Towards Personalized Radio-Chemotherapy – Learning from Clinical Data vs. Model Optimization

Andrzej Świerniak; Jarosław Śmieja; Krzysztof Fujarewicz; Rafał Suwiński

doi:10.1007/978-3-030-41964-6_32

Towards Personalized Radio-Chemotherapy – Learning from Clinical Data vs. Model Optimization

Department of Systems Biology and Engineering (RAU/RAU1)

Maria Sklodowska-Curie Institute of Oncology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

We summarize results of our research studies on models of combined anticancer radio- and chemotherapy and their comparison with real clinical data. We use two mathematical techniques, which, to our knowledge, have not been applied simultaneously: optimal control theory and survival analysis. We recall results of analytical optimization of combined chemo-radio-therapy for a simple model of tumor growth with respect to the order, in which these two modes of treatment should be applied. Then we study both structural and parametric sensitivity of this model and related optimal control problem. Afterwards, we present results of survival analysis based on the Kaplan-Meier curves for different protocols of chemo-radio-therapy and compare them with real clinical data and results of optimal treatment protocols.

Original language	English
Title of host publication	Intelligent Information and Database Systems - 12th Asian Conference, ACIIDS 2020, Proceedings
Editors	Ngoc Thanh Nguyen, Bogdan Trawinski, Kietikul Jearanaitanakij, Suphamit Chittayasothorn, Ali Selamat
Publisher	Springer
Pages	371-379
Number of pages	9
ISBN (Print)	9783030419639
DOIs	https://doi.org/10.1007/978-3-030-41964-6_32
Publication status	Published - 2020
Event	12th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2020 - Phuket, Thailand Duration: 23 Mar 2020 → 26 Mar 2020

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12033 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	12th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2020
Country/Territory	Thailand
City	Phuket
Period	23/03/20 → 26/03/20

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Survival analysis
Therapy optimization

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-030-41964-6_32

Cite this

Świerniak, A., Śmieja, J., Fujarewicz, K., & Suwiński, R. (2020). Towards Personalized Radio-Chemotherapy – Learning from Clinical Data vs. Model Optimization. In N. T. Nguyen, B. Trawinski, K. Jearanaitanakij, S. Chittayasothorn, & A. Selamat (Eds.), Intelligent Information and Database Systems - 12th Asian Conference, ACIIDS 2020, Proceedings (pp. 371-379). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12033 LNAI). Springer. https://doi.org/10.1007/978-3-030-41964-6_32

Świerniak, Andrzej ; Śmieja, Jarosław ; Fujarewicz, Krzysztof et al. / Towards Personalized Radio-Chemotherapy – Learning from Clinical Data vs. Model Optimization. Intelligent Information and Database Systems - 12th Asian Conference, ACIIDS 2020, Proceedings. editor / Ngoc Thanh Nguyen ; Bogdan Trawinski ; Kietikul Jearanaitanakij ; Suphamit Chittayasothorn ; Ali Selamat. Springer, 2020. pp. 371-379 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Towards Personalized Radio-Chemotherapy – Learning from Clinical Data vs. Model Optimization",

abstract = "We summarize results of our research studies on models of combined anticancer radio- and chemotherapy and their comparison with real clinical data. We use two mathematical techniques, which, to our knowledge, have not been applied simultaneously: optimal control theory and survival analysis. We recall results of analytical optimization of combined chemo-radio-therapy for a simple model of tumor growth with respect to the order, in which these two modes of treatment should be applied. Then we study both structural and parametric sensitivity of this model and related optimal control problem. Afterwards, we present results of survival analysis based on the Kaplan-Meier curves for different protocols of chemo-radio-therapy and compare them with real clinical data and results of optimal treatment protocols.",

keywords = "Survival analysis, Therapy optimization",

author = "Andrzej {\'S}wierniak and Jaros{\l}aw {\'S}mieja and Krzysztof Fujarewicz and Rafa{\l} Suwi{\'n}ski",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 12th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2020 ; Conference date: 23-03-2020 Through 26-03-2020",

year = "2020",

doi = "10.1007/978-3-030-41964-6\_32",

language = "English",

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Świerniak, A , Śmieja, J , Fujarewicz, K & Suwiński, R 2020, Towards Personalized Radio-Chemotherapy – Learning from Clinical Data vs. Model Optimization. in NT Nguyen, B Trawinski, K Jearanaitanakij, S Chittayasothorn & A Selamat (eds), Intelligent Information and Database Systems - 12th Asian Conference, ACIIDS 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12033 LNAI, Springer, pp. 371-379, 12th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2020, Phuket, Thailand, 23/03/20. https://doi.org/10.1007/978-3-030-41964-6_32

Towards Personalized Radio-Chemotherapy – Learning from Clinical Data vs. Model Optimization. / Świerniak, Andrzej ; Śmieja, Jarosław ; Fujarewicz, Krzysztof et al.
Intelligent Information and Database Systems - 12th Asian Conference, ACIIDS 2020, Proceedings. ed. / Ngoc Thanh Nguyen; Bogdan Trawinski; Kietikul Jearanaitanakij; Suphamit Chittayasothorn; Ali Selamat. Springer, 2020. p. 371-379 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12033 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Towards Personalized Radio-Chemotherapy – Learning from Clinical Data vs. Model Optimization

AU - Świerniak, Andrzej

AU - Śmieja, Jarosław

AU - Fujarewicz, Krzysztof

AU - Suwiński, Rafał

PY - 2020

Y1 - 2020

N2 - We summarize results of our research studies on models of combined anticancer radio- and chemotherapy and their comparison with real clinical data. We use two mathematical techniques, which, to our knowledge, have not been applied simultaneously: optimal control theory and survival analysis. We recall results of analytical optimization of combined chemo-radio-therapy for a simple model of tumor growth with respect to the order, in which these two modes of treatment should be applied. Then we study both structural and parametric sensitivity of this model and related optimal control problem. Afterwards, we present results of survival analysis based on the Kaplan-Meier curves for different protocols of chemo-radio-therapy and compare them with real clinical data and results of optimal treatment protocols.

AB - We summarize results of our research studies on models of combined anticancer radio- and chemotherapy and their comparison with real clinical data. We use two mathematical techniques, which, to our knowledge, have not been applied simultaneously: optimal control theory and survival analysis. We recall results of analytical optimization of combined chemo-radio-therapy for a simple model of tumor growth with respect to the order, in which these two modes of treatment should be applied. Then we study both structural and parametric sensitivity of this model and related optimal control problem. Afterwards, we present results of survival analysis based on the Kaplan-Meier curves for different protocols of chemo-radio-therapy and compare them with real clinical data and results of optimal treatment protocols.

KW - Survival analysis

KW - Therapy optimization

UR - https://www.scopus.com/pages/publications/85082294452

U2 - 10.1007/978-3-030-41964-6_32

DO - 10.1007/978-3-030-41964-6_32

M3 - Conference contribution

AN - SCOPUS:85082294452

SN - 9783030419639

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 371

EP - 379

BT - Intelligent Information and Database Systems - 12th Asian Conference, ACIIDS 2020, Proceedings

A2 - Nguyen, Ngoc Thanh

A2 - Trawinski, Bogdan

A2 - Jearanaitanakij, Kietikul

A2 - Chittayasothorn, Suphamit

A2 - Selamat, Ali

PB - Springer

T2 - 12th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2020

Y2 - 23 March 2020 through 26 March 2020

ER -

Świerniak A , Śmieja J , Fujarewicz K, Suwiński R. Towards Personalized Radio-Chemotherapy – Learning from Clinical Data vs. Model Optimization. In Nguyen NT, Trawinski B, Jearanaitanakij K, Chittayasothorn S, Selamat A, editors, Intelligent Information and Database Systems - 12th Asian Conference, ACIIDS 2020, Proceedings. Springer. 2020. p. 371-379. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-41964-6_32

Towards Personalized Radio-Chemotherapy – Learning from Clinical Data vs. Model Optimization

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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