The Development and Study of a 3D-Printed Model for Surgical Planning of Lung Cancer with Realistic Subsegmental Boundaries and Complete Tissue Structures

NCT06507774 | Completed

• 1 other identifier: 19277731D
• Study Type: observational
• Target: 150
• Locations: 1 country
• Sites: 1

Brief Summary

This project focuses on the development of a precision multi-organ surgical planning model aided by artificial intelligence (AI), computer-aided design (CAD), multi-material 3D printing, and multimodal 3D modeling. The integration of these advanced technologies aims to enhance the accuracy and efficiency of preoperative planning for complex surgical procedures involving multiple organs. By leveraging AI and CAD, the project seeks to create detailed, patient-specific 3D models that incorporate various imaging modalities. These models will be used to guide multi-material 3D printing, producing highly accurate replicas of anatomical structures. The ultimate goal is to improve surgical outcomes by providing surgeons with precise and comprehensive tools for planning and executing intricate surgeries.

Conditions

Lung Cancer

Outcome Measures

Primary Outcomes (3)

• Operation Time

  Measure the total duration of the surgery in minutes.

  During the surgery

• Blood Loss

  Assess the total blood loss during surgery in milliliters.

  During the surgery

• Postoperative Complications

  Record any complications within 30 days post-surgery.

  Within 30 days post-surgery

Study Arms (2)

3D reconstruction

Patients in this group underwent surgical planning with the aid of 3D reconstruction technology, which included preoperative imaging and 3D modeling to assist in the planning of thoracic surgery.

Device: 3D Reconstruction Technology

Non-3D reconstruction

Patients in this group underwent traditional surgical planning without the use of 3D reconstruction technology, relying on standard preoperative imaging and planning techniques.

Device: No 3D reconstruction is used

Interventions

3D Reconstruction Technology DEVICE

Utilization of 3D reconstruction technology to assist in preoperative planning and surgical procedures for thoracic surgery patients.

3D reconstruction

No 3D reconstruction is used DEVICE

This group did not use 3D reconstruction for surgical navigation

Non-3D reconstruction

Eligibility Criteria

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

Study Population

The study includes all lung cancer patients who underwent surgery at the Affiliated Hospital of Hebei University from 2020 to 2023.

You may qualify if:

• Patients diagnosed with lung cancer
• Complete clinical case data;
• All patients underwent surgical treatment;
• Voluntarily participate in the study and sign the informed consent.

You may not qualify if:

• Severe comorbidities, such as uncontrolled heart disease or diabetes
• History of major surgeries or other interventions
• Unwillingness to participate in the study

Sponsors & Collaborators

• Ke Zhang: lead

Study Sites (1)

Affiliated Hospital of Hebei University

Baoding, Hebei, 071000, China

Location

MeSH Terms

Conditions

Lung Neoplasms

Condition Hierarchy (Ancestors)

Respiratory Tract Neoplasms; Thoracic Neoplasms; Neoplasms by Site; Neoplasms; Lung Diseases; Respiratory Tract Diseases

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: M.D.

Study Record Dates

• First Submitted: July 12, 2024
• First Posted: July 18, 2024
• Study Start: January 1, 2023
• Primary Completion: December 1, 2023
• Study Completion: January 1, 2024
• Last Updated: September 19, 2024

Record last verified: 2024-09

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)