feasibility analysis of lcd-sla 3d printing technology for overall surgical planning of liver malignant tumors

Conditions: Hepatobiliary Surgery; Liver Diseases

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.

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.

Eligibility criteria:
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

Keywords: 3d printing artificial intelligence (ai) deep learning liver model surgical precision hepatobiliary surgery 3d modeling randomized controlled trial medical imaging digital simulations