Modelling systematic anatomical uncertainties of head and neck cancer patients during fractionated radiotherapy treatment.
Phys Med Biol
; 69(15)2024 Jul 23.
Article
em En
| MEDLINE
| ID: mdl-38981595
ABSTRACT
Objective.Head and neck cancer patients experience systematic as well as random day to day anatomical changes during fractionated radiotherapy treatment. Modelling the expected systematic anatomical changes could aid in creating treatment plans which are more robust against such changes.Approach.Inter- patient correspondence aligned all patients to a model space. Intra- patient correspondence between each planning CT scan and on treatment cone beam CT scans was obtained using diffeomorphic deformable image registration. The stationary velocity fields were then used to develop B-Spline based patient specific (SM) and population average (AM) models. The models were evaluated geometrically and dosimetrically. A leave-one-out method was used to compare the training and testing accuracy of the models.Main results.Both SMs and AMs were able to capture systematic changes. The average surface distance between the registration propagated contours and the contours generated by the SM was less than 2 mm, showing that the SM are able to capture the anatomical changes which a patient experiences during the course of radiotherapy. The testing accuracy was lower than the training accuracy of the SM, suggesting that the model overfits to the limited data available and therefore, also captures some of the random day to day changes. For most patients the AMs were a better estimate of the anatomical changes than assuming there were no changes, but the AMs could not capture the variability in the anatomical changes seen in all patients. No difference was seen in the training and testing accuracy of the AMs. These observations were highlighted in both the geometric and dosimetric evaluations and comparisons.Significance.In this work, a SM and AM are presented which are able to capture the systematic anatomical changes of some head and neck cancer patients over the course of radiotherapy treatment. The AM is able to capture the overall trend of the population, but there is large patient variability which highlights the need for more complex, capable population models.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Planejamento da Radioterapia Assistida por Computador
/
Fracionamento da Dose de Radiação
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Neoplasias de Cabeça e Pescoço
Limite:
Humans
Idioma:
En
Revista:
Phys Med Biol
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Reino Unido