Incremental value of pericarotid adipose tissue radiomics in predicting in-stent restenosis after carotid artery stenting.

IF 4.3 1区 医学 Q1 NEUROIMAGING
Dongqing Ren, Yu Lan, Hongyi Li, Dongbo Li, Ronghui Ju, Yang Hou
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引用次数: 0

Abstract

Objective: To evaluate the potential of pericarotid adipose tissue radiomics to improve the prediction of in-stent restenosis (ISR) after carotid artery stenting (CAS).

Methods: This retrospective study included 191 patients who underwent carotid CT angiography (CTA) and CAS within 1 week at two centers from September 2019 to December 2023. ISR was defined as ≥50% stenosis on follow-up Doppler ultrasound or CTA. Three predictive models were developed and defined as follows: Model A (Clinical), Model B (Clinical + Imaging), and Model C (Clinical + Imaging + Radiomics) using receiver operating characteristic (ROC) analysis, calibration curves, and decision curve analysis.

Results: ISR occurred in 44 patients with a mean time interval of 11.3 months. Multivariate Cox regression analyses identified diabetes, fibrinogen, systolic blood pressure, calcified plaque volume, and pericarotid adipose tissue radiomics as independent predictors of ISR. The radiomics score, derived from 15 significant characteristics, outperformed conventional imaging markers. In the training set, Model C (AUC=0.881) significantly outperformed Model A (AUC=0.664) and Model B (AUC=0.840), with statistically significant differences (Model A vs Model C: P=0.001; Model B vs Model C: P=0.0246). This trend was consistent in the validation sets. Calibration curves showed good agreement between predicted and actual ISR probabilities, and decision curve analysis indicated that Model C provided greater net benefits.

Conclusion: The radiomic characteristics of pericarotid adipose tissue provide incremental value in predicting ISR after CAS and serve as a valuable biomarker for restenosis risk assessment.

颈动脉支架植入术后颈动脉周围脂肪组织放射组学预测支架内再狭窄的增量价值。
目的:评价颈动脉支架植入术(CAS)后颈动脉支架内再狭窄(ISR)的预测应用颈动脉周围脂肪组织放射组学的潜力。方法:本回顾性研究包括2019年9月至2023年12月在两个中心接受颈动脉CT血管造影(CTA)和CAS检查的191例患者,时间为1周。ISR定义为随访多普勒超声或CTA检查狭窄程度≥50%。通过受试者工作特征(ROC)分析、校准曲线和决策曲线分析,建立并定义了三个预测模型:模型A(临床)、模型B(临床+影像学)和模型C(临床+影像学+放射组学)。结果:44例患者发生ISR,平均时间间隔11.3个月。多变量Cox回归分析发现糖尿病、纤维蛋白原、收缩压、钙化斑块体积和颈动脉周围脂肪组织放射组学是ISR的独立预测因子。放射组学评分来自15个重要特征,优于传统的成像标记。在训练集中,模型C (AUC=0.881)显著优于模型A (AUC=0.664)和模型B (AUC=0.840),差异有统计学意义(模型A vs模型C: P=0.001;模型B vs模型C: P=0.0246)。这一趋势在验证集中是一致的。校正曲线显示,预测ISR概率与实际ISR概率吻合较好,决策曲线分析表明,模型C提供了更大的净效益。结论:颈动脉周围脂肪组织的放射组学特征对预测CAS后的ISR具有增加价值,并可作为再狭窄风险评估的有价值的生物标志物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
9.50
自引率
14.60%
发文量
291
审稿时长
4-8 weeks
期刊介绍: The Journal of NeuroInterventional Surgery (JNIS) is a leading peer review journal for scientific research and literature pertaining to the field of neurointerventional surgery. The journal launch follows growing professional interest in neurointerventional techniques for the treatment of a range of neurological and vascular problems including stroke, aneurysms, brain tumors, and spinal compression.The journal is owned by SNIS and is also the official journal of the Interventional Chapter of the Australian and New Zealand Society of Neuroradiology (ANZSNR), the Canadian Interventional Neuro Group, the Hong Kong Neurological Society (HKNS) and the Neuroradiological Society of Taiwan.
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