Department of Interventional Vascular Medicine, Hefei Hospital Affiliated to Anhui Medical University, The Second People's Hospital of Hefei, 574 Changjiang East Road, Yaohai District, Hefei City, 230011, Anhui Province, China.
The Fifth Clinical College of Medicine, Anhui Medical University, 1166 Wangjiang West Road, Shushan District, Hefei City, 230011, Anhui Province, China.
BMC Cardiovasc Disord. 2024 Feb 10;24(1):99. doi: 10.1186/s12872-024-03762-w.
This study endeavors to examine the feasibility of predicting the clinical outcomes of patients suffering from peripheral artery disease (PAD) who undergo endovascular intervention, by employing the Syngo iFlow technology.
Retrospectively enrolling 76 patients from December 2021 to May 2023, yielding a total of 77 affected limbs, this study employs clinical outcomes (improvement or otherwise) as the gold standard. Two physicians conducted visual assessments on both DSA and iFlow images to gauge patient improvement and assessed inter-observer consistency for each image modality. The Time to Peak (TTP) of regions of interest (ROI) at the femoral head, knee joint, and ankle joint was measured. Differences in pre- and post-procedure TTP were juxtaposed, and statistically significant parameter cutoff values were identified via ROC analysis. Employing these cutoffs for TTP classification, multivariate logistic regression and the C-statistic were utilized to assess the predictive value of distinct parameters for clinical success.
Endovascular procedure exhibited technical and clinical success rates of 82.58 and 75.32%, respectively. Diagnostic performance of iFlow image visual assessment surpassed that of DSA images. Inter-observer agreement for iFlow and DSA image evaluations was equivalent (κ = 0.48 vs 0.50). Post-classification using cutoff values, multivariate logistic regression demonstrated the statistical significance of ankle joint TTP in post-procedure iFlow images of the endovascular procedure for clinical success evaluation (OR 7.21; 95% CI 1.68, 35.21; P = 0.010), with a C-statistic of 0.612.
Syngo iFlow color-encoded imagery holds practical value in assessing the technical success of post-endovascular procedures, offering comprehensive lower limb arterial perfusion visualization. Its quantifiable parameters exhibit promising potential for prognosticating clinical success.
本研究旨在探讨利用 Syngo iFlow 技术预测接受血管内介入治疗的外周动脉疾病(PAD)患者临床结局的可行性。
回顾性纳入 2021 年 12 月至 2023 年 5 月的 76 例患者,共 77 条受累肢体,以临床结局(改善或未改善)作为金标准。两名医生对 DSA 和 iFlow 图像进行视觉评估,以评估患者的改善情况,并评估每种图像模态的观察者间一致性。测量感兴趣区(ROI)在股骨头、膝关节和踝关节的达峰时间(TTP)。比较术前和术后 TTP 的差异,并通过 ROC 分析确定统计学显著的参数截断值。采用 TTP 分类的这些截断值,利用多变量逻辑回归和 C 统计量评估不同参数对临床成功的预测价值。
血管内手术的技术成功率和临床成功率分别为 82.58%和 75.32%。iFlow 图像视觉评估的诊断性能优于 DSA 图像。iFlow 和 DSA 图像评估的观察者间一致性相当(κ=0.48 比 0.50)。采用分类后截断值,多变量逻辑回归显示血管内手术后 iFlow 图像中踝关节 TTP 对临床成功评估具有统计学意义(OR 7.21;95%CI 1.68,35.21;P=0.010),C 统计量为 0.612。
Syngo iFlow 彩色编码图像在外周血管内介入术后技术成功评估中具有实用价值,提供全面的下肢动脉灌注可视化。其可量化参数对预测临床成功具有潜在的应用前景。