Accuracy of Common Femoral Artery Doppler Waveform Analysis in Predicting Haemodynamically Significant Aortoiliac

Varsha P Rangankar1, Kishor B Taori2, Rajesh G Mundhada3

  • 1Associate Professor, Department of Radiology, Smt. Kashibai Navale Medical College , Pune, India .

Insights

Common femoral artery (CFA) Doppler waveform analysis accurately predicts significant aortoiliac stenosis or occlusion in peripheral arterial disease. This noninvasive method offers high sensitivity and specificity for diagnosing these critical vascular conditions.

Area of Science:

  • Vascular Medicine
  • Diagnostic Imaging
  • Noninvasive Cardiology

Background:

  • Doppler ultrasound is a cost-effective, noninvasive tool for evaluating peripheral arterial disease.
  • Visualizing aortoiliac arteries can be challenging, hindering diagnosis of related lesions.
  • Doppler waveform changes distal to stenosis are documented, suggesting indirect diagnostic potential.

Purpose of the Study:

  • To assess the accuracy of common femoral artery (CFA) Doppler waveform analysis.
  • To diagnose hemodynamically significant aortoiliac stenosis or occlusion in peripheral arterial disease patients.

Main Methods:

  • Retrospective analysis of 67 patients (114 aortoiliac segments) with suspected peripheral arterial disease.
  • CFA Doppler waveforms were analyzed and categorized as normal (triphasic) or abnormal (biphasic/monophasic).
  • Results were compared against intra-arterial angiography as the gold standard.

Main Results:

  • Abnormal CFA waveforms correctly identified significant aortoiliac lesions in 41 of 114 segments.
  • The technique demonstrated 87% sensitivity, 92% specificity, and 90% overall accuracy.
  • Low velocity monophasic waveforms reliably predicted significant disease with 93% positive predictive value.

Conclusions:

  • CFA Doppler waveform analysis is a sensitive and accurate method.
  • This technique effectively predicts hemodynamically significant aortoiliac stenosis or occlusion.
  • It offers a valuable noninvasive approach for diagnosing proximal arterial disease.
Abstract