Mixed Reality and Artificial Intelligence: A Holistic Approach to Multimodal Visualization and Extended Interaction in Knee Osteotomy.

Lower limb osteotomy deep neural networks image segmentation surgical planning

Journal

IEEE journal of translational engineering in health and medicine
ISSN: 2168-2372
Titre abrégé: IEEE J Transl Eng Health Med
Pays: United States
ID NLM: 101623153

Informations de publication

Date de publication:
2024
Historique:
received: 25 07 2023
revised: 16 10 2023
revised: 03 11 2023
accepted: 17 11 2023
medline: 27 2 2024
pubmed: 27 2 2024
entrez: 27 2 2024
Statut: epublish

Résumé

Recent advancements in augmented reality led to planning and navigation systems for orthopedic surgery. However little is known about mixed reality (MR) in orthopedics. Furthermore, artificial intelligence (AI) has the potential to boost the capabilities of MR by enabling automation and personalization. The purpose of this work is to assess Holoknee prototype, based on AI and MR for multimodal data visualization and surgical planning in knee osteotomy, developed to run on the HoloLens 2 headset. Two preclinical test sessions were performed with 11 participants (eight surgeons, two residents, and one medical student) executing three times six tasks, corresponding to a number of holographic data interactions and preoperative planning steps. At the end of each session, participants answered a questionnaire on user perception and usability. During the second trial, the participants were faster in all tasks than in the first one, while in the third one, the time of execution decreased only for two tasks ("Patient selection" and "Scrolling through radiograph") with respect to the second attempt, but without statistically significant difference (respectively [Formula: see text] = 0.14 and [Formula: see text] = 0.13, [Formula: see text]). All subjects strongly agreed that MR can be used effectively for surgical training, whereas 10 (90.9%) strongly agreed that it can be used effectively for preoperative planning. Six (54.5%) agreed and two of them (18.2%) strongly agreed that it can be used effectively for intraoperative guidance. In this work, we presented Holoknee, the first holistic application of AI and MR for surgical planning for knee osteotomy. It reported promising results on its potential translation to surgical training, preoperative planning, and surgical guidance. Clinical and Translational Impact Statement - Holoknee can be helpful to support surgeons in the preoperative planning of knee osteotomy. It has the potential to impact positively the training of the future generation of residents and aid surgeons in the intraoperative stage.

Identifiants

pubmed: 38410183
doi: 10.1109/JTEHM.2023.3335608
pmc: PMC10896423
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

279-290

Informations de copyright

© 2023 The Authors.

Auteurs

Andrea Moglia (A)

Department of ElectronicsInformation and BioengineeringPolitecnico di Milano 20133 Milan Italy.

Luca Marsilio (L)

Department of ElectronicsInformation and BioengineeringPolitecnico di Milano 20133 Milan Italy.

Matteo Rossi (M)

Department of ElectronicsInformation and BioengineeringPolitecnico di Milano 20133 Milan Italy.
Istituto Auxologico Italiano IRCCS 20149 Milan Italy.

Maria Pinelli (M)

Department of Management, Economics and Industrial EngineeringPolitecnico di Milano 20133 Milan Italy.

Emanuele Lettieri (E)

Department of Management, Economics and Industrial EngineeringPolitecnico di Milano 20133 Milan Italy.

Luca Mainardi (L)

Department of ElectronicsInformation and BioengineeringPolitecnico di Milano 20133 Milan Italy.

Alfonso Manzotti (A)

Hospital ASST FBF-Sacco 20157 Milan Italy.

Pietro Cerveri (P)

Department of ElectronicsInformation and BioengineeringPolitecnico di Milano 20133 Milan Italy.
Istituto Auxologico Italiano IRCCS 20149 Milan Italy.

Classifications MeSH