AI-surrogate structure and dose correlation for left anterior descending artery in lung stereotactic body radiotherapy.

BACKGROUND

The left anterior descending (LAD) coronary artery is a critical organ-at-risk in thoracic radiotherapy. In thoracic stereotactic body radiation therapy (SBRT), sharp dose gradients and poor LAD contrast on 4DCT scans introduce uncertainty in LAD dose assessment.

METHODS

We evaluated the performance of an AI-generated LAD region structure as a surrogate for manual LAD contours in early-stage NSCLC. We used deep inspiration breath hold (DIBH) scans from 49 patients with manually delineated LADs; planning risk volume contours were expanded by 3 mm. Then, 96 lung SBRT dose maps were registered by matching the left anterior portion of the heart contours. Dice similarity coefficient (DSC), inclusion ratios (IR), dose-volume histogram (DVH) metrics, linear regression, and linear mixed models were used to compare the structures. The correlation of the AI LAD region and LAD dose to mean heart dose (MHD) was assessed.

RESULTS

The AI LAD region showed strong correlation with manual LAD contours for maximum dose (D1%, R2 = 0.93) and volume receiving ≥10 Gy (V10Gy, R2 = 0.81). The planning risk volume also demonstrated high correlation to the AI LAD region. MHD was a poor predictor of LAD dose (R2≈0.4). Additional dose metric correlations were assessed.

DISCUSSION: To investigate dose volume effects to the LAD during radiotherapy for stage I NSCLC, a robust segmentation paradigm must be established. It must be easily implementable on typical imaging acquired during treatment, with an emphasis on clinical translatability. Our model has shown that the AI LAD region has a strong correlation with LAD dose under typical lung SBRT doses and supports its use for further investigation into LAD dose volume constraints during lung SBRT.

CONCLUSION

AI LAD region provides a clinically feasible and scalable alternative to manual LAD contouring for dose estimation in lung SBRT. Its strong correlation with key dose metrics validates its use in large-scale retrospective and prospective studies.