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.
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.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
QUADRUPLE
Enrollment
64
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.
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.
Affiliated Hospital of Hebei University
Baoding, Hebei, China
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.
Time frame: 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.
Time frame: 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.
Time frame: 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.
Time frame: 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.
Time frame: 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.
Time frame: From the date of surgery until discharge, assessed up to 30 days.
Age
Document the age of each patient at the time of surgery in both the 3D Printed Model Group (3DP) and the 3D Virtual Model Group (3DV).
Time frame: Before surgery
Sex
Record the sex of each patient in both the 3D Printed Model Group (3DP) and the 3D Virtual Model Group (3DV).
Time frame: Before surgery
BMI (Body Mass Index)
Measure and record the Body Mass Index (BMI) of each patient in both the 3D Printed Model Group (3DP) and the 3D Virtual Model Group (3DV).
Time frame: Before surgery
AFP (Alpha-Fetoprotein)
Measure the levels of Alpha-Fetoprotein (AFP) in the blood of each patient in both the 3D Printed Model Group (3DP) and the 3D Virtual Model Group (3DV) to assess liver cancer biomarkers.
Time frame: Before surgery
Tumor Size
Measure the size of the tumor in each patient in both the 3D Printed Model Group (3DP) and the 3D Virtual Model Group (3DV).
Time frame: During the surgery
Presence of Liver Cirrhosis
Record whether each patient has liver cirrhosis in both the 3D Printed Model Group (3DP) and the 3D Virtual Model Group (3DV).
Time frame: Before surgery
HBV DNA Levels
Measure the levels of HBV DNA in the blood of each patient in both the 3D Printed Model Group (3DP) and the 3D Virtual Model Group (3DV) to assess the presence and extent of hepatitis B infection.
Time frame: Before surgery
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