[Computer-based three-dimensional reconstruction of lung cancer using 64-slice CT scanning data and virtual surgery]

Area of Science:

• Medical Imaging
• Surgical Oncology
• Computer-Aided Surgery

Background:

• Lung cancer treatment often requires complex surgical interventions.
• Accurate pre-operative planning is crucial for successful lung cancer surgery.
• Traditional surgical planning relies on 2D imaging, which may limit spatial understanding.

Purpose of the Study:

• To evaluate the clinical utility of three-dimensional (3D) reconstruction of the lung and its vasculature for virtual surgery in lung cancer patients.
• To compare surgical outcomes between patients undergoing virtual surgery planning and those receiving conventional surgical treatment.

Main Methods:

• 24 non-small cell lung cancer patients were divided into experimental (3D model group) and control (conventional group) cohorts.
• 3D models were created using Mimics software from CT scan data for virtual surgical simulation.
• Key surgical metrics including operation time, blood loss, and hospital stay were recorded and compared.

Main Results:

• Successful reconstruction of detailed 3D lung cancer models, including vasculature and adjacent structures.
• 3D models provided enhanced visualization of tumor characteristics and spatial relationships, aiding surgical planning.
• The experimental group demonstrated a significantly shorter operation time compared to the control group (P<0.05).
• No significant differences were observed in blood loss or postoperative hospital stay between the groups.

Conclusions:

• Individualized 3D lung cancer modeling is valuable for preoperative risk assessment and precise surgical planning.
• Virtual surgery simulation using 3D models can optimize surgical strategies for lung cancer.
• This technology has the potential to improve surgical efficiency and patient outcomes in lung cancer treatment.