Multi-atlas attenuation correction supports full quantification of static and dynamic brain PET data in PET-MR

In simultaneous PET-MR, attenuation maps are not directly available. Essential for absolute radioactivity quantification, they need to be derived from MR or PET data to correct for gamma photon attenuation by the imaged object. We evaluate a multi-atlas attenuation correction method for brain imaging (MaxProb) on static [18F]FDG PET and, for the first time, on dynamic PET, using the serotoninergic tracer [18F]MPPF. Methods A database of 40 MR/CT image pairs (atlases) was used. The MaxProb method synthesises subject-specific pseudo-CTs by registering each atlas to the target subject space. Atlas CT intensities are then fused via label propagation and majority voting. Here, we compared these pseudo-CTs with the real CTs in a leave-one-out design, contrasting the MaxProb approach with a simplified single-atlas method (SingleAtlas). We evaluated the impact of pseudo-CT accuracy on reconstructed PET images, compared to PET data reconstructed with real CT, at the regional and voxel levels for the following: radioactivity images; time-activity curves; and kinetic parameters (non-displaceable binding potential, BPND). Results On static [18F]FDG, the mean bias for MaxProb ranged between 0 and 1% for 73 out of 84 regions assessed, and exceptionally peaked at 2.5% for only one region. Statistical parametric map analysis of MaxProb-corrected PET data showed significant differences in less than 0.02% of the brain volume, whereas SingleAtlas-corrected data showed significant differences in 20% of the brain volume. On dynamic [18F]MPPF, most regional errors on BPND ranged from -1 to +3% (maximum bias 5%) for the MaxProb method. With SingleAtlas, errors were larger and had higher variability in most regions. PET quantification bias increased over the duration of the dynamic scan for SingleAtlas, but not for MaxProb. We show that this effect is due to the interaction of the spatial tracer-distribution heterogeneity variation over time with the degree of accuracy of the attenuation maps. Conclusion This work demonstrates that inaccuracies in attenuation maps can induce bias in dynamic brain PET studies. Multi-atlas attenuation correction with MaxProb enables quantification on hybrid PET-MR scanners, eschewing the need for CT.</p

Analysis of Variance in Neuroreceptor Ligand Imaging Studies

Radioligand positron emission tomography (PET) with dual scan paradigms can provide valuable insight into changes in synaptic neurotransmitter concentration due to experimental manipulation. The residual t-test has been utilized to improve the sensitivity of the t-test in PET studies. However, no further development of statistical tests using residuals has been proposed so far to be applied in cases when there are more than two conditions. Here, we propose the residual f-test, a one-way analysis of variance (ANOVA), and examine its feasibility using simulated [11C]raclopride PET data. We also re-visit data from our previously published [11C]raclopride PET study, in which 10 individuals underwent three PET scans under different conditions. We found that the residual f-test is superior in terms of sensitivity than the conventional f-test while still controlling for type 1 error. The test will therefore allow us to reliably test hypotheses in the smaller sample sizes often used in explorative PET studies

Brain atrophy and white matter hyperintensities are independently associated with plasma neurofilament light chain in an Asian cohort of cognitively impaired patients with concomitant cerebral small vessel disease

Introduction: Plasma neurofilament light chain (NfL) is a potential biomarker for neurodegeneration in Alzheimer's disease (AD), ischemic stroke, and non-dementia cohorts with cerebral small vessel disease (CSVD). However, studies of AD in populations with high prevalence of concomitant CSVD to evaluate associations of brain atrophy, CSVD, and amyloid beta (Aβ) burden on plasma NfL are lacking. Methods: Associations were tested between plasma NfL and brain Aβ, medial temporal lobe atrophy (MTA) as well as neuroimaging features of CSVD, including white matter hyperintensities (WMH), lacunes, and cerebral microbleeds. Results: We found that participants with either MTA (defined as MTA score ≥2; neurodegeneration [N]+WMH−) or WMH (cut-off for log-transformed WMH volume at 50th percentile; N−WMH+) manifested increased plasma NfL levels. Participants with both pathologies (N+WMH+) showed the highest NfL compared to N+WMH−, N−WMH+, and N−WMH− individuals. Discussion: Plasma NfL has potential utility in stratifying individual and combined contributions of AD pathology and CSVD to cognitive impairment

Validation of low-dose lung cancer PET-CT protocol and PET image improvement using machine learning

PURPOSE: To conduct a simplified lesion-detection task of a low-dose (LD) PET-CT protocol for frequent lung screening using 30% of the effective PETCT dose and to investigate the feasibility of increasing clinical value of low-statistics scans using machine learning. METHODS: We acquired 33 SD PET images, of which 13 had actual LD (ALD) PET, and simulated LD (SLD) PET images at seven different count levels from the SD PET scans. We employed image quality transfer (IQT), a machine learning algorithm that performs patch-regression to map parameters from low-quality to high-quality images. At each count level, patches extracted from 23 pairs of SD/SLD PET images were used to train three IQT models - global linear, single tree, and random forest regressions with cubic patch sizes of 3 and 5 voxels. The models were then used to estimate SD images from LD images at each count level for 10 unseen subjects. Lesion-detection task was carried out on matched lesion-present and lesion-absent images. RESULTS: LD PET-CT protocol yielded lesion detectability with sensitivity of 0.98 and specificity of 1. Random forest algorithm with cubic patch size of 5 allowed further 11.7% reduction in the effective PETCT dose without compromising lesion detectability, but underestimated SUV by 30%. CONCLUSION: LD PET-CT protocol was validated for lesion detection using ALD PET scans. Substantial image quality improvement or additional dose reduction while preserving clinical values can be achieved using machine learning methods though SUV quantification may be biased and adjustment of our research protocol is required for clinical use

Head-to-head comparison of amplified plasmonic exosome Aβ42 platform and single-molecule array immunoassay in a memory clinic cohort

Background: Various blood biomarkers reflecting brain amyloid‐β (Aβ) load have recently been proposed with promising results. However, to date, no comparative study among blood biomarkers has been reported. Our objective is to examine the diagnostic performance and cost effectiveness of three blood biomarkers on the same cohort. Methods: Using the same cohort (n=68), we compared the performance of the single‐molecule array (Simoa)‐Aβ40 and Aβ42, Aβ42/Aβ40 and the amplified plasmonic exosome (APEX)‐Aβ42 blood biomarkers using amyloid PET as the reference standard. We also determined the extent to which these blood tests can reduce the recruitment cost of clinical trials by identifying Amyloid positive (Aβ+) participants. Results: Compared to Simoa biomarkers, APEX‐Aβ42 showed significantly higher correlations with amyloid PET retention values and excellent diagnostic performance (sensitivity=100%, specificity=93.3%, AUC=0.995). When utilized for clinical trial recruitment, our simulation showed that pre‐screening with blood biomarkers followed by a confirmatory amyloid PET imaging would roughly half the cost (56.8% reduction for APEX‐Aβ42 and 48.6% for Simoa‐Aβ42/Aβ40) as compared to the situation where only PET imaging is used. Moreover, with a 100% sensitivity; APEX‐Aβ42 pre‐screening does not increase the required number of initial participants. Conclusions: With its high diagnostic performance, APEX is an ideal candidate for Aβ+ subject identification, monitoring, primary care screening, and could efficiently enrich clinical trials with Aβ+ participants while halving recruitment costs