Literature DB >> 20189743

Detection and localization of peripheral vascular bleeding using Doppler ultrasound.

Wenbo Luo1, Hamid Hosseini, Vesna Zderic, Frederick Mann, Grant O'Keefe, Shahram Vaezy.   

Abstract

BACKGROUND: Hemorrhage from wounds in the extremities is the leading cause of preventable death on the battlefield. To successfully treat these injuries, the exact source of bleeding must be localized.
OBJECTIVE: The purpose of this study was to determine the feasibility of using Doppler ultrasound to precisely detect and localize peripheral vascular bleeding.
METHODS: Injuries were produced in common femoral arteries (diameter of ∼5 mm) of 28 pigs in vivo. Single puncture injuries were produced using 6 French (F) (n = 10), 9 F (n = 22), and 12 F (n = 12) catheters. In addition, multiple punctures were made (using 6 F and 9 F catheters) in eight common femoral arteries to simulate bleeding from multiple injuries. Finally, laceration injuries were produced using a scalpel in 10 femoral vessels.
RESULTS: In color Doppler images, bleeding was observed as a turbulent jet flow originating from the injury site in the vessel. This jet flow had checkered red-blue color pattern at the bleeding site, as opposed to a uniform color pattern in an intact artery. Peak systolic velocity at the injury site, measured using pulsed Doppler, was elevated to up to 152.0 ± 81.6 cm/s, as compared to 78.8 ± 17.5 cm/s in normal arteries. Further, end diastolic velocity increased from 6.1 ± 4.9 cm/s before the injury to up to 59.1 ± 33.1 cm/s after the injury. Resistance index was significantly lower (0.6 for 9 F and 12 F punctures, and 0.8 for 6 F punctures) at the bleeding site in injured arteries as compared to the resistance index of intact arteries (of 0.9).
CONCLUSION: Our results showed a characteristic change in the systolic and diastolic velocities, as well as resistance indices at the injury site in peripheral arteries. These findings may serve as groundwork for development of automated bleeding detection and localization methods, and facilitate various hemorrhage control treatments.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 20189743     DOI: 10.1016/j.jemermed.2010.01.001

Source DB:  PubMed          Journal:  J Emerg Med        ISSN: 0736-4679            Impact factor:   1.484


  3 in total

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Authors:  Michael A Rothfuss; Nicholas G Franconi; Jignesh V Unadkat; Michael L Gimbel; Alexander Star; Marlin H Mickle; Ervin Sejdic
Journal:  IEEE J Transl Eng Health Med       Date:  2016-08-25       Impact factor: 3.316

2.  Automatic Hemorrhage Detection From Color Doppler Ultrasound Using a Generative Adversarial Network (GAN)-Based Anomaly Detection Method.

Authors:  Jhimli Mitra; Jianwei Qiu; Michael MacDonald; Prem Venugopal; Kirk Wallace; Hossam Abdou; Michael Richmond; Noha Elansary; Joseph Edwards; Neerav Patel; Jonathan Morrison; Luca Marinelli
Journal:  IEEE J Transl Eng Health Med       Date:  2022-08-19

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Journal:  BMC Musculoskelet Disord       Date:  2018-11-20       Impact factor: 2.362

  3 in total

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