Association Between Aneurysm Wall Inflammation Detected by Imaging Perivascular Fat and Secondary Intervention Risk for Abdominal Aortic Aneurysm Patients After Endovascular Repair

医学 腹主动脉瘤 腔内修复术 动脉瘤 放射科 计算机断层血管造影 主动脉瘤 Lasso(编程语言) 血管造影 外科 心脏病学 万维网 计算机科学
作者
Jiangping Gao,Hongpeng Zhang,Jiang Xiong,Xin Jia,Xiaohui Ma,Wei Guo
出处
期刊:Journal of Endovascular Therapy [SAGE]
标识
DOI:10.1177/15266028231204807
摘要

To investigate the association between the imaging biomarker (volumetric perivascular characterization index [VPCI]) which indicates the aortic wall inflammation by mapping the spatial changes of perivascular fat attenuation on computed tomography angiography (CTA) and the reintervention risk for abdominal aortic aneurysm (AAA) patients after endovascular aortic repair (EVAR).This case-control study included AAA patients undergoing EVAR from a single center (n=260). Cases were AAA patients undergoing reintervention after EVAR and a 1:1 frequency-matched control group of AAA patients post-EVAR with a shrunken or ≥3-year stable sac and free of reintervention signs during the follow-up. The predictive variable (VPCI trajectory) was converted to binary variables according to the changing trend of VPCI with follow-up time. As a quasi-complete separation data pattern, least absolute shrinkage and selection operator (lasso) regression was used to screen and prove the VPCI trajectory as the best predictor, and the performance was evaluated by calculating the accuracy, sensitivity, and specificity.Between 2010 and 2021, 15 AAA patients after EVAR with type I/III endoleak, aneurysm rupture, or impending rupture were included. Compared with the 1:1 frequency-matched controls with a shrunken or ≥3-year stable sac and free of reintervention signs during the follow-up, VPCI trajectories of the case group were all upward trends, whereas the controls showed 86.7% downward trends (p<0.001). The best predictive model of lasso regressions included 4 variables, and VPCI trajectory was the most outstanding, followed by the proximal landing zone, the distal landing zone, and the infrarenal β angle. The accuracy, sensitivity, and specificity of predicting the risk of reintervention were as follows, respectively: 93.3%, 100%, and 86.7%.The wall inflammation detected by imaging perivascular adipose tissue based on the CTAs was strongly associated with the reintervention risk for AAA patients after EVAR, which might hold major promise as a new imaging biomarker for the mechanism and treatment study of human AAAs before and after EVAR.The study introduces a novel imaging biomarker which indicates the aortic wall inflammation by mapping spatial changes of perivascular fat attenuation on CTA. This biomarker demonstrates a strong association with the reintervention risk in AAA patients after EVAR. Incorporation of VPCI into clinical practice has the potential to enhance the traditional surveillance methods (CT/CTAs) by providing clinicians with a non-invasive method to assess aortic wall inflammation and predict the risk of reintervention. Additionally, this study might offer a valuable tool for mechanism and treatment research in humans with AAAs both pre- and post-EVAR, ultimately improving patient outcomes and refining therapeutic strategies.
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