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Optimizing b‐values schemes for diffusion MRI of the brain with segmented Intravoxel Incoherent Motion (IVIM) model

PURPOSE: To define an optimal set of b‐values for accurate derivation of diffusion MRI parameters in the brain with segmented Intravoxel Incoherent Motion (IVIM) model. METHODS: Simulations of diffusion signals were performed to define an optimal set of b‐values targeting different perfusion regimes...

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Detalles Bibliográficos
Autores principales: Paganelli, Chiara, Zampini, Marco Andrea, Morelli, Letizia, Buizza, Giulia, Fontana, Giulia, Anemoni, Luca, Imparato, Sara, Riva, Giulia, Iannalfi, Alberto, Orlandi, Ester, Baroni, Guido
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10243330/
https://www.ncbi.nlm.nih.gov/pubmed/37031365
http://dx.doi.org/10.1002/acm2.13986
Descripción
Sumario:PURPOSE: To define an optimal set of b‐values for accurate derivation of diffusion MRI parameters in the brain with segmented Intravoxel Incoherent Motion (IVIM) model. METHODS: Simulations of diffusion signals were performed to define an optimal set of b‐values targeting different perfusion regimes, by relying on an optimization procedure which minimizes the total relative error on estimated IVIM parameters computed with a segmented fitting procedure. Then, the optimal b‐values set was acquired in vivo on healthy subjects and skull base chordoma patients to compare the optimized protocol with a clinical one. RESULTS: The total relative error on simulations decreased of about 40% when adopting the optimal set of 13 b‐values (0 10 20 40 50 60 200 300 400 1200 1300 1400 1500 s/mm(2)), showing significant differences and increased precision on D and f estimates with respect to simulations with a non‐optimized b‐values set. Similarly, in vivo acquisitions demonstrated a dependency of IVIM parameters on the b‐values array, with differences between the optimal set of b‐values and a clinical non‐optimized acquisition. IVIM parameters were compatible to literature values, with D (0.679/0.701 [0.022/0.008] ·10(−3)mm(2) /s), f (5.49/5.80 [0.70/1.14] %), and D* (8.25/7.67 [0.92/0.83] ·10(−3)mm(2) /s) median [interquartile range] estimates for white matter/gray matter in volunteers and D (0.709/0.715/1.06 [0.035/0.023/0.271] ·10(−3)mm(2) /s), f (7.08/7.84/21.54 [1.20/1.06/6.05] %), and D* (10.85/11.84/2.32 [1.38/2.32/4.94] ·10(−3)mm(2) /s) for white matter/gray matter/Gross Tumor Volume in patients with skull‐base chordoma tumor. CONCLUSIONS: The definition of an optimal b‐values set can improve the estimation of quantitative IVIM parameters. This allows setting up an optimized approach that can be adopted for IVIM studies in the brain.