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Proceedings Paper

Intraoperative ultrasound to monitor spinal cord blood flow after spinal cord injury
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Paper Abstract

Spinal cord injury (SCI) affects approximately 2.5 million people worldwide. The primary phase of SCI is initiated by mechanical trauma to the spinal cord, while the secondary phase involves the ensuing tissue swelling and ischemia that worsen tissue damage and functional outcome. Optimizing blood flow to the spinal cord after SCI can mitigate injury progression and improve outcome. Accurate, sensitive, real-time monitoring is critical to assessing the spinal cord perfusion status and optimizing management, particularly in those with injuries severe enough to require surgery. However, the complex anatomy of the spinal cord vasculature and surrounding structures present significant challenges to such a monitoring strategy. In this study, Doppler ultrasound was hypothesized to be a potential solution to detect and monitor spinal cord tissue perfusion in SCI patients who required spinal decompression and/or stabilization surgeries. This approach could provide real-time visual blood flow information and pulsatility of the spinal cord as biomarkers of tissue perfusion. Importantly, Doppler ultrasound could be readily integrated into the surgical workflow, because the spinal cord was exposed during surgery, thereby allowing easy access for Doppler deployment, while keeping the dura intact. Doppler ultrasound successfully measured blood flow in single and bifurcated microfluidic channels at physiologically relevant flow rates and dimensions in both in-vitro and in-vivo porcine SCI models. Furthermore, perfusion was quantified from the obtained images. Our results provide a promising and viable solution to intraoperatively assess and monitor blood flow at the SCI site to optimize tissue perfusion and improve functional recovery in SCI patients.

Paper Details

Date Published: 28 February 2020
PDF: 8 pages
Proc. SPIE 11317, Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging, 113170B (28 February 2020); doi: 10.1117/12.2548789
Show Author Affiliations
Amir Manbachi, Johns Hopkins Univ. (United States)
Sandeep Kambhampati, Johns Hopkins Univ. (United States)
Ana Ainechi, Johns Hopkins Univ. (United States)
Smruti Mahapatra, Johns Hopkins Univ. (United States)
Micah Belzberg, Johns Hopkins Univ. (United States)
Guoliang Ying, Harvard Medical School (United States)
Rongrong Chai, Harvard Medical School (United States)
Yu Shrike Zhang, Harvard Medical School (United States)
Noah Gorelick, Johns Hopkins Univ. (United States)
Zach Pennington, Johns Hopkins Univ. (United States)
Erick Westbroek, Johns Hopkins Univ. (United States)
Bowen Jiang, Johns Hopkins Univ. (United States)
Brian Hwang, Johns Hopkins Univ. (United States)
Thomas Benassi, Johns Hopkins Univ. (United States)
George Coles, Johns Hopkins Applied Physics Lab. (United States)
Betty Tyler, Johns Hopkins Univ. (United States)
Ian Suk, Johns Hopkins Univ. (United States)
Youseph Yazdi, Johns Hopkins Univ. (United States)
Nicholas Theodore, Johns Hopkins Univ. (United States)


Published in SPIE Proceedings Vol. 11317:
Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging
Andrzej Krol; Barjor S. Gimi, Editor(s)

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