Introduction: Unrestricted elbow range of motion (ROM) is essential for daily function, yet flexion and extension limitations frequently occur following elbow trauma. These restrictions may result from osseous deformities, soft tissue contracture, or both, requiring accurate identification of the dominant cause to guide treatment. Although CT imaging provides detailed evaluations of bony pathology, conventional single CT lacks functional information, and dynamic 4D-CT faces clinical limitations. Therefore, alternative approaches to assess osseous contributions to motion restrictions are needed.

Objective: This study aims to introduce and validate a 3D computational kinematic bone model based on segmented single CT scans. The model enables patient-specific simulation of elbow flexion and extension, enabling quantifiable assessment of osseous related motion restrictions to support clinical decision making.

Methods: Eight non-affected cadaveric elbows were scanned using computed tomography in seven positions ranging from full extension to full flexion and segmented into 3D models. Anatomical landmarks were automatically identified to define a landmark-based rotation axis (LMA), which was validated against a kinematically derived average helical axis (AHA). The primary outcomes were the angular deviation and the minimal distance between the axes. The simulated ulnar motion was generated by applying finite helical axis-derived rotations to the neutral ulnar pose. Predicted poses were compared to scanned poses at each flexion angle, with translational and rotational deviations calculated to assess simulation accuracy. Clinical applicability was evaluated by applying the model to bilateral CT scans of ten patients with elbow flexion and extension restrictions. Model-based ROM was determined by simulating flexion and extension and identifying the onset of osseous impingement, and compared to clinically recorded ROM.

Results: Alignment between the LMA and the AHA showed a mean positional difference of 0.41 mm (SD 0.22) and an angular deviation of 2.76° (SD: 1.32). LMA-based simulated ulnar poses demonstrated increasing translational and rotational errors with flexion, predominantly in distal, lateral and valgus directions. Specimens exhibited impingement exclusively in the ulnohumeral region at the trochlea and the greater sigmoid notch. In patients, model-based ROM showed a mean absolute difference of 6.7° for terminal extension and 14.2° for terminal flexion, with false-positive impingement primarily observed in the ulnohumeral region.

Conclusion: This study validated a 3D computational model for simulating elbow flexion and extension using single CT scans. The model accurately estimated ROM and identified osseous impingement locations. Although it demonstrated sensitivity to false-positive detections, it provides a clinically applicable tool for assessing osseous motion restrictions. Future improvement should focus on enhancing landmark accuracy and potentially restricting impingement detection to anatomically relevant regions.