TY - JOUR
T1 - Untangling surgical gesture analysis-are we even speaking the same language?
T2 - a systematic review
AU - Olsen, Rikke Groth
AU - Andersen, Annarita Ghosh
AU - Hung, Andrew J
AU - Svendsen, Morten Bo Søndergaard
AU - Dagnæs-Hansen, Julia Abildgaard
AU - Konge, Lars
AU - Røder, Andreas
AU - Bjerrum, Flemming
N1 - © 2025. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2025/9
Y1 - 2025/9
N2 - BACKGROUND: Surgeons' technical performance directly influences postoperative outcomes after surgery. Therefore, it is essential to develop the best methods for surgical quality. One method is surgical gesture analysis which can be used with AI models. Our objective was to conduct a systematic review to assess the current evidence for the use of surgical gesture use in minimally invasive surgery, including how surgical gestures have been defined and applied in the existing literature.METHODS: A systematic literature review was performed on September 2nd, 2024, by searching four electronic databases. We identified studies examining minimally invasive surgical procedures assessed with any form of surgical gestures. The modified Joanna Briggs Institute critical appraisal checklist was used for quality assessment and the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) criteria were used for assessment of risk of bias. The protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) prior to the systematic literature review (CRD42024487587).RESULTS: A total of 75 studies were included. The objectives of the studies were assigned to three categories: engineering (n = 59), educational (n = 24), and clinical (n = 4) use of surgical gestures. Surgical gestures were used to assess the experience levels of the surgeons and to provide feedback. Only four studies examined whether surgical gestures could predict patient outcomes but found it was better than traditional clinical features. One-fourth of the studies failed to report on the methods of data collection, data source, and study subjects used.CONCLUSION: Surgical gesture analysis has the potential to be used for competency and quality assessment. However, the current literature lacks consensus on the terminology, study reporting methodology, and data granularity needed to develop solid AI models. This can delay the development and use of surgical gestures. Although using surgical gestures to predict patient outcomes is promising, the field is still in its early stages, and multi-disciplinary collaboration is essential for future research.
AB - BACKGROUND: Surgeons' technical performance directly influences postoperative outcomes after surgery. Therefore, it is essential to develop the best methods for surgical quality. One method is surgical gesture analysis which can be used with AI models. Our objective was to conduct a systematic review to assess the current evidence for the use of surgical gesture use in minimally invasive surgery, including how surgical gestures have been defined and applied in the existing literature.METHODS: A systematic literature review was performed on September 2nd, 2024, by searching four electronic databases. We identified studies examining minimally invasive surgical procedures assessed with any form of surgical gestures. The modified Joanna Briggs Institute critical appraisal checklist was used for quality assessment and the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) criteria were used for assessment of risk of bias. The protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) prior to the systematic literature review (CRD42024487587).RESULTS: A total of 75 studies were included. The objectives of the studies were assigned to three categories: engineering (n = 59), educational (n = 24), and clinical (n = 4) use of surgical gestures. Surgical gestures were used to assess the experience levels of the surgeons and to provide feedback. Only four studies examined whether surgical gestures could predict patient outcomes but found it was better than traditional clinical features. One-fourth of the studies failed to report on the methods of data collection, data source, and study subjects used.CONCLUSION: Surgical gesture analysis has the potential to be used for competency and quality assessment. However, the current literature lacks consensus on the terminology, study reporting methodology, and data granularity needed to develop solid AI models. This can delay the development and use of surgical gestures. Although using surgical gestures to predict patient outcomes is promising, the field is still in its early stages, and multi-disciplinary collaboration is essential for future research.
KW - Humans
KW - Artificial Intelligence
KW - Clinical Competence
KW - Gestures
KW - Minimally Invasive Surgical Procedures/standards
KW - Surgeons/standards
UR - http://www.scopus.com/inward/record.url?scp=105012312944&partnerID=8YFLogxK
U2 - 10.1007/s00464-025-11907-x
DO - 10.1007/s00464-025-11907-x
M3 - Review
C2 - 40739419
SN - 0930-2794
VL - 39
SP - 5538
EP - 5557
JO - Surgical Endoscopy
JF - Surgical Endoscopy
IS - 9
ER -