Pierre Guy

Prospective Graduate Students / Postdocs

This faculty member is currently not actively recruiting graduate students or Postdoctoral Fellows, but might consider co-supervision together with another faculty member.


Research Classification

Research Interests

Surgical Technologies
Hip Fracture Care
Health services research

Affiliations to Research Centres, Institutes & Clusters

Research Options

I am available and interested in collaborations (e.g. clusters, grants).
I am interested in and conduct interdisciplinary research.

Graduate Student Supervision

Doctoral Student Supervision

Dissertations completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest dissertations.

An integrated system for ultrasound-based surgical navigation of iliosacral screws (2023)

Pelvic fractures require a complex surgery to realign the fracture and stabilize the pelvic ring. The conventional method for placing iliosacral screws (ISS) in the pelvis relies heavily on intraoperative fluoroscopy. However, due to the narrow sacral passage the screw must pass through, this technique is susceptible to high rates of screw malplacement which can lead to iatrogenic complications. Additionally, fluoroscopy requires ionizing radiation and therefore exposes the surgical staff to harm. This thesis proposes and evaluates an alternative surgical protocol using a navigation system based on ultrasound (US) imaging, which enables accurate bone surface imaging without requiring ionizing radiation.This system's development involves four contributions, the first two of which focus on the requirement of automatically identifying bone in US. First, we developed a multi-institutional US bone imaging dataset and corresponding evaluation framework, allowing for more systematic evaluation of US bone segmentation algorithms. Using this, we benchmarked six segmentation algorithms on thousands of US images and found deep convolutional neural networks are the most accurate. Second, we characterized a wide range of uncertainty estimation techniques and novel loss functions for US bone segmentation, and found that deep ensembling used with versions of the binary cross entropy loss can significantly improve segmentation (mean Dice: 0.75) and calibration errors (mean expected calibration error: 0.24%). Third, we validated multiple graphical visualizations, and found that bullseye visualizations achieve the best ISS targeting with mean distance and angulation errors of 0.51 mm and 0.55°.Finally, we combined these components to develop an integrated US-based surgical navigation system which we call NOFUSS (Navigated Orthopaedic Fixation using Ultrasound System). We surgically inserted ISSs in human cadaver specimens using NOFUSS, and compared its accuracy and efficiency to the conventional fluoroscopic-based surgery. We found that with NOFUSS, ISSs can be placed with comparable accuracy as fluoroscopy guidance, while requiring no intraoperative radiation and with a 60% reduction in median insertion times. This work demonstrates that combining US imaging with surgical navigation techniques is feasible and can likely enable surgeons to perform ISS insertions with accuracy and efficiency comparable to conventional procedures, but with little or no radiation exposure.

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