Assisting vascular access surgery planning for hemodialysis by using MR, image segmentation techniques, and computer simulations.
Med Biol Eng Comput
; 51(8): 879-89, 2013 Aug.
Article
em En
| MEDLINE
| ID: mdl-23526414
ABSTRACT
The surgical creation of a vascular access, used for hemodialysis treatment of renal patients, has considerable complication rates (30-50 %). Image-based computational modeling might assist the surgeon in planning by enhanced analysis of preoperative hemodynamics, and in the future might serve as platform for outcome prediction. The objective of this study is to investigate preoperative personalization of the computer model using magnetic resonance (MR). MR-angiography and MR-flow data were obtained for eight patients and eight volunteers. Blood vessels were extracted for model input by a segmentation algorithm. Windkessel elements were added at the ends to represent the peripheral beds. Monte Carlo-based calibration was used to estimate the most influential non-measurable parameters. The predicted flow waveforms were compared with the MR-flow measurements for framework evaluation. The vasculature of all subjects were segmented in on average <5 min. The Monte Carlo-calibrated simulations showed a deviation between measured and simulated flow waveforms of 9 and 10 % for volunteers and patients, respectively. The presented method accurately mimics the preoperative hemodynamic state. Furthermore, the surgeon can interactively explore the hemodynamics at any vascular tree position. This integration of measurements in a modeling approach can provide the surgeon with additional information for preoperative planning.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Processamento de Imagem Assistida por Computador
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Imageamento por Ressonância Magnética
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Diálise Renal
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Cirurgia Assistida por Computador
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Modelos Cardiovasculares
Tipo de estudo:
Prognostic_studies
Limite:
Adult
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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
Revista:
Med Biol Eng Comput
Ano de publicação:
2013
Tipo de documento:
Article