The role of regularization in deformable image registration for head and neck adaptive radiotherapy.
Technol Cancer Res Treat
; 12(4): 323-31, 2013 Aug.
Article
em En
| MEDLINE
| ID: mdl-23448576
ABSTRACT
Deformable image registration provides a robust mathematical framework to quantify morphological changes that occur along the course of external beam radiotherapy treatments. As clinical reliability of deformable image registration is not always guaranteed, algorithm regularization is commonly introduced to prevent sharp discontinuities in the quantified deformation and achieve anatomically consistent results. In this work we analyzed the influence of regularization on two different registration methods, i.e. B-Splines and Log Domain Diffeomorphic Demons, implemented in an open-source platform. We retrospectively analyzed the simulation computed tomography (CTsim) and the corresponding re-planning computed tomography (CTrepl) scans in 30 head and neck cancer patients. First, we investigated the influence of regularization levels on hounsfield units (HU) information in 10 test patients for each considered method. Then, we compared the registration results of the open-source implementation at selected best performing regularization levels with a clinical commercial software on the remaining 20 patients in terms of mean volume overlap, surface and center of mass distances between manual outlines and propagated structures. The regularized B-Splines method was not statistically different from the commercial software. The tuning of the regularization parameters allowed open-source algorithms to achieve better results in deformable image registration for head and neck patients, with the additional benefit of a framework where regularization can be tuned on a patient specific basis.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Planejamento da Radioterapia Assistida por Computador
/
Interpretação de Imagem Radiográfica Assistida por Computador
/
Neoplasias de Cabeça e Pescoço
Tipo de estudo:
Guideline
/
Observational_studies
Limite:
Animals
/
Humans
Idioma:
En
Revista:
Technol Cancer Res Treat
Assunto da revista:
NEOPLASIAS
/
TERAPEUTICA
Ano de publicação:
2013
Tipo de documento:
Article
País de afiliação:
Itália