Joint aspiration, also known as arthrocentesis, and injections require successful access of the joint space. In the emergency room and clinics where these procedures are performed, unpracticed clinicians face difficulty in visualizing the correct area to insert the needle, and if not performed correctly, can lead to preventable patient complications including injury to surrounding joint space structures like blood vessels, tendons, and muscle. Additionally, while both aspirations and injections are used to provide therapeutic relief, arthrocentesis serves a diagnostic function as well, including the detection of joint sepsis. If left untreated, joint sepsis may result in kidney failure, gangrene, organ damage, and even death; despite antibiotic use, the in-hospital septic arthritis mortality rate remains at 15%. Thus, it is critical for joint access procedures to be performed properly.

To aid with practicing this procedure prior to performing on a live patient, task trainers serve as models that help clinicians simulate the process. However, current task trainers for arthrocentesis/joint injection present various shortcomings including lack of biofidelic representation, poor reusability, high costs, and ultrasound incompatibility. Our team, SynoSim, is targeting these gaps by designing a novel joint access training model that is biofidelic in structure and visual ultrasound-ability, provides visual feedback to the user, and is readily reusable. Through this solution, we aim to increase clinician confidence and competence in joint access procedures prior to performing on patients.

Team Members

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Project Mentors, Sponsors, and Partners

• Dr. Tiffany Fong (Clinical Mentor)

• Dr. Won Jun Kuk (Clinical Mentor)

• Dr. Constanza Miranda (BME Mentor)

• Antony Fuleihan (TA)

• Dr. Jemima Albayda (Committee Member)

• Dr. Richard Schaefer (Committee Member)

• Dr. Geoffrey Miller (Committee Member)

Course Faculty

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Project Links

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Additional Project Information