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

NCT ID: NCT06526754

Last Updated: 2024-12-18

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

64 participants

Study Classification

INTERVENTIONAL

Study Start Date

2019-01-01

Study Completion Date

2024-01-01

Brief Summary

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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. Development and validation of 35 3D-printed liver models, focusing on timeliness, cost, precision, and alignment with digital planning tools.
2. Optimization of the 3D reconstruction process using deep learning to enhance model accuracy and efficiency.
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.

Detailed Description

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The study was conducted in three phases to assess the effectiveness of 3D-printed liver models for hepatobiliary surgery planning, comparing these models with traditional digital simulations.

Phase One: This phase involved the development and validation of 35 3D-printed liver models. The focus was on timeliness, cost, precision, and alignment with digital planning tools. The goal was to ensure that the physical models accurately represented the liver's anatomy as planned digitally.

Phase Two: In this phase, the 3D reconstruction process was optimized using deep learning techniques. The study compared AI-assisted automatic segmentation with manual methods to enhance the accuracy and efficiency of the models. This phase aimed to streamline the model creation process and reduce the time and effort required.

Phase Three: This phase conducted a retrospective comparative analysis involving 64 patients who underwent hepatobiliary surgery. These patients were divided into two groups: one group used validated physical 3D models, and the other group used digital simulations for surgical planning. The phase evaluated various surgical outcomes, including the extent of resection, operation time, intraoperative blood loss, and hospitalization duration. The primary objective was to determine the clinical effectiveness of using 3D-printed models compared to traditional digital simulations in hepatobiliary surgery planning.

By systematically analyzing these three phases, the study aims to provide comprehensive insights into the benefits and potential limitations of using 3D-printed models in surgical planning, ultimately enhancing patient outcomes and surgical precision.

Conditions

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Hepatobiliary Surgery Liver Diseases

Keywords

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

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

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.
Primary Study Purpose

TREATMENT

Blinding Strategy

QUADRUPLE

Participants Caregivers Investigators Outcome Assessors
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.

Study Groups

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3D Printed Model Group (3DP)

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.

Group Type EXPERIMENTAL

3D-Printed Liver Model

Intervention Type 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 Virtual Model Group (3DV)

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.

Group Type EXPERIMENTAL

Digital Simulation-Based Surgical Planning

Intervention Type 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.

Interventions

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3D-Printed Liver Model

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.

Intervention Type DEVICE

Digital Simulation-Based Surgical Planning

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.

Intervention Type PROCEDURE

Eligibility Criteria

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Inclusion Criteria

* 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

Exclusion Criteria

* 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
Minimum Eligible Age

18 Years

Maximum Eligible Age

75 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Yang Jihong

OTHER

Sponsor Role lead

Responsible Party

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Yang Jihong

Doctor of Medicine(M.D.)

Responsibility Role SPONSOR_INVESTIGATOR

Locations

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Affiliated Hospital of Hebei University

Baoding, Hebei, China

Site Status

Countries

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China

Other Identifiers

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2017Z001

Identifier Type: -

Identifier Source: org_study_id