EC Gynaecology

Background and Objective: Minimally invasive surgery (MIS) is the standard of care for most gynecological conditions in pediatric and adolescent populations. While robotic-assisted surgery (RAS) has seen widespread adoption in adult gynecology, its application in pediatric and adolescent gynecology (PAG) remains limited by anatomical constraints, instrument size, and specialized training requirements. Concurrently, artificial intelligence (AI) is transforming robotic platforms through enhanced navigation, tool tracking, and automated skill assessment. This narrative review evaluates the current evidence for RAS in PAG and explores how emerging AI applications could overcome existing limitations and shape the future of the field.

Methods: A comprehensive literature search was conducted across PubMed, Scopus, and ScienceDirect for articles published between 2010 and 2026. Keywords included “robotic surgery”, “pediatric gynecology”, “adolescent gynecology”, “artificial intelligence”, and “machine learning”. Studies detailing clinical outcomes of RAS in PAG, technical limitations in pediatric patients, and AI integration in robotic surgery were synthesized.

Results: Current evidence demonstrates that RAS is safe and feasible for complex PAG indications, including ovarian-sparing surgery for large adnexal masses, excision of Müllerian remnants, and advanced endometriosis. Reported complication and conversion rates are remarkably low, though data remain limited to retrospective series. The primary technical barriers are the discrepancy between standard 8-mm robotic trocars and the limited pediatric abdominal working space. AI applications particularly convolutional neural networks for real-time tool tracking, automated skill assessment using system kinematics, and predictive modeling for surgical planning offer promising solutions to accelerate the steep learning curve and enhance intraoperative safety in confined anatomical spaces.

Conclusion: RAS represents a safe and enabling technology for complex reconstructive and extirpative procedures in PAG. The integration of AI into robotic platforms has the potential to mitigate current technical limitations, standardize training, and improve objective performance metrics. High-quality prospective studies are urgently needed to define standardized indications and validate AI-driven surgical metrics in the pediatric population.

Keywords: Robotic-Assisted Surgery; Artificial Intelligence; Pediatric and Adolescent Gynecology; Minimally Invasive Surgery; Machine Learning; Surgical Education

1. McCracken M., et al. “Laparoscopy in pediatric and adolescent gynecology”. Obstetrics and Gynecology Clinics of North America 4 (2024): 609-619.
2. Bertozzi M., et al. “Pediatric ovarian torsion and its recurrence: a multicenter study”. Journal of Pediatric and Adolescent Gynecology 3 (2017): 413-417.
3. Pelizzo G., et al. “Pediatric and adolescent gynecology: treatment perspectives in minimally invasive surgery”. Pediatric Reports 4 (2019): 8029.
4. Nakib G., et al. “Robotic assisted surgery in pediatric gynecology: promising innovation in mini invasive surgical procedures”. Journal of Pediatric and Adolescent Gynecology 1 (2013): e5-e7.
5. Nobbenhuis MAE., et al. “Robotic surgery in gynaecology: Scientific Impact Paper No. 71 (July 2022)”. BJOG: An International Journal of Obstetrics and Gynaecology 1 (2023): e1-e8.
6. Krebs TF., et al. “Robotically assisted surgery in children-A perspective”. Children (Basel)5 (2022): 839.
7. Tasdemirci C., et al. “Review on the utility of artificial intelligence in robotic surgery”. Current Problems in Surgery 74 (2025): 101941.
8. Soleymani A., et al. “Applications to surgical skills assessment and transfer”. Robotic Surgery (2023).
9. Esposito C., et al. “Seven years of pediatric robotic-assisted surgery: insights from 105 procedures”. Journal of Robotic Surgery 1 (2025): 157.
10. Fusi G., et al. “Pediatric robotic gynecologic surgery: a retrospective institutional experience and systematic review”. Journal of Pediatric Surgery 12 (2025): 162713.
11. Cantagalli MM., et al. “Robotic-assisted surgery as an enabling technology for ovarian-sparing surgery”. Frontiers in Pediatrics 13 (2026): 1880852.
12. Kebodeaux CA., et al. “Robotic-assisted laparoscopic approach to removal of Müllerian remnants”. Journal of Pediatric and Adolescent Gynecology 1 (2022): 98-100.
13. Kim C., et al. “Robotic sigmoid vaginoplasty: a novel technique”. Urology4 (2008): 847-849.
14. Shen LT and Tou J. “Application and prospects of robotic surgery in children: a scoping review”. World Journal of Pediatric Surgery 4 (2022): e000482.
15. Padoy N. “Machine learning for surgical workflows”. Artificial Intelligence Surgery (2019).
16. Mattioli G., et al. “Advancements and outcomes of robotic-assisted surgery in pediatric patients: a multicenter study”. Frontiers in Pediatrics 13 (2025): 1652840.
17. Pedrett R., et al. “Technical skill assessment in minimally invasive surgery using artificial intelligence: a systematic review”. Surgical Endoscopy 10 (2023): 7412-7424.