Literature DB >> 35817046

Modeling the propagation of tumor fronts with shortest path and diffusion models-implications for the definition of the clinical target volume.

Thomas Bortfeld1, Gregory Buti1,2.   

Abstract

Objective.The overarching objective is to make the definition of the clinical target volume (CTV) in radiation oncology less subjective and more scientifically based. The specific objective of this study is to investigate similarities and differences between two methods that model tumor spread beyond the visible gross tumor volume (GTV): (1) the shortest path model, which is the standard method of adding a geometric GTV-CTV margin, and (2) the reaction-diffusion model.Approach.These two models to capture the invisible tumor 'fire front' are defined and compared in mathematical terms. The models are applied to example cases that represent tumor spread in non-uniform and anisotropic media with anatomical barriers.Main results.The two seemingly disparate models bring forth traveling waves that can be associated with the front of tumor growth outward from the GTV. The shape of the fronts is similar for both models. Differences are seen in cases where the diffusive flow is reduced due to anatomical barriers, and in complex spatially non-uniform cases. The diffusion model generally leads to smoother fronts. The smoothness can be controlled with a parameter defined by the ratio of the diffusion coefficient and the proliferation rate.Significance.Defining the CTV has been described as the weakest link of the radiotherapy chain. There are many similarities in the mathematical description and the behavior of the common geometric GTV-CTV expansion method, and the definition of the CTV tumor front via the reaction-diffusion model. Its mechanistic basis and the controllable smoothness make the diffusion model an attractive alternative to the standard GTV-CTV margin model.
© 2022 Institute of Physics and Engineering in Medicine.

Entities:  

Keywords:  anisotropy; clinical target volume; fast marching method; glioblastoma multiforme; reaction-diffusion model

Mesh:

Year:  2022        PMID: 35817046      PMCID: PMC9388053          DOI: 10.1088/1361-6560/ac8043

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   4.174


  20 in total

1.  ESTRO-ACROP guideline "target delineation of glioblastomas".

Authors:  Maximilian Niyazi; Michael Brada; Anthony J Chalmers; Stephanie E Combs; Sara C Erridge; Alba Fiorentino; Anca L Grosu; Frank J Lagerwaard; Giuseppe Minniti; René-Olivier Mirimanoff; Umberto Ricardi; Susan C Short; Damien C Weber; Claus Belka
Journal:  Radiother Oncol       Date:  2016-01-06       Impact factor: 6.280

2.  Image guided personalization of reaction-diffusion type tumor growth models using modified anisotropic eikonal equations.

Authors:  Ender Konukoglu; Olivier Clatz; Bjoern H Menze; Bram Stieltjes; Marc-André Weber; Emmanuel Mandonnet; Hervé Delingette; Nicholas Ayache
Journal:  IEEE Trans Med Imaging       Date:  2009-07-14       Impact factor: 10.048

3.  The interaction of growth rates and diffusion coefficients in a three-dimensional mathematical model of gliomas.

Authors:  P K Burgess; P M Kulesa; J D Murray; E C Alvord
Journal:  J Neuropathol Exp Neurol       Date:  1997-06       Impact factor: 3.685

Review 4.  Grand challenges for medical physics in radiation oncology.

Authors:  Claudio Fiorino; Robert Jeraj; Catharine H Clark; Cristina Garibaldi; Dietmar Georg; Ludvig Muren; Wouter van Elmpt; Thomas Bortfeld; Nuria Jornet
Journal:  Radiother Oncol       Date:  2020-10-08       Impact factor: 6.280

5.  Automated delineation of the clinical target volume using anatomically constrained 3D expansion of the gross tumor volume.

Authors:  Nadya Shusharina; Jonas Söderberg; David Edmunds; Fredrik Löfman; Helen Shih; Thomas Bortfeld
Journal:  Radiother Oncol       Date:  2020-02-27       Impact factor: 6.280

6.  A mathematical model of glioma growth: the effect of extent of surgical resection.

Authors:  D E Woodward; J Cook; P Tracqui; G C Cruywagen; J D Murray; E C Alvord
Journal:  Cell Prolif       Date:  1996-06       Impact factor: 6.831

7.  Mathematical modelling of microtumour infiltration based on in vitro experiments.

Authors:  Emmanuel Luján; Liliana N Guerra; Alejandro Soba; Nicolás Visacovsky; Daniel Gandía; Juan C Calvo; Cecilia Suárez
Journal:  Integr Biol (Camb)       Date:  2016-07-28       Impact factor: 2.192

8.  A mathematical model of glioma growth: the effect of chemotherapy on spatio-temporal growth.

Authors:  P Tracqui; G C Cruywagen; D E Woodward; G T Bartoo; J D Murray; E C Alvord
Journal:  Cell Prolif       Date:  1995-01       Impact factor: 6.831

9.  Extrapolating glioma invasion margin in brain magnetic resonance images: suggesting new irradiation margins.

Authors:  Ender Konukoglu; Olivier Clatz; Pierre-Yves Bondiau; Hervé Delingette; Nicholas Ayache
Journal:  Med Image Anal       Date:  2009-12-03       Impact factor: 8.545

10.  From patient-specific mathematical neuro-oncology to precision medicine.

Authors:  A L Baldock; R C Rockne; A D Boone; M L Neal; A Hawkins-Daarud; D M Corwin; C A Bridge; L A Guyman; A D Trister; M M Mrugala; J K Rockhill; K R Swanson
Journal:  Front Oncol       Date:  2013-04-02       Impact factor: 6.244

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