P64 Carotid Artery Tracking with Automated Wall Position Resets Yields Robust Distension Waveforms in Long-term Ultrasonic Recordings
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Background: Carotid artery tracking has high clinical relevance for the investigation of arterial stiffness indicators like Pulse Wave Velocity (PWV). However, current tracking systems are unreliable and/or not fully automated [1,2]. In this work we propose a novel wall tracking algorithm for long-term ultrasonic recordings, featuring automated beat-to-beat end-diastolic wall position resets.
Methods: Carotid artery ultrasound (Vantage64, Verasonics, USA) and simultaneous ECG (ECG100C, BIOPAC, USA) were acquired from 10 subjects (38 ± 10 years) in 6 repeated measurements, each involving a resting, breathing and handgrip intervention. The ECG triggers an automated algorithm, whose heuristics utilize the hypoechogenic lumen to detect the end-diastolic wall positions in the ultrasound data. Subsequently, wall motion is tracked throughout the cardiac cycle by complex cross-correlation . Further processing yields carotid distension waveforms and local PWV via spatiotemporal fitting of waveform fiducials. The novel per-beat algorithm was benchmarked against a manually initialized per-intervention algorithm, while ground truth wall positions were manually annotated. Performance was assessed for temporal efficiency, spatial accuracy and feature consistency.
Results: Average results show a ~4000% higher temporal efficiency, 20% increased spatial accuracy (μ error: 0.66 to 0.53 [mm]) and 14% improved feature consistency (ơPWV: 2.2 to 1.9 [m/s]) for the per-beat algorithm. Results of exceptional cases reveal even more significant performance, e.g. 60% increased spatial accuracy (μ error: 1.57 to 0.64 [mm]) for gradual drift and 58% improved feature consistency (ơPWV: 1.9 to 0.8 [m/s]) for instant vessel loss (see Figure 1).
Conclusion: The proposed algorithm demonstrates significant temporal efficiency, spatial accuracy and feature consistency, particularly during perturbations. Such robustness is essential for long-term monitoring, making the algorithm a powerful tool in ambulatory vascular research.
- © 2019 Association for Research into Arterial Structure and Physiology. Publishing services by Atlantis Press International B.V.
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Cite this article
TY - JOUR AU - Fabian Beutel AU - Laura Mansilla Valle AU - Chris Van Hoof AU - Evelien Hermeling PY - 2020 DA - 2020/02/17 TI - P64 Carotid Artery Tracking with Automated Wall Position Resets Yields Robust Distension Waveforms in Long-term Ultrasonic Recordings JO - Artery Research SP - S106 EP - S107 VL - 25 IS - Supplement 1 SN - 1876-4401 UR - https://doi.org/10.2991/artres.k.191224.095 DO - 10.2991/artres.k.191224.095 ID - Beutel2020 ER -