Parametric estimation of reference signal intensity in the quantification of amyloid-beta deposition: an

Alzheimer’s disease (AD) Amyloid-beta (Aβ) florbetapir positron emission tomography parametric estimation of reference signal intensity (PERSI) quantification standardized uptake value ratio (SUVR)

Journal

Quantitative imaging in medicine and surgery
ISSN: 2223-4292
Titre abrégé: Quant Imaging Med Surg
Pays: China
ID NLM: 101577942

Informations de publication

Date de publication:
Jan 2021
Historique:
entrez: 4 1 2021
pubmed: 5 1 2021
medline: 5 1 2021
Statut: ppublish

Résumé

Positron emission tomography (PET) with the radiotracer florbetapir ( We enrolled 479 people with The SUVRs derived from PERSI-WM showed significantly higher trace retention in the frontal, parietal, temporal, and occipital lobes, as well as in the anterior cingulate, posterior cingulate, precuneus, and global cortex in the AD Aβ-positive (+) group (mean: +43.3%±5.4%, P<0.01) and MCI Aβ+ group (mean: +29.6%±5.3%, P<0.01). For the global cortex, PERSI-WM had the greatest Cohen's d effect size compared with the HC Aβ-negative (-) group (AD Aβ+ and MCI Aβ+: 3.02, AD Aβ+: 3.56, MCI Aβ+: 2.34), and the highest area under the curve (AUC) between the HC Aβ- and AD Aβ+ groups (AUC: 0.983, 95% confidence interval: 0.978-0.998). PERSI-WM could mitigate the influence of PVE and improve the semi-quantification of

Sections du résumé

BACKGROUND BACKGROUND
Positron emission tomography (PET) with the radiotracer florbetapir (
METHODS METHODS
We enrolled 479 people with
RESULTS RESULTS
The SUVRs derived from PERSI-WM showed significantly higher trace retention in the frontal, parietal, temporal, and occipital lobes, as well as in the anterior cingulate, posterior cingulate, precuneus, and global cortex in the AD Aβ-positive (+) group (mean: +43.3%±5.4%, P<0.01) and MCI Aβ+ group (mean: +29.6%±5.3%, P<0.01). For the global cortex, PERSI-WM had the greatest Cohen's d effect size compared with the HC Aβ-negative (-) group (AD Aβ+ and MCI Aβ+: 3.02, AD Aβ+: 3.56, MCI Aβ+: 2.34), and the highest area under the curve (AUC) between the HC Aβ- and AD Aβ+ groups (AUC: 0.983, 95% confidence interval: 0.978-0.998).
CONCLUSIONS CONCLUSIONS
PERSI-WM could mitigate the influence of PVE and improve the semi-quantification of

Identifiants

pubmed: 33392026
doi: 10.21037/qims-20-110
pii: qims-11-01-249
pmc: PMC7719939
doi:

Types de publication

Journal Article

Langues

eng

Pagination

249-263

Subventions

Organisme : NIA NIH HHS
ID : U01 AG024904
Pays : United States

Informations de copyright

2021 Quantitative Imaging in Medicine and Surgery. All rights reserved.

Déclaration de conflit d'intérêts

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/qims-20-110). The authors have no conflicts of interest to declare.

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Auteurs

Min Wang (M)

Shanghai Institute for Advanced Communication and Data Science, School of Communication and Information Engineering, Shanghai University, Shanghai, China.
Institute of Biomedical Engineering, School of Communication and Information Engineering, Shanghai University, Shanghai, China.

Zhuangzhi Yan (Z)

Institute of Biomedical Engineering, School of Communication and Information Engineering, Shanghai University, Shanghai, China.

Huiwei Zhang (H)

PET Center, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.

Jiaying Lu (J)

PET Center, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.

Ling Li (L)

PET Center, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.

Jintai Yu (J)

Department of Neurology and Institute of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.

Jian Wang (J)

Department of Neurology and Institute of Neurology, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.

Hiroshi Matsuda (H)

Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan.

Chuantao Zuo (C)

PET Center, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.

Jiehui Jiang (J)

Shanghai Institute for Advanced Communication and Data Science, School of Communication and Information Engineering, Shanghai University, Shanghai, China.
Institute of Biomedical Engineering, School of Communication and Information Engineering, Shanghai University, Shanghai, China.

Classifications MeSH