Innovations in Surgical Simulation: New Technologies for Training and Intraoperative Support

The field of surgical simulation has rapidly evolved due to the integration of emerging technologies, profoundly impacting both surgical training and intraoperative support. Recent years have witnessed a proliferation of advanced tools—such as Extended Reality (XR), artificial intelligence (AI), digital twins, and computer vision—reshaping the landscape of surgical education and operative practice. These innovations promise to enhance surgical precision, streamline preoperative planning, and personalize intraoperative guidance, offering more realistic training scenarios and improving patient-specific outcomes. Nonetheless, significant gaps persist in establishing robust scientific evidence regarding their benefits, largely resulting from heterogeneous study designs, insufficient sample sizes, limited clinical adoption, and a lack of standardized validation across platforms and specialties.

While preliminary investigations highlight the great promise of simulation-based approaches and AI-driven decision support for improving technical skills and real-time surgical performance, many studies remain in the proof-of-concept stage. Debates continue around benchmarking, safety, and integration into clinical workflows, as well as the transferability of simulation-driven competencies to real-world outcomes. Moreover, interdisciplinary collaboration has introduced a diversity of perspectives and terminology, complicating comprehensive assessment and synthesis of progress in this rapidly changing domain. These challenges necessitate concerted efforts to unify research methodologies, clinical validation protocols, and educational standards for adoption at scale.

This Research Topic aims to advance the state of knowledge in surgical simulation and intraoperative support by showcasing innovative technologies and rigorously evaluating their clinical, educational, and practical impact. We seek to clarify the translational pathways from simulation to improved surgical practice, foster interdisciplinary consensus, and promote solutions that address equity and sustainable development goals in global health.

To gather further insights in strengthening the evidence base and cross-disciplinary understanding of surgical simulation and intraoperative technologies, we welcome articles addressing, but not limited to, the following themes:
o Development, integration, and assessment of XR, AI, and computer vision in surgical simulation;
o Patient-specific 3D models, digital twins, and preoperative planning tools;
o Robotic and laparoscopic simulation, including haptic feedback and human factors;
o Algorithms for real-time intraoperative guidance, evaluation, and decision support;
o Benchmarking, latency and safety metrics, and simulator-to-clinic validation protocols;
o Curriculum design and adoption challenges in simulation-based medical education;
o Equity, diversity, and global accessibility in simulation technologies;
o Clinical validation studies linking simulation metrics to operative performance and patient outcomes.

We encourage submissions, but are not limited to, in the form of original research articles, reviews, and perspectives.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Curriculum, Instruction, and Pedagogy
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Curriculum, Instruction, and Pedagogy
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: Training, surgical simulation, intraoperative guidance, artificial intelligence, Extended Reality, digital twin, 3D model, computer vision, surgical robotics, laparoscopy, simulation-based training, real-time decision support, clinical validation, preoper

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.