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. (Principal Investigator), Burnham, K. (Co-Investigator), Skworcow, P. (Research Assistant) & Sahih, A. (Research Assistant)
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

Y1 - 2007/2/1

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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JF - Measurement and Control

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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