18氟代脱氧葡萄糖PET/CT对活动性恶性肿瘤患者发生急性缺血性卒中预测作用研究

doi:10.3969/j.issn.1673-5765.2024.02.005

摘要/Abstract

摘要： 目的探讨18氟代脱氧葡萄糖（18F-fluorodeoxyglucose，18F-FDG）PET/CT预测活动性恶性肿瘤（active cancer，AC）患者发生急性缺血性卒中（acute ischemic stroke，AIS）的标志物指标。
方法回顾性纳入2021年1月—2022年5月于潍坊医学院第一附属医院行18F-FDG PET/CT检查的AC住院患者，根据其检查后1年内是否发生AIS分为AIS组和非AIS组，通过患者基本特征（性别、年龄、体重、恶性肿瘤部位、PET/CT检查前空腹血糖）进行1∶1倾向评分匹配，分析两组患者的临床及18F-FDG PET/CT影像学资料差异。影像学资料主要有颈动脉（carotid artery，CA）、升主动脉和主动脉弓（ascending aorta and aortic arch，AAO-AOA）、降主动脉（descending aorta，DAO）、髂动脉和股动脉（iliac artery and femoral artery，IA-FA）、内脏脂肪组织（visceral adipose tissue，VAT）、皮下脂肪组织（subcutaneous adipose tissue，SAT）以及全肠道（total bowel，TB）的靶本底比（target to background ratio，TBR），VAT和SAT面积以及两者比值。对单因素logistic回归中P＜0.1的变量采用逐步向后logistic回归筛选AC患者发生AIS的独立危险因素，应用ROC曲线评估独立危险因素联合模型对AIS的预测价值。
结果共纳入88例患者，平均年龄（69.8±8.8）岁，男性占72.7%（64例），AIS组和非AIS组各
44例。AIS组合并冠心病比例较非AIS组高，CA、AAO-AOA、DAO、IA-FA、VAT、SAT以及TB的TBR均较非AIS组增高，而VAT面积较AIS组低，差异均有统计学意义。多因素logistic回归显示，冠心病（OR 3.92，95%CI 1.11～13.87，P=0.034）、CA TBR≥1.80（OR 2.90，95%CI 1.04～8.10，P=0.042）、DAO TBR≥2.30（OR 4.13，95%CI 1.45～11.75，P=0.008）、TB TBR≥3.34（OR 2.87，95%CI 1.01～8.12，P=0.047）和VAT TBR≥0.44（OR 3.92，95%CI 1.39～11.09，P=0.010）是AC患者发生AIS的独立危险因素，联合上述5个指标绘制ROC的AUC为0.821（95%CI 0.736～0.906，P＜0.001），预测肿瘤患者发生AIS的敏感度为68.2%，特异度为81.8%。
结论有冠心病史，CA、DAO、VAT和TB的TBR增高是AC患者发生AIS的独立危险因素，上述5个指标联合对AC患者AIS的发生具有一定的预测价值。

文章导读： 本研究报道了VAT和肠道FDG摄取水平与AC患者发生AIS风险的相关性，提示动脉炎症、脂肪组织和肠道代谢活动可能增加AC患者后续发生AIS的风险。

关键词: 恶性肿瘤; 缺血性卒中; 正电子发射断层显像; 计算机断层扫描; ¹⁸氟代脱氧葡萄糖

Abstract: Objective To explore which indicators of 18F-fluorodeoxyglucose (18F-FDG) PET/CT imaging can be used as markers for predicting acute ischemic stroke (AIS) in active cancer (AC) patients.
Methods Inpatients with AC who underwent 18F-FDG PET/CT in the First Affiliated Hospital of Weifang Medical University from January 2021 to May 2022 were retrospectively included, and divided into AIS group and non-AIS group according to whether they developed AIS within 1 year after the examination. According to the basic characteristics of the patients (gender, age, weight, cancer site, fasting blood glucose before PET/CT examination) by 1∶1 propensity score matching, clinical and 18F-FDG PET/CT imaging data of both groups of patients were analyzed, mainly including the target to background ratios (TBRs) of carotid arteries (CA), ascending aorta and aortic arch (AAO-AOA), descending aorta (DAO), iliac artery and femoral artery (IA-FA), visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT) and total bowel (TB), the area of VAT and SAT and the ratio between the two. For variables with P<0.1 in univariate logistic regression, stepwise backward logistic regression was used to analyze the independent risk factors for AIS in AC patients. ROC curve was used to evaluate the predictive value of combined independent risk factors for AIS.
Results A total of 88 patients were included (44 in the AIS group and 44 in the non-AIS group), with a mean age of (69.8±8.8) years and 72.7% (64 cases) of males. The proportion of coronary heart disease in AIS group was higher than that in non-AIS group, the TBRs of CA, AAO-AOA, DAO, IA-FA, VAT, SAT and TB were increased compared with non-AIS group, while the VAT area was lower than that in AIS group, and the differences were statistically significant. Multivariate logistic regression showed that coronary heart disease (OR 3.92, 95%CI 1.11-13.87, P=0.034), CA TBR≥1.80 (OR 2.90, 95%CI 1.04-8.10, P=0.042), DAO TBR≥2.30 (OR 4.13, 95%CI 1.45-11.75, P=0.008), TB TBR≥3.34 (OR 2.87, 95%CI 1.01-8.12, P=0.047) and VAT TBR≥0.44 (OR 3.92, 95%CI 1.39-11.09, P=0.010) were independent risk factors for AIS in AC patients. The AUC of ROC curve combined with these five indexes was 0.821 (95%CI 0.736-0.906, P<0.001), and the sensitivity and specificity of AIS prediction in tumor patients were 68.2% and 81.8%.
Conclusions Coronary heart disease and the increased TBR of CA, DAO, VAT and TB are independent risk factors for AIS in AC patients, and the combination of these 5 indicators has certain predictive value for AIS in AC patients.

Key words: Malignant tumor; Ischemic stroke; Positron-emission tomography; Computed tomography; ¹⁸F-Deoxyglucose

中图分类号:

李爱媛, 范萍, 李现军, 赵喆, 战同霞, 谢海. ¹⁸氟代脱氧葡萄糖PET/CT对活动性恶性肿瘤患者发生急性缺血性卒中预测作用研究[J]. 中国卒中杂志, 2024, 19(2): 150-157.

LI Aiyuan, FAN Ping, LI Xianjun, ZHAO Zhe, ZHAN Tongxia, XIE Hai. The Predictive Value of¹⁸F-FDG PET/CT on Acute Ischemic Stroke in Patients with Active Cancer[J]. Chinese Journal of Stroke, 2024, 19(2): 150-157.

参考文献

[1] QI J L，LI M L，WANG L J，et al. National and subnational trends in cancer burden in China，2005—20：an analysis of national mortality surveillance data[J/OL]. Lancet Public Health，2023，8（12）：e943-e955[2023-06-15]. https://doi.org/10.1016/S2468-2667（23）00211-6.
[2] 郑欣雅，邱宝山，王伊龙. 血栓炎症在缺血性卒中发生发展机制中的研究进展[J]. 中华脑血管病杂志（电子版），2023，17（6）：533-538.
ZHENG X Y，QIU B S，WANG Y L. Research progress on the mechanism of thromboinflammation in the occurrence and development of ischemic stroke[J]. Chinese Journal of Cerebrovascular Diseases（Electronic Edition），2023，17（6）：533-538.
[3] ZUBER M. Stroke and cancer[J]. Rev Neurol（Paris），2023，179（5）：417-424.
[4] SINGH A，SCHURMAN S H，BEKTAS A，et al. Aging and Inflammation[J/OL]. Cold Spring Harb Perspect Med，2023：a041197[2023-06-15]. https://doi.org/10.1101/cshperspect.a041197.
[5] YANG C，YANG Q F，XIE Z Y，et al. Association of systemic immune-inflammation-index with all-cause and cause-specific mortality among type 2 diabetes：a cohort study base on population[J/OL]. Endocrine，2023[2023-06-15]. https://doi.org/10.1007/s12020-023-03587-1.
[6] RATH S，HAWSAWI Y M，ALZAHRANI F，et al. Epigenetic regulation of inflammation：the metabolomics connection[J/OL]. Semin Cell Dev Biol，2024，154（Pt C）：355-363[2023-06-15]. https://doi.org/10.1016/j.semcdb.2022.09.008.
[7] WANG Z M，ZHOU Y X，XIAO X，et al. Inflammation and cardiometabolic diseases induced by persistent organic pollutants and nutritional interventions：effects of multi-organ interactions
[J/OL]. Environ Pollut，2023，339：122756[2023-06-15].
https://doi.org/10.1016/j.envpol.2023.122756.
[8] RAGHUBEER S. The influence of epigenetics and inflammation on cardiometabolic risks[J/OL]. Semin Cell Dev Biol，2024，154（Pt C）：175-184[2023-06-15]. https://doi.org/10.1016/j.semcdb.2023.02.006.
[9] FURMAN D，CAMPISI J，VERDIN E，et al. Chronic inflammation in the etiology of disease across the life span[J]. Nat Med，2019，25（12）：1822-1832.
[10] AGUILAR-CAZARES D，CHAVEZ-DOMINGUEZ R，MARROQUIN-MUCIÑO M，et al. The systemic-level repercussions of cancer-associated inflammation mediators produced in the tumor microenvironment
[J/OL]. Front Endocrinol，2022，13：929572[2023-06-15]. https://doi.org/10.3389/fendo.2022.929572.
[11] ZIETZ A，GOREY S，KELLY P J，et al. Targeting inflammation to reduce recurrent stroke[J/OL]. Int J Stroke，2023：17474930231207777[2023-06-15]. https://doi.org/10.1177/17474930231207777.
[12] LI J J，LIN J X，PAN Y S，et al. Interleukin-6 and YKL-40 predicted recurrent stroke after ischemic stroke or TIA：analysis of 6 inflammation biomarkers in a prospective cohort study[J/OL]. J Neuroinflammation，2022，19（1）：131[2023-06-15]. https://doi.org/10.1186/s12974-022-02467-1.
[13] CHENG W K，BU X C，XU C H，et al. Higher systemic immune-inflammation index and systemic inflammation response index levels are associated with stroke prevalence in the asthmatic population：a cross-sectional analysis of the NHANES 1999—2018[J/OL]. Front Immunol，2023，14：1191130[2023-06-15]. https://doi.org/10.3389/fimmu.2023.1191130.
[14] SLAVICH G M. Understanding inflammation，its regulation，and relevance for health：a top scientific and public priority[J/OL]. Brain Behav Immun，2015，45：13-14[2023-06-15]. https://doi.org/10.1016/j.bbi.2014.10.012.
[15] REIJRINK M，DE BOER S A，TE VELDE-KEYZER C A，et al. [18F]FDG and [18F]NaF as PET markers of systemic atherosclerosis progression：a longitudinal descriptive imaging study in patients with type 2 diabetes mellitus[J]. J Nucl Cardiol，2022，29（4）：1702-1709.
[16] KWON H W，LEE S M，LEE J W，et al. Association between volume and glucose metabolism of abdominal adipose tissue in healthy population[J/OL]. Obes Res Clin Pract，2017，11（5 Suppl 1）：133-143[2023-06-15]. https://doi.org/10.1016/j.orcp. 2016.12.007.
[17] YOON H J，KIM H N，BANG J I，et al. Physiologic intestinal 18F-FDG uptake is associated with alteration of gut microbiota and proinflammatory cytokine levels in breast cancer[J/OL]. Sci Rep，2019，9（1）：18273[2023-06-15]. https://doi.org/10.1038/s41598-019-54680-3.
[18] 王琳，王晶，申园，等. 急性颈内动脉系统脑梗死患者颈内动脉角与动脉粥样硬化斑块形态关系的研究[J]. 中国卒中杂志，2019，14（7）：671-676.
WANG L，WANG J，SHEN Y，et al. Relationship between internal carotid artery angle and plaque morphology in patients with acute anterior circulation infarction[J]. Chin J Stroke，14（7）：671-676.
[19] ZONG P Y，FENG J L，YUE Z C，et al. TRPM2 deficiency in mice protects against atherosclerosis by inhibiting TRPM2-CD36 inflammatory axis in macrophages[J]. Nat Cardiovasc Res，2022，1（4）：344-360.
[20] OGAWA M，NAKAMURA S，SAITO Y，et al. What can be seen by 18F-FDG PET in atherosclerosis imaging? The effect of foam cell formation on 18F-FDG uptake to macrophages in vitro[J]. J Nucl Med，2012，53（1）：55-58.
[21] HYAFIL F，SCHINDLER A，SEPP D，et al. High-risk plaque features can be detected in non-stenotic carotid plaques of patients with ischaemic stroke classified as cryptogenic using combined（18）F-FDG PET/MR imaging[J]. Eur J Nucl Med Mol Imaging，2016，43（2）：270-279.
[22] NG S J，LAU H C，NASEER R，et al. Atherosclerosis imaging：positron emission tomography[J]. PET Clin，2023，18（1）：71-80.
[23] MIKAIL N，MESEGUER E，LAVALLÉE P，et al. Evaluation of non-stenotic carotid atherosclerotic plaques with combined FDG-PET imaging and CT angiography in patients with ischemic stroke of unknown origin[J]. J Nucl Cardiol，2022，29（3）：1329-1336.
[24] GARCIA E，CAMPS-RENOM P，PUIG N，et al. Soluble low-density lipoprotein receptor-related protein 1 as a surrogate marker of carotid plaque inflammation assessed by 18F-FDG PET in patients with a recent ischemic stroke[J/OL]. J Transl Med，2023，21（1）：131[2023-06-15]. https://doi.org/10.1186/s12967-022-03867-w.
[25] ZHENG Y L，LIM M J R，TAN B Y，et al. Role of plaque inflammation in symptomatic carotid stenosis
[J/OL]. Front Neurol，2023，14：1086465[2023-06-15]. https://doi.org/10.3389/fneur.2023.1086465.
[26] KIM J，CHOI K H，SONG H C，et al. 18F-FDG PET/CT imaging factors that predict ischaemic stroke in cancer patients[J]. Eur J Nucl Med Mol Imaging，2016，43（12）：2228-2235.
[27] PAHK K，KIM E J，JOUNG C，et al. Association of glucose uptake of visceral fat and acute myocardial infarction：a pilot 18F-FDG PET/CT study[J/OL]. Cardiovasc Diabetol，2020，19（1）：145[2023-06-15]. https://doi.org/10.1186/s12933-020-01115-3.
[28] ATAWIA R T，BUNCH K L，TOQUE H A，et al. Mechanisms of obesity-induced metabolic and vascular dysfunctions[J]. Front Biosci（Landmark Ed），2019，24（5）：890-934.
[29] ALBANO D，DONDI F，TREGLIA G，et al. Longitudinal body composition changes detected by [18F]FDG PET/CT during and after chemotherapy and their prognostic role in elderly Hodgkin lymphoma
[J/OL]. Cancers（Basel），2022，14（20）：5147[2023-06-15]. https://doi.org/10.3390/cancers14205147.
[30] KIM H J，KIM D，BAE S J，et al. 18F-FDG uptake of visceral adipose tissue on preoperative PET/CT as a predictive marker for breast cancer recurrence
[J/OL]. Sci Rep，2022，12（1）：21109[2023-06-15].
https://doi.org/10.1038/s41598-022-25540-4.
[31] SULEIMANOV A，SADUAKASSOVA A，VINNIKOV
D，et al. Predictive value of 18F-fluorodeoxyglucose accumulation in visceral fat activity to detect colorectal cancer metastases（prospective observational cohort study）[J/OL]. F1000Res，2022，11：1158[2023-06-15]. https://doi.org/10.12688/f1000research.122814.1.
[32] MUURONEN A T，TAINA M，HEDMAN M，et al. Increased visceral adipose tissue as a potential risk factor in patients with embolic stroke of undetermined source（ESUS）[J/OL]. PLoS One，2015，10（3）：e0120598[2023-06-15]. https://doi.org/10.1371/journal.pone.0120598.
[33] XU R，HU X Z，WANG T，et al. Visceral adiposity and risk of stroke：a Mendelian randomization study[J/OL]. Front Neurol，2022，13：804851[2023-06-15]. https://doi.org/10.3389/fneur.2022.804851.
[34] YAN S Y，YANG Y W，JIANG X Y，et al. Fat quantification：Imaging methods and clinical applications in cancer[J/OL]. Eur J Radiol，2023，164：110851[2023-06-15]. https://doi.org/10.1016/j.
ejrad.2023.110851.
[35] ZHAO L N，XIAO J，LI S L，et al. The interaction between intestinal microenvironment and stroke
[J/OL]. CNS Neurosci Ther，2023，29 Suppl 1（Suppl 1）：185-199[2023-06-15]. https://doi.org/10.1111/cns.14275.
[36] FRANQUET E，PALMER M R，GIFFORD A E，et al. Rifaximin suppresses background intestinal 18F-FDG uptake on PET/CT scans[J]. Nucl Med Commun，2014，35（10）：1026-1031.
[37] KANG J Y，KIM H N，CHANG Y，et al. Gut microbiota and physiologic bowel 18F-FDG uptake [J/OL]. EJNMMI Res，2017，7（1）：72[2023-06-15]. https://doi.org/10.1186/s13550-017-0318-8.
[38] TIBERIO P，ANTUNOVIC L，GAUDIO M，et al. The relationship among bowel [18]F-FDG PET uptake，pathological complete response，and eating habits in breast cancer patients undergoing neoadjuvant chemotherapy[J/OL]. Nutrients，2023，15（1）：211[2023-06-15]. https://doi.org/10.3390/nu15010211.

[39] TROESCHEL A N，BYRD D A，JUDD S，et al. Associations of dietary and lifestyle inflammation scores with mortality due to CVD，cancer，and all causes among black and white American men and women[J]. Br J Nutr，2023，129（3）：523-534.

¹⁸氟代脱氧葡萄糖PET/CT对活动性恶性肿瘤患者发生急性缺血性卒中预测作用研究

The Predictive Value of¹⁸F-FDG PET/CT on Acute Ischemic Stroke in Patients with Active Cancer

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

[1]	曾潮坤, 赵振强. Willis环变异与缺血性卒中相关性的研究进展[J]. 中国卒中杂志, 2024, 19(2): 213-218.
[2]	杨嘉欣, 何春渝, 刘蕾, 陈文博, 谢艳. 急性缺血性卒中静脉溶栓后症状性颅内出血预测模型的系统评价[J]. 中国卒中杂志, 2024, 19(1): 76-86.
[3]	康志明, 梅斌. 急性大血管闭塞性卒中机械取栓术后出血转化的研究进展[J]. 中国卒中杂志, 2024, 19(1): 94-104.
[4]	张心邈, 徐曼, 丁玲玲, 荆京, 龚浠平, 董可辉, 赵性泉, 王拥军, 李子孝. 脑血管病临床决策支持系统对卒中医疗服务质量关键绩效指标的影响研究[J]. 中国卒中杂志, 2024, 19(1): 120-124.
[5]	吴敌, 荆京, 潘岳松, 陈绪珠, 赵性泉. 自发性颈动脉夹层相关缺血性卒中颅内缺血病灶分布特征与受累血管节段的关系研究[J]. 中国卒中杂志, 2023, 18(9): 993-1000.
[6]	王丽佳, 时代, 刘慧慧, 曹勇军, 刘春风, 石际俊. 茎突综合征相关颈内动脉夹层致缺血性卒中1例报道[J]. 中国卒中杂志, 2023, 18(9): 1049-1053.
[7]	任晓佳, 刘关杰, 郝汶强. 金纳多治疗烟雾病所致缺血性卒中个案报道[J]. 中国卒中杂志, 2023, 18(9): 1060-1064.
[8]	陆靖, 李传发, 张大启, 陈蓉, 李其富. 急性缺血性卒中血管内治疗后出血转化的研究进展[J]. 中国卒中杂志, 2023, 18(9): 1065-1072.
[9]	周雨萌, 陈丽霞. 急性缺血性卒中机械取栓患者的血压管理研究进展[J]. 中国卒中杂志, 2023, 18(9): 1073-1078.
[10]	李超, 姜英玉, 张心邈, 杨昕, 王春娟, 谷鸿秋, 杜珂瑾, 王拥军, 李子孝. 缺血性卒中后出血转化的影响因素分析[J]. 中国卒中杂志, 2023, 18(9): 1079-1084.
[11]	程实, 李静, 郭军平, 胡爱香, 于鑫玮, 韩玮, 梁瑛, 冀瑞俊, 张越巍. 卒中后感染对急性缺血性卒中患者出院结局的影响[J]. 中国卒中杂志, 2023, 18(8): 885-890.
[12]	刘丽萍, 周宏宇, 段婉莹, 霍晓川, 聂曦明, 刘慧慧, 李子孝, 徐蔚海, 李淑娟, 缪中荣, 王拥军, 中国卒中学会中国脑血管病临床管理指南撰写工作委员会. 中国脑血管病临床管理指南（第2版）（节选）——第4章缺血性脑血管病临床管理推荐意见[J]. 中国卒中杂志, 2023, 18(8): 910-933.
[13]	范萍, 岳奎涛, 李爱媛, 赵喆, 谢海, 吴春艳（第一作者）. 影像组学在急性缺血性卒中中的应用进展[J]. 中国卒中杂志, 2023, 18(8): 952-957.
[14]	陈义彤, 武美茹, 苗亚杰, 魏文宇, 李子孝. 定制个体化可视化健康教育在缺血性卒中患者中的应用[J]. 中国卒中杂志, 2023, 18(8): 959-965.
[15]	王文洁, 毛佳文, 侯叶叶, 杨昕, 李子孝. 英国国家卒中临床指南2023版要点及解读——卒中的组织化服务[J]. 中国卒中杂志, 2023, 18(12): 1344-1351.