Functional Innovation and Application Research of Domestic Advanced Low-Dose DSA/CT-DSA

Enhancing CBCT-Guided Lung Nodule Puncture Efficiency With Generative AI

The goal of this clinical trial is to learn if Generative AI Based Puncture Surgery Navigation System (GPS) can guide lung puncture in adults better. It will also learn about the quality improvement of cone beam CT (CBCT) by GPS. The main questions it aims to answer are:

• Does GPS lower the number of punctures, radiation dose, and complications of participants undergo percutaneous lung puncture?
• Does GPS improve the quality of CBCT images? Researchers will compare GPS to a conventional CBCT guided percutaneous lung puncture to see if GPS can improve the efficacy of lung puncture.

Participants will:

• Take the percutaneous lung puncture by the guidance of GPS or conventional CBCT (placebo)
• The number of punctures, the success rate of the procedure, the radiation dose, intraoperative complications and postoperative complications at 7 days will be recorded
• The images of CBCT will be collected

Inclusion Criteria:

• Participants who require CBCT-guided precutaneous lung puncture (PLP) and meet the clinical indications for the procedure.
• Participants with pre-operation CT images available.
• Participants whose physical condition is suitable for PLP.

Exclusion Criteria:

• Participants have metallic implants in the body, which severely affects the image quality.
• Participants with a history of allergy or serious adverse reactions to iodine contrast media or other related drugs.
• Participants are pregnant or breastfeeding.
• Participants are unwilling or unable to sign informed consent.