Hepatobiliary Surgery, Liver Diseases
Conditions
Keywords
3D Printing, Artificial Intelligence (AI), Deep Learning, Liver Model, Surgical Precision, Hepatobiliary Surgery, 3D Modeling, Randomized Controlled Trial, Medical Imaging, Digital Simulations
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. 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
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.
Interventions
DEVICE3D-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.
PROCEDUREDigital 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.
Sponsors
Yang Jihong
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
QUADRUPLE (Subject, Caregiver, Investigator, Outcomes Assessor)
Masking description
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.
Intervention model description
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.
Eligibility
Sex/Gender
ALL
Age
18 Years to 75 Years
Healthy volunteers
No
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Intraoperative Blood Loss | During the surgery | 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. |
| Blood Transfusion | During the surgery | 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. |
| Operation Duration | During the surgery | 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. |
| Surgical Margin Status | Immediately after surgery | 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. |
| Postoperative Hospital Stay | From surgery to discharge | 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. |
| Postoperative Complications | From the date of surgery until discharge, assessed up to 30 days. | 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. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Age | Before surgery | 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). |
| HBV DNA Levels | Before surgery | 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. |
| Sex | Before surgery | Record the sex of each patient in both the 3D Printed Model Group (3DP) and the 3D Virtual Model Group (3DV). |
| BMI (Body Mass Index) | Before surgery | 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). |
| AFP (Alpha-Fetoprotein) | Before surgery | 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. |
| Tumor Size | During the surgery | Measure the size of the tumor in each patient in both the 3D Printed Model Group (3DP) and the 3D Virtual Model Group (3DV). |
| Presence of Liver Cirrhosis | Before surgery | Record whether each patient has liver cirrhosis in both the 3D Printed Model Group (3DP) and the 3D Virtual Model Group (3DV). |
Countries
China
Outcome results
None listed