A validated high-fidelity synthetic model for internal mammary vessel preparation in autologous breast reconstruction

Aims: The precise and safe preparation of internal mammary vessels (IMVs) is a critical step in microvascular autologous breast reconstruction. These vessels lie within a confined, dynamic space, requiring refined dexterity and careful tissue handling. Opportunities for structured training remain limited. This study aimed to develop and validate a high-fidelity synthetic model for IMV preparation and assess its educational value. Materials & Methods: A synthetic post-mastectomy chest model was designed in collaboration with specialist technicians with expertise in simulation design and implementation, with iterative input from consultant microsurgeons. Five novice and five expert surgeons participated. Face and content validity were assessed by independent expert evaluation. Construct validity was examined using a task-specific checklist and the Objective Structured Assessment of Technical Skills (OSATS), scored by two blinded assessors. Novice confidence was assessed pre- and post-training. Results: Expert evaluation demonstrated good face validity, with high ratings for overall realism and anatomical fidelity (4.5/5), vessel dissection (3.25/5) and teaching suitability and utility for higher surgical training (4.25/5). Construct validity was supported by higher expert performance (OSATS: 23.5 vs 18.9; checklist: 10.0 vs 9.4), and faster task completion time (13.8 vs 15.8 min). Inter-rater reliability was moderate to strong (ICC 0.575–0.820). Novice confidence improved significantly following training (mean increase 2.6, t = 6.50, p = 0.003). Conclusions: This realistically responsive training model demonstrates strong face, content and construct validity. It provides a practical and objective platform for training and assessing internal mammary vessel preparation and supports safer skill acquisition before progression to the operating theatre.