Feasibility Analysis of LCD-SLA 3D Printing Technology for Overall Surgical Planning of Liver Malignant Tumors

NCT06526754 | Completed DMC

• 1 other identifier: 2017Z001
• Study Type: interventional
• Target: 64
• Locations: 1 country
• Sites: 1

Brief Summary

This study aims to evaluate the effectiveness of 3D-printed liver models in hepatobiliary surgery planning compared to traditional digital simulations. It is conducted in three phases:

1. 1.Development and validation of 35 3D-printed liver models, focusing on timeliness, cost, precision, and alignment with digital planning tools.
2. 2.Optimization of the 3D reconstruction process using deep learning to enhance model accuracy and efficiency.
3. 3.A retrospective comparative analysis of surgical outcomes in 64 patients, with one group using 3D-printed models and the other using digital simulations for surgical planning.

Conditions

Hepatobiliary Surgery; Liver Diseases

Keywords

3D Printing; Artificial Intelligence (AI); Deep Learning; Liver Model; Surgical Precision; Hepatobiliary Surgery; 3D Modeling; Randomized Controlled Trial; Medical Imaging; Digital Simulations

Outcome Measures

Primary Outcomes (6)

• Intraoperative Blood Loss

  Measure the volume of blood loss during surgery for each patient in both the 3D Printed Model Group (3DP) and the 3D Virtual Model Group (3DV). This outcome assesses the efficacy of using 3D-printed liver models in reducing intraoperative blood loss compared to digital simulations.

  During the surgery

• Blood Transfusion

  Assess the need for intraoperative blood transfusions for each patient in both the 3D Printed Model Group (3DP) and the 3D Virtual Model Group (3DV). This outcome evaluates the impact of using 3D-printed liver models on the necessity for transfusions.

  During the surgery

• Operation Duration

  Measure the total duration of the surgical procedure for each patient in both the 3D Printed Model Group (3DP) and the 3D Virtual Model Group (3DV). This outcome assesses whether the use of 3D-printed models can reduce operation time.

  During the surgery

• Surgical Margin Status

  Assess the status of surgical margins post-resection to determine the precision of tumor removal in both the 3D Printed Model Group (3DP) and the 3D Virtual Model Group (3DV). R0 indicates no residual tumor, R1 indicates microscopic residual tumor.

  Immediately after surgery

• Postoperative Hospital Stay

  Measure the length of hospital stay post-surgery for each patient in both the 3D Printed Model Group (3DP) and the 3D Virtual Model Group (3DV). This outcome evaluates the impact of 3D-printed models on postoperative recovery time.

  From surgery to discharge

• Postoperative Complications

  Measure the length of hospital stay post-surgery for each patient in both the 3D Printed Model Group (3DP) and the 3D Virtual Model Group (3DV). This outcome evaluates the impact of 3D-printed models on postoperative recovery time.

  From the date of surgery until discharge, assessed up to 30 days.

Secondary Outcomes (7)

• Age

  Before surgery

• Sex

  Before surgery

• BMI (Body Mass Index)

  Before surgery

• AFP (Alpha-Fetoprotein)

  Before surgery

• Tumor Size

  During the surgery

Study Arms (2)

3D Printed Model Group (3DP)

EXPERIMENTAL

Participants in this group will receive surgical planning based on physically developed and validated 3D-printed liver models from Phase One. The surgical procedures will be guided by these 3D-printed models.

Device: 3D-Printed Liver Model

3D Virtual Model Group (3DV)

EXPERIMENTAL

Participants in this group will receive surgical planning based on digital simulations using the fastest AI-assisted segmentation method with manual adjustments from Phase Two. The surgical procedures will be guided by these digital simulations.

Procedure: Digital Simulation-Based Surgical Planning

Interventions

3D-Printed Liver Model DEVICE

Participants in the 3D Printed Model Group (3DP) will receive surgical planning based on physically developed and validated 3D-printed liver models from Phase One. These models will be used to guide the surgical procedures.

3D Printed Model Group (3DP)

Digital Simulation-Based Surgical Planning PROCEDURE

Participants in the 3D Virtual Model Group (3DV) will receive surgical planning based on digital simulations using the fastest AI-assisted segmentation method with manual adjustments from Phase Two. These digital simulations will be used to guide the surgical procedures.

3D Virtual Model Group (3DV)

Eligibility Criteria

• Age: 18 Years - 75 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Age: Patients aged 18-75 years
• Gender: Both male and female patients
• Diagnosis: Confirmed diagnosis of hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (iCCA), or perihilar cholangiocarcinoma (pCCA)
• Surgical Candidates: Patients who are candidates for hepatectomy
• Liver Function: Patients with adequate liver function (Child-Pugh A or B)
• Informed Consent: Patients who provide written informed consent

You may not qualify if:

• Non-Surgical Candidates: Patients not eligible for surgery due to advanced disease or comorbidities
• Pregnancy: Pregnant or breastfeeding women
• Severe Comorbidities: Patients with severe cardiovascular, respiratory, renal, or other systemic diseases
• Previous Liver Surgery: Patients with a history of previous liver resection or transplantation
• Uncontrolled Infections: Patients with uncontrolled active infections
• Inability to Comply: Patients unable to comply with study procedures or follow-up

Sponsors & Collaborators

• Yang Jihong: lead

Study Sites (1)

Affiliated Hospital of Hebei University

Baoding, Hebei, 071000, China

Location

MeSH Terms

Conditions

Liver Diseases

Condition Hierarchy (Ancestors)

Digestive System Diseases

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: QUADRUPLE
• Who Masked: PARTICIPANT, CARE PROVIDER, INVESTIGATOR, OUTCOMES ASSESSOR
• Masking Details: he random allocation sequence was implemented using sequentially numbered, opaque sealed envelopes, each containing a card indicating group assignment. An independent administrative staff member, not involved in enrollment or treatment, prepared the envelopes. To conceal the allocation sequence, envelopes were stored in a secure, locked cabinet accessible only to the study coordinator, who was not involved in patient evaluations or surgeries. This maintained clinician blindness to allocations, preserving the integrity of the randomization process. Third-party medical staff, blinded to group allocation, evaluated the outcomes to ensure objective assessment.
• Purpose: TREATMENT
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Doctor of Medicine(M.D.)

Model Details: This study involves three phases. Phase one focuses on developing and validating 3D-printed liver models. Phase two optimizes the 3D reconstruction process using AI-assisted segmentation. Phase three is a randomized controlled trial comparing surgical outcomes using physical 3D models versus digital simulations.

Study Record Dates

• First Submitted: July 19, 2024
• First Posted: July 30, 2024
• Study Start: January 1, 2019
• Primary Completion: January 1, 2024
• Study Completion: January 1, 2024
• Last Updated: December 18, 2024

Record last verified: 2024-12

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ICF, CSR, ANALYTIC CODE
• Time Frame: The data will be available starting 6 months after the publication and will be accessible for 5 years.
• Access Criteria: Data will be shared with researchers who provide a methodologically sound proposal. Proposals should be directed to \[lilinqian163@163.com\]. To gain access, data requestors will need to sign a data access agreement.

Locations

CN (1)