Improving central line needle insertions using in-situ vascular reconstructions

ABSTRACT

We developed a neck central line insertion guidance system that renders 3D ultrasound (US) surface reconstructions of the carotid artery (CA) and internal jugular vein (IJV), a tracked model of the needle, and needle trajectory on a 2D monitor. Twenty clinicians evaluated this system compared to US-only guidance on a phantom using time and insertion accuracy metrics. The 3D system had a 100% success rate compared to 70% for the US-only system. The average distance from the centre line of the US reconstructed IJV was $1.8\pm 0.9$ mm under $3$D guidance compared to $4.2\pm 2.9$ mm for US-only. Our system significantly improved needle insertion success rates and targeting accuracy compared to the US-only approach through a radiation-free surface reconstruction of the neck vascular structures. This work has the potential to provide a mobile 3D imaging and visualisation system for needle-based vascular interventions.

KEYWORDS:

• Surgical navigation
• needle guidance
• ultrasound reconstruction
• visualisation and targeting

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study was funded by Canadian Foundation for Innovation [20994], the Ontario Research Fund (IDCD), and the Canadian Institutes for Health Research [FDN 201409].

Notes on contributors

Leah A. Groves

Leah Groves is a PhD candidate in Biomedical Engineering at Western University. She is a member of the Virtual Augmentation and Simulation (VASST) Lab at Robarts Research Institute. Her research interests include the development of computer-assisted interventions for surgical navigation with a focus on visualization and deep learning.

Natalie Li

Natalie Li is an undergraduate student working with the Virtual Augmentation and Simulation (VASST) Lab at Robarts Research Institute.  She studies under the Department of Medical Biophysics at Western University, London, Canada.

Blake VanBerlo

Blake VanBerlo is a master’s student at the Cheriton School of Computer Science at the University of Waterloo. He has also completed the software engineering program and two years of the doctor of medicine program at Western University. His research is focused on machine learning and its applications to healthcare.

Natan Veinberg

Natan Veinberg is a 4th year medical student at the Schulich School of Medicine & Dentistry in London, Ontario, Canada. Following graduation, he hopes to pursue a career in family medicine and palliative care

Terry M. Peters

Terry Peters is a Scientist at the Robarts Research Institute and a Professor Emeritus in Medical Imaging, Medical Biophysics and Biomedical Engineering at Western University, London, Canada. He is the Director of the laboratory for Virtual Augmentation and Simulation (VASST Lab) at Robarts, where his research interest is the development of technologies to facilitate image-guided interventions.

Elvis C. S. Chen

Elvis C.S. Chen is a Scientist at the Robarts Research Institute with cross-appointment to Biomedical Engineering and the Department of Medical Biophysics at Western University, London Canada. His research interests is to developed computation methods and mechatronics system for computer-assisted interventional medicine. He is an Associated Editor for IEEE Transactions on Medical Imaging (IEEE-TMI) since 2017.