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Zijdenbos, A. P.

Publications and source records attributed to Zijdenbos, A. P..

2 recordsLinked to original sources
bioRxiv2024

A novel method for harmonization of PET image spatial resolution without phantoms

The most common approach for estimating the spatial resolution of PET images in multi-center studies typically uses Hoffman phantom data as a surrogate. Specifically, the phantom-based matching resolution approach assumes that scanned phantom PET images are well approximated by a ground truth, noise-free digital phantom convolved with a Gaussian kernel of unknown size. The size of the kernel is then estimated by an exhaustive search on the amount of blurring needed to match the smoothed digital phantom to a particular scanned phantom image. Unfortunately, Hoffman phantom images may not always be readily available, and phantom-based approaches may yield sub-optimal results. We propose a new, computational approach that allows estimation of spatial resolution directly from the PET image itself. We generalized the so-called logarithmic intensity plots method to the 3D case to perform a spatial resolution estimation in both axial and in-plane directions of the PET images. The proposed approach was applied to two different cohorts. The first cohort consisted of [18F]florbetapir amyloid PET images and matching phantoms coming from a Phase II clinical trial and includes different scanner models and/or orientation and grid reconstructions. The second cohort included {beta}-amyloid, FDG and tau PET images from the Alzheimers Disease Neuroimaging Initiative (ADNI) study. We obtained in-plane and axial resolution estimators that vary between 3.5 mm and 8.5 mm for both PET and matching phantom images. In both cases, we obtained small across-subject variability in groups of images sharing the same PET scanner model and reconstruction parameters. For human PET images, we also obtained a strong cross-tracer and longitudinal consistency in the spatial resolution estimators. Our novel approach does not only eliminate the need for surrogate brain phantom data, but also provides a general framework that can be applied to a wide range of tracers and other image modalities, such as SPECT.

neuroscience↗
bioRxiv2024

Tau-related reduction of glucose metabolism in mild cognitive impairment occurs independently of APOE ε4 genotype and is gradually modulated by β amyloid

BackgroundPET imaging studies have shown that spatially distributed measurements of {beta}-amyloid are significantly correlated with glucose metabolism in Mild Cognitive Impairment (MCI) independently of the APOE {varepsilon}4 genotype. In contrast, the relationship between tau and glucose metabolism at different stages of Alzheimers Disease (AD) has not been fully understood. ObjectiveWe hypothesize that spatially distributed scores of tau PET are associated with an even stronger reduction of glucose metabolism, independent of the APOE {varepsilon}4 genotype and gradually modulated by {beta}-amyloid. MethodsWe applied a cross-sectional statistical analysis to concurrent [18F]flortaucipir PET, [18F]florbetapir PET, and 2-[18F]fluoro-2-deoxyglucose (FDG) PET images from the Alzheimers Disease Neuroimaging Initiative (ADNI) study. We employed a Singular Value Decomposition (SVD) approach to the cross-correlation matrix between tau and the FDG images, as well as between tau and {beta}-amyloid PET images. The resulting SVD-based tau scores are associated with cortical regions where a reduced glucose metabolism is maximally correlated with distributed patterns of tau, accounting for the effect of spatially distributed {beta}-amyloid. ResultsFrom a population of MCI subjects, we found that the SVD-based tau scores had their maximal spatial representation within the entorhinal cortex and the lateral inferior temporal gyrus, and were significantly correlated with glucose metabolism in several cortical regions, independently from the confounding effect of the {beta}-amyloid scores and APOE {varepsilon}4. Moreover, {beta}-amyloid gradually modulated the association between tau and glucose metabolism. ConclusionsOur approach uncovered spatially distributed patterns of the tau-glucose metabolism relationship after accounting for the {beta}-amyloid effects. We showed that the SVD-based tau scores have a strong relationship with decreasing glucose metabolism. By highlighting the more significant role of tau, rather than {beta}-amyloid, on the reduction of glucose metabolism, our results could have important consequences in the therapeutic treatment of AD.

neuroscience↗