ArticleFrontiers in oncology2026
Comparative dosimetric and radiobiological assessment of a hybrid-VMAT strategy incorporating supplemental short-arcs for left-sided postmastectomy radiotherapy.
Article in Frontiers in oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Purpose: Postmastectomy radiotherapy (PMRT) for left-sided breast cancer poses persistent dosimetric challenges due to the complex target geometry and its proximity to critical organs at risk (OARs), particularly the heart and the left anterior descending (LAD) coronary artery. This study evaluated the dosimetric and radiobiological performance of a volumetric modulated arc therapy (VMAT) approach incorporating a supplemental short-arc segment, comparing it against conventional IMRT and standard VMAT strategies. Methods: Thirty-six left-sided breast cancer patients undergoing PMRT were retrospectively replanned using six techniques: 5-field and 7-field IMRT, tangential half-arc and wide-arc VMAT (THVP, TWVP), and two modified VMAT plans augmented with a 40° short-arc segment (sub-THVP, sub-TWVP) designed for coronary sparing. Plan quality was assessed via dose-volume histogram (DVH) metrics. Radiobiological evaluation included Normal Tissue Complication Probability (NTCP) via the Lyman-Kutcher-Burman and Poisson-LQ models, alongside secondary cancer risk (EAR/ERR) quantification using the full mechanistic Schneider OED model. Results: All VMAT-based techniques significantly improved target conformity and homogeneity over IMRT (p< 0.001). Among all evaluated strategies, sub-TWVP achieved the optimal trade-off between target coverage and cardiopulmonary sparing. It yielded the lowest ipsilateral lung exposure (V Conclusion: Incorporating a 40° supplemental short-arc into tangential VMAT-particularly within a wide-arc configuration-significantly enhances cardiac and LAD sparing while preserving VMAT's superior target coverage. Integrating complementary radiobiological modeling with DVH metrics provides critical insights for optimizing technique selection, effectively balancing normal-tissue toxicity against secondary cancer risks.
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