A knowledge-based planning model to identify fraction-reduction opportunities in brain stereotactic radiotherapy

被引:0
|
作者
Mccarthy, Shane [1 ]
St Clair, William [1 ]
Pokhrel, Damodar [1 ]
机构
[1] Univ Kentucky, Dept Radiat Med, Med Phys Grad Program, Lexington, KY 40536 USA
来源
JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS | 2025年 / 26卷 / 04期
关键词
clinical efficiency; HyperArc; multiple brain lesions; patient time in the clinic; planning automation; RapidPlan; SIML; stereotactic radiotherapy; treatment planning; RADIOSURGERY; CONFORMITY; RAPIDPLAN;
D O I
10.1002/acm2.70055
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Objective: To develop and validate a HyperArc-based RapidPlan (HARP) model for three-fraction brain stereotactic radiotherapy (SRT) plans to then use to replan previously treated five-fraction SRT plans. Demonstrating the possibility of reducing the number of fractions while achieving acceptable organs-at-risk (OAR) doses with improved target biological effective dose (BED) to brain lesions. Methods: Thirty-nine high-quality clinical three-fraction HyperArc brain SRT plans (24-27 Gy) were used to train the HARP model, with a separate 10 plans used to validate its effectiveness. Fifty-eight five-fraction HyperArc brain SRT plans (30-40 Gy) attempted to be retrospectively replanned for three fractions scheme using the HARP model. All planning was done within the Eclipse treatment planning system for a TrueBeam LINAC with a 6 MV-FFF beam and Millenium 120 MLCs and dosimetric parameters were analyzed per brain SRT protocol. Results: The HyperArc RapidPlan model was successfully trained and tested, with the validation set demonstrating a statistically significant (p = 0.01) increase in GTV D-100% from 28.5 +/- 0.7 Gy to 29.4 +/- 0.6 Gy from the original to RapidPlan plans. No statistically significant differences were found for the OAR metrics (p > 0.05). The five-fraction replans were successful for 20 of the 58 five-fraction brain SRT plans. For those 20 successful brain SRT plans, the maximum doses to OAR were clinically acceptable with a three-fraction scheme including an average V-18Gy to Brain-PTV of 9.9 +/- 5.9 cc. Additionally, the replanned five-fraction brain SRT plans achieved a higher BED to the tumors, increasing from a GTV D-100% of 52.9 +/- 4.5 Gy for the original five-fraction plans to 57.3 +/- 3.1 Gy for the three-fraction RapidPlan plans. All RapidPlan plans were generated automatically, without manual input, in under 20 min. Conclusions: The HARP model developed in this research was used to successfully identify select five-fraction plans that were able to be reduced to three-fraction SRT treatments while achieving clinically acceptable OAR doses and improved target BED. This tool encourages a fast and standardized way to provide physicians with more options when choosing the necessary fractionation scheme(s) for HyperArc SRT to single- and multiple brain lesions.
引用
收藏
页数:11
相关论文
共 29 条
  • [21] Evaluating the plan quality of a general head-and-neck knowledge-based planning model versus separate unilateral/bilateral models
    Luca, Kirk
    Roper, Justin
    Wolf, Jonathan
    Kayode, Oluwatosin
    Bradley, Jeffrey
    Stokes, William A.
    Zhang, Jiahan
    MEDICAL DOSIMETRY, 2023, 48 (01) : 44 - 50
  • [22] Standardization of knowledge-based volumetric modulated arc therapy planning with a multi-institution model (broad model) to improve prostate cancer treatment quality
    Ueda, Yoshihiro
    Fukunaga, Jun-ichi
    Kamima, Tatsuya
    Shimizu, Yumiko
    Kubo, Kazuki
    Doi, Hiroshi
    Monzen, Hajime
    PHYSICAL AND ENGINEERING SCIENCES IN MEDICINE, 2023, 46 (03) : 1091 - 1100
  • [23] Standardization of knowledge-based volumetric modulated arc therapy planning with a multi-institution model (broad model) to improve prostate cancer treatment quality
    Yoshihiro Ueda
    Jun-ichi Fukunaga
    Tatsuya Kamima
    Yumiko Shimizu
    Kazuki Kubo
    Hiroshi Doi
    Hajime Monzen
    Physical and Engineering Sciences in Medicine, 2023, 46 : 1091 - 1100
  • [24] Optimal beam angle selection and knowledge-based planning significantly reduces radiotherapy dose to organs at risk for lung cancer patients
    Hoffmann, L.
    Knap, M. M.
    Alber, M.
    Moller, D. S.
    ACTA ONCOLOGICA, 2021, 60 (03) : 293 - 299
  • [25] Fast generation of lung SBRT plans with a knowledge-based planning model on ring-mounted Halcyon Linac
    Visak, Justin
    Webster, Aaron
    Bernard, Mark E.
    Kudrimoti, Mahesh
    Randall, Marcus E.
    McGarry, Ronald C.
    Pokhrel, Damodar
    JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS, 2021, 22 (11): : 54 - 63
  • [26] Validation of in-house knowledge-based planning model for predicting change in target coverage during VMAT radiotherapy to in-operable advanced-stage NSCLC patients
    Tambe, Nilesh S.
    Pires, Isabel M.
    Moore, Craig
    Wieczorek, Andrew
    Upadhyay, Sunil
    Beavis, Andrew W.
    BIOMEDICAL PHYSICS & ENGINEERING EXPRESS, 2021, 7 (06)
  • [27] Stereotactic radiotherapy of brain metastases: clinical impact of three-dimensional SPACE imaging for 3T-MRI-based treatment planning
    Welzel, Thomas
    El Shafie, Rami A.
    Nettelbladt, Bastian, V
    Bernhardt, Denise
    Rieken, Stefan
    Debus, Juergen
    STRAHLENTHERAPIE UND ONKOLOGIE, 2022, 198 (10) : 926 - 933
  • [28] Linear accelerator-based single-fraction stereotactic radiosurgery versus hypofractionated stereotactic radiotherapy for intact and resected brain metastases up to 3 cm: A multi-institutional retrospective analysis
    Diamond, Brett H.
    Jairam, Vikram
    Zuberi, Shaharyar
    Li, Jessie Y.
    Marquis, Timothy J.
    Rutter, Charles E.
    Park, Henry S.
    JOURNAL OF RADIOSURGERY AND SBRT, 2020, 7 (03): : 179 - +
  • [29] Consideration of optimal isodose surface selection for target coverage in micro-multileaf collimator-based stereotactic radiotherapy for large cystic brain metastases: comparison of 90%, 80% and 70% isodose surface-based planning
    Ohtakara, K.
    Hayashi, S.
    Tanaka, H.
    Hoshi, H.
    BRITISH JOURNAL OF RADIOLOGY, 2012, 85 (1017) : E640 - E646