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Dynamic mode decomposition of dynamic MRI for assessment of pulmonary ventilation and perfusion.
Ilicak, Efe; Ozdemir, Safa; Zapp, Jascha; Schad, Lothar R; Zöllner, Frank G.
Afiliación
  • Ilicak E; Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
  • Ozdemir S; Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
  • Zapp J; Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
  • Schad LR; Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
  • Zöllner FG; Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
Magn Reson Med ; 90(2): 761-769, 2023 08.
Article en En | MEDLINE | ID: mdl-36989180
PURPOSE: To introduce dynamic mode decomposition (DMD) as a robust alternative for the assessment of pulmonary functional information from dynamic non-contrast-enhanced acquisitions. METHODS: Pulmonary fractional ventilation and normalized perfusion maps were obtained using DMD from simulated phantoms as well as in vivo dynamic acquisitions of healthy volunteers at 1.5T. The performance of DMD was compared with conventional Fourier decomposition (FD) and matrix pencil (MP) methods in estimating functional map values. The proposed method was evaluated based on estimated signal amplitude in functional maps across varying number of measurements. RESULTS: Quantitative assessments performed on phantoms and in vivo measurements indicate that DMD is capable of successfully obtaining pulmonary functional maps. Specifically, compared to FD and MP methods, DMD is able to reduce variations in estimated amplitudes across different number of measurements. This improvement is evident in the fractional ventilation and normalized perfusion maps obtain from phantom simulations with frequency variations and noise, as well as in the maps obtained from in vivo measurements. CONCLUSIONS: A robust method for accurately estimating pulmonary ventilation and perfusion related signal changes in dynamic acquisitions is presented. The proposed method uses DMD to obtain functional maps reliably, while reducing amplitude variations caused by differences in number of measurements.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Imagen por Resonancia Magnética / Pulmón Límite: Humans Idioma: En Revista: Magn Reson Med Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2023 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Imagen por Resonancia Magnética / Pulmón Límite: Humans Idioma: En Revista: Magn Reson Med Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2023 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Estados Unidos