Journal of Vascular and Endovascular Therapy

Optimal Ultrasound Criteria for Grading Stenosis of the Superficial Femoral Artery

3^rd Edition of World Congress & Exhibition on Vascular Surgery
May 24-25, 2018 London, UK

Mingjie Gao, Yang Hua, Xinyu Zhao, Lingyun Jia, Jie Yang and Beibei Liu

Xuanwu Hospital of Capital Medical University, China

ScientificTracks Abstracts: J Vasc Endovasc Therapy

DOI: 10.21767/2573-4482-C1-002

Abstract

Objective: This retrospective study determined the duplex ultrasound scanning (DUS) criteria for detecting 50-69% and 7099% stenosis of the superficial femoral artery (SFA). Methods Examinations of 278 limbs in 185 subjects with peripheral arterial disease were performed. Duplex ultrasound scanning was used to measure the residual diameter of the stenotic segment and the diameter of the original lumen, the peak systolic velocity (PSV) at the stenotic segment of the SFA (PSVst), the segment proximal to the stenosis (PSVpro), and the popliteal artery (PSVpop; distal to the stenosis). The ratios PSVst/PSVpro and PSVst/PSVpop were calculated. Receiver operator characteristic curves were plotted, with digital subtraction angiography as the reference. Results: The studied limbs included 205 limbs with stenotic SFAs: 43 (15.5%) with 50-69% stenosis, and 162 (58.3%) with 70-99% stenosis. The control group consisted of 73 limbs: 44 (15.8%) were normal and 29 (10.4%) had <50% stenotic SFAs. According to the results of the ROC analysis, the optimal cut-off values for detecting 50-69% stenosis of the SFA were PSVst ≥ 210 cm/s, PSVst/PSVpop ≥ 2.5, or PSVst/PSVpro ≥ 1.7. PSVst was the most useful hemodynamic parameter for predicting 50-69% stenosis, with 95.6% sensitivity, 98.6% specificity, and 96.4% accuracy. For predicting 70-99% stenosis of the SFA, the thresholds were PSVst ≥ 275 cm/s, PSVst/PSVpop ≥ 4.0, or PSVst/PSVpro ≥ 2.5. PSVst/PSVpop ≥ 4.0 was the most useful Doppler parameter, with 96.3% sensitivity, 93.9% specificity, and 95.3% accuracy. PSVst/ PSVpopï¼�?PSVst was the best combined parameter to detect SFA 70-99% stenosis with 96.3% sensitivity, 94.8% specificity, and 95.7% accuracy. Conclusions This study determined the cutoff values of DUS hemodynamic parameters for diagnosing 50-69% and 70-99% stenosis of the SFA. PSVst/PSVpop may be a better ratio parameter than the traditional parameter of PSVst/PSVpro for diagnosing SFA stenosis, especially for 70-99% stenosis
 Recent Publications 1. Conte MS, Pomposelli FB, Clair DG, et al. Society for Vascular Surgery practice guidelines for atherosclerotic occlusive disease of the lower extremities: management of asymptomatic disease and claudication. J Vasc Surg 2015; 61:2S-41S. 2. Cossman DV, Ellison JE, Wagner WH, et al. Comparison of contrast arteriography to arterial mapping with colorflow duplex imaging in the lower extremities. J Vasc Surg 1989; 10:522-8; discussion 28-9.2. 3. Gao M, Hua Y, Zhao X, et al. Incidence and Predictors of In-stent Re-Stenosis in the Superficial Femoral Artery: Evaluation of Long-Term Outcomes by Color Duplex Ultrasound. Ultrasound Med Biol 2016; 42:717-26. 4. Khan SZ, Khan MA, Bradley B, et al. Utility of duplex ultrasound in detecting and grading de novo femoropopliteal lesions. J Vasc Surg 2011; 54:1067-73. 5. Zwiebel WJ, Pellerito JS. Introduction to vascular ultrasonography, 6th edition; Philadelphia,PA, Elsevier Press, 2012;294-30.

Biography

Associate Professor Mingjie Gao has worked in the field of vascular ultrasound for more than 10 years and has good expertise in lower extremity artery ultrasound. Her research focuses on the following areas: 1) Systemical evaluation of the vessel structures and hemodynamics in lower extremity artery by multiple-modes of ultrasound in patients with peripheral arterial disease. 2) Evaluation of the vessel structures and hemodynamic alterations before and after interventional therapy such as stenting. She and her study group also performed a series of studies in the risk factors for SFA in stent restenosis. She has published almost 10 articles in the above areas.

Email:gaomingjie163@163.com