In Vivo Classification and Characterization of Carotid Atherosclerotic Lesions with Integrated <sup>18</sup>F-FDG PET/MRI
Fan Yu,
Yue Zhang,
Heyu Sun,
Xiaoran Li,
Yi Shan,
Chong Zheng,
Bixiao Cui,
Jing Li,
Yang Yang,
Bin Yang,
Yan Ma,
Yabing Wang,
Liqun Jiao,
Xiang Li,
Jie Lu
Affiliations
Fan Yu
Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Changchun Street, No. 45, Beijing 100053, China
Yue Zhang
Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Changchun Street, No. 45, Beijing 100053, China
Heyu Sun
Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Changchun Street, No. 45, Beijing 100053, China
Xiaoran Li
Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Changchun Street, No. 45, Beijing 100053, China
Yi Shan
Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Changchun Street, No. 45, Beijing 100053, China
Chong Zheng
Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Changchun Street, No. 45, Beijing 100053, China
Bixiao Cui
Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Changchun Street, No. 45, Beijing 100053, China
Jing Li
Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Changchun Street, No. 45, Beijing 100053, China
Yang Yang
Beijing United Imaging Research Institute of Intelligent Imaging, Beijing 100094, China
Bin Yang
Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Changchun Street, No. 45, Beijing 100053, China
Yan Ma
Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Changchun Street, No. 45, Beijing 100053, China
Yabing Wang
Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Changchun Street, No. 45, Beijing 100053, China
Liqun Jiao
Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Changchun Street, No. 45, Beijing 100053, China
Xiang Li
Division of Nuclear Medicine, Department of Biomedical Imaging and Image-Guided Therapy, Vienna General Hospital, Medical University of Vienna, 1090 Vienna, Austria
Jie Lu
Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Changchun Street, No. 45, Beijing 100053, China
Background: The aim of this study was to exploit integrated PET/MRI to simultaneously evaluate the morphological, component, and metabolic features of advanced atherosclerotic plaques and explore their incremental value. Methods: In this observational prospective cohort study, patients with advanced plaque in the carotid artery underwent 18F-FDG PET/MRI. Plaque morphological features were measured, and plaque component features were determined via MRI according to AHA lesion-types. Maximum standardized uptake values (SUVmax) and tissue to background ratio (TBR) on PET were calculated. Area under the receiver-operating characteristic curve (AUC) and net reclassification improvement (NRI) were used to compare the incremental contribution of FDG uptake when added to AHA lesion-types for symptomatic plaque classification. Results: A total of 280 patients with advanced plaque in the carotid artery were recruited. A total of 402 plaques were confirmed, and 87 of 402 (21.6%) were symptomatic plaques. 18F-FDG PET/MRI was performed a mean of 38 days (range 1–90) after the symptom. Increased stenosis degree (61.5% vs. 50.0%, p p < 0.001) were observed in symptomatic plaques compared with asymptomatic plaques. The performance of the combined model (AHA lesion type VI + stenosis degree + TBR) for predicting symptomatic plaques was the best among all models (AUC = 0.789). The improvement of the combined model (AHA lesion type VII + stenosis degree + TBR) over AHA lesion type VII model for predicting symptomatic plaques was the highest (AUC = 0.757/0.454, combined model/AHA lesion type VII model), and the NRI was 50.7%. Conclusions: Integrated PET/MRI could simultaneously evaluate the morphological component and inflammation features of advanced atherosclerotic plaques and provide supplementary optimization information over AHA lesion-types for identifying vulnerable plaques in atherosclerosis subjects to achieve further stratification of stroke risk.
