Stephen Sebastyan

Instrument Recovery

Part of my PhD research work focused on developing an approach for catheter position and pose recovery in a distorted field.

Motivation & Challenges

EAM systems can be prone to misalignment (progressive and spontaneous), which we have colloquially termed “drift” and “shift”. In other words, the reference origin can move spontaneously or progressively from its previous position. From a user’s perspective, this can appear as if the instruments are in a different position in the heart (e.g., at one instant the catheter could be positioned inside the heart, and the next it appears outside the heart altogether).

At present, the operator’s sole recourse is to reset the system, which requires remapping the endocardium and results in loss of previous data (electro-anatomic map and ablation points). This is highly undesirable.

Preliminary Work

This research is still in progress.

Computer Assisted Mosaic Arthroplasty

Osteoarthritis is the most common form of arthritis and a degenerative joint disease. Cartilage in joints does not naturally recover quickly once damaged (due to injury or “wear and tear”). It is generally painful, and the common long-term practice is joint replacement (often reserved for older patients since artificial joints have a limited lifespan).

An alternative is mosaic arthroplasty (osteochondral implantation). In this procedure, the orthopaedic surgeon harvests joint cartilage from non-load-bearing parts of the joint and implants them at the damage site (the lesion) — analogous to filling a pothole.

Traditional mosaic arthroplasty is difficult: the surgeon must recreate the original joint surface near perfectly. If they insert plugs too high/proud, they shear off. If too shallow, the defect can fill with less desirable fibrocartilage instead of articular cartilage. If too large a gap is left below the plug, it can fill with fluid and form a cyst-like structure.

Computer intervention removes much of the human error and guesswork. My (collaborative) work has taken two forms: (1) thermoplastic custom 3D-printed templates (customized jigs), and (2) opto-electronic tracking of surgical tools.

Initial Step

The initial step is acquiring preoperative diagnostic CT (or MR) and segmenting the joint. Segmentation can be achieved semi-automatically using thresholding, edge detection, and region growing methods, but the region of interest (the lesion) is typically manually segmented (or edited). The patient’s ideal curvature is recreated by consultation with the surgeon using a manual planner (Dr. Kunz and others) or planning software (originally designed by Dr. Jiro Inoue, PhD). Using the reconstructed joint, surgical sites are planned.

Method 1 - Custom Template Guides

One approach uses thermo-plastic templates. Using reconstructed patient knee models, surgical sites are planned and used to design thermoplastic templates that are 3D-printed. These templates fit the patient’s joint and guide the surgical instrument from harvest to recipient site (accounting for 6 degrees of freedom).

My work showed this method to be significantly more accurate (in customized bone models) than the conventional procedure, with reduced variance. The shortcoming is that it requires a more invasive opening of the joint cavity compared to the opto-electronic method.

Method 2 - Optical Electronic Guidance

The other method involves attaching optical LED markers and tracking instruments using a stereoscopic camera (analogous to tracking used in motion-gaming systems, but with significantly greater reliability and accuracy). The surgical plan is overlaid on the patient’s model. The system is calibrated using 3D-printed and machined calibration blocks. Then, using an ICP-variant, the patient’s joint is registered with the computational model. The navigation system tracks instruments relative to the joint surface, providing visual feedback (6 DOF) to the surgeon.

This process is significantly more accurate than the conventional procedure and only marginally less accurate than the template method. It is more time-consuming due to calibration/registration steps, but has the advantage of being usable in less-invasive arthroscopic variants.

Validation

More Detailed Reading

Sebastyan, S., Kunz, M., Stewart, A. J., & Bardana, D. D. (2015). Image-guided techniques improve accuracy of mosaic arthroplasty. International Journal of Computer Assisted Radiology and Surgery. LINKED HERE

Sebastyan, S. (2013). Computer-assisted mosaic arthroplasty: A femur model trial. LINKED HERE