Purpose: To evaluate the impact of different aperture shape controller (ASC) stratification strategies on the dosimetric quality and treatment efficiency of HyperArc plans for intracranial oligometastases.
Methods: This retrospective study analyzed 17 patients with 1–3 intracranial oligometastases. For each patient, the HyperArc plans were reoptimized using six ASC strength settings (off, very low, low, moderate, high, and very high). Evaluations encompassed planning target volume (PTV) and organ at risk (OAR) dosimetric parameters (Paddick Conformity Index [Paddick CI], Gradient Index [GI], D2cm, OAR Dmax/Dmean, Gamma passing rate), and treatment efficiency parameters (monitor units [MUs], segment number [SN], Modulation Complexity Score [MCS], Average Leaf Trajectory [ALT], and aperture irregularity [AI]).
Results: No statistically significant differences were observed in the PTV and OAR dosimetric parameters or gamma passing rates among the ASC strategy groups (p > 0.05), indicating a minimal impact of the ASC on plan dosimetric quality. In addition, SN, MCS, and ALT demonstrated no significant intergroup differences (p > 0.05). However, AI improved with moderate and high ASC strength. Critically, the total MUs differed significantly among the groups (F = 2.904, p < 0.05), with high ASC strength causing significantly lower MUs than ASC-off (p < 0.05), suggesting enhanced treatment efficiency.
Conclusions: ASC stratification strategies do not significantly compromise plan dosimetric quality in HyperArc treatment for intracranial oligometastases; however, these can markedly optimize treatment efficiency, particularly by reducing MUs. Considering both plan complexity and treatment efficiency, a moderate or high ASC strength is recommended to maintain high-quality radiotherapy while improving workflow efficiency.
| [1] |
Dona Lemus OM, Cao M, Cai B, et al. Adaptive Radiotherapy: Next-Generation Radiotherapy. Cancers (Basel). 2024;16(6):1206.
|
| [2] |
Hansen CR, Hussein M, Bernchou U, et al. Plan quality in radiotherapy treatment planning–Review of the factors and challenges. J Med Imaging Radiat Oncol. 2022; 66(2): 267–278.
|
| [3] |
Buciuman N, Marcu LG. Dosimetric justification for the use of volumetric modulated arc therapy in head and neck cancer—A systematic review of the literature. Laryngoscope Investig Otolaryngol. 2021; 6(5): 999–1007.
|
| [4] |
Hunte SO, Clark CH, Zyuzikov N, et al. Volumetric modulated arc therapy (VMAT): a review of clinical outcomes—what is the clinical evidence for the most effective implementation? Br J Radiol. 2022; 95(1136): 20201289.
|
| [5] |
Ohira S, Ueda Y, Akino Y, et al. HyperArc VMAT planning for single and multiple brain metastases stereotactic radiosurgery: a new treatment planning approach. Radiat Oncol. 2018; 13: 1–9.
|
| [6] |
Rajadurai E, Kumar AS, Govindarajan KN, et al. Planning and Dosimetry Study of Dynamic Intensity-Modulated Radiotherapy and Volumetric-Modulated Arc Therapy for Carcinomas of the Pharynx Using 6MV Flattening Filter and Flattening Filter-free Beams. J Med Phys. 2025; 50(1): 75–85.
|
| [7] |
Rossi M, Boman E. The use of aperture shape controller and convergence mode in radiotherapy treatment planning. J Radiother Pract. 2022; 21(2): 171–178.
|
| [8] |
Miura H, Matsuura T, Nakao M, et al. Influence of aperture shape controller settings on dose distribution and treatment efficiency in lung stereotactic body radiation therapy with a 10 MV flattening filter-free beam. Med Dosim. 2025; 50(2): 185–190.
|
| [9] |
Binny D, Spalding M, Crowe SB, et al. Investigating the use of aperture shape controller in VMAT treatment deliveries. Med Dosim. 2020; 45(3): 284–292.
|
| [10] |
Wong FH, Moleme PA, Ali OA, et al. Clinical implementation of HyperArc. Phys Eng Sci Med. 2022; 45(2): 577–587.
|
| [11] |
Kihara S, Ohira S, Kanayama N, et al. Effects of Institutional Experience on Plan Quality in Stereotactic Radiotherapy Using HyperArc for Brain Metastases. In Vivo. 2025;39(1): 210–217.
|
| [12] |
Smyth G, Evans PM, Bamber JC, et al. Recent developments in non-coplanar radiotherapy. Br J Radiol. 2019; 92(1097): 20180908.
|
| [13] |
Woods K, Chin RK, Cook KA, et al. Automated non-coplanar VMAT for dose escalation in recurrent head and neck cancer patients. Cancers. 2021; 13(8): 1910.
|
| [14] |
Quintero P, Cheng Y, Benoit D, et al. Effect of treatment planning system parameters on beam modulation complexity for treatment plans with single-layer multi-leaf collimator and dual-layer stacked multi-leaf collimator. Br J Radiol. 2021; 94(1122): 20201011.
|
| [15] |
Saroj DK, Haldar SYS, Shende R. Exploring the Convergence Mode and Aperture Shape Controller for Volumetric Modulated Arc Radiation Therapy Techniques. South Asia Cent. Med Phys Cancer Res. 2024; 6(1): 10–12.
|
| [16] |
Peng Q, Fan P, Wang X, Tao F, Niu R, Chen L. The impact of plan complexity on dose delivery deviations resulting from multileaf collimator positioning errors in volumetric modulated arc therapy. Br J Radiol. 2025; 98(1169): 785–792.
|
| [17] |
Manna S, Singh S, Gupta PK. Dosimetric and radiobiological impact of flattening filter-free beam and dose calculation algorithm using RapidArc plans for cervical cancer treatment. Precis Radiat Oncol. 2023; 7(3): 197–206.
|
| [18] |
Al-Rawi SAI, Abouelenein H, Nagdy ME-SE, et al. Assessment of dose gradient index variation during simultaneously integrated boost intensity-modulated radiation therapy for head and neck cancer patients. Precis Radiat Oncol. 2022; 6(3): 216–224.
|
| [19] |
La Rosa A, Wieczorek DJJ, Tolakanahalli R, et al. Dosimetric impact of lesion number, size, and volume on mean brain dose with stereotactic radiosurgery for multiple brain metastases. Cancers. 2023; 15(3): 780.
|
| [20] |
Das S, Kharade V, Pandey VP, et al. Gamma index analysis as a patient-specific quality assurance tool for high-precision radiotherapy: A clinical perspective of single institute experience. Cureus 2022; 14(10):e30885.
|
| [21] |
Huang Y, Pi Y, Ma K, et al. Virtual patient-specific quality assurance of IMRT using UNet++: classification, gamma passing rates prediction, and dose difference prediction. Front Oncol. 2021; 11: 700343.
|
| [22] |
McNiven AL, Sharpe MB, Purdie TG. A new metric for assessing IMRT modulation complexity and plan deliverability. Med Phys. 2010; 37(2): 505–515.
|
| [23] |
Masi L, Doro R, Favuzza V, et al. Impact of plan parameters on the dosimetric accuracy of volumetric modulated arc therapy. Med Phys. 2013; 40(7): 071718.
|
| [24] |
Sumida I, Yamaguchi H, Das IJ, et al. Organ-specific modulation complexity score for the evaluation of dose delivery. J Radiat Res. (Tokyo) 2017; 58(5): 675–684.
|
| [25] |
Chen L, Luo H, Tan L, Feng B, Yang X, Jin F. Pretreatment Prediction of Multi-Leaf Collimator Positional Deviations in Patient-Specific Plan Control Points Using Complexity Metrics. Int J Radiat Oncol Biol Phys. 2024; 120(2): e108–e109.
|
| [26] |
Hui CB, Pourmoghaddas A, Mutaf YD. The effects of flattening filter-free beams and aperture shape controller on the complexity of conventional large-field treatment plans. J Appl Clin Med Phys. 2023; 24(11): e14108.
|
| [27] |
Takaaki I, Tamura M, Monzen H, et al. Impact of aperture shape controller on knowledge-based VMAT planning of prostate cancer. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2021; 77(1): 23–31.
|
| [28] |
Zhu H, Yang T, Zhu W, et al. Application of aperture shape controller algorithm in volumetric modulated arc therapy for postoperative cervical cancer. Chin Med Equip J. 2022; 43(05): 44–49.
|
| [29] |
Pokhrel D, Kudrimoti M, Bernard M. Stereotactic Radiosurgery of Small Brain Lesions Via MLC Aperture-Shape Controller HyperArc VMAT. Med Phys. 2022;49: E270–E271.
|
RIGHTS & PERMISSIONS
2025 The Author(s). Precision Radiation Oncology published by John Wiley & Sons Australia, Ltd on behalf of Shandong Cancer Hospital & Institute.