Registration error of the liver CT using deformable image registration of MIM Maestro and Velocity AI.
BMC Med Imaging
; 17(1): 30, 2017 05 04.
Article
em En
| MEDLINE
| ID: mdl-28472925
ABSTRACT
BACKGROUND:
Understanding the irradiated area and dose correctly is important for the reirradiation of organs that deform after irradiation, such as the liver. We investigated the spatial registration error using the deformable image registration (DIR) software products MIM Maestro (MIM) and Velocity AI (Velocity).METHODS:
Image registration of pretreatment computed tomography (CT) and posttreatment CT was performed in 24 patients with liver tumors. All the patients received proton beam therapy, and the follow-up period was 4-14 (median 10) months. We performed DIR of the pretreatment CT and compared it with that of the posttreatment CT by calculating the dislocation of metallic markers (implanted close to the tumors).RESULTS:
The fiducial registration error was comparable in both products 0.4-32.9 (9.3 ± 9.9) mm for MIM and 0.5-38.6 (11.0 ± 10.0) mm for Velocity, and correlated with the tumor diameter for MIM (r = 0.69, P = 0.002) and for Velocity (r = 0.68, P = 0.0003). Regarding the enhancement effect, the fiducial registration error was 1.0-24.9 (7.4 ± 7.7) mm for MIM and 0.3-29.6 (8.9 ± 7.2) mm for Velocity, which is shorter than that of plain CT (P = 0.04, for both).CONCLUSIONS:
The DIR performance of both MIM and Velocity is comparable with regard to the liver. The fiducial registration error of DIR depends on the tumor diameter. Furthermore, contrast-enhanced CT improves the accuracy of both MIM and Velocity. INSTITUTIONAL REVIEW BOARD APPROVAL H28-102; July 14, 2016 approved.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
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Software
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Interpretação de Imagem Radiográfica Assistida por Computador
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Tomografia Computadorizada por Raios X
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Técnica de Subtração
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Fígado
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Neoplasias Hepáticas
Tipo de estudo:
Diagnostic_studies
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Evaluation_studies
Limite:
Aged
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Aged80
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Ano de publicação:
2017
Tipo de documento:
Article