Non-Invasive Glucose Metabolism Quantification Method Based on Unilateral ICA Image Derived Input Function by Hybrid PET/MR in Ischemic Cerebrovascular Disease
机构:[1]School of Life Science, Shanghai University, Shanghai 200444, China[2]Department of Radiology and Nuclear Medicine, Xuanwu Hospital Capital Medical University, Beijing 100053, China医技科室放射科首都医科大学宣武医院[3]Quantitative Imaging and Medical Physics, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna 1090, Austria[4]Department of Nuclear Medicine. Inselspital, Bern University Hospital, University of Bern, Bern 3012, Switzerland[5]Chair for Computer-Aided Medical Procedures and Augmented Reality, Technical University of Munich, Munich 85748, Germany
The non-invasive quantification of the cerebral metabolic rate for glucose (CMRGlc) and the characterization of cerebral metabolism in the cerebrovascular territories are helpful in understanding ischemic cerebrovascular disease (ICVD). Firstly, we investigated a non-invasive quantification approach based on an image-derived input function (IDIF) in ICVD. Second, we studied the metabolic changes in CMRGlc after surgical intervention. We evaluated the hypothesis that the IDIF method based on the unilateral internal carotid artery could address challenges in ICVD quantification. The CMRGlc and standardized uptake value ratio (SUVR) were used to measure glucose metabolism activity. Healthy controls showed no significant differences in CMRGlc values between bilateral and unilateral IDIF measurements (intraclass correlation coefficient [ICC]: 0.91-0.98). Patients with ICVD showed significantly increased CMRGlc values after surgical intervention for all territories (percentage changes: 7.4%-22.5%). In contrast, SUVR showed minor differences between postoperative and preoperative patients, indicating that it was a poor biomarker for the diagnosis of ICVD. A significant association between CMRGlc and the National Institutes of Health Stroke Scale (NIHSS) scores was observed (r=-0.54). Our findings suggested that IDIF could be a valuable tool for CMRGlc quantification in patients with ICVD and may advance personalized precision interventions.
基金:
National Natural Science Foundation of China [81974261, 82130058, 82020108013]; Xuanwu Hospital Science Program for Fostering Young Scholars [QNPY2021037]; Shanghai Municipal Science and Technology Major Project [2017SHZDZX01, 2018SHZDZX03]; 111 Project [D20031]
第一作者机构:[1]School of Life Science, Shanghai University, Shanghai 200444, China
通讯作者:
推荐引用方式(GB/T 7714):
Wang Min,Cui Bixiao,Shan Yi,et al.Non-Invasive Glucose Metabolism Quantification Method Based on Unilateral ICA Image Derived Input Function by Hybrid PET/MR in Ischemic Cerebrovascular Disease[J].IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS.2022,26(10):5122-5129.doi:10.1109/JBHI.2022.3193190.
APA:
Wang, Min,Cui, Bixiao,Shan, Yi,Yang, Hongwei,Yan, Zhuangzhi...&Lu, Jie.(2022).Non-Invasive Glucose Metabolism Quantification Method Based on Unilateral ICA Image Derived Input Function by Hybrid PET/MR in Ischemic Cerebrovascular Disease.IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS,26,(10)
MLA:
Wang, Min,et al."Non-Invasive Glucose Metabolism Quantification Method Based on Unilateral ICA Image Derived Input Function by Hybrid PET/MR in Ischemic Cerebrovascular Disease".IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS 26..10(2022):5122-5129