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Optimization of sub-arc collimator angles in volumetric modulated arc therapy: a heatmap-based blocking index approach for multiple brain metastases.
- Source :
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Physical and engineering sciences in medicine [Phys Eng Sci Med] 2024 Dec; Vol. 47 (4), pp. 1639-1650. Date of Electronic Publication: 2024 Sep 05. - Publication Year :
- 2024
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Abstract
- To develop and assess an automated Sub-arc Collimator Angle Optimization (SACAO) algorithm and Cumulative Blocking Index Ratio (CBIR) metrics for single-isocenter coplanar volumetric modulated arc therapy (VMAT) to treat multiple brain metastases. This study included 31 patients with multiple brain metastases, each having 2 to 8 targets. Initially, for each control point, the MLC blocking index was calculated at different collimator angles, resulting in a two-dimensional heatmap. Optimal sub-arc segmentation and collimator angle optimization were achieved using an interval dynamic programming algorithm. Subsequently, VMAT plans were designed using two approaches: SACAO and the conventional Full-Arc Fixed Collimator Angle. CBIR was calculated as the ratio of the cumulative blocking index between the two plan approaches. Finally, dosimetric and planning parameters of both plans were compared. Normal brain tissue, brainstem, and eyes received better protection in the SACAO group (Pā<ā0.05).Query Notable reductions in the SACAO group included 11.47% in gradient index (GI), 15.03% in monitor units (MU), 15.73% in mean control point Jaw area (A <subscript>Jaw,mean</subscript> ), and 19.14% in mean control point Jaw-X width (W <subscript>Jaw-X,mean</subscript> ), all statistically significant (Pā<ā0.001). Furthermore, CBIR showed a strong negative correlation with the degree of plan improvement. The SACAO method enhanced protection of normal organs while improving transmission efficiency and optimization performance of VMAT. In particular, the CBIR metrics show promise in quantifying the differences specifically in the 'island blocking problem' between SACAO and conventional VMAT, and in guiding the enhanced application of the SACAO algorithm.<br />Competing Interests: Declarations. Competing interests: The authors declare that they have no competing interests. Ethics approval: This retrospective study was approved by the Hunan Cancer Hospital Medical Ethics Review Committee, with the ethical approval number being the 52nd of the 2024 Scientific Research Ethics Review.<br /> (© 2024. Australasian College of Physical Scientists and Engineers in Medicine.)
Details
- Language :
- English
- ISSN :
- 2662-4737
- Volume :
- 47
- Issue :
- 4
- Database :
- MEDLINE
- Journal :
- Physical and engineering sciences in medicine
- Publication Type :
- Academic Journal
- Accession number :
- 39235667
- Full Text :
- https://doi.org/10.1007/s13246-024-01477-y