scholarly journals Parametric Estimation of Reference Signal Intensity for Semi-Quantification of Tau Deposition: A Flortaucipir and [18F]-APN-1607 Study

2021 ◽  
Vol 15 ◽  
Author(s):  
Huiwei Zhang ◽  
Min Wang ◽  
Jiaying Lu ◽  
Weiqi Bao ◽  
Ling Li ◽  
...  

BackgroundTau positron emission tomography (PET) imaging can reveal the pathophysiology and neurodegeneration that occurs in Alzheimer’s disease (AD) in vivo. The standardized uptake value ratio (SUVR) is widely used for semi-quantification of tau deposition but is susceptible to disturbance from the reference region and the partial volume effect (PVE). To overcome this problem, we applied the parametric estimation of reference signal intensity (PERSI) method—which was previously evaluated for flortaucipir imaging—to two tau tracers, flortaucipir and [18F]-APN-1607.MethodsTwo cohorts underwent tau PET scanning. Flortaucipir PET imaging data for cohort I (65 healthy controls [HCs], 60 patients with mild cognitive impairment [MCI], and 12 AD patients) were from the AD Neuroimaging Initiative database. [18F]-APN-1607 ([18F]-PM-PBB3) PET imaging data were for Cohort II, which included 21 patients with a clinical diagnosis of amyloid PET-positive AD and 15 HCs recruited at Huashan Hospital. We used white matter (WM) postprocessed by PERSI (PERSI-WM) as the reference region and compared this with the traditional semi-quantification method that uses the whole cerebellum as the reference. SUVRs were calculated for regions of interest including the frontal, parietal, temporal, and occipital lobes; anterior and posterior cingulate; precuneus; and Braak I/II (entorhinal cortex and hippocampus). Receiver operating characteristic (ROC) curve analysis and effect sizes were used to compare the two methods in terms of ability to discriminate between different clinical groups.ResultsIn both cohorts, regional SUVR determined using the PERSI-WM method was superior to using the cerebellum as reference region for measuring tau retention in AD patients (e.g., SUVR of the temporal lobe: flortaucipir, 1.08 ± 0.17 and [18F]-APN-1607, 1.57 ± 0.34); and estimates of the effect size and areas under the ROC curve (AUC) indicated that it also increased between-group differences (e.g., AUC of the temporal lobe for HC vs AD: flortaucipir, 0.893 and [18F]-APN-1607: 0.949).ConclusionThe PERSI-WM method significantly improves diagnostic discrimination compared to conventional approach of using the cerebellum as a reference region and can mitigate the PVE; it can thus enhance the efficacy of semi-quantification of multiple tau tracers in PET scanning, making it suitable for large-scale clinical application.

2017 ◽  
Vol 59 (6) ◽  
pp. 944-951 ◽  
Author(s):  
Sudeepti Southekal ◽  
Michael D. Devous ◽  
Ian Kennedy ◽  
Michael Navitsky ◽  
Ming Lu ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
pp. 249-263
Author(s):  
Min Wang ◽  
◽  
Zhuangzhi Yan ◽  
Huiwei Zhang ◽  
Jiaying Lu ◽  
...  

2021 ◽  
Vol 11 (5) ◽  
pp. 1991
Author(s):  
Alexander P. Seiffert ◽  
Adolfo Gómez-Grande ◽  
Eva Milara ◽  
Sara Llamas-Velasco ◽  
Alberto Villarejo-Galende ◽  
...  

Amyloid positron emission tomography (PET) brain imaging with radiotracers like [18F]florbetapir (FBP) or [18F]flutemetamol (FMM) is frequently used for the diagnosis of Alzheimer’s disease. Quantitative analysis is usually performed with standardized uptake value ratios (SUVR), which are calculated by normalizing to a reference region. However, the reference region could present high variability in longitudinal studies. Texture features based on the grey-level co-occurrence matrix, also called Haralick features (HF), are evaluated in this study to discriminate between amyloid-positive and negative cases. A retrospective study cohort of 66 patients with amyloid PET images (30 [18F]FBP and 36 [18F]FMM) was selected and SUVRs and 6 HFs were extracted from 13 cortical volumes of interest. Mann–Whitney U-tests were performed to analyze differences of the features between amyloid positive and negative cases. Receiver operating characteristic (ROC) curves were computed and their area under the curve (AUC) was calculated to study the discriminatory capability of the features. SUVR proved to be the most significant feature among all tests with AUCs between 0.692 and 0.989. All HFs except correlation also showed good performance. AUCs of up to 0.949 were obtained with the HFs. These results suggest the potential use of texture features for the classification of amyloid PET images.


2020 ◽  
Vol 16 (S4) ◽  
Author(s):  
Lloyd Prosser ◽  
Thomas Veale ◽  
Ian B Malone ◽  
William Coath ◽  
Nick C Fox ◽  
...  

2006 ◽  
Vol 14 (7S_Part_15) ◽  
pp. P807-P807
Author(s):  
Michael H. Rosenbloom ◽  
Kathryn A. Wyman-Chick ◽  
Lauren O. Erickson ◽  
Paul Carolan ◽  
Joshua Johnson ◽  
...  

Epilepsia ◽  
1992 ◽  
Vol 33 (1) ◽  
pp. 28-35 ◽  
Author(s):  
P. Ryvlin ◽  
L. Garcia-Larrea ◽  
B. Philippon ◽  
J. C. Froment ◽  
C. Fischer ◽  
...  

2018 ◽  
Vol 32 (1) ◽  
pp. 35-42 ◽  
Author(s):  
Rafid Mustafa ◽  
Jared R. Brosch ◽  
Gil D. Rabinovici ◽  
Bradford C. Dickerson ◽  
Maria C. Carrillo ◽  
...  

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