Theodore W Cary1, Courtney B Reamer2, Laith R Sultan1, Emile R Mohler2, Chandra M Sehgal1. 1. Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104. 2. Department of Medicine, Division of Cardiovascular Medicine, Section of Vascular Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104.
Abstract
PURPOSE: To use feed-forward active contours (snakes) to track and measure brachial artery vasomotion on ultrasound images recorded in both transverse and longitudinal views; and to compare the algorithm's performance in each view. METHODS: Longitudinal and transverse view ultrasound image sequences of 45 brachial arteries were segmented by feed-forward active contour (FFAC). The segmented regions were used to measure vasomotion artery diameter, cross-sectional area, and distention both as peak-to-peak diameter and as area. ECG waveforms were also simultaneously extracted frame-by-frame by thresholding a running finite-difference image between consecutive images. The arterial and ECG waveforms were compared as they traced each phase of the cardiac cycle. RESULTS: FFAC successfully segmented arteries in longitudinal and transverse views in all 45 cases. The automated analysis took significantly less time than manual tracing, but produced superior, well-behaved arterial waveforms. Automated arterial measurements also had lower interobserver variability as measured by correlation, difference in mean values, and coefficient of variation. Although FFAC successfully segmented both the longitudinal and transverse images, transverse measurements were less variable. The cross-sectional area computed from the longitudinal images was 27% lower than the area measured from transverse images, possibly due to the compression of the artery along the image depth by transducer pressure. CONCLUSIONS: FFAC is a robust and sensitive vasomotion segmentation algorithm in both transverse and longitudinal views. Transverse imaging may offer advantages over longitudinal imaging: transverse measurements are more consistent, possibly because the method is less sensitive to variations in transducer pressure during imaging.
PURPOSE: To use feed-forward active contours (snakes) to track and measure brachial artery vasomotion on ultrasound images recorded in both transverse and longitudinal views; and to compare the algorithm's performance in each view. METHODS: Longitudinal and transverse view ultrasound image sequences of 45 brachial arteries were segmented by feed-forward active contour (FFAC). The segmented regions were used to measure vasomotion artery diameter, cross-sectional area, and distention both as peak-to-peak diameter and as area. ECG waveforms were also simultaneously extracted frame-by-frame by thresholding a running finite-difference image between consecutive images. The arterial and ECG waveforms were compared as they traced each phase of the cardiac cycle. RESULTS: FFAC successfully segmented arteries in longitudinal and transverse views in all 45 cases. The automated analysis took significantly less time than manual tracing, but produced superior, well-behaved arterial waveforms. Automated arterial measurements also had lower interobserver variability as measured by correlation, difference in mean values, and coefficient of variation. Although FFAC successfully segmented both the longitudinal and transverse images, transverse measurements were less variable. The cross-sectional area computed from the longitudinal images was 27% lower than the area measured from transverse images, possibly due to the compression of the artery along the image depth by transducer pressure. CONCLUSIONS: FFAC is a robust and sensitive vasomotion segmentation algorithm in both transverse and longitudinal views. Transverse imaging may offer advantages over longitudinal imaging: transverse measurements are more consistent, possibly because the method is less sensitive to variations in transducer pressure during imaging.
Authors: Dick H J Thijssen; Mark A Black; Kyra E Pyke; Jaume Padilla; Greg Atkinson; Ryan A Harris; Beth Parker; Michael E Widlansky; Michael E Tschakovsky; Daniel J Green Journal: Am J Physiol Heart Circ Physiol Date: 2010-10-15 Impact factor: 4.733
Authors: Spyretta Golemati; John Stoitsis; Emmanouil G Sifakis; Thomas Balkizas; Konstantina S Nikita Journal: Ultrasound Med Biol Date: 2007-07-25 Impact factor: 2.998
Authors: Yong He; Yan-Ting Shiu; Daniel B Pike; Prabir Roy-Chaudhury; Alfred K Cheung; Scott A Berceli Journal: J Vasc Surg Date: 2018-05-18 Impact factor: 4.268