Chapter title |
Accounting for Two Forms of Hypoxia for Predicting Tumour Control Probability in Radiotherapy: An In Silico Study
|
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Chapter number | 29 |
Book title |
Oxygen Transport to Tissue XL
|
Published in |
Advances in experimental medicine and biology, August 2018
|
DOI | 10.1007/978-3-319-91287-5_29 |
Pubmed ID | |
Book ISBNs |
978-3-31-991285-1, 978-3-31-991287-5
|
Authors |
Emely Lindblom, Iuliana Toma-Dasu, Alexandru Dasu, Lindblom, Emely, Toma-Dasu, Iuliana, Dasu, Alexandru |
Abstract |
The progress in functional imaging and dose delivery has opened the possibility of targeting tumour hypoxia with radiotherapy. Advanced approaches apply quantitative information on tumour oxygenation retrieved from imaging in dose prescription. These do not, however, take into account the potential difference in radiosensitivity of chronically and acutely hypoxic cells. It was the aim of this study to evaluate the implications of assuming the same or different sensitivities for the hypoxic cells. An in silico 3D-model of a hypoxic tumour with heterogeneous oxygenation was used to model the probabilities of tumour control with different radiotherapy regimens. The results show that by taking into account the potential lower radioresistance of chronically hypoxic cells deprived of oxygen and nutrients, the total dose required to achieve a certain level of control is substantially reduced for a given fractionation scheme in comparison to the case when chronically and acutely hypoxic cells are assumed to have similar features. The results also suggest that the presence of chronic hypoxia could explain the success of radiotherapy for some hypoxic tumours. Given the implications for clinical dose escalation trials, further exploration of the influence of the different forms of hypoxia on treatment outcome is therefore warranted. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 2 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 1 | 50% |
Other | 1 | 50% |
Readers by discipline | Count | As % |
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Medicine and Dentistry | 1 | 50% |
Engineering | 1 | 50% |