Exactech today shared new research demonstrating the potential of AI and radiomic analyses in shoulder arthroplasty.

The Gainesville, Florida–based company also shared new advances in its Active Intelligence ecosystem of smart technologies. It presented its findings at the Congress of International Society for Technology in Arthroplasty (ISTA) in Nashville, Tennessee.

Exactech’s research demonstrated how machine learning techniques, such as clustering, can aggregate CT image-derived radiomic data with patient demographic data. These techniques can identify clinically relevant muscle classifications that predict clinical outcomes after shoulder arthroplasty.

The new research looked at deltoid radiomics from CT scans of 1,382 patients. It analyzed the scans to identify five distinct deltoid clusters associated with both high and low levels of motion before and after shoulder arthroplasty. This technique can extend to other muscles and bone to synthesize complex image data for quick interpretation by clinicians.

Two other radiomic studies quantified the 3D deltoid morphology and correlated the data to clinically relevant thresholds for clinical improvement. These identified radiomic measures associated with improved outcomes. The information can help Exactech develop future clinical decision support tools.

Additionally, Exactech shared new developments in knee and ankle surgery technologies. That includes the easy adoption of the Newton knee balancing technology and the accuracy of its GPS for total ankle arthroplasty. AI also powers these data-rich, low-cost solutions.

“Exactech’s presentation of its latest AI-driven research exemplifies our commitment to advancing orthopedic science and clinical knowledge through novel technology and patient-focused analytic techniques,” said Chris Roche, Exactech SVP, Extremities. “The application of this research will facilitate development of new clinical decision support tools that will profoundly change how surgeons treat their patients.”