Purpose: Robotic ultrasound promises continuous, volumetric, and non-ionizing tracking of organ motion during radiation therapy. However, placement of the robot is critical because it is radio-opaque and might severely influence the achievable dose distribution.
Methods: We propose two heuristic optimization strategies for automatic placement of an ultrasound robot around a patient. Considering a kinematically redundant robot arm, we compare a generic approach based on stochastic search and a more problem-specific segmentwise construction approach. The former allows for multiple elbow configurations while the latter is deterministic. Additionally, we study different objective functions guiding the search. Our evaluation is based on data for ten actual prostate cancer cases and we compare the resulting plan quality for both methods to manually chosen robot configurations previously proposed.
Results: The mean improvements in the treatment planning objective value with respect to the best manually selected robot position and a single elbow configuration range from 8.2 to 32.8% and 8.5 to 15.5% for segmentwise construction and stochastic search, respectively. Considering three different elbow configurations, the stochastic search results in better objective values in 80% of the cases, with 30% being significantly better. The optimization strategies are robust with respect to beam sampling and transducer orientation and using previous optimization results as starting point for stochastic search typically results in better solutions compared to random starting points.
Conclusion: We propose a robust and generic optimization scheme, which can be used to optimize the robot placement for robotic ultrasound guidance in radiation therapy. The automatic optimization further mitigates the impact of robotic ultrasound on the treatment plan quality.
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http://dx.doi.org/10.1007/s11548-019-02009-w | DOI Listing |
Mov Ecol
December 2024
Department of Entomology, National Taiwan University, Taipei, Taiwan.
Background: The distribution of hosts and parasitoids across patches is a key factor determining the dynamics of host-parasitoid populations. To connect behavioral rules with population dynamics, it is essential to comprehend how individual-level dispersal behavior influences the distribution of individuals. Typically, a simple deterministic model has been used to describe this connection.
View Article and Find Full Text PDFEJNMMI Phys
December 2024
Department of Control Engineering and Information Technology, Budapest University of Technology and Economics, Műegyetem rkp. 3., Budapest, 1111, Hungary.
Background: In the back projection step of the 3D PET reconstruction, all Lines of Responses (LORs) that go through a given voxel need to be identified and included in an integral. The standard Monte Carlo solution to this task samples stochastically the surfaces of the detector crystals and the volume of the voxel to search for valid LORs. To get a low noise Monte Carlo estimate, the number of samples needs to be very high, making the computational cost of the projection significant.
View Article and Find Full Text PDFPhys Rev E
November 2024
Department of Physics, PUC-Rio, Rua Marquês de São Vicente 225, 22451-900, Rio de Janeiro, RJ, Brazil.
We investigate random searches under stochastic position resetting at rate r, in a bounded 1D environment with space-dependent diffusivity D(x). For arbitrary shapes of D(x) and prescriptions of the associated multiplicative stochastic process, we obtain analytical expressions for the average time T for reaching the target (mean first-passage time), given the initial and reset positions, in good agreement with stochastic simulations. For arbitrary D(x), we obtain an exact closed-form expression for T, within a Stratonovich scenario, while for other prescriptions, like Itô and anti-Itô, we derive asymptotic approximations for small and large rates r.
View Article and Find Full Text PDFPhys Rev E
November 2024
Université Paris-Saclay, Centre National de la Recherche Scientifique, LPTMS, 91405 Orsay, France.
We introduce the profligacy of a search process as a competition between its expected cost and the probability of finding the target. The arbiter of the competition is a parameter λ that represents how much a searcher invests into increasing the chance of success. Minimizing the profligacy with respect to the search strategy specifies the optimal search.
View Article and Find Full Text PDFPhys Rev E
November 2024
School of Physics, Korea Institute for Advanced Study, Seoul 02455, Republic of Korea.
Stochastic resetting has recently emerged as an efficient target-searching strategy in various physical and biological systems. The efficiency of this strategy depends on the type of environmental noise, whether it is thermal or telegraphic (active). While the impact of each noise type on a search process has been investigated separately, their combined effects have not been explored.
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