Inline automatic quality control of 2D phase-contrast flow MRI for subject-specific scan time adaptation.
Magn Reson Med
; 92(2): 751-760, 2024 Aug.
Article
en En
| MEDLINE
| ID: mdl-38469944
ABSTRACT
PURPOSE:
To develop an inline automatic quality control to achieve consistent diagnostic image quality with subject-specific scan time, and to demonstrate this method for 2D phase-contrast flow MRI to reach a predetermined SNR.METHODS:
We designed a closed-loop feedback framework between image reconstruction and data acquisition to intermittently check SNR (every 20 s) and automatically stop the acquisition when a target SNR is achieved. A free-breathing 2D pseudo-golden-angle spiral phase-contrast sequence was modified to listen for image-quality messages from the reconstructions. Ten healthy volunteers and 1 patient were imaged at 0.55 T. Target SNR was selected based on retrospective analysis of cardiac output error, and performance of the automatic SNR-driven "stop" was assessed inline.RESULTS:
SNR calculation and automated segmentation was feasible within 20 s with inline deployment. The SNR-driven acquisition time was 2 min 39 s ± 67 s (aorta) and 3 min ± 80 s (main pulmonary artery) with a min/max acquisition time of 1 min 43 s/4 min 52 s (aorta) and 1 min 43 s/5 min 50 s (main pulmonary artery) across 6 healthy volunteers, while ensuring a diagnostic measurement with relative absolute error in quantitative flow measurement lower than 2.1% (aorta) and 6.3% (main pulmonary artery).CONCLUSION:
The inline quality control enables subject-specific optimized scan times while ensuring consistent diagnostic image quality. The distribution of automated stopping times across the population revealed the value of a subject-specific scan time.Palabras clave
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
Control de Calidad
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Procesamiento de Imagen Asistido por Computador
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Imagen por Resonancia Magnética
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Relación Señal-Ruido
Límite:
Adult
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Female
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Humans
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Male
Idioma:
En
Revista:
Magn Reson Med
Asunto de la revista:
DIAGNOSTICO POR IMAGEM
Año:
2024
Tipo del documento:
Article
País de afiliación:
Estados Unidos