Literature DB >> 24387513

Integral dose investigation of non-coplanar treatment beam geometries in radiotherapy.

Dan Nguyen1, Peng Dong1, Troy Long2, Dan Ruan1, Daniel A Low1, Edwin Romeijn2, Ke Sheng1.   

Abstract

PURPOSE: Automated planning and delivery of non-coplanar plans such as 4π radiotherapy involving a large number of fields have been developed to take advantage of the newly available automated couch and gantry on C-arm gantry linacs. However, there is an increasing concern regarding the potential changes in the integral dose that needs to be investigated.
METHODS: A digital torso phantom and 22 lung and liver stereotactic body radiation therapy (SBRT) patients were included in the study. The digital phantom was constructed as a water equivalent elliptical cylinder with a major axis length of 35.4 cm and minor axis of 23.6 cm. A 4.5 cm diameter target was positioned at varying depths along the major axis. Integral doses from intensity modulated, non-coplanar beams forming a conical pattern were compared against the equally spaced coplanar beam plans. Integral dose dependence on the phantom geometry and the beam number was also quantified. For the patient plans, the non-coplanar and coplanar beams and fluences were optimized using a column generation and pricing approach and compared against clinical VMAT plans using two full (lung) or partial coplanar arcs (liver) entering at the side proximal to the tumor. Both the average dose to the normal tissue volume and the total volumes receiving greater than 2 Gy (V2) and 5 Gy (V5) were evaluated and compared.
RESULTS: The ratio of integral dose from the non-coplanar and coplanar plans depended on the tumor depth for the phantom; for tumors shallower than 10 cm, the non-coplanar integral doses were lower than coplanar integral doses for non-coplanar angles less than 60°. Similar patterns were observed in the patient plans. The smallest non-coplanar integral doses were observed for tumor 6-8 cm deep. For the phantom, the integral dose was independent of the number of beams, consistent with the liver SBRT patients but the lung SBRT patients showed slight increase in the integral dose when more beams were used. Larger tumor size and larger patient body size did not change the overall relationship of integral doses between non-coplanar and coplanar cases. However, the thin disk-shaped tumor received at least 40% greater integral doses with the non-coplanar plans. Overall, patient non-coplanar integral doses and V5 were comparable to those of coplanar doses from the same optimization engine and 15%-20% lower than state of the art VMAT plans. However, non-coplanar beams significantly increased V2 in both the phantom and patients. On average, the lung and liver SBRT patient normal tissue volumes receiving dose greater than 2 Gy were increased by 749 and 532 cm(3), respectively.
CONCLUSIONS: The authors used a digital phantom simulating a patient torso and 22 SBRT patients to show that the integral doses from the plans employing optimized non-coplanar beams are comparable to those of the coplanar plans using an equal number of discrete beams and are significantly lower than those of VMAT plans. The non-coplanar beams expose a larger normal tissue volume to non-zero doses, whose impact will need to be evaluated individually to determine the risk/benefit ratio of the non-coplanar plans.

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Year:  2014        PMID: 24387513     DOI: 10.1118/1.4845055

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  8 in total

1.  4π plan optimization for cortical-sparing brain radiotherapy.

Authors:  Vyacheslav L Murzin; Kaley Woods; Vitali Moiseenko; Roshan Karunamuni; Kathryn R Tringale; Tyler M Seibert; Michael J Connor; Daniel R Simpson; Ke Sheng; Jona A Hattangadi-Gluth
Journal:  Radiother Oncol       Date:  2018-03-05       Impact factor: 6.280

2.  Using deep learning to predict beam-tunable Pareto optimal dose distribution for intensity-modulated radiation therapy.

Authors:  Gyanendra Bohara; Azar Sadeghnejad Barkousaraie; Steve Jiang; Dan Nguyen
Journal:  Med Phys       Date:  2020-08-02       Impact factor: 4.071

3.  Fraction-variant beam orientation optimization for non-coplanar IMRT.

Authors:  Daniel O'Connor; Victoria Yu; Dan Nguyen; Dan Ruan; Ke Sheng
Journal:  Phys Med Biol       Date:  2018-02-15       Impact factor: 3.609

4.  A reinforcement learning application of a guided Monte Carlo Tree Search algorithm for beam orientation selection in radiation therapy.

Authors:  Azar Sadeghnejad-Barkousaraie; Gyanendra Bohara; Steve Jiang; Dan Nguyen
Journal:  Mach Learn Sci Technol       Date:  2021-05-13

5.  In regard to "Tran A, Zhang J, Woods K, Yu V, Nguyen D, Gustafson G, Rosen L, Sheng K. Treatment planning comparison of IMPT, VMAT and 4π radiotherapy for prostate cases. Radiation oncology. 2017 Jan 11; 12(1):10".

Authors:  Biplab Sarkar
Journal:  Radiat Oncol       Date:  2018-04-12       Impact factor: 3.481

6.  4π Radiotherapy Using a Linear Accelerator: A Misnomer in Violation of the Solid Geometric Boundary Conditions in Three-Dimensional Euclidean Space.

Authors:  Biplab Sarkar; Tharmarnadar Ganesh; Anusheel Munshi; Arjunan Manikandan; Bidhu Kalyan Mohanti
Journal:  J Med Phys       Date:  2019-12-11

7.  A collision prediction framework for noncoplanar radiotherapy planning and delivery.

Authors:  Naveed Islam; Josh Kilian-Meneghin; Steven deBoer; Matthew Podgorsak
Journal:  J Appl Clin Med Phys       Date:  2020-06-19       Impact factor: 2.102

8.  Data-Driven Dose-Volume Histogram Prediction.

Authors:  Mitchell Polizzi; Robert W Watkins; William T Watkins
Journal:  Adv Radiat Oncol       Date:  2021-10-27
  8 in total

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