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Simulating intrafraction prostate motion with a random walk model

Pommer, Tobias ; Oh, Jung Hun ; Munck af Rosenschöld, Per LU orcid and Deasy, Joseph O. (2017) In Advances in Radiation Oncology 2(3). p.429-436
Abstract

Purpose Prostate motion during radiation therapy (ie, intrafraction motion) can cause unwanted loss of radiation dose to the prostate and increased dose to the surrounding organs at risk. A compact but general statistical description of this motion could be useful for simulation of radiation therapy delivery or margin calculations. We investigated whether prostate motion could be modeled with a random walk model. Methods and materials Prostate motion recorded during 548 radiation therapy fractions in 17 patients was analyzed and used for input in a random walk prostate motion model. The recorded motion was categorized on the basis of whether any transient excursions (ie, rapid prostate motion in the anterior and superior direction... (More)

Purpose Prostate motion during radiation therapy (ie, intrafraction motion) can cause unwanted loss of radiation dose to the prostate and increased dose to the surrounding organs at risk. A compact but general statistical description of this motion could be useful for simulation of radiation therapy delivery or margin calculations. We investigated whether prostate motion could be modeled with a random walk model. Methods and materials Prostate motion recorded during 548 radiation therapy fractions in 17 patients was analyzed and used for input in a random walk prostate motion model. The recorded motion was categorized on the basis of whether any transient excursions (ie, rapid prostate motion in the anterior and superior direction followed by a return) occurred in the trace and transient motion. This was separately modeled as a large step in the anterior/superior direction followed by a returning large step. Random walk simulations were conducted with and without added artificial transient motion using either motion data from all observed traces or only traces without transient excursions as model input, respectively. Results A general estimate of motion was derived with reasonable agreement between simulated and observed traces, especially during the first 5 minutes of the excursion-free simulations. Simulated and observed diffusion coefficients agreed within 0.03, 0.2 and 0.3 mm2/min in the left/right, superior/inferior, and anterior/posterior directions, respectively. A rapid increase in variance at the start of observed traces was difficult to reproduce and seemed to represent the patient's need to adjust before treatment. This could be estimated somewhat using artificial transient motion. Conclusions Random walk modeling is feasible and recreated the characteristics of the observed prostate motion. Introducing artificial transient motion did not improve the overall agreement, although the first 30 seconds of the traces were better reproduced. The model provides a simple estimate of prostate motion during delivery of radiation therapy.

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author
; ; and
publishing date
type
Contribution to journal
publication status
published
keywords
intrafraction motion, motion management, random walk
in
Advances in Radiation Oncology
volume
2
issue
3
pages
8 pages
publisher
Elsevier
external identifiers
  • scopus:85019094979
ISSN
2452-1094
DOI
10.1016/j.adro.2017.03.005
language
English
LU publication?
no
id
57b44343-518f-4455-87b0-2e231860e501
date added to LUP
2020-07-28 08:59:46
date last changed
2023-07-20 08:31:44
@article{57b44343-518f-4455-87b0-2e231860e501,
  abstract     = {{<p>Purpose Prostate motion during radiation therapy (ie, intrafraction motion) can cause unwanted loss of radiation dose to the prostate and increased dose to the surrounding organs at risk. A compact but general statistical description of this motion could be useful for simulation of radiation therapy delivery or margin calculations. We investigated whether prostate motion could be modeled with a random walk model. Methods and materials Prostate motion recorded during 548 radiation therapy fractions in 17 patients was analyzed and used for input in a random walk prostate motion model. The recorded motion was categorized on the basis of whether any transient excursions (ie, rapid prostate motion in the anterior and superior direction followed by a return) occurred in the trace and transient motion. This was separately modeled as a large step in the anterior/superior direction followed by a returning large step. Random walk simulations were conducted with and without added artificial transient motion using either motion data from all observed traces or only traces without transient excursions as model input, respectively. Results A general estimate of motion was derived with reasonable agreement between simulated and observed traces, especially during the first 5 minutes of the excursion-free simulations. Simulated and observed diffusion coefficients agreed within 0.03, 0.2 and 0.3 mm<sup>2</sup>/min in the left/right, superior/inferior, and anterior/posterior directions, respectively. A rapid increase in variance at the start of observed traces was difficult to reproduce and seemed to represent the patient's need to adjust before treatment. This could be estimated somewhat using artificial transient motion. Conclusions Random walk modeling is feasible and recreated the characteristics of the observed prostate motion. Introducing artificial transient motion did not improve the overall agreement, although the first 30 seconds of the traces were better reproduced. The model provides a simple estimate of prostate motion during delivery of radiation therapy.</p>}},
  author       = {{Pommer, Tobias and Oh, Jung Hun and Munck af Rosenschöld, Per and Deasy, Joseph O.}},
  issn         = {{2452-1094}},
  keywords     = {{intrafraction motion; motion management; random walk}},
  language     = {{eng}},
  month        = {{07}},
  number       = {{3}},
  pages        = {{429--436}},
  publisher    = {{Elsevier}},
  series       = {{Advances in Radiation Oncology}},
  title        = {{Simulating intrafraction prostate motion with a random walk model}},
  url          = {{http://dx.doi.org/10.1016/j.adro.2017.03.005}},
  doi          = {{10.1016/j.adro.2017.03.005}},
  volume       = {{2}},
  year         = {{2017}},
}