期刊
ANNALS OF TRANSLATIONAL MEDICINE
卷 10, 期 9, 页码 -出版社
AME PUBLISHING COMPANY
DOI: 10.21037/atm-21-4349
关键词
Mild cognitive impairment (MCI); magnetic resonance imaging (MRI); positron emission tomography (PET); Cox model; radiology
资金
- National Natural Science Foundation of China [61603236, 81830059, 81971641, 81671239, 81361120393]
- Shanghai Municipal Science and Technology Major Project [2017SHZDZX01, 2018SHZDZX03]
- 111 Project [D20031]
- Alzheimer's Disease Neuroimaging Initiative (ADNI
- National Institutes of Health) [U01 AG024904]
- DODADNI (Department of Defense) [W81XWH-12-2-0012]
- National Institute of Aging
- National Institute of Biomedical Imaging and Bioengineering
- AbbVie
- Alzheimer's Association
- Alzheimer's Drug Discovery Foundation
- Araclon Biotech
- BioClinica, Inc.
- Biogen
- Bristol-Myers Squibb Company
- CereSpir, Inc.
- Eisai, Inc.
- Elan Pharmaceuticals, Inc.
- Eli Lilly and Company
- EuroImmun
- F.Hoffmann-La Roche Ltd
- Genentech, Inc.
- Fujirebio
- GE Healthcare
- IXICO Ltd.
- Janssen Alzheimer Immunotherapy Research & Development, LLC
- Johnson & Johnson Pharmaceutical Research & Development LLC
- Lumosity
- Lundbeck
- Merck Co., Inc.
- Meso Scale Diagnostics, LLC
- NeuroRx Research
- Neurotrack Technologies
- Novartis Pharmaceuticals Corporation
- Pfizer, Inc.
- Piramal Imaging
- Servier
- Takeda Pharmaceutical Company
- Transition Therapeutics
- The Canadian Institutes of Health Research
This study aimed to explore the potential of a combination of F-18-FDG PET and MRI in predicting conversion from MCI to AD. The results showed that the dual-modality F-18-FDG PET/MRI had higher predictive accuracy compared to single-modality imaging. There was also a significant correlation between crucial image signatures of different modalities.
Background: This study aimed to explore the potential of a combination of 18F-fluorodeoxyglucose positron emission tomography (F-18-FDG PET) and magnetic resonance imaging (MRI) to improve predictions of conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD). The predictive performances and specific associated biomarkers of these imaging techniques used alone (single-modality imaging) and in combination (dual-modality imaging) were compared. Methods: 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 F-18-FDG PET and MRI scans. Regions of interest (ROIs) were determined using an a priori brain atlas. Radiomic features in these ROIs were extracted from the MRI and F-18-FDG PET scan data. These features were either concatenated or used separately to select features and construct Cox regression models for prediction in each modality. Harrell's concordance index (C-index) was then used to assess the predictive accuracies of the resulting models, and correlations between the MRI and F-18-FDG PET features were evaluated. Results: The C-indices for the two test datasets were 0.77 and 0.80 for dual-modality F-18-FDG PET/MRI, 0.75 and 0.73 for single-modality F-18-FDG PET, and 0.74 and 0.76 for single-modality MRI. In addition, there was a significant correlation between the crucial image signatures of the different modalities. Conclusions: 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 F-18-FDG PET and MRI is limited, and radiomic analysis of a single modality may yield acceptable predictive results.
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