Predictive Tracking For Respiratory Induced Motion Compensation In Adaptive Radiotherapy

Piotr Skworcow; Devi Putra; Abdelhamid Sahih; John Goodband; Olivier Haas; Keith Burnham; John A. Mills

doi:10.1177/002029400704000106

Predictive Tracking For Respiratory Induced Motion Compensation In Adaptive Radiotherapy

Piotr Skworcow, Devi Putra, Abdelhamid Sahih, John Goodband, Olivier Haas, Keith Burnham, John A. Mills

University Hospitals Coventry and Warwickshire NHS Trust

Research output: Contribution to journal › Article › peer-review

10 Citations (Scopus)

Abstract

This paper considers a compensation strategy for respiratory-induced tumour motion for adaptive radiotherapy using a controlled patient support system (PSS).
A model predictive control (MPC) scheme for the PSS to track the tumour motion is proposed together with two methods for predicting tumour motion, including a Kalman filter and neural networks. Simulation results using a clinical data set consisting of 27 traces of respiratory motion show the potential of the proposed control strategy.

Original language	English
Pages (from-to)	16-19
Number of pages	4
Journal	Measurement and Control
Volume	40
Issue number	1
DOIs	https://doi.org/10.1177/002029400704000106
Publication status	Published - 1 Feb 2007

Keywords

MPC
adaptive radiotherapy treatment
patient support system
Respiratory modelling

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10.1177/002029400704000106

MAESTRO: Methods and Advanced Equipment for Simulation and Treatment in Radiation Oncology
haas, O., Burnham, K., Skworcow, P. & Sahih, A.
1/05/04 → 30/04/09
Project: Research

Cite this

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title = "Predictive Tracking For Respiratory Induced Motion Compensation In Adaptive Radiotherapy",

abstract = "This paper considers a compensation strategy for respiratory-induced tumour motion for adaptive radiotherapy using a controlled patient support system (PSS).A model predictive control (MPC) scheme for the PSS to track the tumour motion is proposed together with two methods for predicting tumour motion, including a Kalman filter and neural networks. Simulation results using a clinical data set consisting of 27 traces of respiratory motion show the potential of the proposed control strategy. ",

keywords = "MPC, adaptive radiotherapy treatment, patient support system, Respiratory modelling",

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AU - Skworcow, Piotr

AU - Putra, Devi

AU - Sahih, Abdelhamid

AU - Goodband, John

AU - Haas, Olivier

AU - Burnham, Keith

AU - Mills, John A.

PY - 2007/2/1

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N2 - This paper considers a compensation strategy for respiratory-induced tumour motion for adaptive radiotherapy using a controlled patient support system (PSS).A model predictive control (MPC) scheme for the PSS to track the tumour motion is proposed together with two methods for predicting tumour motion, including a Kalman filter and neural networks. Simulation results using a clinical data set consisting of 27 traces of respiratory motion show the potential of the proposed control strategy.

AB - This paper considers a compensation strategy for respiratory-induced tumour motion for adaptive radiotherapy using a controlled patient support system (PSS).A model predictive control (MPC) scheme for the PSS to track the tumour motion is proposed together with two methods for predicting tumour motion, including a Kalman filter and neural networks. Simulation results using a clinical data set consisting of 27 traces of respiratory motion show the potential of the proposed control strategy.

KW - MPC

KW - adaptive radiotherapy treatment

KW - patient support system

KW - Respiratory modelling

U2 - 10.1177/002029400704000106

DO - 10.1177/002029400704000106

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Predictive Tracking For Respiratory Induced Motion Compensation In Adaptive Radiotherapy

Abstract

Keywords

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Projects

MAESTRO: Methods and Advanced Equipment for Simulation and Treatment in Radiation Oncology

Cite this