Zhu, Libing

Abstract 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%, R 2 = 0.93) and volume receiving ≥10 Gy (V10Gy, R 2 = 0.81). The planning risk volume also demonstrated high correlation to the AI LAD region. MHD was a poor predictor of LAD dose ( R 2 ≈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.

Abstract Background The van Herk margin formula, derived for 3‐D conformal radiotherapy with a uniform 3.2 mm dose penumbra and no intrinsic dose buffer, remains widely used to design CTV‐to‐PTV expansions in contemporary image‐guided prostate radiotherapy. However, coplanar VMAT techniques often feature broader penumbrae and explicit PTV–isodose clearances, potentially violating the assumptions underlying the original formulation and leading to overly conservative margins. Purpose We investigated whether the widely adopted van Herk margin formula overestimates clinical target volume (CTV)‐to‐planning target volume (PTV) expansions for contemporary coplanar volumetric modulated arc therapy (VMAT) prostate treatments. Methods Fifty consecutive intact‐prostate VMAT radiotherapy plans (two coplanar arcs; clinical margins 3 mm, except for 2 mm posterior) were exported. Direction‐specific 90% isodose–to‐PTV gaps and penumbra widths were measured. Candidate anisotropic margins were tested by eroding the PTV to create CTV_eval. Monte‐Carlo simulations combined systematic (Σ) shifts with Gaussian random (σ′) blurring kernels of 0–2 mm were performed. Acceptability criteria of (i) CTV Dmin0.03 cc ≥ 90% Rx in ≥ 90% of simulated scenarios or (ii) population tumor‐control probability (TCP) loss < 1 % were used. Results VMAT plans exhibited intrinsic 90% isodose clearances of 3–5 mm laterally/anteriorly and 1–2 mm superior–inferiorly, while axial‐plane penumbras were up to fivefold broader than van Herk's assumption. With a [0, 0, 2] mm (LR/AP/SI) margin, ≥ 90% of patients maintained Dmin0.03 cc ≥ 90% Rx provided Σ lay within an ellipsoid of [2.0, 1.5, 1.8] mm and σ′ ≤ [1.5, 2.0, 1.5] mm. Under TCP criteria the safe Σ ellipsoid for high‐risk disease was [2.5, 1.9, 2.2] mm, while low‐intermediate risk was even less sensitive. Conclusions For image‐guided coplanar VMAT prostate radiotherapy, an anisotropic [0, 0, 2] mm CTV‐to‐PTV margin is sufficient for target coverage. A modified margin expression that subtracts the measured isodose–to‐PTV gap and uses reduced random‐error coefficients better reflects modern practice.