KEY POINTS
- This study evaluated an artificial intelligence-generated left anterior descending coronary artery region as a surrogate for manual left anterior descending coronary artery contours in lung stereotactic body radiotherapy dose assessment.
- The analysis used deep inspiration breath-hold scans from 49 patients with manual contours and registered 96 lung stereotactic body radiotherapy dose maps, all prescribed 50 Gy in 5 fractions, creating 4704 simulated geometric configurations.
- The surrogate region contained the manual left anterior descending coronary artery with an average inclusion ratio of 99%, and contained the 3 mm planning risk volume with an average inclusion ratio of 78%.
- Dose correlation was strong for maximum dose: R² = 0.93 for the manual artery and R² = 0.96 for the 3 mm planning risk volume.
- Volume receiving at least 10 Gy also correlated well: R² = 0.81 for the manual artery and R² = 0.89 for the 3 mm planning risk volume, while mean heart dose was a poor predictor of artery dose with R² ≈ 0.4.
CLINICAL TAKEAWAY
This artificial intelligence-generated region may offer a scalable way to estimate left anterior descending coronary artery dose in lung stereotactic body radiotherapy, where direct contouring is difficult on typical four-dimensional computed tomography. The main value is enabling larger dosimetric and outcomes studies focused on coronary artery exposure. But this remains a technical validation using registered dose maps and deep inspiration breath-hold anatomy, with robustness on routine four-dimensional computed tomography still under investigation.