Experimental validation of a novel medical device tracking technology

Hepatocellular carcinoma (HCC) is the 5th most common cancer worldwide with 500,000 new cases per year and the highest mortality rate (>97% in 5 yrs). Intravenous chemotherapy is limited and clinical outcomes are generally poor with a median survival rate of less than one year. Transcatheter arterial chemoembolization (TACE) is an image guided interventional oncology procedure that is the mainstay of intermediate stage HCC therapy. It has been shown to control symptoms, however the rapid distribution of the drug in the whole body prevents high intra-tumoral drug concentrations to be sustained. Still, targeting tumor cells by carrying a specific endovascular drug or radioisotopes delivery at the site of the HCC tumor mass is a challenging problem due to the complexity of the liver’s vasculature and current limitations to contrast injections which is unsuitable for some patients.

To deliver the appropriate amount of chemoembolizing agents, groundbreaking work in therapeutic drug delivery and minimally invasive interventions must find the appropriate tracking technologies to facilitate translation in the interventional workflow, with automated image-based multimodal fusion and intra-arterial catheter localization. To better assist interventional radiologists follow the catheter’s position and reach the tumor site with increased accuracy and higher confidence, our ongoing research project is developing an innovative solution for intra-operative medical instrument guidance and real-time non-rigid registration for image-guided interventional procedures. The envisioned platform includes a device composed of optical fibre Bragg gratings with a unique helicoidal core to infer in a real-time fashion, the 3D shape of a catheter inside the body to be visualized by the interventionist. This minimally invasive technology respects a number of critical elements such as offering computational accuracy, integration in complex environments in the operating room or X-ray interventional suite, and real-time interactions for timely information feedback. Due to the stringent accuracy constraints to preserve the alignment with the virtual pathways, real-time motion compensation is a key focus of our efforts. Despite remaining sensitive to external fluctuations, the shape sensing optical fibre based on multiple fibre gratings detects reflected light signals which are integrated into the catheter in order to monitor the dynamic 3D shape of the vessel influenced by breathing or compensate for involuntary movement.

This research project provides a new pathway in device localization, motion estimation and multimodal image fusion during guidance procedures, thereby simplifying the surgical environment and clinical workflow by introducing automated workflows. This will provide a unique opportunity to improve the robustness and reproducibility for introducing flexible devices in vessels and coronaries, and guiding them to a pre-identified target.

Faculty Supervisor:

Samuel Kadoury





Engineering - biomedical





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