当前位置: 首页 > 详情页

Co-reactivity pattern of glucose metabolism and blood perfusion revealing DNA mismatch repair deficiency based on PET/DCE-MRI in endometrial cancer

文献详情

资源类型:
WOS体系:
Pubmed体系:

收录情况: ◇ SCIE

机构: [1]Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China. [2]Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China. [3]Department of Obstetrics and Gynecology, Xuanwu Hospital, Capital Medical University, Beijing, China. [4]Department of Pathology, Xuanwu Hospital, Capital Medical University, Beijing, China. [5]Department of Ultrasound Diagnosis, Xuanwu Hospital, Capital Medical University, Beijing, China. [6]GE Healthcare China, Pudong New Town, Shanghai, China.
出处:
ISSN:

关键词: Endometrial cancer [18F]FDG PET DCE-MRI Mismatch repair defciency

摘要:
Identifying DNA mismatch repair deficiency (MMRd) is important for prognosis risk stratification in patients with early-stage endometrial cancer (EC), but there is a notable absence of cost-effective and non-invasive preoperative assessment techniques. The study explored the co-reactivity pattern of glucose metabolism and blood perfusion in EC based on hybrid [18F]fluorodeoxyglucose ([18F]FDG) PET/dynamic contrast enhanced (DCE)-MRI to provide an imaging biomarker for identifying MMRd.Patients with a history of postmenopausal bleeding and initially diagnosed with EC on ultrasound were recruited to perform a PET/DCE-MRI scan. Glucose metabolism parameters were calculated on PET, and blood perfusion parameters were calculated semi-automatically by the DCE-Tofts pharmacokinetic model. The MMRd of early-stage EC was evaluated by immunohistochemistry. The synchronous variation of PET and DCE-MRI parameters was compared between the MMRd and mismatch repair proficiency (MMRp). The association between PET/DCE-MRI and MMRd was analyzed by logistic regression to establish the digital biomarker for predicting MMRd. Receiver operating characteristic curve, decision curve analysis, and the net reclassification index (NRI) were used to evaluate the value of the digital biomarker in identifying MMRd.Eighty-six early-stage EC cases (58.92 ± 10.13 years old, 34 MMRd) were enrolled. The max/mean standardized uptake value (SUVmax/SUVmean), metabolic tumor volume, total lesion glycolysis, transfer constant (Ktrans), and efflux rate (Kep) were higher in MMRd than those in MMRp (P < 0.001, < 0.001, 0.002, 0.004, < 0.001, and 0.005, respectively). The correlations between glucose metabolism and blood perfusion were different between the MMRd and MMRp subgroups. SUVmax was correlated with Kep (r = 0.36) in the MMRd. SUVmean (odds ratio [OR] = 1.32, P = 0.006) and Ktrans (OR = 1.90, P = 0.021) were independent risk factors for MMRd. And the digital biomarker that combined SUVmean and Ktrans outperformed in identifying MMRd in early-stage EC more than DCE-MRI (AUC: 0.83 vs. 0.78, NRI = 13%).A potential digital biomarker based on [18F]FDG PET/DCE-MRI can identify MMRd for prognosis risk stratification in early-stage EC.© 2024. The Author(s).

基金:
语种:
WOS:
PubmedID:
中科院(CAS)分区:
出版当年[2023]版:
大类 | 2 区 医学
小类 | 2 区 肿瘤学 2 区 核医学
最新[2023]版:
大类 | 2 区 医学
小类 | 2 区 肿瘤学 2 区 核医学
JCR分区:
出版当年[2022]版:
Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Q2 ONCOLOGY
最新[2023]版:
Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Q2 ONCOLOGY

影响因子: 最新[2023版] 最新五年平均 出版当年[2022版] 出版当年五年平均 出版前一年[2021版] 出版后一年[2023版]

第一作者:
第一作者机构: [1]Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China. [2]Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China.
通讯作者:
通讯机构: [1]Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China. [2]Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Capital Medical University, Beijing, China.
推荐引用方式(GB/T 7714):
APA:
MLA:

资源点击量:16409 今日访问量:0 总访问量:869 更新日期:2025-01-01 建议使用谷歌、火狐浏览器 常见问题

版权所有©2020 首都医科大学宣武医院 技术支持:重庆聚合科技有限公司 地址:北京市西城区长椿街45号宣武医院