Literature DB >> 25220369

Direct use of multivariable normal tissue complication probability models in treatment plan optimisation for individualised head and neck cancer radiotherapy produces clinically acceptable treatment plans.

Roel G J Kierkels1, Erik W Korevaar2, Roel J H M Steenbakkers2, Tomas Janssen3, Aart A van't Veld2, Johannes A Langendijk2, Cornelis Schilstra4, Arjen van der Schaaf2.   

Abstract

BACKGROUND AND
PURPOSE: Recently, clinically validated multivariable normal tissue complication probability models (NTCP) for head and neck cancer (HNC) patients have become available. We test the feasibility of using multivariable NTCP-models directly in the optimiser for inverse treatment planning of radiotherapy to improve the dose distributions and corresponding NTCP-estimates in HNC patients.
MATERIAL AND METHODS: For 10 HNC cases, intensity-modulated radiotherapy plans were optimised either using objective functions based on the 'generalised equivalent uniform dose' (OFgEUD) or based on multivariable NTCP-models (OFNTCP). NTCP-models for patient-rated xerostomia, physician-rated RTOG grade II-IV dysphagia, and various patient-rated aspects of swallowing dysfunction were incorporated. The NTCP-models included dose-volume parameters as well as clinical factors contributing to a personalised optimisation process. Both optimisation techniques were compared by means of 'pseudo Pareto fronts' (target dose conformity vs. the sum of the NTCPs).
RESULTS: Both optimisation techniques resulted in clinically realistic treatment plans with only small differences. For nine patients the sum-NTCP was lower for the OFNTCP optimised plans (on average 5.7% (95%CI 1.7-9.9%, p<0.006)). Furthermore, the OFNTCP provided the advantages of fewer unknown optimisation parameters and an intrinsic mechanism of individualisation.
CONCLUSIONS: Treatment plan optimisation using multivariable NTCP-models directly in the OF is feasible as has been demonstrated for HNC radiotherapy.
Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Head and neck cancer; IMRT; Multivariable NTCP-models; Pareto fronts; Plan optimisation

Mesh:

Year:  2014        PMID: 25220369     DOI: 10.1016/j.radonc.2014.08.020

Source DB:  PubMed          Journal:  Radiother Oncol        ISSN: 0167-8140            Impact factor:   6.280


  12 in total

Review 1.  Automation in intensity modulated radiotherapy treatment planning-a review of recent innovations.

Authors:  Mohammad Hussein; Ben J M Heijmen; Dirk Verellen; Andrew Nisbet
Journal:  Br J Radiol       Date:  2018-09-04       Impact factor: 3.039

2.  Beyond mean pharyngeal constrictor dose for beam path toxicity in non-target swallowing muscles: Dose-volume correlates of chronic radiation-associated dysphagia (RAD) after oropharyngeal intensity modulated radiotherapy.

Authors: 
Journal:  Radiother Oncol       Date:  2016-02-17       Impact factor: 6.280

3.  Magnetic resonance imaging of swallowing-related structures in nasopharyngeal carcinoma patients receiving IMRT: Longitudinal dose-response characterization of quantitative signal kinetics.

Authors:  Jay A Messer; Abdallah S R Mohamed; Katherine A Hutcheson; Yao Ding; Jan S Lewin; Jihong Wang; Stephen Y Lai; Steven J Frank; Adam S Garden; Vlad Sandulache; Hillary Eichelberger; Chloe C French; Rivka R Colen; Jack Phan; Jayashree Kalpathy-Cramer; John D Hazle; David I Rosenthal; G Brandon Gunn; Clifton D Fuller
Journal:  Radiother Oncol       Date:  2016-01-28       Impact factor: 6.280

4.  Multicriteria optimization enables less experienced planners to efficiently produce high quality treatment plans in head and neck cancer radiotherapy.

Authors:  Roel G J Kierkels; Ruurd Visser; Hendrik P Bijl; Johannes A Langendijk; Aart A van 't Veld; Roel J H M Steenbakkers; Erik W Korevaar
Journal:  Radiat Oncol       Date:  2015-04-12       Impact factor: 3.481

5.  An integrated strategy of biological and physical constraints in biological optimization for cervical carcinoma.

Authors:  Ziwei Feng; Cheng Tao; Jian Zhu; Jinhu Chen; Gang Yu; Shaohua Qin; Yong Yin; Dengwang Li
Journal:  Radiat Oncol       Date:  2017-04-04       Impact factor: 3.481

6.  Normal tissue complication probability (NTCP) modelling using spatial dose metrics and machine learning methods for severe acute oral mucositis resulting from head and neck radiotherapy.

Authors:  Jamie A Dean; Kee H Wong; Liam C Welsh; Ann-Britt Jones; Ulrike Schick; Kate L Newbold; Shreerang A Bhide; Kevin J Harrington; Christopher M Nutting; Sarah L Gulliford
Journal:  Radiother Oncol       Date:  2016-05-27       Impact factor: 6.280

7.  Incorporating spatial dose metrics in machine learning-based normal tissue complication probability (NTCP) models of severe acute dysphagia resulting from head and neck radiotherapy.

Authors:  Jamie Dean; Kee Wong; Hiram Gay; Liam Welsh; Ann-Britt Jones; Ulricke Schick; Jung Hun Oh; Aditya Apte; Kate Newbold; Shreerang Bhide; Kevin Harrington; Joseph Deasy; Christopher Nutting; Sarah Gulliford
Journal:  Clin Transl Radiat Oncol       Date:  2017-11-21

8.  A new strategy for volumetric-modulated arc therapy planning using AutoPlanning based multicriteria optimization for nasopharyngeal carcinoma.

Authors:  Juanqi Wang; Zhi Chen; Weiwei Li; Wei Qian; Xiaosheng Wang; Weigang Hu
Journal:  Radiat Oncol       Date:  2018-05-16       Impact factor: 3.481

9.  Biological optimization for mediastinal lymphoma radiotherapy - a preliminary study.

Authors:  Laura Ann Rechner; Arezoo Modiri; Line Bjerregaard Stick; Maja V Maraldo; Marianne C Aznar; Stephanie R Rice; Amit Sawant; Søren M Bentzen; Ivan Richter Vogelius; Lena Specht
Journal:  Acta Oncol       Date:  2020-03-27       Impact factor: 4.089

10.  Benefits of intraoral stents for sparing normal tissue in radiotherapy of nasopharyngeal carcinoma: a radiobiological model-based quantitative analysis.

Authors:  Zhen Hou; Shuangshuang Li; Yuya Jiang; Fangfang Sun; Juan Liu; Shanbao Gao; Weitao Chen; Jing Yan
Journal:  Transl Cancer Res       Date:  2021-10       Impact factor: 1.241

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