Dataset Information

Simulating intrafraction prostate motion with a random walk model.

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 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.

SUBMITTER: Pommer T

PROVIDER: S-EPMC5605287 | biostudies-literature | 2017 Jul-Sep

REPOSITORIES: biostudies-literature

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Simulating intrafraction prostate motion with a random walk model.

Pommer Tobias T Oh Jung Hun JH Munck Af Rosenschöld Per P Deasy Joseph O JO

Advances in radiation oncology 20170328 3

<h4>Purpose</h4>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.<h4>Methods and materials</h4>Prostate motion recorded during 548 radiation ...[more]

PMID: 29114612

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Project description:PurposeThe objective of this work is to test the validity of the Gaussian approximation for prostate motion through characterization of its spatial distribution.Methods and materialsReal-time intrafraction prostate motion was observed using Calypso 4-dimensional (4D) nonradioactive electromagnetic tracking system. We report the results from a total of 1024 fractions from 31 prostate cancer patients. First, the correlation of prostate motion in right/left (RL), anteroposterior (AP), and superoinferior (SI) direction were determined using Pearson's correlation of coefficient. Then the spatial distribution of prostate motion was analyzed for individual fraction, individual patient including all fractions, and all patients including all fractions. The displacement in RL, AP, SI, oblique, or total direction is fitted into a Gaussian distribution, and a Lilliefors test was used to evaluate the validity of the hypothesis that the displacement is normally distributed.ResultsThere is high correlation in AP/SI direction (61% of fractions with medium or strong correlation). This is consistent with the longitudinal oblique motion of the prostate, and likely the effect from respiration on an organ confined within the genitourinary diaphragm with the rectum sitting posteriorly and bladder sitting superiorly. In all directions, the non-Gaussian distribution is more common for individual fraction, individual patient including all fractions, and all patients including all fractions. The spatial distribution of prostate motion shows an elongated shape in oblique direction, indicating a higher range of motion in the AP and SI directions.ConclusionsOur results showed that the prostate motion is highly correlated in AP and SI direction, indicating an oblique motion preference. In addition, the spatial distribution of prostate motion is elongated in an oblique direction, indicating that the organ motion dosimetric modeling using Gaussian kernel may need to be modified to account for the particular organ motion character of prostate.

Project description:Understanding the processes that give rise to quantitative measurements associated with molecular sequence data remains an important issue in statistical phylogenetics. Examples of such measurements include geographic coordinates in the context of phylogeography and phenotypic traits in the context of comparative studies. A popular approach is to model the evolution of continuously varying traits as a Brownian diffusion process acting on a phylogenetic tree. However, standard Brownian diffusion is quite restrictive and may not accurately characterize certain trait evolutionary processes. Here, we relax one of the major restrictions of standard Brownian diffusion by incorporating a nontrivial estimable mean into the process. We introduce a relaxed directional random walk (RDRW) model for the evolution of multivariate continuously varying traits along a phylogenetic tree. Notably, the RDRW model accommodates branch-specific variation of directional trends while preserving model identifiability. Furthermore, our development of a computationally efficient dynamic programming approach to compute the data likelihood enables scaling of our method to large data sets frequently encountered in phylogenetic comparative studies and viral evolution. We implement the RDRW model in a Bayesian inference framework to simultaneously reconstruct the evolutionary histories of molecular sequence data and associated multivariate continuous trait data, and provide tools to visualize evolutionary reconstructions. We demonstrate the performance of our model on synthetic data, and we illustrate its utility in two viral examples. First, we examine the spatiotemporal spread of HIV-1 in central Africa and show that the RDRW model uncovers a clearer, more detailed picture of the dynamics of viral dispersal than standard Brownian diffusion. Second, we study antigenic evolution in the context of HIV-1 resistance to three broadly neutralizing antibodies. Our analysis reveals evidence of a continuous drift at the HIV-1 population level towards enhanced resistance to neutralization by the VRC01 monoclonal antibody over the course of the epidemic. [Brownian Motion; Diffusion Processes; Phylodynamics; Phylogenetics; Phylogeography; Trait Evolution.].

Project description:BackgroundStereotactic Body Radiotherapy (SBRT) is as a standard treatment for prostate cancer (PCa). Tight margins and high dose gradients are needed, and the precise localization of the target is mandatory. Our retrospective study reports our experience regarding the evaluation of intrafraction prostate motion during LINAC-based SBRT evaluated with a novel electromagnetic (EM) tracking device. This device consists of an integrated Foley catheter with a transmitter connected to a receiver placed on the treatment table.MethodsWe analyzed 31 patients who received LINAC-based SBRT using flattening filter-free (FFF) volumetric modulated arc therapy (VMAT). The patients were scheduled to be treated for primary (n = 27) or an intraprostatic recurrent PCa (n = 4). A simulation CT scan was conducted while the patients had a filled bladder (100-150 cc) and an empty rectum, and an EM tracking device was used. The same rectal and bladder conditions were employed during the treatment. The patients received 36.25 Gy delivered over five consecutive fractions on the whole prostate and 40 Gy on the nodule(s) visible via MRI, both delivered with a Simultaneous Integrated Boost approach. The CTV-to-PTV margin was 2 mm for both the identified treatment volumes. Patient positioning was verified with XVI ConeBeam-CT (CBCT) matching before each fraction. When the signals exceeded a 2 mm threshold in any of the three spatial directions, the treatment was manually interrupted. A new XVI CBCT was performed if this offset lasted >20 s.ResultsWe analyzed data about 155 fractions. The median and mean treatment times, calculated per fraction, were 10 m31 s and 12 m44 s (range: 6 m36 s-65 m28 s), and 95% of the fractions were delivered with a maximum time of 27 m48 s. During treatment delivery, the mean and median number of XVI CBCT operations realized during the treatment were 2 and 1 (range: 0-11). During the treatment, the prostate was outside the CTV-to-PTV margin (2 mm), thus necessitating the stoppage of the delivery +/- a reacquisition of the XVI CBCT for 11.2%, 8.9%, and 3.9% of the delivery time in the vertical, longitudinal, and lateral direction, respectively.ConclusionsWe easily integrated an EM-transmitter-based gating for prostate LINAC-based SBRT into our normal daily workflow. Using this system, a 2 mm CTV-to-PTV margin could be safely applied. A small number of fractions showed a motion exceeding the predefined 2 mm threshold, which would have otherwise gone undetected without intrafraction motion management.

Project description:PURPOSE:Our purpose was to perform an in vivo validation of ultrasound imaging for intrafraction motion estimation using the Elekta Clarity Autoscan system during prostate radiation therapy. The study was conducted as part of the Clarity-Pro trial (NCT02388308). METHODS AND MATERIALS:Initial locations of intraprostatic fiducial markers were identified from cone beam computed tomography scans. Marker positions were translated according to Clarity intrafraction 3-dimensional prostate motion estimates. The updated locations were projected onto the 2-dimensional electronic portal imager plane. These Clarity-based estimates were compared with the actual portal-imaged 2-dimensional marker positions. Images from 16 patients encompassing 80 fractions were analyzed. To investigate the influence of intraprostatic markers and image quality on ultrasound motion estimation, 3 observers rated image quality, and the marker visibility on ultrasound images was assessed. RESULTS:The median difference between Clarity-defined intrafraction marker locations and portal-imaged marker locations was 0.6 mm (with 95% limit of agreement at 2.5 mm). Markers were identified on ultrasound in only 3 of a possible 240 instances. No linear relationship between image quality and Clarity motion estimation confidence was identified. The difference between Clarity-based motion estimates and electronic portal-imaged marker location was also independent of image quality. Clarity estimation confidence was degraded in a single fraction owing to poor probe placement. CONCLUSIONS:The accuracy of Clarity intrafraction prostate motion estimation is comparable with that of other motion-monitoring systems in radiation therapy. The effect of fiducial markers in the study was deemed negligible as they were rarely visible on ultrasound images compared with intrinsic anatomic features. Clarity motion estimation confidence was robust to variations in image quality and the number of ultrasound-imaged anatomic features; however, it was degraded as a result of poor probe placement.

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Simulating intrafraction prostate motion with a random walk model.

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Simulating intrafraction prostate motion with a random walk model.

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