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Evaluating the Quality of Radiotherapy Treatment Plans for Prostate Cancer

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNChapter (peer-reviewed)

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Evaluating the Quality of Radiotherapy Treatment Plans for Prostate Cancer. / Stubington, Emma; Ehrgott, Matthias; Glyn, Shentall; Nohadani, Omid.

Cases based on Multiple Criteria Decision Making/Aiding methods: Building and Solving Decision Models with Computer Implementations. ed. / Sandra Huber; Martin Josef Geiger; Adiel T. de Almeida. Springer, 2018. p. 41-66 (International Series in Operations Research & Management Science; Vol. 274).

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNChapter (peer-reviewed)

Harvard

Stubington, E, Ehrgott, M, Glyn, S & Nohadani, O 2018, Evaluating the Quality of Radiotherapy Treatment Plans for Prostate Cancer. in S Huber, MJ Geiger & AT de Almeida (eds), Cases based on Multiple Criteria Decision Making/Aiding methods: Building and Solving Decision Models with Computer Implementations. International Series in Operations Research & Management Science, vol. 274, Springer, pp. 41-66. https://doi.org/10.1007/978-3-319-99304-1_2

APA

Stubington, E., Ehrgott, M., Glyn, S., & Nohadani, O. (2018). Evaluating the Quality of Radiotherapy Treatment Plans for Prostate Cancer. In S. Huber, M. J. Geiger, & A. T. de Almeida (Eds.), Cases based on Multiple Criteria Decision Making/Aiding methods: Building and Solving Decision Models with Computer Implementations (pp. 41-66). (International Series in Operations Research & Management Science; Vol. 274). Springer. https://doi.org/10.1007/978-3-319-99304-1_2

Vancouver

Stubington E, Ehrgott M, Glyn S, Nohadani O. Evaluating the Quality of Radiotherapy Treatment Plans for Prostate Cancer. In Huber S, Geiger MJ, de Almeida AT, editors, Cases based on Multiple Criteria Decision Making/Aiding methods: Building and Solving Decision Models with Computer Implementations. Springer. 2018. p. 41-66. (International Series in Operations Research & Management Science). https://doi.org/10.1007/978-3-319-99304-1_2

Author

Stubington, Emma ; Ehrgott, Matthias ; Glyn, Shentall ; Nohadani, Omid. / Evaluating the Quality of Radiotherapy Treatment Plans for Prostate Cancer. Cases based on Multiple Criteria Decision Making/Aiding methods: Building and Solving Decision Models with Computer Implementations. editor / Sandra Huber ; Martin Josef Geiger ; Adiel T. de Almeida. Springer, 2018. pp. 41-66 (International Series in Operations Research & Management Science).

Bibtex

@inbook{e8f4e08a17784bb69bc1bc88fd52bc6c,
title = "Evaluating the Quality of Radiotherapy Treatment Plans for Prostate Cancer",
abstract = "External beam radiation therapy is a common treatment method for cancer. Radiotherapy is planned with the aim to achieve conflicting goals: while a sufficiently high dose of radiation is necessary for tumour control, a low dose of radiation is desirable to avoid complications in normal, healthy, tissue. These goals are encoded in clinical protocols and a plan that does not meet the criteria set out in the protocol may have to be re-optimised using a trial and error process. To support the planning process, it is therefore important to evaluate the quality of treatment plans in order to recognise plans that will benefit from such re-optimisation and distinguish them fromthose for which this is unlikely to be the case. In this chapter we present a case study of evaluating the quality of prostate cancer treatment plans based on data collected from Rosemere Cancer Centre at the Royal Preston Hospital in the UK. We use Principal Component Analysis for data reduction, i.e., to select the most relevant data from the entire set available for each patient.We then apply Data Envelopment Analysis to assess the quality of individual plans. Each plan is compared against the entire set of plans to identify those that could realistically be improved. We further enhance this procedure with simulation techniques to account for uncertainties in the data for treatment plans. The proposed approach to plan evaluation provides a tool to support radiotherapy treatment planners in their task to determine the best possible radiotherapy treatment for cancer patients. With its combination of DEA, PCA and simulation, it allows focusing on the most significant determinants of plan quality, consideration of trade-offs between con icting planning goals and incorporation of uncertainty in treatment data.",
author = "Emma Stubington and Matthias Ehrgott and Shentall Glyn and Omid Nohadani",
year = "2018",
month = dec
day = "23",
doi = "10.1007/978-3-319-99304-1_2",
language = "English",
isbn = "9783319993034",
series = "International Series in Operations Research & Management Science",
publisher = "Springer",
pages = "41--66",
editor = "Sandra Huber and Geiger, {Martin Josef} and {de Almeida}, {Adiel T.}",
booktitle = "Cases based on Multiple Criteria Decision Making/Aiding methods",

}

RIS

TY - CHAP

T1 - Evaluating the Quality of Radiotherapy Treatment Plans for Prostate Cancer

AU - Stubington, Emma

AU - Ehrgott, Matthias

AU - Glyn, Shentall

AU - Nohadani, Omid

PY - 2018/12/23

Y1 - 2018/12/23

N2 - External beam radiation therapy is a common treatment method for cancer. Radiotherapy is planned with the aim to achieve conflicting goals: while a sufficiently high dose of radiation is necessary for tumour control, a low dose of radiation is desirable to avoid complications in normal, healthy, tissue. These goals are encoded in clinical protocols and a plan that does not meet the criteria set out in the protocol may have to be re-optimised using a trial and error process. To support the planning process, it is therefore important to evaluate the quality of treatment plans in order to recognise plans that will benefit from such re-optimisation and distinguish them fromthose for which this is unlikely to be the case. In this chapter we present a case study of evaluating the quality of prostate cancer treatment plans based on data collected from Rosemere Cancer Centre at the Royal Preston Hospital in the UK. We use Principal Component Analysis for data reduction, i.e., to select the most relevant data from the entire set available for each patient.We then apply Data Envelopment Analysis to assess the quality of individual plans. Each plan is compared against the entire set of plans to identify those that could realistically be improved. We further enhance this procedure with simulation techniques to account for uncertainties in the data for treatment plans. The proposed approach to plan evaluation provides a tool to support radiotherapy treatment planners in their task to determine the best possible radiotherapy treatment for cancer patients. With its combination of DEA, PCA and simulation, it allows focusing on the most significant determinants of plan quality, consideration of trade-offs between con icting planning goals and incorporation of uncertainty in treatment data.

AB - External beam radiation therapy is a common treatment method for cancer. Radiotherapy is planned with the aim to achieve conflicting goals: while a sufficiently high dose of radiation is necessary for tumour control, a low dose of radiation is desirable to avoid complications in normal, healthy, tissue. These goals are encoded in clinical protocols and a plan that does not meet the criteria set out in the protocol may have to be re-optimised using a trial and error process. To support the planning process, it is therefore important to evaluate the quality of treatment plans in order to recognise plans that will benefit from such re-optimisation and distinguish them fromthose for which this is unlikely to be the case. In this chapter we present a case study of evaluating the quality of prostate cancer treatment plans based on data collected from Rosemere Cancer Centre at the Royal Preston Hospital in the UK. We use Principal Component Analysis for data reduction, i.e., to select the most relevant data from the entire set available for each patient.We then apply Data Envelopment Analysis to assess the quality of individual plans. Each plan is compared against the entire set of plans to identify those that could realistically be improved. We further enhance this procedure with simulation techniques to account for uncertainties in the data for treatment plans. The proposed approach to plan evaluation provides a tool to support radiotherapy treatment planners in their task to determine the best possible radiotherapy treatment for cancer patients. With its combination of DEA, PCA and simulation, it allows focusing on the most significant determinants of plan quality, consideration of trade-offs between con icting planning goals and incorporation of uncertainty in treatment data.

U2 - 10.1007/978-3-319-99304-1_2

DO - 10.1007/978-3-319-99304-1_2

M3 - Chapter (peer-reviewed)

SN - 9783319993034

T3 - International Series in Operations Research & Management Science

SP - 41

EP - 66

BT - Cases based on Multiple Criteria Decision Making/Aiding methods

A2 - Huber, Sandra

A2 - Geiger, Martin Josef

A2 - de Almeida, Adiel T.

PB - Springer

ER -