Clinical Study to Prove Safety and Effectiveness When Applying RUS™ Surgical Navigation

NCT05039333 | Unknown DMC FDA Device

• 1 other identifier: 1-2021-0036
• Study Type: observational
• Target: 36
• Locations: 1 country
• Sites: 1

Brief Summary

By uploading pre-operative patient information and patient CT data to RUS™, a virtual surgical environment with patient-specific relief prediction models can be provided. First, after uploading the CT and clinical information of a gastric cancer patient diagnosed with gastric cancer through an actual endoscopic biopsy and scheduled for robotic total gastrectomy, RUS™ will operate normally to check whether patient-specific surgical navigation is available before or during surgery. In particular, when using the patient-specific surgery simulation system provided by RUS™, the CT information provides a patient-specific 3D environment well, so it will be checked regarding whether the surgeon can use it before or during surgery without any particular problems. Using RUS™ software, navigation information is used before or during surgery, and among these, parts that can be quantitatively compared with actual measurements will be evaluated as a secondary research goal. After the surgery, the investigators plan to check the amount of bleeding, duration of hospitalization, and the rate of complications by performing robot gastrointestinal resection using the navigation system to ensure that there are no problems with patient safety.

Conditions

Surgery; Gastric Cancer

Keywords

Surgical navigation; Robotic gastrectomy; Image-guided surgery; Anatomy 3D-reconstruction

Outcome Measures

Primary Outcomes (9)

• CT turn around

  After the subject's CT is uploaded to the RUS™ software and segmentation is started, it is evaluated whether the relief model is created, segmentation of organs and blood vessels, and 3D reconstruction are performed and uploaded within 3 days.

  1 week

• Patient-specific pneumoperitoneum model accuracy

  The accuracy is evaluated by comparing the patient-specific relief prediction model presented by the RUS™ surgical navigation with the actual patient's relief model scan data.

  1 month

• Pre-trocar insertion function accuracy

  When the virtual trocar is inserted into the relief model in RUS™, the position and distance information of the trocar is provided, and the accuracy is evaluated by comparing it with the insertion position of the real trocar.

  1 week

• Major blood vessel presentation

  Evaluate whether the major blood vessels (a total of 7 (LGEA, RGEA, LGA, RGA, LGEV, RGEV, LGV)) that must be checked in total gastrectomy are 100% 3D reconstructed on the RUS™ navigation system.

  1 week

• Distance of major blood vessels

  By comparing the branching distance of major blood vessels in RUS™ (total 7 (LGEA, RGEA, LGA, RGA, LGEV, RGEV, LGV)) and the branching distance of major blood vessels during actual surgery, it is evaluated whether the accuracy is greater than 90%.

  1 week

• Bleeding volume

  When robotic total gastrectomy is performed using RUS™ surgical navigation, the amount of bleeding is measured and compared with the previous control group.

  1 day

• Surgery time

  When robotic total gastric resection is performed using RUS™ surgical navigation, the operation time (console time in the case of robotic surgery) is measured and compared with the past control group.

  1 day

• Hospital stay after surgery

  When robotic total gastrectomy is performed using RUS™ surgical navigation, the patient's postoperative hospital stay is checked and compared with the past control group.

  1 month

• Complication rate

  When robotic total gastric resection is performed using RUS™ surgical navigation, the patient's complication rate is checked and compared with the past control group.

  1 month

Study Arms (1)

RUS (Surgical navigation, anatomy 3D-reconstruction)

single-arm study : prospective observational 1-arm (RUS group)

Device: RUS(TM) software : surgical navigation

Interventions

RUS(TM) software : surgical navigation DEVICE

This clinical trial is a sponsor-led clinical trial, and it is intended to confirm that RUS™, a surgical navigation system certified for level 2 endoscopic imaging treatment planning software, can be applied to real people as a clinical study by using preoperative CT and to confirm the safety of surgery. In addition, the secondary research objective was to examine the accuracy of the intra-abdominal surgical navigation system provided by RUS™ including: 1) the accuracy of the undulation prediction model, 2) the accuracy of the trocar insertion position, 3) the adequacy of 3D reconstruction of the main vessels, 4) the accuracy of the major vessel branching distances, 5) the intraoperative bleeding volume and operating time, and 6) the postoperative hospitalization period and complication rate were compared with the past control group.

RUS (Surgical navigation, anatomy 3D-reconstruction)

Eligibility Criteria

• Age: 18 Years - 80 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Diagnosed as gastric cancer Patients who will be carried out Robotic Gastrectomy in Yonsei University Health System, Severance Hospital

You may qualify if:

• Among the subjects, the subjects are selected according to the following criteria:
• Those who have been diagnosed with gastric cancer and are scheduled for robotic total gastrectomy;
• A person who is 18 years of age or older and able to make independent judgment on their own;
• A person who can have a CT scan according to the established protocol;
• Before participating in the clinical trial, an interview was conducted in an independent space, the purpose and contents of the clinical trial were fully explained, and the consent to participate in this study was voluntarily given (approved by the institutional research ethics review committee) and those who signed.

You may not qualify if:

• Vulnerable subjects (those who lack medical ability, or are illiterate, pregnant, newborns, minors (under 18), etc.);
• Persons who cannot have a CT scan according to the prescribed protocol prior to gastric cancer surgery (contrast agent allergy, creatinine 1.5 times the normal maximum, claustrophobia, etc.);
• Persons whose major artery/venous structure in the stomach or abdominal cavity has been altered due to previous surgery (due to gastric cancer or other abdominal surgery);
• Persons with residual gastric cancer with a history of gastric surgery;
• Persons who did not consent to this study or who withdrew consent.

Sponsors & Collaborators

• Hutom Corp: lead

Study Sites (1)

Yonsei University Health System Severance Hospital

Seoul, 03722, South Korea

Location

Related Publications (8)

• Bano J, Hostettler A, Nicolau SA, Cotin S, Doignon C, Wu HS, Huang MH, Soler L, Marescaux J. Simulation of pneumoperitoneum for laparoscopic surgery planning. Med Image Comput Comput Assist Interv. 2012;15(Pt 1):91-8. doi: 10.1007/978-3-642-33415-3_12.

  PMID: 23285539 BACKGROUND

• Nimura Y, Di Qu J, Hayashi Y, Oda M, Kitasaka T, Hashizume M, Misawa K, Mori K. Pneumoperitoneum simulation based on mass-spring-damper models for laparoscopic surgical planning. J Med Imaging (Bellingham). 2015 Oct;2(4):044004. doi: 10.1117/1.JMI.2.4.044004. Epub 2015 Dec 17.

  PMID: 26697510 BACKGROUND

• Nasajiyan N, Javaherfourosh F, Ghomeishi A, Akhondzadeh R, Pazyar F, Hamoonpou N. Comparison of low and standard pressure gas injection at abdominal cavity on postoperative nausea and vomiting in laparoscopic cholecystectomy. Pak J Med Sci. 2014 Sep;30(5):1083-7. doi: 10.12669/pjms.305.5010.

  PMID: 25225531 BACKGROUND

• Dawda S, Camara M, Pratt P, Vale J, Darzi A, Mayer E. Patient-Specific Simulation of Pneumoperitoneum for Laparoscopic Surgical Planning. J Med Syst. 2019 Sep 10;43(10):317. doi: 10.1007/s10916-019-1441-z.

  PMID: 31506884 BACKGROUND

• Oktay O, Zhang L, Mansi T, Mountney P, Mewes P, Nicolau S, Soler L, Chefd'hotel C. Biomechanically driven registration of pre- to intra-operative 3D images for laparoscopic surgery. Med Image Comput Comput Assist Interv. 2013;16(Pt 2):1-9. doi: 10.1007/978-3-642-40763-5_1.

  PMID: 24579117 BACKGROUND

• Mori K, Sakuma I, Sato Y, Barillot C, Navab N. Preface. The 16th international conference on medical image computing and computer-assisted intervention-MICCAI 2013. Med Image Comput Comput Assist Interv. 2013;16(Pt 1):V-VIII. No abstract available.

  PMID: 24505641 BACKGROUND

• Kim YM, Baek SE, Lim JS, Hyung WJ. Clinical application of image-enhanced minimally invasive robotic surgery for gastric cancer: a prospective observational study. J Gastrointest Surg. 2013 Feb;17(2):304-12. doi: 10.1007/s11605-012-2094-0. Epub 2012 Dec 1.

  PMID: 23207683 RESULT

• Park SH, Kim KY, Kim YM, Hyung WJ. Patient-specific virtual three-dimensional surgical navigation for gastric cancer surgery: A prospective study for preoperative planning and intraoperative guidance. Front Oncol. 2023 Feb 21;13:1140175. doi: 10.3389/fonc.2023.1140175. eCollection 2023.

  PMID: 36895483 DERIVED

MeSH Terms

Conditions

Stomach Neoplasms

Condition Hierarchy (Ancestors)

Gastrointestinal Neoplasms; Digestive System Neoplasms; Neoplasms by Site; Neoplasms; Digestive System Diseases; Gastrointestinal Diseases; Stomach Diseases

Central Study Contacts

Yu Min Kim, Professor

CONTACT

+82-2-2228-2100; ymkim@yuhs.ac

Study Design

• Study Type: observational
• Observational Model: CASE ONLY
• Time Perspective: PROSPECTIVE
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: August 26, 2021
• First Posted: September 9, 2021
• Study Start: September 1, 2021
• Primary Completion: December 24, 2021
• Study Completion: June 23, 2022
• Last Updated: September 9, 2021

Record last verified: 2021-09

Data Sharing

• IPD Sharing: Will not share

Locations

KR (1)