The goal of this study aims to investigate the use of artificial intelligence to analyze and evaluate the characteristics and proficiency of surgeons during vascular anastomosis in coronary artery bypass grafting (CABG) procedures. The main question it aims to answer is:

Consistency assessment between AI evaluation scores and human expert evaluation scores for surgeons during left anterior descending (LAD) artery anastomosis.

Inclusion Criteria:

• Age ≥ 18 years
• Undergoing internal mammary artery-to-left anterior descending artery bypass grafting
• First-time recipient of isolated CABG surgery
• Signed written informed consent

Exclusion Criteria:

• Patients with acute coronary syndrome
• Patients with contraindications to coronary CT angiography or coronary angiography
• Patients with renal insufficiency or active liver disease, including those with persistently elevated serum transaminases of unknown cause or any serum transaminase levels exceeding three times the upper limit of normal.

The study population consists of adult patients who meet the inclusion criteria of being aged 18 years or older, undergoing their first isolated coronary artery bypass grafting (CABG) surgery using internal mammary artery-to-left anterior descending artery bypass grafting. All participants should signed written informed consent prior to inclusion in the study.

Exclusion criteria include patients with acute coronary syndrome, contraindications to coronary CT angiography or coronary angiography, and those with renal insufficiency or active liver disease. Specifically, patients with persistently elevated serum transaminases of unknown cause or those with any serum transaminase levels exceeding three times the upper limit of normal will also be excluded from the study.