Hofmann Amun G, Shoumariyeh Tarik, Domenig Christoph, Skrabal Falko, Kovarik Johannes J
Department of Internal Medicine III, Division of Nephrology and Dialysis, Medical University of Vienna, 1090 Vienna, Austria.
Department of General Surgery, Division of Vascular Surgery, Medical University of Vienna, 1090 Vienna, Austria.
J Clin Med. 2023 May 28;12(11):3726. doi: 10.3390/jcm12113726.
Screening and diagnosing abdominal aortic aneurysms (AAA) are currently dependent on imaging studies such as ultrasound or computed tomography angiography. All imaging studies offer distinct advantages but also suffer from inherent limitations such as examiner dependency or ionizing radiation. Bioelectrical impedance analysis has previously been investigated with respect to its use in the detection of several cardiovascular and renal pathologies. The present pilot study assessed the feasibility of AAA detection based on bioimpedance analysis. In this single-center exploratory pilot study, measurements were conducted among three different cohorts: patients with AAA, end-stage renal disease patients without AAA, and healthy controls. The device used in the study, CombynECG, is an open-market accessible device for segmental bioelectrical impedance analysis. The data was preprocessed and used to train four different machine learning models on a randomized training sample (80% of the full dataset). Each model was then evaluated on a test set (20% of the full dataset). The total sample included 22 patients with AAA, 16 chronic kidney disease patients, and 23 healthy controls. All four models showed strong predictive performance in the test partitions. Specificity ranged from 71.4 to 100%, while sensitivity ranged from 66.7 to 100%. The best-performing model had 100% accuracy for classification when applied to the test sample. Additionally, an exploratory analysis to approximate the maximum AAA diameter was conducted. An association analysis revealed several impedance parameters that might possess predictive ability with respect to aneurysm size. AAA detection via bioelectrical impedance analysis is technically feasible and appears to be a promising technology for large-scale clinical studies and routine clinical screening assessments.
目前,腹主动脉瘤(AAA)的筛查和诊断依赖于超声或计算机断层血管造影等影像学检查。所有影像学检查都有其独特优势,但也存在诸如依赖检查者或电离辐射等固有局限性。生物电阻抗分析此前已针对其在多种心血管和肾脏疾病检测中的应用进行了研究。本初步研究评估了基于生物阻抗分析检测AAA的可行性。在这项单中心探索性初步研究中,对三个不同队列进行了测量:AAA患者、无AAA的终末期肾病患者和健康对照者。该研究中使用的设备CombynECG是一种可在市场上获取的用于节段性生物电阻抗分析的设备。对数据进行预处理,并用于在随机训练样本(完整数据集的80%)上训练四种不同的机器学习模型。然后在测试集(完整数据集的20%)上对每个模型进行评估。总样本包括22例AAA患者、16例慢性肾病患者和23名健康对照者。所有四个模型在测试分区中均表现出强大的预测性能。特异性范围为71.4%至100%,而敏感性范围为66.7%至100%。性能最佳的模型应用于测试样本时分类准确率为100%。此外,还进行了一项探索性分析以估算最大AAA直径。关联分析揭示了几个可能与动脉瘤大小具有预测能力的阻抗参数。通过生物电阻抗分析检测AAA在技术上是可行的,并且似乎是大规模临床研究和常规临床筛查评估的一项有前景的技术。