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Inline automatic quality control of 2D phase-contrast flow MRI for subject-specific scan time adaptation.
Daudé, Pierre; Ramasawmy, Rajiv; Javed, Ahsan; Lederman, Robert J; Chow, Kelvin; Campbell-Washburn, Adrienne E.
Afiliación
  • Daudé P; Laboratory of Imaging Technology, Cardiovascular Branch, Division of Intramural Research, National Heart Lung & Blood Institute, National Institutes of Health, Bethesda, Maryland, USA.
  • Ramasawmy R; Laboratory of Imaging Technology, Cardiovascular Branch, Division of Intramural Research, National Heart Lung & Blood Institute, National Institutes of Health, Bethesda, Maryland, USA.
  • Javed A; Laboratory of Imaging Technology, Cardiovascular Branch, Division of Intramural Research, National Heart Lung & Blood Institute, National Institutes of Health, Bethesda, Maryland, USA.
  • Lederman RJ; Laboratory of Cardiovascular Intervention, Cardiovascular Branch, Division of Intramural Research, National Heart Lung & Blood Institute, National Institutes of Health, Bethesda, Maryland, USA.
  • Chow K; Siemens Healthcare Ltd., Calgary, Alberta, Canada.
  • Campbell-Washburn AE; Laboratory of Imaging Technology, Cardiovascular Branch, Division of Intramural Research, National Heart Lung & Blood Institute, National Institutes of Health, Bethesda, Maryland, USA.
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Control de Calidad / Procesamiento de Imagen Asistido por Computador / Imagen por Resonancia Magnética / Relación Señal-Ruido Límite: Adult / Female / Humans / 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 Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Control de Calidad / Procesamiento de Imagen Asistido por Computador / Imagen por Resonancia Magnética / Relación Señal-Ruido Límite: Adult / Female / Humans / 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 Pais de publicación: Estados Unidos