Combining PET with MRI to improve predictions of progression from mild cognitive impairment to Alzheimer's disease: an exploratory radiomic analysis study
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-FI)G 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.
基金:
National Natural Science Foundation of China (Nos. 61603236, 81830059, 81971641, 81671239, and 81361120393), the Shanghai Municipal Science and Technology Major Project (Nos. 2017SHZDZX01 and 2018SHZDZX03), and the 111 Project (No. D20031). Data collection and sharing for this project were funded by the Alzheimer’s Disease Neuroimaging Initiative (ADNI; National Institutes of Health Grant U01 AG024904) and DODADNI (Department of Defense; No. W81XWH-12-2-0012).
第一作者机构:[1]Shanghai Univ, Sch Informat & Commun Engn, Inst Biomed Engn, Shanghai, Peoples R China
共同第一作者:
通讯作者:
通讯机构:[2]Shanghai Univ, Sch Life Sci, Inst Biomed Engn, 98 Shangda Rd, Shanghai 200444, Peoples R China[5]Fudan Univ, Huashan Hosp, PET Ctr, 12 Middle Urumqi Rd, Shanghai 200040, Peoples R China[6]Fudan Univ, Human Phenome Inst, Shanghai, Peoples R China[*1]Institute of Biomedical Engineering, School of Life Science, Shanghai University, 98 Shangda Road, Baoshan District, Shanghai 200444, China[*2]PET Center, Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Jing’an District, Shanghai 200040, China
推荐引用方式(GB/T 7714):
Yang Fan,Jiang Jiehui,Alberts Ian,et al.Combining PET with MRI to improve predictions of progression from mild cognitive impairment to Alzheimer's disease: an exploratory radiomic analysis study[J].ANNALS OF TRANSLATIONAL MEDICINE.2022,10(9):doi:10.21037/atm-21-4349.
APA:
Yang, Fan,Jiang, Jiehui,Alberts, Ian,Wang, Min,Li, Taoran...&Shi, Kuangyu.(2022).Combining PET with MRI to improve predictions of progression from mild cognitive impairment to Alzheimer's disease: an exploratory radiomic analysis study.ANNALS OF TRANSLATIONAL MEDICINE,10,(9)
MLA:
Yang, Fan,et al."Combining PET with MRI to improve predictions of progression from mild cognitive impairment to Alzheimer's disease: an exploratory radiomic analysis study".ANNALS OF TRANSLATIONAL MEDICINE 10..9(2022)