area and volume of the region of interest in PET images. We calculated gray and white matter from trained CT data, prepared using U-net. Shape feature was calculated by multiplying CASS with BAI scores. We measured region-based standard uptake values (SUVr) and performed receiver operating characteristic (ROC) analysis to compare SUVr, shape feature, CASS, and BAI score. We investigated the relationship between shape feature and neuropsychological tests. Fifty subjects (23 with AD and 27 with non-AD) were evaluated. SUVr, shape feature, CASS, and BAI score were significantly higher in patients with AD than in those with non-AD. There was no statistically significant difference between shape feature and SUVr in ROC analysis. Shape feature correlated well with mini-mental state examination scores. Shape feature can effectively quantify beta-amyloid deposition and atrophic changes in the brain. These results suggest that shape feature is useful in the diagnosis of AD.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Characterization of point-spread function specification error on Geometric Transfer Matrix partial volume correction in [11C]PiB amyloid imaging

Purpose

Partial-volume correction (PVC) using the Geometric Transfer Matrix (GTM) method is used in positron emission tomography (PET) to compensate for the effects of spatial resolution on quantitation. We evaluate the effect of misspecification of scanner point-spread function (PSF) on GTM results in amyloid imaging, including the effect on amyloid status classification (positive or negative).

Methods

Twenty-nine subjects with Pittsburgh Compound B ([¹¹C]PiB) PET and structural T1 MR imaging were analyzed. FreeSurfer 5.3 (FS) was used to parcellate MR images into regions-of-interest (ROIs) that were used to extract radioactivity concentration values from the PET images. GTM PVC was performed using our “standard” PSF parameterization [3D Gaussian, full-width at half-maximum (w) of approximately 5 mm]. Additional GTM PVC was performed with “incorrect” parameterizations, taken around the correct value. The result is a set of regional activity values for each of the GTM applications. For each case, activity values from various ROIs were combined and normalized to produce standardized uptake value ratios (SUVRs) for nine standard [¹¹C]PiB quantitation ROIs and a global region. GTM operating-point characteristics were determined from the slope of apparent SUVR versus w curves.

Results

Errors in specification of w on the order of 1 mm (3D) mainly produce only modest errors of up to a few percent. An exception was the anterior ventral striatum in which fractional errors of up to 0.29 per millimeter (3D) of error in w were observed.

Conclusion

While this study does not address all the issues regarding the quantitative strengths and weakness of GTM PVC, we find that with reasonable caution, the unavoidable inaccuracies associated with PSF specification do not preclude its use in amyloid quantitation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40658-021-00403-5.

Association of Tau Pathology With Clinical Symptoms in the Subfields of Hippocampal Formation

Objective: To delineate the relationship between clinical symptoms and tauopathy of the hippocampal subfields under different amyloid statuses. Methods: One hundred and forty-three subjects were obtained from the ADNI project, including 87 individuals with normal cognition, 46 with mild cognitive impairment, and 10 with Alzheimer's disease (AD). All subjects underwent the tau PET, amyloid PET, T1W, and high-resolution T2W scans. Clinical symptoms were assessed by the Neuropsychiatric Inventory (NPI) total score and Alzheimer's Disease Assessment Scale cognition 13 (ADAS-cog-13) total score, comprising memory and executive function scores. The hippocampal subfields including Cornu Ammonis (CA1-3), subiculum (Sub), and dentate gyrus (DG), as well as the adjacent para-hippocampus (PHC) and entorhinal cortex (ERC), were segmented automatically using the Automatic Segmentation of Hippocampal Subfields (ASHS) software. The relationship between tauopathy/volume of the hippocampal subfields and assessment scores was calculated using partial correlation analysis under different amyloid status, by controlling age, gender, education, apolipoprotein E (APOE) allele ɛ4 carrier status, and, time interval between the acquisition time of tau PET and amyloid PET scans. Results: Compared with amyloid negative (A-) group, individuals from amyloid positive (A+) group are more impaired based on the Mini-mental State Examination (MMSE; p = 3.82e-05), memory (p = 6.30e-04), executive function (p = 0.0016), and ADAS-cog-13 scores (p = 5.11e-04). Significant decrease of volume (CA1, DG, and Sub) and increase of tau deposition (CA1, Sub, ERC, and PHC) of the hippocampal subfields of both hemispheres were observed for the A+ group compared to the A- group. Tauopathy of ERC is significantly associated with memory score for the A- group, and the associated regions spread into Sub and PHC for the A+ group. The relationship between the impairment of behavior or executive function and tauopathy of the hippocampal subfield was discovered within the A+ group. Leftward asymmetry was observed with the association between assessment scores and tauopathy of the hippocampal subfield, which is more prominent for the NPI score for the A+ group. Conclusion: The associations of tauopathy/volume of the hippocampal subfields with clinical symptoms provide additional insight into the understanding of local changes of the human HF during the AD continuum and can be used as a reference for future studies.

Metabolic and amyloid PET network reorganization in Alzheimer's disease: differential patterns and partial volume effects

Alzheimer’s disease (AD) is a neurodegenerative disorder, considered a disconnection syndrome with regional molecular pattern abnormalities quantifiable by the aid of PET imaging. Solutions for accurate quantification of network dysfunction are scarce. We evaluate the extent to which PET molecular markers reflect quantifiable network metrics derived through the graph theory framework and how partial volume effects (PVE)-correction (PVEc) affects these PET-derived metrics 75 AD patients and 126 cognitively normal older subjects (CN). Therefore our goal is twofold: 1) to evaluate the differential patterns of [¹⁸F]FDG- and [¹⁸F]AV45-PET data to depict AD pathology; and ii) to analyse the effects of PVEc on global uptake measures of [¹⁸F]FDG- and [¹⁸F]AV45-PET data and their derived covariance network reconstructions for differentiating between patients and normal older subjects. Network organization patterns were assessed using graph theory in terms of “degree”, “modularity”, and “efficiency”. PVEc evidenced effects on global uptake measures that are specific to either [¹⁸F]FDG- or [¹⁸F]AV45-PET, leading to increased statistical differences between the groups. PVEc was further shown to influence the topological characterization of PET-derived covariance brain networks, leading to an optimised characterization of network efficiency and modularisation. Partial-volume effects correction improves the interpretability of PET data in AD and leads to optimised characterization of network properties for organisation or disconnection.

Uncertainty analysis of MR-PET image registration for precision neuro-PET imaging

Accurate regional brain quantitative PET measurements, particularly when using partial volume correction, rely on robust image registration between PET and MR images. We argue here that the precision, and hence the uncertainty, of MR-PET image registration is mainly driven by the registration implementation and the quality of PET images due to their lower resolution and higher noise compared to the structural MR images. We propose a dedicated uncertainty analysis for quantifying the precision of MR-PET registration, centred around the bootstrap resampling of PET list-mode events to generate multiple PET image realisations with different noise (count) levels. The effects of PET image reconstruction parameters, such as the use of attenuation and scatter corrections and different number of iterations, on the precision and accuracy of MR-PET registration were investigated. In addition, the performance of four software packages with their default settings for rigid inter-modality image registration were considered: NiftyReg, Vinci, FSL and SPM. Four distinct PET image distributions made of two early time frames (similar to cortical FDG) and two late frames using two amyloid PET dynamic acquisitions of one amyloid positive and one amyloid negative participants were investigated. For the investigated four PET frames, the biggest impact on the uncertainty was observed between registration software packages (up to 10-fold difference in precision) followed by the reconstruction parameters. On average, the lowest uncertainty for different PET frames and brain regions was observed with SPM and two iterations of fully quantitative image reconstruction. The observed uncertainty for the varying PET count-level (from 5% to 60%) was slightly lower than for the reconstruction parameters. We also observed that the registration uncertainty in quantitative PET analysis depends on amyloid status of the considered PET frames, with increased uncertainty (up to three times) when using post-reconstruction partial volume correction. This analysis is applicable for PET data obtained from either PET/MR or PET/CT scanners.

A Role of PET/MR Imaging in Dementia?

Since many years, magnetic resonance imaging (MRI) and positron emission tomography (PET) have a prominent role in neurodegenerative disorders and dementia, not only in a research setting but also in a clinical setting. For several decades, information from both modalities is combined ranging from individual visual assessments to fully integrating all images. Several tools are available to coregister images from MRI and PET and to covisualize these images. When studying neurodegenerative disorders with PET it is important to perform a partial volume correction and this can be done using the structural information obtained by MRI. With the advent of PET/MR, the question arises in how far this hybrid imaging modality is an added value compared to combining PET and MRI data from two separate modalities. One issue in PET/MR is still not yet completely settled, that is, the attenuation correction. This is of less importance for visual assessments but it can become an issue when combining data from PET/CT and PET/MR scanners in multicenter studies or when using cut-off values to classify patients. Simultaneous imaging has clearly some advantages: for the patient it is beneficial to have only one scan session instead of two but also in cases in which PET data are related to functional of physiological data acquired with MRI (such as functional MRI or arterial spin labeling). However, the most important benefit is currently the more integrated use of PET and MRI. This is also possible with separate measurements but requires more streamlining of the whole process. In that case coregistration of images is mandatory. It needs to be determined in which cases simultaneous PET/MRI leads to new insights or improved diagnosis compared to multimodal imaging using dedicated scanners.

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.

Iterative framework for image registration and partial volume correction in brain positron emission tomography

Imprecise registration between positron emission tomography (PET) and anatomical magnetic resonance (MR) images is a critical source of error in MR imaging-guided partial volume correction (MR-PVC). Here, we propose a novel framework for image registration and partial volume correction, which we term PVC-optimized registration (PoR), to address imprecise registration. The PoR framework iterates PVC and registration between uncorrected PET and smoothed PV-corrected images to obtain precise registration. We applied PoR to the [¹¹C]PiB PET data of 92 participants obtained from the Alzheimer’s Disease Neuroimaging Initiative database and compared the registration results, PV-corrected standardized uptake value (SUV) and its ratio to the cerebellum (SUVR), and intra-region coefficient of variation (CoV) between PoR and conventional registration. Significant differences in registration of as much as 2.74 mm and 3.02° were observed between the two methods (effect size <  − 0.8 or > 0.8), which resulted in considerable SUVR differences throughout the brain, reaching a maximal difference of 62.3% in the sensory motor cortex. Intra-region CoV was significantly reduced using the PoR throughout the brain. These results suggest that PoR reduces error as a result of imprecise registration in PVC and is a useful method for accurately quantifying the amyloid burden in PET.

Error propagation analysis of seven partial volume correction algorithms for [18F]THK-5351 brain PET imaging

BACKGROUND

Novel partial volume correction (PVC) algorithms have been validated by assuming ideal conditions of image processing; however, in real clinical PET studies, the input datasets include error sources which cause error propagation to the corrected outcome.

METHODS

We aimed to evaluate error propagations of seven PVCs algorithms for brain PET imaging with [¹⁸F]THK-5351 and to discuss the reliability of those algorithms for clinical applications. In order to mimic brain PET imaging of [¹⁸F]THK-5351, pseudo-observed SUVR images for one healthy adult and one adult with Alzheimer's disease were simulated from individual PET and MR images. The partial volume effect of pseudo-observed PET images were corrected by using Müller-Gärtner (MG), the geometric transfer matrix (GTM), Labbé (LABBE), regional voxel-based (RBV), iterative Yang (IY), structural functional synergy for resolution recovery (SFS-RR), and modified SFS-RR algorithms with incorporation of error sources in the datasets for PVC processing. Assumed error sources were mismatched FWHM, inaccurate image-registration, and incorrectly segmented anatomical volume. The degree of error propagations in ROI values was evaluated by percent differences (%diff) of PV-corrected SUVR against true SUVR.

RESULTS

Uncorrected SUVRs were underestimated against true SUVRs (- 15.7 and - 53.7% in hippocampus for HC and AD conditions), and application of each PVC algorithm reduced the %diff. Larger FWHM mismatch led to larger %diff of PVC-SUVRs against true SUVRs for all algorithms. Inaccurate image registration showed systematic propagation for most algorithms except for SFS-RR and modified SFS-RR. Incorrect segmentation of the anatomical volume only resulted in error propagations in limited local regions.

CONCLUSIONS

We demonstrated error propagation by numerical simulation of THK-PET imaging. Error propagations of 7 PVC algorithms for brain PET imaging with [¹⁸F]THK-5351 were significant. Robust algorithms for clinical applications must be carefully selected according to the study design of clinical PET data.

Multi-slice representational learning of convolutional neural network for Alzheimer's disease classification using positron emission tomography

BACKGROUND

Alzheimer's Disease (AD) is a degenerative brain disorder that often occurs in people over 65 years old. As advanced AD is difficult to manage, accurate diagnosis of the disorder is critical. Previous studies have revealed effective deep learning methods of classification. However, deep learning methods require a large number of image datasets. Moreover, medical images are affected by various environmental factors. In the current study, we propose a deep learning-based method for diagnosis of Alzheimer's disease (AD) that is less sensitive to different datasets for external validation, based upon F-18 fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT).

RESULTS

The accuracy, sensitivity, and specificity of our proposed network were 86.09%, 80.00%, and 92.96% (respectively) using our dataset, and 91.02%, 87.93%, and 93.57% (respectively) using the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. We observed that our model classified AD and normal cognitive (NC) cases based on the posterior cingulate cortex (PCC), where pathological changes occur in AD. The performance of the GAP layer was considered statistically significant compared to the fully connected layer in both datasets for accuracy, sensitivity, and specificity (p < 0.01). In addition, performance comparison between the ADNI dataset and our dataset showed no statistically significant differences in accuracy, sensitivity, and specificity (p > 0.05).

CONCLUSIONS

The proposed model demonstrated the effectiveness of AD classification using the GAP layer. Our model learned the AD features from PCC in both the ADNI and Severance datasets, which can be seen in the heatmap. Furthermore, we showed that there were no significant differences in performance using statistical analysis.

Longitudinal validity of PET-based staging of regional amyloid deposition

Positron emission tomography (PET)-based staging of regional amyloid deposition has recently emerged as a promising tool for sensitive detection and stratification of pathology progression in Alzheimer's Disease (AD). Here we present an updated methodological framework for PET-based amyloid staging using region-specific amyloid-positivity thresholds and assess its longitudinal validity using serial PET acquisitions. We defined region-specific thresholds of amyloid-positivity based on Florbetapir-PET data of 13 young healthy individuals (age ≤ 45y), applied these thresholds to Florbetapir-PET data of 179 cognitively normal older individuals to estimate a regional amyloid staging model, and tested this model in a larger sample of patients with mild cognitive impairment (N = 403) and AD dementia (N = 85). 2-year follow-up Florbetapir-PET scans from a subset of this sample (N = 436) were used to assess the longitudinal validity of the cross-sectional model based on individual stage transitions and data-driven longitudinal trajectory modeling. Results show a remarkable congruence between cross-sectionally estimated and longitudinally modeled trajectories of amyloid accumulation, beginning in anterior temporal areas, followed by frontal and medial parietal areas, the remaining associative neocortex, and finally primary sensory-motor areas and subcortical regions. Over 98% of individual amyloid deposition profiles and longitudinal stage transitions adhered to this staging scheme of regional pathology progression, which was further supported by corresponding changes in cerebrospinal fluid biomarkers. In conclusion, we provide a methodological refinement and longitudinal validation of PET-based staging of regional amyloid accumulation, which may help improving early detection and in-vivo stratification of pathologic disease progression in AD.

Reshaping the Amyloid Buildup Curve in Alzheimer Disease? Partial-Volume Effect Correction of Longitudinal Amyloid PET Data

It was hypothesized that the brain β-amyloid buildup curve plateaus at an early symptomatic stage of Alzheimer disease (AD). Atrophy-related partial-volume effects (PVEs) degrade signal in hot-spot imaging techniques such as amyloid PET. The current study, a longitudinal analysis of amyloid-sensitive PET data, investigated the effect on the shape of the β-amyloid curve in AD when PVE correction (PVEC) is applied. Methods: We analyzed baseline and 2-y follow-up data for 216 symptomatic individuals on the AD continuum (positive amyloid status) enrolled in the Alzheimer's Disease Neuroimaging Initiative (17 with AD dementia and 199 with mild cognitive impairment), including ¹⁸F-florbetapir PET, MRI, and Mini Mental State Examination scores. For PVEC, the modified Müller-Gärtner method was performed. Results: Compared with non-PVE-corrected data, PVE-corrected data yielded significantly higher changes in regional and composite SUV ratio (SUVR) over time (P = 0.0002 for composite SUVRs). Longitudinal SUVR changes in relation to Mini Mental State Examination decreases showed a significantly higher slope for the regression line in the PVE-corrected than in the non-PVE-corrected PET data (F ₁ = 7.1, P = 0.008). Conclusion: These PVEC results indicate that the β-amyloid buildup curve does not plateau at an early symptomatic disease stage. A further evaluation of the impact of PVEC on the in vivo characterization of time-dependent AD pathology, including the reliable assessment and comparison of other amyloid tracers, is warranted.

Spill-in counts in the quantification of 18F-florbetapir on Aβ-negative subjects: the effect of including white matter in the reference region

Background

We aim to provide a systematic study of the impact of white matter (WM) spill-in on the calculation of standardized uptake value ratios (SUVRs) on Aβ-negative subjects, and we study the effect of including WM in the reference region as a compensation. In addition, different partial volume correction (PVC) methods are applied and evaluated.

Methods

We evaluated magnetic resonance imaging and ¹⁸F-AV-45 positron emission tomography data from 122 cognitively normal (CN) patients recruited at the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Cortex SUVRs were obtained by using the cerebellar grey matter (CGM) (SUVR_CGM) and the whole cerebellum (SUVR_WC) as reference regions. The correlations between the different SUVRs and the WM uptake (WM-SUVR_CGM) were studied in patients, and in a well-controlled framework based on Monte Carlo (MC) simulation. Activity maps for the MC simulation were derived from ADNI patients by using a voxel-wise iterative process (BrainViset). Ten WM uptakes covering the spectrum of WM values obtained from patient data were simulated for different patients. Three different PVC methods were tested (a) the regional voxel-based (RBV), (b) the iterative Yang (iY), and (c) a simplified analytical correction derived from our MC simulation.

Results

WM-SUVR_CGM followed a normal distribution with an average of 1.79 and a standard deviation of 0.243 (13.6%). SUVR_CGM was linearly correlated to WM-SUVR_CGM (r = 0.82, linear fit slope = 0.28). SUVR_WC was linearly correlated to WM-SUVR_CGM (r = 0.64, linear fit slope = 0.13). Our MC results showed that these correlations are compatible with those produced by isolated spill-in effect (slopes of 0.23 and 0.11). The impact of the spill-in was mitigated by using PVC for SUVR_CGM (slopes of 0.06 and 0.07 for iY and RBV), while SUVR_WC showed a negative correlation with SUVR_CGM after PVC. The proposed analytical correction also reduced the observed correlations when applied to patient data (r = 0.27 for SUVR_CGM, r = 0.18 for SUVR_WC).

Conclusions

There is a high correlation between WM uptake and the measured SUVR due to spill-in effect, and that this effect is reduced when including WM in the reference region. We also evaluated the performance of PVC, and we proposed an analytical correction that can be applied to preprocessed data.

MRI-Driven PET Image Optimization for Neurological Applications

Positron emission tomography (PET) and magnetic resonance imaging (MRI) are established imaging modalities for the study of neurological disorders, such as epilepsy, dementia, psychiatric disorders and so on. Since these two available modalities vary in imaging principle and physical performance, each technique has its own advantages and disadvantages over the other. To acquire the mutual complementary information and reinforce each other, there is a need for the fusion of PET and MRI. This combined dual-modality (either sequential or simultaneous) could generate preferable soft tissue contrast of brain tissue, flexible acquisition parameters, and minimized exposure to radiation. The most unique superiority of PET/MRI is mainly manifested in MRI-based improvement for the inherent limitations of PET, such as motion artifacts, partial volume effect (PVE) and invasive procedure in quantitative analysis. Head motion during scanning significantly deteriorates the effective resolution of PET image, especially for the dynamic scan with lengthy time. Hybrid PET/MRI device can offer motion correction (MC) for PET data through MRI information acquired simultaneously. Regarding the PVE associated with limited spatial resolution, the process and reconstruction of PET data can be further optimized by using acquired MRI either sequentially or simultaneously. The quantitative analysis of dynamic PET data mainly relies upon an invasive arterial blood sampling procedure to acquire arterial input function (AIF). An image-derived input function (IDIF) method without the need of arterial cannulization, can serve as a potential alternative estimation of AIF. Compared with using PET data only, combining anatomical or functional information from MRI for improving the accuracy in IDIF approach has been demonstrated. Yet, due to the interference and inherent disparity between the two modalities, these methods for optimizing PET image based on MRI still have many technical challenges. This review discussed upon the most recent progress, current challenges and future directions of MRI-driven PET data optimization for neurological applications, with either sequential or simultaneous acquisition approach.

Beta Amyloid Deposition Is Not Associated With Cognitive Impairment in Parkinson's Disease

The extent to which Alzheimer neuropathology, particularly the accumulation of misfolded beta-amyloid, contributes to cognitive decline and dementia in Parkinson's disease (PD) is unresolved. Here, we used Florbetaben PET imaging to test for any association between cerebral amyloid deposition and cognitive impairment in PD, in a sample enriched for cases with mild cognitive impairment. This cross-sectional study used Movement Disorders Society level II criteria to classify 115 participants with PD as having normal cognition (PDN, n = 23), mild cognitive impairment (PD-MCI, n = 76), or dementia (PDD, n = 16). We acquired 18F-Florbetaben (FBB) amyloid PET and structural MRI. Amyloid deposition was assessed between the three cognitive groups, and also across the whole sample using continuous measures of both global cognitive status and average performance in memory domain tests. Outcomes were cortical FBB uptake, expressed in centiloids and as standardized uptake value ratios (SUVR) using the Centiloid Project whole cerebellum region as a reference, and regional SUVR measurements. FBB binding was higher in PDD, but this difference did not survive adjustment for the older age of the PDD group. We established a suitable centiloid cut-off for amyloid positivity in Parkinson's disease (31.3), but there was no association of FBB binding with global cognitive or memory scores. The failure to find an association between PET amyloid deposition and cognitive impairment in a moderately large sample, particularly given that it was enriched with PD-MCI patients at risk of dementia, suggests that amyloid pathology is not the primary driver of cognitive impairment and dementia in most patients with PD.

Applicability of in vivo staging of regional amyloid burden in a cognitively normal cohort with subjective memory complaints: the INSIGHT-preAD study

BACKGROUND

Current methods of amyloid PET interpretation based on the binary classification of global amyloid signal fail to identify early phases of amyloid deposition. A recent analysis of 18F-florbetapir PET data from the Alzheimer's disease Neuroimaging Initiative cohort suggested a hierarchical four-stage model of regional amyloid deposition that resembles neuropathologic estimates and can be used to stage an individual's amyloid burden in vivo. Here, we evaluated the validity of this in vivo amyloid staging model in an independent cohort of older people with subjective memory complaints (SMC). We further examined its potential association with subtle cognitive impairments in this population at elevated risk for Alzheimer's disease (AD).

METHODS

The monocentric INSIGHT-preAD cohort includes 318 cognitively intact older individuals with SMC. All individuals underwent 18F-florbetapir PET scanning and extensive neuropsychological testing. We projected the regional amyloid uptake signal into the previously proposed hierarchical staging model of in vivo amyloid progression. We determined the adherence to this model across all cases and tested the association between increasing in vivo amyloid stage and cognitive performance using ANCOVA models.

RESULTS

In total, 156 participants (49%) showed evidence of regional amyloid deposition, and all but 2 of these (99%) adhered to the hierarchical regional pattern implied by the in vivo amyloid progression model. According to a conventional binary classification based on global signal (SUVR_Cereb = 1.10), individuals in stages III and IV were classified as amyloid-positive (except one in stage III), but 99% of individuals in stage I and even 28% of individuals in stage II were classified as amyloid-negative. Neither in vivo amyloid stage nor conventional binary amyloid status was significantly associated with cognitive performance in this preclinical cohort.

CONCLUSIONS

The proposed hierarchical staging scheme of PET-evidenced amyloid deposition generalizes well to data from an independent cohort of older people at elevated risk for AD. Future studies will determine the prognostic value of the staging approach for predicting longitudinal cognitive decline in older individuals at increased risk for AD.

A Comparison of Partial Volume Correction Techniques for Measuring Change in Serial Amyloid PET SUVR

Longitudinal PET studies in aging and Alzheimer's disease populations rely on accurate and precise measurements of change over time from serial PET scans. Various methods for partial volume correction (PVC) are commonly applied to such studies, but existing comparisons and validations of these PVC methods have focused on cross-sectional measurements. Rate of change measurements inherently have smaller magnitudes than cross-sectional measurements, so levels of noise amplification due to PVC must be smaller, and it is necessary to re-evaluate methods in this context. Here we compare the relative precision in longitudinal measurements from serial amyloid PET scans when using geometric transfer matrix (GTM) PVC versus the traditional two-compartment (Meltzer-style), three-compartment (Müller-Gärtner-style), and no-PVC approaches. We used two independent implementations of standardized uptake value ratio (SUVR) measurement and PVC (one in-house pipeline based on SPM12 and ANTs, and one using FreeSurfer 6.0). For each approach, we also tested longitudinal-specific variants. Overall, we found that measurements using GTM PVC had significantly worse relative precision (unexplained within-subject variability ≈4-8%) than those using two-compartment, three-compartment, or no PVC (≈2-4%). Longitudinally-stabilized approaches did not improve these properties. This data suggests that GTM PVC methods may be less suitable than traditional approaches when measuring within-person change over time in longitudinal amyloid PET.

Imaging and Molecular Mechanisms of Alzheimer's Disease: A Review

Alzheimer's disease is the most common form of dementia and is a significant burden for affected patients, carers, and health systems. Great advances have been made in understanding its pathophysiology, to a point that we are moving from a purely clinical diagnosis to a biological one based on the use of biomarkers. Among those, imaging biomarkers are invaluable in Alzheimer's, as they provide an in vivo window to the pathological processes occurring in Alzheimer's brain. While some imaging techniques are still under evaluation in the research setting, some have reached widespread clinical use. In this review, we provide an overview of the most commonly used imaging biomarkers in Alzheimer's disease, from molecular PET imaging to structural MRI, emphasising the concept that multimodal imaging would likely prove to be the optimal tool in the future of Alzheimer's research and clinical practice.

Dissociation of Tau Deposits and Brain Atrophy in Early Alzheimer's Disease: A Combined Positron Emission Tomography/Magnetic Resonance Imaging Study

The recent advent of tau-specific positron emission tomography (PET) has enabled in vivo assessment of tau pathology in Alzheimer’s disease (AD). However, because PET scanners have limited spatial resolution, the measured signals of small brain structures or atrophied areas are underestimated by partial volume effects (PVEs). The aim of this study was to determine whether partial volume correction (PVC) improves the precision of measures of tau deposits in early AD. We investigated tau deposits in 18 patients with amyloid-positive early AD and in 36 amyloid-negative healthy controls using ¹⁸F-THK5351 PET. For PVC, we applied the SPM toolbox PETPVE12. The PET images were then spatially normalized and subjected to voxel-based group analysis using SPM12 for comparison between the early AD patients and healthy controls. We also compared these two groups in terms of brain atrophy using voxel-based morphometry of MRI. We found widespread neocortical tracer retention predominantly in the posterior cingulate and precuneus areas, but also in the inferior temporal lobes, inferior parietal lobes, frontal lobes, and occipital lobes in the AD patients compared with the controls. The pattern of tracer retention was similar between before and after PVC, suggesting that PVC had little effect on the precision of tau load measures. Gray matter atrophy was detected in the medial/lateral temporal lobes and basal frontal lobes in the AD patients. Interestingly, only a few associations were found between atrophy and tau deposits, even after PVC. In conclusion, PVC did not significantly affect ¹⁸F-THK5351 PET measures of tau deposits. This discrepancy between tau deposits and atrophy suggests that tau load precedes atrophy.

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.

PET/MRI Hybrid Systems

Over the last decade, the combination of PET and MRI in one system has proven to be highly successful in basic preclinical research, as well as in clinical research. Nowadays, PET/MRI systems are well established in preclinical imaging and are progressing into clinical applications to provide further insights into specific diseases, therapeutic assessments, and biological pathways. Certain challenges in terms of hardware had to be resolved concurrently with the development of new techniques to be able to reach the full potential of both combined techniques. This review provides an overview of these challenges and describes the opportunities that simultaneous PET/MRI systems can exploit in comparison with stand-alone or other combined hybrid systems. New approaches were developed for simultaneous PET/MRI systems to correct for attenuation of 511 keV photons because MRI does not provide direct information on gamma photon attenuation properties. Furthermore, new algorithms to correct for motion were developed, because MRI can accurately detect motion with high temporal resolution. The additional information gained by the MRI can be employed to correct for partial volume effects as well. The development of new detector designs in combination with fast-decaying scintillator crystal materials enabled time-of-flight detection and incorporation in the reconstruction algorithms. Furthermore, this review lists the currently commercially available systems both for preclinical and clinical imaging and provides an overview of applications in both fields. In this regard, special emphasis has been placed on data analysis and the potential for both modalities to evolve with advanced image analysis tools, such as cluster analysis and machine learning.

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.

Exploring APOE genotype effects on Alzheimer's disease risk and amyloid β burden in individuals with subjective cognitive decline: The FundacioACE Healthy Brain Initiative (FACEHBI) study baseline results

INTRODUCTION

Subjective cognitive decline (SCD) has been proposed as a potential preclinical stage of Alzheimer's disease (AD). Nevertheless, the genetic and biomarker profiles of SCD individuals remain mostly unexplored.

METHODS

We evaluated apolipoprotein E (APOE) ε4's effect in the risk of presenting SCD, using the Fundacio ACE Healthy Brain Initiative (FACEHBI) SCD cohort and Spanish controls, and performed a meta-analysis addressing the same question. We assessed the relationship between APOE dosage and brain amyloid burden in the FACEHBI SCD and Alzheimer's Disease Neuroimaging Initiative cohorts.

RESULTS

Analysis of the FACEHBI cohort and the meta-analysis demonstrated SCD individuals presented higher allelic frequencies of APOE ε4 with respect to controls. APOE dosage explained 9% (FACEHBI cohort) and 11% (FACEHBI and Alzheimer's Disease Neuroimaging Initiative cohorts) of the variance of cerebral amyloid levels.

DISCUSSION

The FACEHBI sample presents APOE ε4 enrichment, suggesting that a pool of AD patients is nested in our sample. Cerebral amyloid levels are partially explained by the APOE allele dosage, suggesting that other genetic or epigenetic factors are involved in this AD endophenotype.

PET/MR Imaging: New Frontier in Alzheimer's Disease and Other Dementias

Alzheimer's disease (AD) is the most common form of dementia; a progressive neurodegenerative disease that currently lacks an effective treatment option. Early and accurate diagnosis, in addition to quick elimination of differential diagnosis, allows us to provide timely treatments that delay the progression of AD. Imaging plays an important role for the early diagnosis of AD. The newly emerging PET/MR imaging strategies integrate the advantages of PET and MR to diagnose and monitor AD. This review introduces the development of PET/MR imaging systems, technical considerations of PET/MR imaging, special considerations of PET/MR in AD, and the system's potential clinical applications and future perspectives in AD.

A Survey of White Matter Neurons at the Gyral Crowns and Sulcal Depths in the Rhesus Monkey

Gyrencephalic brains exhibit deformations of the six neocortical laminae at gyral crowns and sulcal depths, where the deeper layers are, respectively, expanded and compressed. The present study addresses: (1) the degree to which the underlying white matter neurons (WMNs) observe the same changes at gyral crowns and sulcal depths; and (2) whether these changes are consistent or variable across different cortical regions. WMNs were visualized by immunohistochemistry using the pan-neuronal label NeuN, and their density was quantified in eight rhesus monkey brains for four regions; namely, frontal (FR), superior frontal gyrus (SFG), parietal (Par) and temporal (TE). In all four regions, there were about 50% fewer WMNs in the sulcal depth, but there was also distinct variability from region to region. For the gyral crown, we observed an average density per 0.21 mm2 of 82 WMNs for the FR, 51 WMNs for SFG, 80 WMNs for Par and 93 WMNs for TE regions. By contrast, for the sulcal depth, the average number of WMNs per 0.21 mm2 was 41 for FR, 31 for cingulate sulcus (underlying the SFG), 54 for Par and 63 for TE cortical regions. Since at least some WMNs participate in cortical circuitry, these results raise the possibility of their differential influence on cortical circuitry in the overlying gyral and sulcal locations. The results also point to a possible role of WMNs in the differential vulnerability of gyral vs. sulcal regions in disease processes, and reinforce the increasing awareness of the WMNs as part of a complex, heterogeneous and structured microenvironment.

A comparison of five partial volume correction methods for Tau and Amyloid PET imaging with [18F]THK5351 and [11C]PIB

PURPOSE

To suppress partial volume effect (PVE) in brain PET, there have been many algorithms proposed. However, each methodology has different property due to its assumption and algorithms. Our aim of this study was to investigate the difference among partial volume correction (PVC) method for tau and amyloid PET study.

METHODS

We investigated two of the most commonly used PVC methods, Müller-Gärtner (MG) and geometric transfer matrix (GTM) and also other three methods for clinical tau and amyloid PET imaging. One healthy control (HC) and one Alzheimer's disease (AD) PET studies of both [¹⁸F]THK5351 and [¹¹C]PIB were performed using a Eminence STARGATE scanner (Shimadzu Inc., Kyoto, Japan). All PET images were corrected for PVE by MG, GTM, Labbé (LABBE), Regional voxel-based (RBV), and Iterative Yang (IY) methods, with segmented or parcellated anatomical information processed by FreeSurfer, derived from individual MR images. PVC results of 5 algorithms were compared with the uncorrected data.

RESULTS

In regions of high uptake of [¹⁸F]THK5351 and [¹¹C]PIB, different PVCs demonstrated different SUVRs. The degree of difference between PVE uncorrected and corrected depends on not only PVC algorithm but also type of tracer and subject condition.

CONCLUSION

Presented PVC methods are straight-forward to implement but the corrected images require careful interpretation as different methods result in different levels of recovery.

Cortical amyloid accumulation is associated with alterations of structural integrity in older people with subjective memory complaints

We determined the effect of cortical amyloid load using ¹⁸F-florbetapir PET on cognitive performance and gray matter structural integrity derived from MRI in 318 cognitively normally performing older people with subjective memory impairment from the INSIGHT-preAD cohort using multivariate partial least squares regression. Amyloid uptake was associated with reduced gray matter structural integrity in hippocampus, entorhinal and cingulate cortex, middle temporal gyrus, prefrontal cortex, and lentiform nucleus (p < 0.01, permutation test). Higher amyloid load was associated with poorer global cognitive performance, delayed recall and attention (p < 0.05), independently of its effects on gray matter connectivity. These findings agree with the assumption of a two-stage effect of amyloid on cognition, (1) an early direct effect in the preclinical stages of Alzheimer's disease and (2) a delayed effect mediated by downstream effects of amyloid accumulation, such as gray matter connectivity decline.

Regional brain amyloid-β accumulation associates with domain-specific cognitive performance in Parkinson disease without dementia

Parkinson disease patients develop clinically significant cognitive impairment at variable times over their disease course, which is often preceded by milder deficits in memory, visuo-spatial, and executive domains. The significance of amyloid-β accumulation to these problems is unclear. We hypothesized that amyloid-β PET imaging by 18F-florbetapir, a radiotracer that detects fibrillar amyloid-β plaque deposits, would identify subjects with global cognitive impairment or poor performance in individual cognitive domains in non-demented Parkinson disease patients. We assessed 61 non-demented Parkinson disease patients with detailed cognitive assessments and 18F-florbetapir PET brain imaging. Scans were interpreted qualitatively (positive or negative) by two independent nuclear medicine physicians blinded to clinical data, and quantitatively by a novel volume-weighted method. The presence of mild cognitive impairment was determined through an expert consensus process using Level 1 criteria from the Movement Disorder Society. Nineteen participants (31.2%) were diagnosed with mild cognitive impairment and the remainder had normal cognition. Qualitative 18F-florbetapir PET imaging was positive in 15 participants (24.6%). Increasing age and presence of an APOE ε4 allele were associated with higher composite 18F-florbetapir binding. In multivariable models, an abnormal 18F-florbetapir scan by expert rating was not associated with a diagnosis of mild cognitive impairment. However, 18F-florbetapir retention values in the posterior cingulate gyrus inversely correlated with verbal memory performance. Retention values in the frontal cortex, precuneus, and anterior cingulate gyrus retention values inversely correlated with naming performance. Regional cortical amyloid-β amyloid, as measured by 18F-florbetapir PET, may be a biomarker of specific cognitive deficits in non-demented Parkinson disease patients.

Optimized classification of 18F-Florbetaben PET scans as positive and negative using an SUVR quantitative approach and comparison to visual assessment

Introduction

Standardized uptake value ratios (SUVRs) calculated from cerebral cortical areas can be used to categorize ¹⁸F-Florbetaben (FBB) PET scans by applying appropriate cutoffs. The objective of this work was first to generate FBB SUVR cutoffs using visual assessment (VA) as standard of truth (SoT) for a number of reference regions (RR) (cerebellar gray matter (GCER), whole cerebellum (WCER), pons (PONS), and subcortical white matter (SWM)). Secondly, to validate the FBB PET scan categorization performed by SUVR cutoffs against the categorization made by post-mortem histopathological confirmation of the Aβ presence. Finally, to evaluate the added value of SUVR cutoff categorization to VA.

Methods

SUVR cutoffs were generated for each RR using FBB scans from 143 subjects who were visually assessed by 3 readers. SUVR cutoffs were validated in 78 end-of life subjects using VA from 8 independent blinded readers (3 expert readers and 5 non-expert readers) and histopathological confirmation of the presence of neuritic beta-amyloid plaques as SoT. Finally, the number of correctly or incorrectly classified scans according to pathology results using VA and SUVR cutoffs was compared.

Results

Composite SUVR cutoffs generated were 1.43 (GCER), 0.96 (WCER), 0.78 (PONS) and 0.71 (SWM). Accuracy values were high and consistent across RR (range 83–94% for histopathology, and 85–94% for VA). SUVR cutoff performed similarly as VA but did not improve VA classification of FBB scans read either by expert readers or the majority read but provided higher accuracy than some non-expert readers.

Conclusion

The accurate scan classification obtained in this study supports the use of VA as SoT to generate site-specific SUVR cutoffs. For an elderly end of life population, VA and SUVR cutoff categorization perform similarly in classifying FBB scans as Aβ-positive or Aβ-negative. These results emphasize the additional contribution that SUVR cutoff classification may have compared with VA performed by non-expert readers.

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SUVR cutoffs to classify Florbetaben PET scans as positive and negative were generated.

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SUVR cutoffs were validated against post-mortem histopathological confirmation.

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Added value of SUVR cutoff classification to visual assessment was evaluated.

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SUVR cutoff classification provided higher accuracy than some non-expert readers.

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Results emphasize the contribution that SUVR cutoffs may have to visual assessment.

Contributions of imprecision in PET-MRI rigid registration to imprecision in amyloid PET SUVR measurements

Quantitative measurement of β-amyloid from amyloid PET scans typically relies on localizing target and reference regions by image registration to MRI. In this work, we present a series of simulations where 50 small random perturbations of starting location and orientation were applied to each subject's PET scan, and rigid registration using spm_coreg was performed between each perturbed PET scan and its corresponding MRI. We then measured variation in the output PET-MRI registrations and how this variation affected the resulting SUVR measurements. We performed these experiments using scans of 1196 participants, half using 18F florbetapir and half using 11C PiB. From these experiments, we measured the magnitude of the imprecision in the rigid registration steps used to localize measurement regions, and how this contributes to the overall imprecision in SUVR measurements. Unexpectedly, we found for both tracers that the imprecision in these measurements depends on the degree of amyloid tracer uptake, and thus also indirectly on Alzheimer's disease clinical status. We then examined common choices of reference regions, and we show that SUVR measurements using supratentorial white matter references are relatively resistant to this source of error. We also show that the use of partial volume correction further magnifies the effects of registration imprecision on SUVR measurements. Together, these results suggest that this rigid registration step is an attractive target for future work in improving measurement techniques. Hum Brain Mapp 38:3323-3336, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Reference region selection and the association between the rate of amyloid accumulation over time and the baseline amyloid burden

Relative quantitative analysis of amyloid plaque burden in Alzheimer's disease (AD) patients can be reported as standardized uptake value ratio (SUVR) from positron emission tomography (PET). Here, the SUVR is the ratio of the mean amyloid radioligand retention in a composite (COMP) neocortical volume of interest (VOI) to that in a reference VOI, such as the cerebellum, brainstem (BST)/pons, or white matter (WM). Some longitudinal PET investigations show that the rate of amyloid accumulation to follow-up has an inverted U relationship with baseline amyloid SUVR relative to cerebellar or brainstem/pons reference VOIs. The corresponding association with SUVR relative to WM is unknown. To test the possible benefits of WM normalization, we analyzed [¹⁸F]-AV45 PET data from 404 subjects in the AD Neuroimaging Initiative (ADNI) database at baseline and 2-year follow-up (144 cognitively normal controls, 225 patients with mild cognitive impairment, and 35 AD patients). Reference regions included subcortical WM as well as conventional cerebellar gray matter (CBL), and BST. We tested associations between each subject's inter-session change (∆) of SUVR and their baseline SUVR by applying linear, logarithmic, and quadratic regression analyses. Unscaled standardized uptake values (SUVs) were correlated between VOIs at baseline and follow-up, and within VOIs in the longitudinal run. The association between ∆SUVR and baseline SUVR relative to WM reference was best described by an inverted U-shaped function. Correlation analyses demonstrated a high regional and temporal correlation between COMP and WM VOI SUVs. For WM normalization, we confirm that the rate of amyloid accumulation over time follows an inverted U-shaped function of baseline amyloid burden. Reference region selection, however, has substantial effects on SUVR results. This reflects the extent of covariance between SUVs in the COMP VOI and those in the various reference VOIs. We speculate that PET labeling of amyloid deposition within target regions is partially confounded by effects of longitudinal changes of cerebral blood flow (CBF) on tracer delivery. Indeed, CBF may be the leading factor influencing longitudinal SUV changes. We suggest that SUVR relative to WM may be more robust to changes in CBF, and thus fitter for sensitive detection of amyloid accumulation in intervention studies.

Optimal Reference Region to Measure Longitudinal Amyloid-β Change with 18F-Florbetaben PET

Accurate measurement of changes in amyloid-β (Aβ) deposition over time is important in longitudinal studies, particularly in anti-Aβ therapeutic trials. To achieve this, the optimal reference region (RR) must be selected to reduce variance of Aβ PET measurements, allowing early detection of treatment efficacy. The aim of this study was to determine the RR that allows earlier detection of subtle Aβ changes using ¹⁸F-florbetaben PET. Methods: Forty-five patients with mild cognitive impairment (mean age ± SD, 72.69 ± 6.54 y; 29 men/16 women) who underwent up to 3 ¹⁸F-florbetaben scans were included. Baseline scans were visually classified as high (Aβ+) or low (Aβ-) amyloid. Six cortical regions were quantified using a standardized region-of-interest atlas applied to the spatially normalized gray matter image obtained from segmentation of the baseline T1-weighted volumetric MRI. Four RRs (cerebellar gray matter [CGM], whole cerebellum [WCER], pons, and subcortical white matter [SWM]) were studied. The SUV ratio (SUVR) for each RR was calculated by dividing cortex activity by RR activity, with a composite SUVR averaged over 6 cortical regions. SUVR increase from baseline to 1 and 2 y, and percentage Aβ deposition per year, were assessed across Aβ+ and Aβ- groups. Results: SUVs for any RR were not significantly different over time. Percentage Aβ accumulation per year derived from composite SUVR was 0.10 ± 1.72 (Aβ-) and 1.36 ± 1.98 (Aβ+) (P = 0.02) for CGM and 0.13 ± 1.47 and 1.32 ± 1.75 (P = 0.01), respectively, for WCER. Compared with baseline, the composite SUVR increase in Aβ+ scans was significantly larger than in Aβ- scans at 1 y (P = 0.04 [CGM]; P = 0.03 [WCER]) and 2 y (P = 0.02 [CGM]; P = 0.01 [WCER]) using these 2 RRs. Significant SUVR changes using the pons as the RR were detected only at 2 y (P = 0.46 [1 y], P = 0.001 [2 y]). SUVR using the SWM as the RR showed no significant differences at either follow-up (P = 0.39 [1 y], P = 0.09 [2 y]). Conclusion: RR selection influences reliable early measurement of Aβ changes over time. Compared with SWM and pons, which do not fulfil the RR requirements and have limited sensitivity to detect Aβ changes, cerebellar RRs are recommended for ¹⁸F-florbetaben PET because they allow earlier detection of Aβ accumulation.