A model-based reconstruction technique for quantitative myocardial perfusion imaging.
Magn Reson Med
; 76(3): 880-7, 2016 09.
Article
en En
| MEDLINE
| ID: mdl-26414857
ABSTRACT
PURPOSE:
To reduce saturation effects in the arterial input function (AIF) estimation of quantitative myocardial first-pass saturation recovery perfusion imaging by employing a model-based reconstruction. THEORY ANDMETHODS:
Imaging was performed with a saturation recovery prepared radial FLASH sequence. A model-based reconstruction was applied for reconstruction. By exploiting prior knowledge about the relaxation process, an image series with different saturation recovery times was reconstructed. By evaluating images with an effective saturation time of approximately 3 ms, saturation effects in the AIF determination were reduced. In a volunteer study, this approach was compared with a standard prebolus technique.RESULTS:
In comparison to the low-dose injection of a prebolus acquisition, saturation effects were further reduced in the AIFs determined using the model-based approach. These effects, which were clearly visible for all six volunteers, were reflected in a statistically significant difference of up to 20% in the absolute perfusion values.CONCLUSION:
The application of model-based reconstruction algorithms in quantitative myocardial perfusion imaging promises a significant improvement of the AIF determination. In addition to greatly reducing saturation effects that occur even for the prebolus methods, only a single bolus has to be applied. Magn Reson Med 76880-887, 2016. © 2015 Wiley Periodicals, Inc.Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Velocidad del Flujo Sanguíneo
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Imagen por Resonancia Magnética
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Medios de Contraste
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Circulación Coronaria
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Imagen de Perfusión Miocárdica
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Modelos Cardiovasculares
/
Miocardio
Tipo de estudio:
Diagnostic_studies
/
Evaluation_studies
/
Prognostic_studies
Límite:
Adult
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Female
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Humans
/
Male
Idioma:
En
Revista:
Magn Reson Med
Asunto de la revista:
DIAGNOSTICO POR IMAGEM
Año:
2016
Tipo del documento:
Article
País de afiliación:
Alemania