A new preoperative localization of pulmonary nodules guided by mixed reality: a pilot study of an animal model.

Mixed reality (MR) localization pilot study pulmonary nodules

Journal

Translational lung cancer research
ISSN: 2218-6751
Titre abrégé: Transl Lung Cancer Res
Pays: China
ID NLM: 101646875

Informations de publication

Date de publication:
31 Jan 2023
Historique:
received: 26 10 2022
accepted: 03 01 2023
entrez: 10 2 2023
pubmed: 11 2 2023
medline: 11 2 2023
Statut: ppublish

Résumé

With the popularity of high-resolution computed tomography (HRCT), more and more pulmonary nodules are being discovered. Video-assisted thoracoscopic surgery (VATS) has become the first choice for surgical treatment of pulmonary nodules. The use of accurate preoperative localization is crucial for successful resection in VATS. At present, there are many kinds of preoperative localization methods, but there are certain disadvantages. This study aimed to evaluate the feasibility and safety of mixed reality (MR)-guided pulmonary nodules localization, which is a new method that can benefit patients to a greater extent. By constructing an animal model of pulmonary nodules localization, 28 cases of pulmonary nodules were located by MR-guided localization. We recorded the localization accuracy, localization time, insertion attempts, and incidence of complications related to localization under MR-guidance. All 28 nodules were successfully located: the deviation of MR-guided localization was 5.71±2.59 mm, localization time was 8.07±1.44 min, and insertion attempts was 1. A pneumothorax and localizer dislodgement occurred in 1 case, respectively. Since preoperative localization is critical for VATS resection of pulmonary nodules, we investigated a new localization method. As indicated by our study, MR-guided localization of pulmonary nodules is feasible and safe, which is worthy of further research and promotion. We have also registered corresponding clinical trials to further investigate and help to improve our understanding of this technique.

Sections du résumé

Background UNASSIGNED
With the popularity of high-resolution computed tomography (HRCT), more and more pulmonary nodules are being discovered. Video-assisted thoracoscopic surgery (VATS) has become the first choice for surgical treatment of pulmonary nodules. The use of accurate preoperative localization is crucial for successful resection in VATS. At present, there are many kinds of preoperative localization methods, but there are certain disadvantages. This study aimed to evaluate the feasibility and safety of mixed reality (MR)-guided pulmonary nodules localization, which is a new method that can benefit patients to a greater extent.
Methods UNASSIGNED
By constructing an animal model of pulmonary nodules localization, 28 cases of pulmonary nodules were located by MR-guided localization. We recorded the localization accuracy, localization time, insertion attempts, and incidence of complications related to localization under MR-guidance.
Results UNASSIGNED
All 28 nodules were successfully located: the deviation of MR-guided localization was 5.71±2.59 mm, localization time was 8.07±1.44 min, and insertion attempts was 1. A pneumothorax and localizer dislodgement occurred in 1 case, respectively.
Conclusions UNASSIGNED
Since preoperative localization is critical for VATS resection of pulmonary nodules, we investigated a new localization method. As indicated by our study, MR-guided localization of pulmonary nodules is feasible and safe, which is worthy of further research and promotion. We have also registered corresponding clinical trials to further investigate and help to improve our understanding of this technique.

Identifiants

pubmed: 36762064
doi: 10.21037/tlcr-22-884
pii: tlcr-12-01-150
pmc: PMC9903086
doi:

Types de publication

Journal Article

Langues

eng

Pagination

150-157

Informations de copyright

2023 Translational Lung Cancer Research. All rights reserved.

Déclaration de conflit d'intérêts

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-22-884/coif). GD reports personal fees from ASTRA ZENECA, outside the submitted work. The other authors have no conflicts of interest to declare.

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Auteurs

Ning Xin (N)

Department of Thoracic Surgery, PLA 960th Hospital, Jinan, China.
Department of Thoracic Surgery, Shanghai Changzheng Hospital, Navy Military Medical University, Shanghai, China.

Xiaoyu Wu (X)

School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.

Zihao Chen (Z)

Department of Thoracic Surgery, Shanghai Changzheng Hospital, Navy Military Medical University, Shanghai, China.

Rongqiang Wei (R)

Department of Thoracic Surgery, Shanghai Changzheng Hospital, Navy Military Medical University, Shanghai, China.

Yuichi Saito (Y)

Department of Surgery, Teikyo University School of Medicine, Tokyo, Japan.

Samy Lachkar (S)

Department of Pulmonology, Thoracic Oncology and Respiratory Intensive Care, Hôpital Charles Nicolle, CHU de Rouen, Rouen Cedex, France.

Alberto Salvicchi (A)

Thoracic Surgery Unit, Careggi University Hospital, Florence, Italy.

Satoshi Fumimoto (S)

Department of Thoracic and Cardiovascular Surgery, Osaka Medical and Pharmaceutical University, Osaka, Japan.

Gabrielle Drevet (G)

Department of Thoracic Surgery, Lung and Heart-Lung Transplantation, Louis Pradel Hospital, Hospices Civils de Lyon, Lyon, France.

Zhifei Xu (Z)

Department of Thoracic Surgery, Shanghai Changzheng Hospital, Navy Military Medical University, Shanghai, China.

Kenan Huang (K)

Department of Thoracic Surgery, Shanghai Changzheng Hospital, Navy Military Medical University, Shanghai, China.

Hua Tang (H)

Department of Thoracic Surgery, Shanghai Changzheng Hospital, Navy Military Medical University, Shanghai, China.

Classifications MeSH