Karl Terence Butterworth1, Mihaela Ghita1, Stephen J McMahon1,2, Conor K Mcgarry1,3, Robert J Griffin4, Alan R Hounsell1,3, Kevin M Prise1. 1. 1 Centre for Cancer Research and Cell Biology, Queen's University Belfast, Belfast, Northern Ireland, UK. 2. 2 Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. 3. 3 Radiotherapy Physics, Northern Ireland Cancer Centre, Belfast, Northern Ireland, UK. 4. 4 Department of Radiation Oncology, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
Abstract
OBJECTIVE: Radiotherapy is planned to achieve the optimal physical dose distribution to the target tumour volume whilst minimizing dose to the surrounding normal tissue. Recent in vitro experimental evidence has demonstrated an important role for intercellular communication in radiobiological responses following non-uniform exposures. This study aimed to model the impact of these effects in the context of techniques involving highly modulated radiation fields or spatially fractionated treatments such as spatially fractionated radiotherapy (GRID). METHODS: Using the small-animal radiotherapy research platform as a key enabling technology to deliver precision imaged-guided radiotherapy, it is possible to achieve spatially modulated dose distributions that model typical clinical scenarios. In this work, we planned uniform and spatially fractionated dose distributions using multiple isocentres with beam sizes of 0.5-5 mm to obtain 50% volume coverage in a subcutaneous murine tumour model and applied a model of cellular response that incorporates intercellular communication to assess the potential impact of signalling effects with different ranges. RESULTS: Models of GRID treatment plans which incorporate intercellular signalling showed increased cell killing within the low-dose region. This results in an increase in the equivalent uniform dose for GRID exposures compared with standard models, with some GRID exposures being predicted to be more effective than uniform delivery of the same physical dose. CONCLUSION: This study demonstrates the potential impact of radiation-induced signalling on tumour cell response for spatially fractionated therapies and identifies key experiments to validate this model and quantify these effects in vivo. Advances in knowledge: This study highlights the unique opportunities now possible using advanced preclinical techniques to develop a foundation for biophysical optimization in radiotherapy treatment planning.
OBJECTIVE: Radiotherapy is planned to achieve the optimal physical dose distribution to the target tumour volume whilst minimizing dose to the surrounding normal tissue. Recent in vitro experimental evidence has demonstrated an important role for intercellular communication in radiobiological responses following non-uniform exposures. This study aimed to model the impact of these effects in the context of techniques involving highly modulated radiation fields or spatially fractionated treatments such as spatially fractionated radiotherapy (GRID). METHODS: Using the small-animal radiotherapy research platform as a key enabling technology to deliver precision imaged-guided radiotherapy, it is possible to achieve spatially modulated dose distributions that model typical clinical scenarios. In this work, we planned uniform and spatially fractionated dose distributions using multiple isocentres with beam sizes of 0.5-5 mm to obtain 50% volume coverage in a subcutaneous murinetumour model and applied a model of cellular response that incorporates intercellular communication to assess the potential impact of signalling effects with different ranges. RESULTS: Models of GRID treatment plans which incorporate intercellular signalling showed increased cell killing within the low-dose region. This results in an increase in the equivalent uniform dose for GRID exposures compared with standard models, with some GRID exposures being predicted to be more effective than uniform delivery of the same physical dose. CONCLUSION: This study demonstrates the potential impact of radiation-induced signalling on tumour cell response for spatially fractionated therapies and identifies key experiments to validate this model and quantify these effects in vivo. Advances in knowledge: This study highlights the unique opportunities now possible using advanced preclinical techniques to develop a foundation for biophysical optimization in radiotherapy treatment planning.
Authors: Karl T Butterworth; Kelly M Redmond; Stephen J McMahon; Aidan J Cole; Suneil Jain; Helen O McCarthy; Joe M O'Sullivan; Alan R Hounsell; Kevin M Prise Journal: Int J Radiat Biol Date: 2014-11-20 Impact factor: 2.694
Authors: X Zhang; J Penagaricano; Y Yan; S Sharma; R J Griffin; M Hardee; E Y Han; V Ratanatharathom Journal: Technol Cancer Res Treat Date: 2014-12-02
Authors: M Mohiuddin; M Fujita; W F Regine; A S Megooni; G S Ibbott; M M Ahmed Journal: Int J Radiat Oncol Biol Phys Date: 1999-10-01 Impact factor: 7.038
Authors: Stephen J McMahon; Karl T Butterworth; Colman Trainor; Conor K McGarry; Joe M O'Sullivan; Giuseppe Schettino; Alan R Hounsell; Kevin M Prise Journal: PLoS One Date: 2013-01-22 Impact factor: 3.240
Authors: Hualiang Zhong; Stephen Brown; Suneetha Devpura; X Allen Li; Indrin J Chetty Journal: Theor Biol Med Model Date: 2018-12-27 Impact factor: 2.432