Open-source software for ultrasound-based guidance in spinal fusion surgery. [r-libre/3127]

Gueziri, Houssem-Eddine; Yan, X B Charles, & Collins, D Louis (2020). Open-source software for ultrasound-based guidance in spinal fusion surgery.. Ultrasound in Medicine and Biology, 46 (12), 3353-3368. https://doi.org/10.1016/j.ultrasmedbio.2020.08.005

File(s) available for this item:

PDF - UMB2020_preprint.pdf
License : Creative Commons Attribution.

Download

Item Type:	Journal Articles
Refereed:	Yes
Status:	Published
Abstract:	Spinal instrumentation and surgical manipulations may cause loss of navigation accuracy requiring an efficient re-alignment of the patient anatomy with pre-operative images during surgery. While intra-operative ultrasound (iUS) guidance has shown clear potential to reduce surgery time, compared with clinical computed tomography (CT) guidance, rapid registration aiming to correct for patient misalignment has not been addressed. In this article, we present an open-source platform for pedicle screw navigation using iUS imaging. The alignment method is based on rigid registration of CT to iUS vertebral images and has been designed for fast and fully automatic patient re-alignment in the operating room. Two steps are involved: first, we use the iUS probe's trajectory to achieve an initial coarse registration; then, the registration transform is refined by simultaneously optimizing gradient orientation alignment and mean of iUS intensities passing through the CT-defined posterior surface of the vertebra. We evaluated our approach on a lumbosacral section of a porcine cadaver with seven vertebral levels. We achieved a median target registration error of 1.47 mm (100% success rate, defined by a target registration error <2 mm) when applying the probe's trajectory initial alignment. The approach exhibited high robustness to partial visibility of the vertebra with success rates of 89.86% and 88.57% when missing either the left or right part of the vertebra and robustness to initial misalignments with a success rate of 83.14% for random starts within ±20° rotation and ±20 mm translation. Our graphics processing unit implementation achieves an efficient registration time under 8 s, which makes the approach suitable for clinical application.
Official URL:	https://doi.org/10.1016/j.ultrasmedbio.2020.08.005
Depositor:	GUEZIRI, Houssem
Owner / Manager:	Houssem Gueziri
Deposited:	14 Dec 2023 21:32
Last Modified:	14 Dec 2023 21:32

Actions (login required)

RÉVISER