Tau positron emission tomography in patients with cognitive impairment and suspected Alzheimer's disease

Alzheimer's disease (AD) is diagnosed by the presence of both amyloid β and tau proteins. Recent advances in molecular PET imaging have made it possible to assess the accumulation of these proteins in the living brain. PET ligands have been developed that bind to 3R/4R tau in AD, but not to 3R tau or 4R tau alone. Of the first-generation PET ligands, 18F-flortaucipir has recently been approved by the Food and Drug Administration. Several second-generation PET probes with less off-target binding have been developed and are being applied clinically. Visual interpretation of tau PET should be based on neuropathological neurofibrillary tangle staging instead of a simple positive or negative classification. Four visual read classifications have been proposed: "no uptake," "medial temporal lobe (MTL) only," "MTL AND," and "outside MTL." As an adjunct to visual interpretation, quantitative analysis has been proposed using MRI-based native space FreeSurfer parcellations. The standardized uptake value ratio of the target area is measured using the cerebellar gray matter as a reference region. In the near future, the Centiloid scale of tau PET is expected to be used as a harmonized value for standardizing each analytical method or PET ligand used, similar to amyloid PET

Centiloid scale analysis for 18F-THK5351 PET imaging in Alzheimer\u27s disease

Purpose: A standardized method for quantification is required for analyzing PET data, but such standards have not been established for tau PET imaging. The Centiloid scale has recently been proposed as a standard method for quantifying amyloid deposition on PET imaging. Therefore, the present study aimed to apply the Centiloid scale to 18F-THK5351 PET imaging in Alzheimer’s disease (AD). Methods: We acquired 18F-THK5351 PET, 11C-PiB PET, and MR images from 47 cognitively normal (CN) individuals and 28 patients with AD with mild to moderate dementia. PET images were spatially normalized to Montreal Neurological Institute space. The PET signals were then normalized using the signal in the reference volume of interest (VOI). Target VOI for specific 18F-THK5351 retention in AD was extracted by voxel-wise comparison of PET images between the 47 CN individuals and 16 AD patients with moderate dementia. Scale anchor points were defined by the CN individuals as 0-anchor points and by that of the average of the typical AD patients as 100-anchor points.Results: Specific retention of 18F-THK5351 was predominant in the angular gyrus, inferior temporal cortex, and parieto-occipital regions in patients with AD. Standardized uptake value ratio (SUVR) of 1.227 and 1.797 were defined as 0- and 100-anchor points, respectively. 18F-THK5351 PET data could be expressed using the Centiloid scale, with the SUVR of the 18F-THK5351 PET images converted to Centiloid using our VOI, the standard Centiloid reference VOI, and the following equation: Centiloid = 169.0 × SUVR–204.6. Conclusion: Centiloid methods can be applied to tau PET imaging using 18F-THK5351

Impact of γ factor in the penalty function of Bayesian penalized likelihood reconstruction (Q.Clear) to achieve high-resolution PET images

Abstract Background The Bayesian penalized likelihood PET reconstruction (BPL) algorithm, Q.Clear (GE Healthcare), has recently been clinically applied to clinical image reconstruction. The BPL includes a relative difference penalty (RDP) as a penalty function. The β value that controls the behavior of RDP determines the global strength of noise suppression, whereas the γ factor in RDP controls the degree of edge preservation. The present study aimed to assess the effects of various γ factors in RDP on the ability to detect sub-centimeter lesions. Methods All PET data were acquired for 10 min using a Discovery MI PET/CT system (GE Healthcare). We used a NEMA IEC body phantom containing spheres with inner diameters of 10, 13, 17, 22, 28 and 37 mm and 4.0, 5.0, 6.2, 7.9, 10 and 13 mm. The target-to-background ratio of the phantom was 4:1, and the background activity concentration was 5.3 kBq/mL. We also evaluated cold spheres containing only non-radioactive water with the same background activity concentration. All images were reconstructed using BPL + time of flight (TOF). The ranges of β values and γ factors in BPL were 50–600 and 2–20, respectively. We reconstructed PET images using the Duetto toolbox for MATLAB software. We calculated the % hot contrast recovery coefficient (CRChot) of each hot sphere, the cold CRC (CRCcold) of each cold sphere, the background variability (BV) and residual lung error (LE). We measured the full width at half maximum (FWHM) of the micro hollow hot spheres ≤ 13 mm to assess spatial resolution on the reconstructed PET images. Results The CRChot and CRCcold for different β values and γ factors depended on the size of the small spheres. The CRChot, CRCcold and BV increased along with the γ factor. A 6.2-mm hot sphere was obvious in BPL as lower β values and higher γ factors, whereas γ factors ≥ 10 resulted in images with increased background noise. The FWHM became smaller when the γ factor increased. Conclusion High and low γ factors, respectively, preserved the edges of reconstructed PET images and promoted image smoothing. The BPL with a γ factor above the default value in Q.Clear (γ factor = 2) generated high-resolution PET images, although image noise slightly diverged. Optimizing the β value and the γ factor in BPL enabled the detection of lesions ≤ 6.2 mm

Determination of optimal regularization factor in Bayesian penalized likelihood reconstruction of brain PET images using [ F]FDG and [ C]PiB.

The Bayesian penalized likelihood (BPL) reconstruction algorithm, Q.Clear, can achieve a higher signal-to-noise ratio on images and more accurate quantitation than ordered subset-expectation maximization (OSEM). The reconstruction parameter (β) in BPL requires optimization according to the radiopharmaceutical tracer. The present study aimed to define the optimal β value in BPL required to diagnose Alzheimer disease from brain positron emission tomography (PET) images acquired using F-fluoro-2-deoxy-D-glucose ([ F]FDG) and C-labeled Pittsburg compound B ([ C]PiB)

Free water derived by multi‐shell diffusion MRI reflects tau/neuroinflammatory pathology in Alzheimer's disease

Abstract Introduction Free‐water (FW) imaging, a new analysis method for diffusion magnetic resonance imaging (MRI), can indicate neuroinflammation and degeneration. We evaluated FW in Alzheimer's disease (AD) using tau/inflammatory and amyloid positron emission tomography (PET). Methods Seventy‐one participants underwent multi‐shell diffusion MRI, 18F‐THK5351 PET, 11C‐Pittsburgh compound B PET, and neuropsychological assessments. They were categorized into two groups: healthy controls (HCs) (n = 40) and AD‐spectrum group (AD‐S) (n = 31) using the Centiloid scale with amyloid PET and cognitive function. We analyzed group comparisons in FW and PET, correlations between FW and PET, and correlation analysis with neuropsychological scores. Results In AD‐S group, there was a significant positive correlation between FW and 18F‐THK5351 in the temporal lobes. In addition, there were negative correlations between FW and cognitive function in the temporal lobe and cingulate gyrus, and negative correlations between 18F‐THK5351 and cognitive function in the same regions. Discussion FW imaging could be a biomarker for tau in AD alongside clinical correlations