Combining PET with MRI to improve predictions of progression from mild cognitive impairment to Alzheimer's disease: an exploratory radiomic analysis study.

Cox model Mild cognitive impairment (MCI) magnetic resonance imaging (MRI) positron emission tomography (PET) radiology

Journal

Annals of translational medicine
ISSN: 2305-5839
Titre abrégé: Ann Transl Med
Pays: China
ID NLM: 101617978

Informations de publication

Date de publication:
May 2022
Historique:
received: 18 08 2021
accepted: 19 12 2021
entrez: 5 8 2022
pubmed: 6 8 2022
medline: 6 8 2022
Statut: ppublish

Résumé

This study aimed to explore the potential of a combination of 18F-fluorodeoxyglucose positron emission tomography ( This study enrolled 377 patients with MCI and 94 healthy control participants from 2 medical centers. Enrolment was based on the patients' brain MRI and PET images. Radiomic analysis was performed to evaluate the predictive performance of dual-modality The C-indices for the two test datasets were 0.77 and 0.80 for dual-modality These results indicate the value of imaging features in monitoring the progress of MCI in populations at high risk of developing AD. However, the incremental benefit of combining

Sections du résumé

Background UNASSIGNED
This study aimed to explore the potential of a combination of 18F-fluorodeoxyglucose positron emission tomography (
Methods UNASSIGNED
This study enrolled 377 patients with MCI and 94 healthy control participants from 2 medical centers. Enrolment was based on the patients' brain MRI and PET images. Radiomic analysis was performed to evaluate the predictive performance of dual-modality
Results UNASSIGNED
The C-indices for the two test datasets were 0.77 and 0.80 for dual-modality
Conclusions UNASSIGNED
These results indicate the value of imaging features in monitoring the progress of MCI in populations at high risk of developing AD. However, the incremental benefit of combining

Identifiants

pubmed: 35928737
doi: 10.21037/atm-21-4349
pii: atm-10-09-513
pmc: PMC9347042
doi:

Types de publication

Journal Article

Langues

eng

Pagination

513

Subventions

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

Informations de copyright

2022 Annals of Translational Medicine. All rights reserved.

Déclaration de conflit d'intérêts

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://atm.amegroups.com/article/view/10.21037/atm-21-4349/coif). The authors have no conflicts of interest to declare.

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Auteurs

Fan Yang (F)

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

Jiehui Jiang (J)

Institute of Biomedical Engineering, School of Life Science, Shanghai University, Shanghai, China.

Ian Alberts (I)

Department of Nuclear Medicine, University Hospital Bern, Bern, Switzerland.

Min Wang (M)

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

Taoran Li (T)

Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China.

Xiaoming Sun (X)

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

Axel Rominger (A)

Department of Nuclear Medicine, University Hospital Bern, Bern, Switzerland.

Chuantao Zuo (C)

PET Center, Huashan Hospital, Fudan University, Shanghai, China.
Human Phenome Institute, Fudan University, Shanghai, China.

Kuangyu Shi (K)

Department of Nuclear Medicine, University Hospital Bern, Bern, Switzerland.
Department of Informatics, Technische Universität München, Munich, Germany.

Classifications MeSH