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

Abstract

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

The Pons as an Optimal Background Reference Region for Spinal 18F-FET PET/MRI Evaluation

“…For instance, Li et al conducted a study on neurodegenerative diseases and found that the calculated SUVR was more effective in distinguishing between cognitively normal and cognitively impaired Alzheimer's patients when using the pons as the reference region compared to cerebellum gray matter and centrum semiovale [50]. In our study, the pons demonstrated superior performance in differentiating tumors from myelitis, both for SUVRmean and SUVRmax values, corresponding to its stable uptake characteristics.…”

Multiparametric hippocampal signatures for early diagnosis of Alzheimer's disease using 18F‐FDG PET/MRI Radiomics

“…Subsequently, PET and CBF images were also normalized to the MNI space with the same transformation matrix. Moreover, 18 F‐FDG PET images were converted to standardized uptake value ratio (SUVR) maps, referring to the pons 24,25 …”

“…Moreover, 18 F‐FDG PET images were converted to standardized uptake value ratio (SUVR) maps, referring to the pons. 24 , 25 …”

Changes of “brain-GI” interplay in Parkinson’s disease: a pilot study of dynamic total-body [11C]CFT PET/CT and kinetic modeling

“…VOIs were manually drawn within descending aorta, duodenum, pancreas, and stomach using PMOD 4.3 software (PMOD Technologies Ltd.), where the descending aorta was selected to reflect the blood radiotracer concentration. To extract the TACs from the brain regions, all PET images were first processed by head motion correction and spatial normalization, both using Statistical Parametric Mapping software (SPM12, Wellcome Department of Imaging Neuroscience) in the MATLAB (2019b, The MathWorks Inc.) environment, followed by the co-registration of the PET images to the standard Montreal Neurologic Institute (MNI) space based on an MRI template 25 . Caudate, putamen, pallidum, and substantial nigra, which are the major brain regions associated with PD, were selected for the analysis.…”